U.S. Department 

Of Transportation 

National Highway 

Traffic Safety Administration 

Final Regulatory Impact Analysis 

Corporate Average Fuel Economy 

for MY 2012-MY 2016 

Passenger Cars and 

Light Trucks 

Office of Regulatory Analysis and Evaluation 

National Center for Statistics and Analysis 

March 2010 

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TABLE OF CONTENTS 

EXECUTIVE SUMMARY ............................................................................................................ 1 

I. INTRODUCTION .................................................................Error! Bookmark not defined.

II. NEED OF THE NATION TO CONSERVE ENERGY........Error! Bookmark not defined.

III. BASELINE AND ALTERNATIVES..................................Error! Bookmark not defined.

IV. IMPACT OF OTHER FEDERAL MOTOR VEHICLE STANDARDS ON FUEL 

ECONOMY ...................................................................................Error! Bookmark not defined.

V. FUEL ECONOMY ENHANCING TECHNOLOGIES AND THE VOLPE MODEL........ 86 

VI. MANUFACTURER CAFE CAPABILITIES..................................................................... 86 

VII. COST IMPACTS...............................................................Error! Bookmark not defined.

VIII. BENEFITS FROM IMPROVED FUEL ECONOMY ................................................... 380 

IX. IMPACT OF WEIGHT REDUCTION ON SAFETY.........Error! Bookmark not defined.

X. NET BENEFITS AND SENSITIVITY ANALYSES........................................................ 455 

XI. FLEXIBILITIES IN MEETING THE STANDARD...........Error! Bookmark not defined.

XII. PROBABILISTIC UNCERTAINTY ANALYSIS............Error! Bookmark not defined.

XIII. REGULATORY FLEXIBILITY ACT AND UNFUNDED MANDATES REFORM ACT 

ANALYSIS....................................................................................Error! Bookmark not defined.
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EXECUTIVE SUMMARY 

This assessment examines the costs and benefits of improving the fuel economy of passenger 

cars and light trucks for model years (MY) 2012 through MY 2016. It includes a discussion of 

the technologies that can improve fuel economy, analysis of the potential impact on retail prices, 

safety, lifetime fuel savings and their value to consumers, and other societal benefits such as 

improved energy security and reduced emissions of pollutants and greenhouse gases.1

 

As required by the Energy Independence and Security Act of 2007 (EISA), NHTSA sets 

attribute-based corporate average fuel economy (CAFE) standards that are based on a 

mathematical function. For purposes of MYs 2012-2016, as for MY 2011 passenger cars and 

MYs 2008-2011 light trucks, the CAFE standards have been based on vehicle footprint.2

 The 

mathematical function or “curve” representing the footprint-based standards is a constrained 

linear function (as compared to the constrained logistic function used for the MY 2011 

standards), that provides a separate fuel economy target for each vehicle footprint, generally with 

more stringent targets for smaller vehicles and less stringent targets for larger vehicles. Different 

parameters for the continuous mathematical function are derived. Individual manufacturers will 

be required to comply with a single fuel economy level that is based on the distribution of its 

production among the footprints of its vehicles. Although a manufacturer’s compliance 

obligation is determined in the same way for both passenger cars and light trucks, the footprint 

target curves for the different fleets are established with different continuous mathematical 

functions that are specific to the vehicles’ design capabilities. 

The baseline assumptions for this rulemaking differ from previous analyses in support of 

previous CAFE standards. For previous analyses, NHTSA developed a baseline using 

confidential product plans for each model year provided by the manufacturers regulated by the 

rule. For purposes of this analysis, in contrast, in the interest of improving transparency, the 

baseline was developed using each manufacturer’s MY 2008 fleet as represented in CAFE 

certification data available to EPA. In order to conduct this analysis, we assume that similar 

vehicles will be produced through MY 2016 and technologies are added to this baseline fleet to 

determine what mpg levels could be achieved by the manufacturers in the MYs 2012-2016 

timeframe. NHTSA has examined a variety of alternatives to the final standards for MYs 2012-

2016. The eight alternatives examined include five that are annual percentage improvements 

over the baseline – 3%/year, 4%/year, 5%/year, 6%/year, and 7%/year. In addition to those five 

are what NHTSA has called the “Preferred Alternative,” the “Maximum Net Benefits” 

alternative, and the “Total Costs Equal Total Benefits” alternative. The “Preferred Alternative” 

would require fuel economy levels that are generally between the 4 and 5 percent annual increase 

alternatives, although the percentage increase varies from year to year. The “Maximum Net 

Benefits” alternative is based upon availability of technologies and a marginal cost/benefit 

analysis. In this case the model continues to include technologies until marginal cost of adding 

the next technology exceeds the marginal benefit. The “Total Costs Equal Total Benefits” 

alternative represents an increase in the standard to a point where essentially total costs of the 

1

 This analysis does not contain NHTSA’s assessment of the potential environmental impacts of the final rule for 

purposes of the National Environmental Policy Act (NEPA), 42 U.S.C. 4321-4347. 

2

 Vehicle Footprint is defined as the wheelbase (the distance from the center of the front axle to the center of the 

rear axle) times the average track width (the distance between the centerline of the tires) of the vehicle (in square 

feet). 
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technologies added together over the baseline added equals total benefits over the baseline. In 

this analysis, for brevity, at times it is labeled “TC = TB.” 

Table 1a shows the agency’s projection of the estimated actual harmonic average that would be 

achieved by the manufacturers, assuming that some manufacturers will pay fines rather than 

meet the required levels. Table 1b shows the estimated required levels. All of the tables in this 

analysis compare an adjusted baseline to the projected achieved harmonic average. 

Costs: Costs were estimated based on the specific technologies that were applied to improve 

each manufacturer’s fuel economy up to their achieved level under each alternative or fines that 

would be assessed. Table 2 provides the cost and fine estimates on an average per-vehicle basis, 

and Table 3 provides those estimates (without counting fines) on a fleet-wide basis in millions of 

dollars. 

Benefits: Benefits are determined mainly from fuel savings over the lifetime of the vehicle, but 

also include externalities such as reductions in criteria pollutants. The agency uses a 3 percent 

and 7 percent discount rate to value intra-generational future benefits and costs. Intergenerational3

 benefits from future carbon dioxide reductions are discounted at 3 percent in the 

main analysis, even when intra-generational benefits are discounted at 7 percent. Sensitivity 

analyses in Chapter X analyze other inter-generational discount rates that accompany alternative 

estimates of the social cost of carbon. Table 4 provides those estimates on an industry-wide 

basis at a 3 percent discount rate and Table 6 provides the estimates at a 7 percent discount rate. 

Net Benefits: Tables 5 and 7 compares societal costs and societal benefits of each alternative at 

the 3 percent and 7 percent discount rates, respectively. 

Fuel Savings: Table 8 shows the lifetime fuel savings in millions of gallons. 

3

 Inter-generational benefits, which include reductions in the expected future economic damages caused by increased 

global temperatures, a rise in sea levels, and other projected impacts of climate change, are anticipated to extend 

over a period from approximately fifty to two hundred or more years in the future, and will thus be experienced 

primarily by generations that are not now living. 
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Table 1a 

Alternative CAFE Levels 

 Projected Achieved Harmonic Average for the Fleet, in mpg 

Alternative 

MY 

2012 

MY 

2013 

MY 

2014 

MY 

2015 

MY 

2016 

Passenger Cars 

Preferred Alternative 32.8 34.4 35.3 36.3 37.2 

3% Annual Increase 32.2 33.2 33.7 34.3 35.2 

4% Annual Increase 32.3 33.6 34.6 35.5 36.7 

5% Annual Increase 32.6 34.4 35.8 36.9 38.3 

6% Annual Increase 32.8 34.9 36.6 38.0 39.7 

7% Annual Increase 33.0 35.4 37.4 38.9 40.7 

Max Net Benefits 33.0 35.5 37.3 38.4 39.8 

Total Cost = Total 

Benefit 33.1 35.7 37.7 39.0 40.5 

Light Trucks 

Preferred Alternative 25.1 26.0 27.0 27.6 28.5 

3% Annual Increase 24.4 25.0 25.8 26.4 26.9 

4% Annual Increase 24.7 25.5 26.5 27.2 28.1 

5% Annual Increase 24.9 26.0 27.4 28.3 29.3 

6% Annual Increase 25.0 26.5 28.1 29.4 30.6 

7% Annual Increase 25.2 26.9 28.8 30.1 31.4 

Max Net Benefits 25.5 27.3 28.8 29.9 30.6 

Total Cost = Total 

Benefit 25.5 27.4 29.1 30.2 31.1 

Passenger Cars & Light Trucks 

Preferred Alternative 29.3 30.6 31.7 32.6 33.7 

3% Annual Increase 28.6 29.5 30.3 31.0 31.8 

4% Annual Increase 28.8 30.0 31.1 32.1 33.2 

5% Annual Increase 29.1 30.6 32.1 33.3 34.6 

6% Annual Increase 29.3 31.2 32.9 34.4 36.0 

7% Annual Increase 29.4 31.6 33.7 35.2 36.9 

Max Net Benefits 29.6 31.8 33.6 34.9 36.1 

Total Cost = Total 

Benefit 29.7 32.0 34.0 35.4 36.7 

Preferred Alternative CAFE Levels 

 Projected Achieved Harmonic Average for the Fleet, in gallons per 100 miles 

MY 

2012 

MY 

2013 

MY 

2014 

MY 

2015 

MY 

2016 

PC 3.0517 2.9111 2.8321 2.7581 2.6877 

LT 3.9894 3.8417 3.7059 3.6206 3.5048 
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Table 1b 

Alternative CAFE Levels 

 Estimated Required Average for the Fleet, in mpg 

Alternative 

MY 

2012 

MY 

2013 

MY 

2014 

MY 

2015 

MY 

2016 

Passenger Cars 

Preferred Alternative 33.3 34.2 34.9 36.2 37.8 

3% Annual Increase 31.7 32.6 33.5 34.4 35.4 

4% Annual Increase 32.1 33.3 34.5 35.8 37.2 

5% Annual Increase 32.4 33.9 35.5 37.1 39.0 

6% Annual Increase 32.7 34.5 36.5 38.6 40.9 

7% Annual Increase 33.0 35.2 37.6 40.1 42.9 

Max Net Benefits 33.0 36.1 38.1 39.4 40.9 

Total Cost = Total 

Benefit 33.4 36.7 39.2 40.7 42.3 

Light Trucks 

Preferred Alternative 25.4 26.0 26.6 27.5 28.8 

3% Annual Increase 24.1 24.8 25.5 26.2 27.0 

4% Annual Increase 24.4 25.3 26.3 27.2 28.3 

5% Annual Increase 24.6 25.8 27.0 28.3 29.7 

6% Annual Increase 24.9 26.3 27.8 29.4 31.1 

7% Annual Increase 25.1 26.8 28.6 30.5 32.6 

Max Net Benefits 26.3 27.7 29.1 30.3 31.1 

Total Cost = Total 

Benefit 26.3 28.0 29.7 30.7 31.8 

Passenger Cars & Light Trucks 

Preferred Alternative 29.7 30.5 31.3 32.6 34.1 

3% Annual Increase 28.3 29.1 30.0 31.0 32.0 

4% Annual Increase 28.6 29.7 30.9 32.2 33.6 

5% Annual Increase 28.8 30.3 31.8 33.4 35.2 

6% Annual Increase 29.1 30.8 32.7 34.7 36.9 

7% Annual Increase 29.4 31.4 33.7 36.0 38.7 

Max Net Benefits 30.0 32.3 34.2 35.6 36.9 

Total Cost = Total 

Benefit 30.3 32.8 35.0 36.5 38.0 

Estimated Required Preferred Alternative CAFE Levels 

 Projected Achieved Harmonic Average for the Fleet, in gallons per 100 miles 

MY 2012 

MY 

2013 

MY 

2014 

MY 

2015 

MY 

2016 

PC 2.9988 2.9277 2.8624 2.7628 2.6483 
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LT 3.9370 3.8472 3.7622 3.6298 3.4766 
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Table 2 

Average Incremental Cost or Fines 

Per Vehicle 

(2007 Dollars) 

Alternative 

MY 

2012 

MY 

2013 

MY 

2014 

MY 

2015 

MY 

2016 

Passenger Cars 

Preferred Alternative $505 $573 $690 $799 $907 

3% Annual Increase $191 $248 $317 $394 $493 

4% Annual Increase $254 $366 $500 $640 $764 

5% Annual Increase $362 $558 $749 $918 $1,088 

6% Annual Increase $526 $758 $1,064 $1,321 $1,546 

7% Annual Increase $616 $952 $1,361 $1,634 $1,941 

Max Net Benefits $612 $954 $1,282 $1,460 $1,628 

Total Cost = Total Benefit $675 $1,065 $1,440 $1,653 $1,878 

Light Trucks 

Preferred Alternative $322 $416 $621 $752 $961 

3% Annual Increase $1 $78 $234 $348 $484 

4% Annual Increase $166 $293 $506 $646 $830 

5% Annual Increase $417 $633 $1,036 $1,186 $1,361 

6% Annual Increase $516 $943 $1,394 $1,706 $2,007 

7% Annual Increase $575 $1,222 $1,716 $2,181 $2,549 

Max Net Benefits $761 $1,249 $1,665 $1,948 $2,082 

Total Cost = Total Benefit $780 $1,344 $1,806 $2,157 $2,366 

Passenger Cars & Light 

Trucks 

Preferred Alternative $434 $513 $665 $782 $926 

3% Annual Increase $117 $183 $287 $378 $490 

4% Annual Increase $220 $338 $502 $642 $787 

5% Annual Increase $384 $587 $855 $1,013 $1,182 

6% Annual Increase $522 $829 $1,185 $1,457 $1,705 

7% Annual Increase $600 $1,055 $1,492 $1,828 $2,150 

Max Net Benefits $670 $1,066 $1,423 $1,633 $1,784 

Total Cost = Total Benefit $716 $1,171 $1,575 $1,831 $2,046 
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Table 3 

Incremental Total Costs by Societal Perspective4

, by Alternative 

(Millions of 2007 Dollars) 

Alternative MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 5-Year Total 

Passenger Cars 

Preferred Alternative $4,148 $5,411 $6,855 $8,221 $9,534 $34,170 

3% Annual Increase $1,622 $2,341 $3,142 $4,047 $5,222 $16,375 

4% Annual Increase $2,148 $3,455 $4,944 $6,561 $8,031 $25,138 

5% Annual Increase $3,074 $5,288 $7,426 $9,410 $11,403 $36,601 

6% Annual Increase $4,504 $7,196 $10,567 $13,546 $16,130 $51,943 

7% Annual Increase $5,263 $8,985 $13,451 $16,627 $19,898 $64,224 

Max Net Benefits $5,217 $8,837 $12,535 $14,930 $17,050 $58,568 

TC = TB $5,674 $9,779 $13,898 $16,673 $19,403 $65,427 

Light Trucks 

Preferred Alternative $1,754 $2,479 $3,657 $4,318 $5,369 $17,578 

3% Annual Increase $8 $463 $1,371 $2,009 $2,719 $6,570 

4% Annual Increase $968 $1,747 $2,975 $3,714 $4,647 $14,051 

5% Annual Increase $2,407 $3,791 $6,103 $6,833 $7,614 $26,749 

6% Annual Increase $2,950 $5,646 $8,157 $9,813 $11,226 $37,793 

7% Annual Increase $3,260 $7,298 $10,020 $12,478 $14,074 $47,130 

Max Net Benefits $4,149 $7,370 $9,698 $11,163 $11,648 $44,028 

TC = TB $4,247 $7,891 $10,464 $12,330 $13,218 $48,149 

Passenger Cars & Light Trucks 

Preferred Alternative $5,903 $7,890 $10,512 $12,539 $14,904 $51,748 

3% Annual Increase $1,630 $2,804 $4,513 $6,057 $7,941 $22,944 

4% Annual Increase $3,116 $5,202 $7,919 $10,275 $12,678 $39,189 

5% Annual Increase $5,482 $9,079 $13,529 $16,243 $19,017 $63,350 

6% Annual Increase $7,455 $12,842 $18,724 $23,359 $27,356 $89,736 

7% Annual Increase $8,524 $16,283 $23,471 $29,104 $33,972 $111,354 

Max Net Benefits $9,366 $16,207 $22,233 $26,092 $28,698 $102,597 

TC = TB $9,921 $17,670 $24,362 $29,003 $32,620 $113,577 

 

4

 Includes technology costs and societal costs, but does not include fines. 
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Table 4 

Present Value of Lifetime Societal Benefits5

, 

by Alternative (3% Discount Rate) 

(Millions of 2007 Dollars) 

Alternative 

MY 

2012 

MY 

2013 

MY 

2014 

MY 

2015 

MY 

2016 

5-Year 

Total 

Passenger Cars 

Preferred Alternative $6,826 $15,155 $21,626 $28,677 $35,200 $107,483 

3% Annual Increase $3,397 $8,374 $12,331 $16,760 $23,122 $63,984 

4% Annual Increase $4,186 $11,006 $17,315 $24,469 $32,309 $89,286 

5% Annual Increase $6,152 $15,404 $24,075 $32,114 $40,905 $118,649 

6% Annual Increase $7,071 $18,062 $28,137 $37,552 $47,754 $138,576 

7% Annual Increase $8,038 $20,627 $32,225 $42,010 $52,606 $155,507 

Max Net Benefits $8,019 $20,896 $31,683 $39,863 $48,228 $148,689 

TC = TB $8,666 $22,374 $33,916 $42,737 $51,659 $159,352 

Light Trucks 

Preferred Alternative $5,110 $10,684 $15,506 $19,364 $24,310 $74,974 

3% Annual Increase $687 $3,920 $7,635 $11,604 $14,940 $38,786 

4% Annual Increase $2,590 $7,361 $12,580 $17,089 $21,830 $61,450 

5% Annual Increase $4,003 $10,407 $17,686 $23,206 $28,324 $83,626 

6% Annual Increase $4,893 $13,933 $22,031 $28,987 $34,727 $104,571 

7% Annual Increase $5,634 $16,326 $25,550 $32,714 $38,229 $118,453 

Max Net Benefits $7,528 $18,302 $25,913 $31,563 $34,835 $118,141 

TC = TB $7,631 $18,954 $27,294 $33,381 $37,262 $124,522 

Passenger Cars & Light Trucks 

Preferred Alternative $11,936 $25,840 $37,132 $48,040 $59,509 $182,457 

3% Annual Increase $4,085 $12,294 $19,966 $28,364 $38,062 $102,770 

4% Annual Increase $6,776 $18,367 $29,895 $41,559 $54,139 $150,735 

5% Annual Increase $10,155 $25,811 $41,760 $55,320 $69,229 $202,275 

6% Annual Increase $11,964 $31,995 $50,168 $66,539 $82,481 $243,147 

7% Annual Increase $13,672 $36,953 $57,776 $74,724 $90,835 $273,960 

Max Net Benefits $15,547 $39,198 $57,596 $71,426 $83,063 $266,830 

TC = TB $16,297 $41,328 $61,209 $76,118 $88,922 $283,874 

 

5

 These benefits are considered from a “societal perspective” because they include externalities. They are 

distinguished from a consumer perspective, because consumers generally would not think about the value of carbon 

dioxide, etc. 
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Table 5 

Present Value of 

Net Total Benefits6

 by Alternative 

(Millions of 2007 Dollars) 

(3% Discount Rate) 

Alternative MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 5-Year Total 

Passenger Cars 

Preferred Alternative $2,677 $9,745 $14,770 $20,455 $25,665 $73,313 

3% Annual Increase $1,776 $6,033 $9,188 $12,713 $17,900 $47,609 

4% Annual Increase $2,038 $7,551 $12,371 $17,909 $24,278 $64,147 

5% Annual Increase $3,077 $10,116 $16,649 $22,704 $29,502 $82,048 

6% Annual Increase $2,567 $10,866 $17,570 $24,005 $31,624 $86,633 

7% Annual Increase $2,775 $11,642 $18,775 $25,383 $32,709 $91,283 

Max Net Benefits $2,802 $12,059 $19,148 $24,933 $31,179 $90,121 

TC = TB $2,992 $12,595 $20,017 $26,064 $32,257 $93,925 

Light Trucks 

Preferred Alternative $3,356 $8,205 $11,849 $15,045 $18,940 $57,396 

3% Annual Increase $679 $3,458 $6,264 $9,595 $12,222 $32,217 

4% Annual Increase $1,622 $5,614 $9,605 $13,375 $17,183 $47,399 

5% Annual Increase $1,596 $6,616 $11,582 $16,373 $20,710 $56,877 

6% Annual Increase $1,943 $8,287 $13,874 $19,174 $23,501 $66,779 

7% Annual Increase $2,373 $9,028 $15,531 $20,236 $24,155 $71,324 

Max Net Benefits $3,379 $10,932 $16,215 $20,400 $23,186 $74,112 

TC = TB $3,384 $11,063 $16,830 $21,050 $24,045 $76,373 

Passenger Cars & Light Trucks 

Preferred Alternative $6,033 $17,950 $26,619 $35,501 $44,606 $130,709 

3% Annual Increase $2,455 $9,490 $15,453 $22,307 $30,121 $79,826 

4% Annual Increase $3,660 $13,165 $21,976 $31,284 $41,461 $111,546 

5% Annual Increase $4,673 $16,732 $28,231 $39,076 $50,213 $138,925 

6% Annual Increase $4,509 $19,154 $31,444 $43,180 $55,125 $153,412 

7% Annual Increase $5,148 $20,670 $34,305 $45,619 $56,864 $162,606 

Max Net Benefits $6,181 $22,991 $35,363 $45,333 $54,365 $164,233 

TC = TB $6,377 $23,658 $36,847 $47,114 $56,301 $170,297 

 

6

 This table is from a societal perspective, thus, fines are deleted from the costs because they are a transfer payment. 
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Table 6 

Present Value of Lifetime Societal Benefits7

, 

by Alternative (7% Discount Rate) 

(Millions of 2007 Dollars) 

Alternative 

MY 

2012 

MY 

2013 

MY 

2014 

MY 

2015 

MY 

2016 

5-Year 

Total 

Passenger Cars 

Preferred Alternative $5,474 $12,255 $17,499 $23,235 $28,567 $87,031 

3% Annual Increase $2,727 $6,778 $9,980 $13,585 $18,774 $51,844 

4% Annual Increase $3,356 $8,904 $14,015 $19,838 $26,241 $72,353 

5% Annual Increase $4,941 $12,472 $19,493 $26,030 $33,185 $96,122 

6% Annual Increase $5,667 $14,612 $22,763 $30,402 $38,735 $112,180 

7% Annual Increase $6,448 $16,692 $26,080 $34,028 $42,669 $125,917 

Max Net Benefits $6,134 $16,378 $25,041 $31,517 $38,120 $117,191 

TC = TB $6,957 $18,112 $27,453 $34,625 $41,897 $129,044 

Light Trucks 

Preferred Alternative $4,015 $8,427 $12,243 $15,302 $19,225 $59,212 

3% Annual Increase $545 $3,099 $6,035 $9,178 $11,823 $30,679 

4% Annual Increase $2,035 $5,802 $9,927 $13,500 $17,260 $48,524 

5% Annual Increase $3,129 $8,189 $13,929 $18,300 $22,365 $65,913 

6% Annual Increase $3,823 $10,966 $17,349 $22,842 $27,385 $82,366 

7% Annual Increase $4,404 $12,838 $20,108 $25,767 $30,132 $93,248 

Max Net Benefits $5,736 $12,761 $18,525 $22,485 $25,290 $84,797 

TC = TB $6,039 $14,926 $21,502 $26,237 $29,295 $97,999 

Passenger Cars & Light Trucks 

Preferred Alternative $9,490 $20,682 $29,742 $38,538 $47,791 $146,243 

3% Annual Increase $3,272 $9,877 $16,014 $22,763 $30,597 $82,523 

4% Annual Increase $5,390 $14,706 $23,942 $33,338 $43,500 $120,877 

5% Annual Increase $8,070 $20,661 $33,422 $44,330 $55,551 $162,035 

6% Annual Increase $9,490 $25,579 $40,111 $53,245 $66,120 $194,545 

7% Annual Increase $10,852 $29,530 $46,187 $59,795 $72,801 $219,165 

Max Net Benefits $11,870 $29,140 $43,566 $54,002 $63,410 $201,988 

TC = TB $12,997 $33,037 $48,955 $60,862 $71,193 $227,044 

 

7

 These benefits are considered from a “societal perspective” because they include externalities. They are 

distinguished from a consumer perspective, because consumers generally would not think about the value of carbon 

dioxide, etc. 
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Table 7 

Present Value of 

Net Total Benefits8

 by Alternative 

(Millions of 2007 Dollars) 

(7% Discount Rate) 

Alternative MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 5-Year Total 

Passenger Cars 

Preferred Alternative $1,326 $6,844 $10,644 $15,014 $19,032 $52,861 

3% Annual Increase $1,106 $4,436 $6,838 $9,537 $13,552 $35,469 

4% Annual Increase $1,208 $5,449 $9,071 $13,277 $18,210 $47,215 

5% Annual Increase $1,867 $7,184 $12,067 $16,620 $21,782 $59,521 

6% Annual Increase $1,163 $7,416 $12,196 $16,856 $22,605 $60,237 

7% Annual Increase $1,185 $7,707 $12,629 $17,401 $22,771 $61,693 

Max Net Benefits $1,170 $7,894 $12,838 $16,969 $21,583 $60,454 

TC = TB $1,283 $8,333 $13,555 $17,952 $22,495 $63,617 

Light Trucks 

Preferred Alternative $2,261 $5,948 $8,586 $10,984 $13,855 $41,635 

3% Annual Increase $537 $2,636 $4,664 $7,169 $9,104 $24,110 

4% Annual Increase $1,067 $4,055 $6,952 $9,786 $12,613 $34,473 

5% Annual Increase $722 $4,398 $7,826 $11,467 $14,751 $39,164 

6% Annual Increase $872 $5,321 $9,192 $13,029 $16,159 $44,573 

7% Annual Increase $1,143 $5,540 $10,088 $13,289 $16,058 $46,119 

Max Net Benefits $1,647 $6,581 $10,195 $12,936 $15,123 $46,482 

TC = TB $1,579 $7,463 $10,988 $13,982 $16,229 $50,241 

Passenger Cars & Light Trucks 

Preferred Alternative $3,587 $12,792 $19,230 $25,998 $32,888 $94,495 

3% Annual Increase $1,642 $7,073 $11,501 $16,706 $22,656 $59,579 

4% Annual Increase $2,274 $9,504 $16,023 $23,064 $30,822 $81,688 

5% Annual Increase $2,589 $11,583 $19,893 $28,087 $36,534 $98,685 

6% Annual Increase $2,035 $12,737 $21,387 $29,885 $38,764 $104,810 

7% Annual Increase $2,328 $13,247 $22,717 $30,690 $38,829 $107,812 

Max Net Benefits $2,818 $14,475 $23,033 $29,904 $36,706 $106,936 

TC = TB $2,863 $15,795 $24,543 $31,933 $38,724 $113,858 

 

8

 This table is from a societal perspective, thus, fines are deleted from the costs because they are a transfer payment. 
12

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Table 8 

Savings in Millions of Gallons of Fuel 

Undiscounted Over the Lifetime of the Model Year 

Alternative 

MY 

2012 

MY 

2013 

MY 

2014 

MY 

2015 

MY 

2016 

5-Year 

Total 

Passenger Cars 

Preferred Alternative 2,396 5,153 7,233 9,446 11,433 35,660 

3% Annual Increase 1,197 2,845 4,120 5,509 7,490 21,161 

4% Annual Increase 1,476 3,740 5,787 8,046 10,475 29,524 

5% Annual Increase 2,157 5,230 8,066 10,630 13,381 39,463 

6% Annual Increase 2,520 6,200 9,530 12,589 15,770 46,609 

7% Annual Increase 2,855 7,086 10,933 14,080 17,419 52,374 

Max Net Benefits 2,848 7,159 10,731 13,324 15,893 49,956 

TC = TB 3,071 7,673 11,492 14,295 17,086 53,619 

Light Trucks 

Preferred Alternative 1,805 3,698 5,281 6,504 8,061 25,350 

3% Annual Increase 234 1,349 2,589 3,882 4,935 12,988 

4% Annual Increase 916 2,557 4,298 5,751 7,251 20,773 

5% Annual Increase 1,434 3,631 6,076 7,856 9,463 28,460 

6% Annual Increase 1,758 4,869 7,584 9,859 11,677 35,747 

7% Annual Increase 2,019 5,718 8,813 11,139 12,866 40,555 

Max Net Benefits 2,688 6,395 8,919 10,735 11,700 40,437 

TC = TB 2,724 6,621 9,392 11,348 12,507 42,591 

Passenger Cars & Light Trucks 

Preferred Alternative 4,201 8,851 12,514 15,950 19,494 61,010 

3% Annual Increase 1,431 4,193 6,709 9,391 12,425 34,149 

4% Annual Increase 2,391 6,296 10,085 13,798 17,726 50,297 

5% Annual Increase 3,590 8,860 14,142 18,486 22,845 67,923 

6% Annual Increase 4,279 11,069 17,114 22,448 27,447 82,356 

7% Annual Increase 4,875 12,804 19,746 25,219 30,285 92,929 

Max Net Benefits 5,536 13,555 19,650 24,059 27,593 90,392 

TC = TB 5,795 14,294 20,884 25,643 29,593 96,210 
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Breakdown of costs and benefits for the preferred alternative

Tables 9 and 10 provides a breakdown of the costs and benefits for the preferred alternative 

using a 3 percent and 7 percent discount rate, respectively, safety estimates are not included. 

Table 9 

Preferred Alternative 

Cost and Benefit Estimates 

Passenger Cars and Light Trucks Combined 

3% Discount Rate 

MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 Total 

Technology Costs $5,695 $9,295 $12,454 $15,080 $17,633 $60,157 

Benefits 

Lifetime Fuel Expenditures $10,197 $22,396 $32,715 $41,880 $50,823 $158,012 

Consumer Surplus from 

Additional Driving $751 $1,643 $2,389 $3,029 $3,639 $11,451 

Refueling Time Value $776 $1,551 $2,198 $2,749 $3,277 $10,550 

Petroleum Market Externalities $559 $1,194 $1,700 $2,129 $2,538 $8,121 

Congestion Costs ($460) ($934) ($1,332) ($1,657) ($1,991) ($6,376)

Noise Costs ($7) ($14) ($21) ($26) ($31) ($99)

Crash Costs ($217) ($437) ($625) ($776) ($930) ($2,985)

CO2 $1,028 $2,287 $3,382 $4,376 $5,372 $16,446 

CO $0 $0 $0 $0 $0 $0 

VOC $41 $80 $108 $131 $156 $518 

NOX $82 $132 $155 $174 $200 $744 

PM $220 $438 $621 $771 $904 $2,956 

SOX $161 $345 $490 $613 $731 $2,341 

Total $13,132 $28,680 $41,781 $53,394 $64,687 $201,676 

Net Benefits $7,044 $18,759 $27,090 $34,710 $41,386 $128,992 
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Table 10 

Preferred 

Alternative 

Cost and Benefit Estimates 

Passenger Cars and Light Trucks Combined 

7% Discount Rate 

MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 Total 

Technology Costs $5,695 $9,295 $12,454 $15,080 $17,633 $60,157 

Benefits 

Lifetime Fuel Expenditures $7,991 $17,671 $25,900 $33,264 $40,478 $125,305 

Consumer Surplus from 

Additional Driving $590 $1,301 $1,896 $2,412 $2,904 $9,102 

Refueling Time Value $624 $1,249 $1,770 $2,215 $2,642 $8,500 

Petroleum Market Externalities $448 $960 $1,367 $1,712 $2,043 $6,531 

Congestion Costs ($371) ($753) ($1,074) ($1,335) ($1,606) ($5,138)

Noise Costs ($6) ($12) ($16) ($21) ($24) ($80)

Crash Costs ($173) ($352) ($503) ($626) ($749) ($2,403)

CO2 $797 $1,781 $2,634 $3,410 $4,189 $12,813 

CO $0 $0 $0 $0 $0 $0 

VOC $33 $65 $87 $106 $125 $416 

NOX $60 $99 $120 $135 $156 $570 

PM $170 $344 $492 $613 $721 $2,339 

SOX $129 $278 $394 $493 $588 $1,882 

Total $10,292 $22,631 $33,066 $42,380 $51,468 $159,837 

Net Benefits $4,281 $12,832 $18,818 $24,414 $29,293 $89,638 
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I. INTRODUCTION 

The purpose of this study is to analyze the effects of changes in the fuel economy standards for 

passenger cars and for light trucks for MY 2012 - 2016. It includes a discussion of the 

technologies that can improve fuel economy, the potential impacts on retail prices, safety, the 

discounted lifetime net benefits of fuel savings, and the potential gallons of fuel saved. 

The agency issued a final rule on April 7, 2003 (68 FR 16868), setting the CAFE standard 

applicable to light trucks for MY 2005 at 21.0 mpg, for MY 2006 at 21.6 mpg, and for MY 2007 

at 22.2 mpg. On April 6, 2006 (71 FR 17566), the agency issued a final rule for light trucks for 

MYs 2008 to 2011 under a new “CAFE Reform” structure. 

In December 2007, Congress passed the Energy Independence and Security Act (EISA). EISA 

mandates the setting of separate standards for passenger cars and for light trucks at levels 

sufficient to ensure that the average fuel economy of the combined fleet of all passenger cars and 

light trucks sold by all manufacturers in the U.S. in model year 2020 equals or exceeds 35 miles 

per gallon. EISA additionally gave NHTSA authority to reform passenger car CAFE, allowing 

the agency to set standards for those vehicles according to an attribute-based mathematical 

function. 

In mid-October 2008, the agency completed and released a final environmental impact statement 

in anticipation of issuing standards for those years. Based on its consideration of the public 

comments and other available information, including information on the financial condition of 

the automotive industry, the agency adjusted its analysis and the standards and prepared a final 

rule and Final Regulatory Impact Analysis (FRIA) for MYs 2011-2015. On November 14, the 

Office of Information and Regulatory Affairs (OIRA) of the Office of Management and Budget 

concluded review of the rule and FRIA.9

 However, issuance of the final rule was held in 

abeyance. On January 7, 2009, the Department of Transportation announced that the final rule 

would not be issued, writing: 

The Bush Administration will not finalize its rulemaking on Corporate Fuel 

Economy Standards. The recent financial difficulties of the automobile industry 

will require the next administration to conduct a thorough review of matters 

affecting the industry, including how to effectively implement the Energy 

Independence and Security Act of 2007 (EISA). The National Highway Traffic 

Safety Administration has done significant work that will position the next 

Transportation Secretary to finalize a rule before the April 1, 2009 deadline.10

In light of the requirement to prescribe standards for MY 2011 by March 30, 2009 and in order 

to provide additional time to consider issues concerning the analysis used to determine the 

appropriate level of standards for MYs 2012 and beyond, the President issued a memorandum on 

January 26, 2009, requesting the Secretary of Transportation and Administrator of the National 

9

 Record of OIRA’s action can be found at http://www.reginfo.gov/public/do/eoHistReviewSearch (last visited 

March 4, 2010). To find the report on the clearance of the draft final rule, select “Department of Transportation” 

under “Economically Significant Reviews Completed” and select “2008” under “Select Calendar Year.” 

10 The statement can be found at http://www.dot.gov/affairs/dot0109.htm (last accessed March 4, 2010). 
16

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Highway Traffic Safety Administration NHTSA to divide the rulemaking into two parts: (1) MY 

2011 standards, and (2) standards for MY 2012 and beyond. 

The request that the final rule establishing CAFE standards for MY 2011 passenger cars and 

light trucks be prescribed by March 30, 2009 was based on several factors. One was the 

requirement that the final rule regarding fuel economy standards for a given model year must be 

adopted at least 18 months before the beginning of that model year (49 U.S.C. 32902(g)(2)). The 

other was that the beginning of MY 2011 is considered for the purposes of CAFE standard 

setting to be October 1, 2010. As part of that final rule, the President requested that NHTSA 

consider whether any provisions regarding preemption are consistent with the EISA, the 

Supreme Court's decision in Massachusetts v. EPA and other relevant provisions of law and the 

policies underlying them. 

The President requested that, before promulgating a final rule concerning the model years after 

model year 2011, NHTSA

[C]onsider the appropriate legal factors under the EISA, the comments filed in 

response to the Notice of Proposed Rulemaking, the relevant technological and 

scientific considerations, and to the extent feasible, the forthcoming report by the 

National Academy of Sciences mandated under section 107 of EISA. 

In addition, the President requested that NHTSA further consider whether any provisions 

regarding preemption are appropriate under applicable law and policy. 

On March 20, 2009 (74 FR 14196) NHTSA issued a final rule for MY 2011 passenger cars and 

light trucks, superseding the previously issued final rule for MY 2011 light trucks. Similar to 

this report, a Final Regulatory Impact Analysis accompanied that final rule.11 

In keeping with the President’s remarks on January 26 for new national policies to address the 

closely intertwined issues of energy independence, energy security and climate change, and for 

the initiation of serious and sustained domestic and international action to address them, NHTSA 

and EPA proposed standards for MY 2012 - 2016 after collecting new information, conducting a 

careful review of technical and economic inputs and assumptions, and standard setting 

methodology, and completing new analyses. The NPRM was issued on September 22, 2009 (74 

FR 48192) and it was accompanied by a Preliminary Regulatory Impact Analysis, Corporate 

Average Fuel Economy for MY 2012-MY 2016 Passenger Cars and Light Trucks, (Docket No. 

2009-0059-0016.1). 

The goal of the review and re-evaluation was to ensure that the approach used for MY 2012 and 

thereafter produces standards that contribute, to the maximum extent possible under 

EPCA/EISA, to meeting the energy and environmental challenges and goals outlined by the 

President. We seek to craft our program with the goal of creating the maximum incentives for 

innovation, providing flexibility to the regulated parties, and meeting the goal of making 

substantial and continuing reductions in the consumption of fuel. 

 

11 “Final Regulatory Impact Analysis, Corporate Average Fuel Economy for MY 2011 Passenger Cars and Light 

Trucks”, March 2009, Docket No. NHTSA-2009-0062-0004.1. 
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17

 

 

The dual fuel incentive program, through which manufacturers may improve their calculated fuel 

economies by producing vehicles capable of operating on alternative fuels, is not considered in 

this analysis. By law, the agency has always analyzed fuel economy without considering the 

dual fuel credits.12 

Throughout this analysis, unless otherwise noted, the agency has not considered the ability of 

manufacturers to use credits or credit trading in achieving the alternative fuel economy levels. 

This is also a statutory requirement.13 

Throughout this document, confidential information is presented in brackets [ ].

12 See 49 U.S.C. § 32902(h) 

13 Id. 
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II. NEED OF THE NATION TO CONSERVE ENERGY 

The Energy Policy and Conservation Act (EPCA) states that: 

“When deciding maximum feasible average fuel economy ... the Secretary of 

Transportation shall consider technological feasibility, economic practicability, the 

effect of other motor vehicle standards of the Government on fuel economy, and the 

need of the United States to conserve energy.”14

Thus, (EPCA) specifically directs the Department to balance the technological and economic 

challenges related to fuel economy with the nation's need to conserve energy. The concerns 

about energy security and the effects of energy prices and supply on national economic wellbeing that led to the enactment of EPCA persist today. The demand for petroleum grew in the 

U.S. up through the year 2005 and is now declining slowly averaging approximately 19.4 million 

barrels per day in 2008.15 World demand, however, is expected to continue to rise until 2030.16

Since 1970, there have been a series of events that suggest that the behavior of petroleum 

markets is a matter for public concern. 

• Average annual crude oil prices rose from $68 per barrel in 2007 to $99 per barrel in 

2008, having peaked at $129 per barrel in July 2008. Prices declined to $49 per barrel in 

April 2009, but then rose to $75 per barrel in February 2010.17 As recently as 1998, 

crude prices averaged about $13 per barrel.18 Gasoline prices more than doubled during 

this ten-year period, from $1.22 in 1998 to $3.32 in 2008, declining to $2.75 in early 

March 2010.19

• U.S. domestic petroleum production stood at 10 million barrels per day in 1975, rose 

slightly, then declined to 6.7 million barrels per day in 2008. Between 1975 and 2008, 

U.S. petroleum consumption increased from 16.3 million barrels per day to 20.8 million 

barrels per day. In 2008, net petroleum imports accounted for 57 percent of U.S. 

domestic petroleum consumption.20 

• Worldwide oil demand is fairly inelastic: declining prices do not induce large increases 

in consumption, while higher prices do not significantly restrain consumption. For 

example, the price of unleaded regular gasoline rose from an average of $2.59 in 2006 to 

$2.80 in 2007 (an 8.1 percent increase) and vehicle miles traveled decreased by 0.6 

14 49 U.S.C. § 32902(f) 

15 U.S. Department of Energy, Energy Information Administration, Petroleum Basic Statistics, October 2009. 

 See http://www.eia.doe.gov/emeu/international/oilconsumption.html (last accessed March 4, 2010). 16 U.S. Department of Energy, Energy Information Administration, International Energy Outlook 2009. 

See http://www.eia.doe.gov/oiaf/ieo/highlights.html (last accessed March 4, 2010). 17 U.S. Department of Energy, Energy Information Administration, World Crude Oil Prices. See

http://tonto.eia.doe.gov/dnav/pet/pet_pri_wco_k_w.htm (last accessed March 4, 2010). 

18 U.S. Department of Energy, Energy Information Administration, Petroleum Marketing Monthly, July 2009, 

Table 1. See

http://www.eia.doe.gov/oil_gas/petroleum/data_publications/petroleum_marketing_monthly/pmm.html (last 

accessed March 4, 2010). 

19 U.S. Department of Energy, Energy Information Administration, Weekly Retail and Gasoline Diesel Prices. See

http://tonto.eia.doe.gov/dnav/pet/pet_pri_gnd_dcus_nus_w.htm (last accessed March 4, 2010). 

20 U.S. Department of Energy, Energy Information Administration, Monthly Energy Review, February 2010. See 

http://www.eia.doe.gov/emeu/mer/pdf/pages/sec3_7.pdf (last accessed March 4, 2010). 
19

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carbon dioxide emissions. 

es a 

bove, U.S. energy consumption has increasingly been outstripping U.S. energy production. 

ile imports of 

etroleum have been increasing to meet the rising U.S. demand for petroleum. 

y security and can reduce the flow 

f oil profits to certain states now hostile to the U.S. 

lting in more fuel-efficient vehicles, i.e., vehicles 

requiring less fuel consumption per unit mile.

 

percent. Within the United States, demand for gasoline, diesel, and jet fuel within the 

transportation sector is particularly inelastic. 

• Demand for oil may increase significantly in Asia and worldwide in the future resulting 

in upward oil cost pressure. 

• Foreign oil production facilities, refineries, and supply chains have been disrupted from 

time to time, either by wars, political action by oil producers, civil unrest, or natural 

disasters. 

• High oil prices, sometimes induced by disruptions in oil markets, have often coincided 

with rising inflation and subsequent economic recessions. 

• Greenhouse gas emissions from the consumption of petroleum have become a subject of 

increasing public policy concern, both in the United States and internationally. 

Greenhouse gases in general and carbon dioxide in particular have not thus far been 

subject to national regulation. Studies by multiple sources suggest that rising 

atmospheric concentrations of greenhouse gases will damage human health and 

welfare.21 There is a direct linkage between the consumption of fossil energy and 

emissions of the greenhouse gas carbon dioxide, as essentially all of the carbon in 

hydrocarbon fuels is oxidized into carbon dioxide when the fuel is combusted. Reducing 

U.S. fossil petroleum consumption will generally induce a proportional reduction in 

Energy is an essential input to the U.S. economy, and having a strong economy is essential to

maintaining and strengthening our national security. Secure, reliable, and affordable energy 

sources are fundamental to economic stability and development. Rising energy demand pos

challenge to energy security, given increased reliance on global energy markets. As noted 

a

Table II-1 presents trend data on the production and consumption of petroleum for 

transportation. Domestic petroleum production has been decreasing over time, wh

p

Conserving energy, especially reducing the nation’s dependence on petroleum, benefits 

the U.S. in several ways. Improving energy efficiency has benefits for economic growth 

and the environment, as well as other benefits, such as reducing pollution and improving 

security of energy supply. More specifically, reducing total petroleum use decreases our 

economy’s vulnerability to oil price shocks. Reducing dependence on oil imports from 

regions with uncertain conditions enhances our energ

o

This CAFE final rule encourages conservation of petroleum for transportation by the application 

of broader use of fuel saving technologies, resu

21 IPCC 2007: Climate Change 2007: Synthesis Report: Contributions of Working Groups I, II, and III to the 

Fourth Assessment Report of the Intergovernmental Panel on Climate Change, [Core writing team, Pachauri, R.K. 

and Reisinger, A. 9eds.)] (Published by the Intergovernmental Panel on Climate Change, 2008). Available at 

http://www.ipcc.ch/, (last accessed March 4, 2010). 
20

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21

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Table II-1 

Petroleum Production and Supply 

(Million Barrels per Day)22

 

Domestic 

Petroleum 

Production 

Net 

Petroleum 

Imports 

U.S. 

Petroleum 

Consumption

World 

Petroleum 

Consumption 

Net Imports 

as a Share of 

U.S. 

Consumption 

1975 10.0 5.8 16.3 56.2 35.8% 

1985 10.6 4.3 15.7 60.1 27.3% 

1995 8.3 7.9 17.7 70.1 44.5% 

2005 6.9 12.5 20.8 84.0 60.3% 

2008 6.7 11.0 19.4 N/A 56.9% 

DOE 

Predictions 

 

2015 7.6 9.7 20.2 90.6 49% 

2025 9.1 8.0 20.8 101.1 40% 

2030 9.3 8.4 21.7 106.6 41% 

Note: DOE predictions are based on petroleum demand. 

Table II-2 

Petroleum 

Transportation Consumption by Mode 

(Thousand Barrels per Day)23

 

Passenger 

Cars 

Light 

Trucks 

Total Light 

Vehicles 

Total 

Transportation

Light 

Vehicles as 

% of Trans. 

1975 4,836 1,245 6,081 8,474 72% 

1985 4,665 1,785 6,450 9,538 68% 

1995 4,440 2,975 7,415 11,347 65% 

2005 5,050 3,840 8,890 13,537 66% 

2007 4,850 4,032 8,883 13,710 65% 

 

22 U.S. Department of Energy, EIA, Monthly Energy Review, February 2010, Table 3.1. Available at

http://www.eia.doe.gov/emeu/mer/petro.html (last accessed March 4, 2010). U.S. Department of Energy, EIA, 

Annual Energy Outlook 2009, Table 20. Available at

http://www.eia.doe.gov/oiaf/archive/aeo09/pdf/0383(2009).pdf (last accessed March 4, 2010). 

23 U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Transportation Energy Data 

Book, Table 1.14. Available at http://cta.ornl.gov/data/chapter1.shtml (last accessed March 4, 2010). 
22

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23

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f 

odel year 2008 data. The baseline fleet is created in order to 

track th volumes and types of fuel economy-improving technologies which are already present 

ards. 

. How was the baseline vehicle fleet developed? 

data 

t required 

SD. 

III. BASELINE AND ALTERNATIVES 

A. The baseline vehicle fleet 

1. Why establish a baseline vehicle fleet? 

In order to calculate the impacts of the final rule, it is necessary to estimate the composition o

the future vehicle fleet absent the final CAFE standards in order to conduct comparisons. EPA 

in consultation with NHTSA developed a comparison fleet in two parts. The first step was to 

develop a baseline fleet based on m

e

in today’s fleet. Creating a baseline fleet helps to keep, to some extent, the agencies’ models 

from adding technologies to vehicles that already have these technologies, which would result in 

“double counting” of technologies’ costs and benefits. The second step was to project the 

baseline fleet sales into MYs 2011-2016. This is called the reference fleet, and it represents the 

fleet that would exist in MYs 2011-2016 absent any change from current regulations. The third 

step was to add technologies to that fleet such that each manufacturer’s average car and truck 

CO2 levels are in compliance with their MY 2011 CAFE standards. This final “reference fleet” 

is the light duty fleet estimated to exist in MYs 2012-2016 without the final CAFE stand

All of the agency’s estimates of fuel economy improvements, costs, and societal impacts are 

developed in relation to the respective reference fleets. 

2

At proposal, EPA and NHTSA developed a baseline fleet comprised of model year 2008 

gathered from EPA’s emission certification and fuel economy database. MY 2008 was used as

the basis for the baseline vehicle fleet because it was the most recent model year for which a 

complete set of data is publicly available. This remains the case. Manufacturers are no

to submit final sales and mpg figures for MY 2009 until April 2010, 24 after the CAFE standard’s

mandated promulgation date. Consequently, in this final rule, EPA and NHTSA made no 

changes to the method or the results of the MY 2008 baseline fleet used at proposal, except for 

some specific corrections to engineering inputs for some vehicle models reflected in the market 

forecast input to NHTSA’s CAFE model. More details about how the agencies constructed this 

baseline fleet can be found in Chapter 1.2 of the Joint TSD. Corrections to engineering inputs 

for some vehicle models in the market forecast input to NHTSA’s CAFE model are discussed in

Chapter 2 of the Joint T

3. How was the projected MY 2011-2016 vehicle fleet developed? 

EPA and NHTSA have based the projection of total car and total light truck sales for MYs 2011-

2016 on projections made by the Department of Energy’s Energy Information Administration 

(EIA). EIA publishes a mid-term projection of national energy use called the Annual Energy 

 

Outlook (AEO). This projection utilizes a number of technical and econometric models which 

are designed to reflect both economic and regulatory conditions expected to exist in the future. 

In support of its projection of fuel use by light-duty vehicles, EIA projects sales of new cars and 

 el Year Report 24 40 CFR 600.512-08, Mod
24

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in 

f 

. Although 

e total level of sales of 16.5 million units is similar to pre-2008 levels, the fraction of car sales 

rage 

el 

FE standards—of a number of 2-wheel drive sport utility 

vehicles from the truck fleet to the car fleet for MYs 2011 and after. Sales projections of cars 

and trucks for future model years can be found in the Joint TSD for these final rules. 

In addition to a shift towards more car sales, sales of segments within both the car and truck 

markets have been changing and are expected to continue to change. Manufacturers are 

introducing more crossover models which offer much of the utility of SUVs but use more carlike designs. The AEO 2010 report does not, however, distinguish such changes within the car 

and truck classes. In order to reflect these changes in fleet makeup, EPA and NHTSA 

considered several other available forecasts. EPA purchased and shared with NHTSA forecasts 

from two well-known industry analysts, CSM Worldwide (CSM), and J.D. Powers. NHTSA and 

EPA decided to use the forecast from CSM, modified as described below, for several reasons 

presented in the NPRM preamble26 and draft Joint TSD. The changes between company market 

share and industry market segments were most significant from 2011-2014, while for 2014-2015 

the changes were relatively small. Noting this, and lacking a credible forecast of company and 

segment shares after 2015, the agencies assumed 2016 market share and market segments to be 

the same as for 2015. 

CSM Worldwide provides quarterly sales forecasts for the automotive industry. In the NPRM, 

the agencies identified a concern with the 2nd quarter CSM forecast that was used as a basis for 

light trucks. In the proposal, the agencies used the three reports published by EIA as part of the 

AEO 2009. We also stated that updated versions of these reports could be used in the final rules 

should AEO timely issue a new version. EIA published an early version of its AEO 2010 

December 2009, and the agencies are making use of it in this final rulemaking. The differences 

in projected sales in the 2009 report (used in the NPRM) and the early 2010 report are very 

small, so NHTSA and EPA have decided to simply scale the NPRM volumes for cars and trucks 

(in the aggregate) to match those in the 2010 report. We thus employ the sales projections 

from the scaled updated 2009 Annual Energy Outlook, which is equivalent to AEO 2010 Early 

Release, for the final rule. The scaling factors for each model year are presented in Chapter 1 o

the Joint TSD for this final rule. 

In the AEO 2010 Early Release, EIA projects that total light-duty vehicle sales will gradually 

recover from their currently depressed levels by around 2013. In 2016, car sales are projected to 

be 9.4 million (57 percent) and truck sales are projected to be 7.1 million (43 percent)

25

th

is projected to be higher than that existing in the 2000-2007 timeframe. This projection reflects 

the impact of higher fuel prices, as well as EISA’s requirement that the new vehicle fleet ave

at least 35 mpg by MY 2020. The agencies note that AEO does not represent the fleet at a lev

of detail sufficient to explicitly account for the reclassification—promulgated as part of 

NHTSA’s final rule for MY 2011 CA

the projection. CSM projections at that time were based on an industry that was going through a 

significant financial transition, and as a result the market share forecasts for some companies 

 

25 EPA and NHTSA have evaluated the differences between the AEO 2010 (early draft) and AEO 2009 and found 

refore conclude that EIA has made no significant changes to 

little difference in the fleet projections (or fuel prices). This analysis can be found in the memo to the docket: 

(Docket EPA-HQ-OAR-2009-0472). The agencies the

its projections. 

26 See, e.g., 74 FR 49484. 
25

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were impacted in surprising ways. As the indus ation has settled somewhat over the past 

y

fold increase in sales for Chrysler compared t cant loss of market share shown for 

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et for this ru

f 

e, copies of t

making.29

by m

and 

he 2 , 3 , 

We then projec the CSM for sts for rela ive sales of nd truck by manufac urer and by 

market s

show t

 the total sales 

rojections f

estimates of 

r the referen

AEO 2010. Tab

2016 mod

les III.

 year and co

-1 and III.A

pare these t

.3-2 

o actual 

e 2 ad

d light truc

 ye

 

bl

definitio

 usually large 27 GM argued that the un vo quire

As discussed below, the agencies’ analysis for the al rule corrects the number of l e pickups. W this 

tion and other up e o r t c

ng e final stand ev e rm f

are very similar to those from the NPRM, especially for light trucks. 

28 These include the Ford F-250 & F-350, Econoline E-250, & E-350; Chevy Express, Silverado 2500, & 3500; 

GMC Savana, Dodge 2500, & 3500; among others. 

29 The CSM Sales Forecast Excel file (“CSM North America Sales Forecasts 2Q09 3Q09 4Q09 for the Docket”) is 

available in the docket (Docket EPA-HQ-OAR-2009-0472). 

lume of large pickups led to higher overall re ments for those vehicles. 

fin

ncies’ market f

ing the averag

arg

analytical inpu

ance levels de

ith 

s, the target fun

ining the nation

correc

defini

dates to the ag

ards (and achi

recast and othe

required perfo

tions 

 th al program) 
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 Cars Light Trucks Total 

Table III-1. Annual Sales of Light-Duty Vehicles by Manufacturer in 2008 and Estimated for 

2016 

2008 MY 2016 MY 2 8 MY 2016 MY Y 00 2008 M 2016 MY 

BMW 

 

 

 

291,796 424,923 61,324 171,560 353,120 596,482 

Chrysler 

 

537,808 5, 5

 

340,908 1,119,397 52 128 1,657,20 866,037 

Daimler 

 

208,052 272,252 126, 7

 

 79,135 880 287,18 399,133 

Ford 

 

709,583 3, 8

 

1,118,727 1,158,805 1,36 256 1,868,38 2,481,983 

General Motor

 

s 1,370,280 95,054

 

230,705 1,749,227 3,119,507 325,760 

Honda 

 

899,498 

 

1,283,937 612,281 1,585,828 1,511,779 2,869,766 

Hyundai 

 

270,293 

 

811,214 120,734 671,437 391,027 1,482,651 

Kia 

 

145,863 

 

401,372 135,589 211,996 281,452 613,368 

Mazda 

 

191,326 

 

455,643 111,220 210,717 302,546 666,360 

Mitsubishi 76,701 350,055 24,028 144,992 100,729 

 

 495,047 

Porsche 18,909 49,914 18,797 88,754 37,706 138,668 

 

Nissan 20 

 

653,121 

 

33,471 370,294 16,749 1,023,415 50,2

Subaru 876,677 49,211 457,114 198,581 1,333,790 

 

149,370

 

S

 

uzuki 68,720 97,466 45,938 26,108 114,658 123,574 

Tata 1 

 

9,596 

 

65,806 55,584 42,695 65,180 108,50

Toyota 002 

 

1,143,696 

 

2,069,283 1,067,804 1,249,719 2,211,500 3,319,

Volkswa en g 290,385 586,011 26,999 124,703 317,384 710,011 

 

Total 

 

7,034,997 

 

9,468,365 6,806,367 7,112,689 13,841,364 16,580,353
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Table III-2. Annual S ty Vehicles b in 2008 and Estimated for 

2016 

Cars Light Trucks 

ales of Light-Du y Market Segment 

2008 MY 2016 MY 2008 MY 2016 MY 

Full-Size Car 829,896 530,945 Full-Size Pickup 1,331,989 1,379,036 

Luxury Car 1,048,341 1,548,242 Mid-Size Pickup 452,013 332,082 

Mid-Size Car 2,166,849 2,550,561 Full-Size Van 33,384 65,650 

Mini Car 617,902 1,565,373 Mid-Size Van 719,529 839,194 

Small Car 1,912,736 2,503,566 Mid-Size MAV* 110,353 116,077 

Specialty Car 459,273 769,679 Small MAV 231,265 62,514 

 Full-Size SUV* 559,160 232,619 

 Mid-Size SUV 436,080 162,502 

 Small SUV 196,424 108,858 

 Full-Size CUV* 264,717 260,662 

 Mid-Size CUV 923,165 1,372,200 

 Small CUV 1,548,288 2,181,296 

Total Sales** 7,034,997 9,468,365 6,806,367 7,079,323 

* MAV – Multi-Activity Vehicle, SUV – Sport Utility Vehicle, CUV – Crossover Utility Vehicle 

**Total Sales are based on the classic Car/Truck definition. 

Determining which traditionally-defined trucks will be defined as cars for purposes of this 

analysis using the revised definition established by NHTSA for MYs 2011 and beyond requires 

more detailed information about each vehicle model. This is described in greater detail in 

Chapter 1 of the final TSD. 

The forecasts obtained from CSM provided estimates of car and truck sales by segment and by 

manufacturer, but not by manufacturer for each market segment. Therefore, NHTSA and EPA 

needed other information on which to base these more detailed projected market splits. For this 

task, th agencies used as a starting point each manufacturer’s sales by market segment from e 

model year 2008, which is the baseline fleet. Because of the larger number of segments in the 

truck market, the agencies used slightly different methodologies for cars and trucks. 

The first step for both cars and trucks was to break down each manufacturer’s 2008 sales 

according to the market segment definitions used by CSM. For example, the agencies found that 

Ford’s30 cars sales in 2008 were broken down as shown in Table III-3: 

 

30 Note: In the NPRM, Ford’s 2008 sales per segment, and the total number of cars was different than shown here

The change in values is due to a correction of vehicle segments for some of Ford’s vehicles. 

. 
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Table III-3. Breakdown of Ford’s 2008 Car Sales 

Full-size cars 160,857 units 

Mid-size Cars 170,399 units 

Small/Compact Cars 180,249 units 

Subcompact/Mini Cars None 

Luxury cars 87,272 units 

Specialty cars 110,805 units 

 

EPA and NHTSA then adjusted each manufacturer’s sales of each of its car segments (and truck 

segments, separately) so that the manufacturer’s total sales of cars (and trucks) matched the total 

estimated for each future model year based on AEO and CSM forecasts. For example, as 

 for cars, the agencies first adjusted sales of luxury, 

, any 

other 

s 

rs 

341 units in 2008. 

four 

e 

change over the remaining three segments, the agencies assigned the entire change to mid-size 

of 

indicat Table III-1, Ford’s total car sales in 2008 were 709,583 units, while the agencies 

project that they will increase to 1,113,333 units by 2016. This represents an increase of 56.9 

percent. Thus, the agencies increased the 2008 sales of each Ford car segment by 56.9 percent. 

This produced estimates of future sales which matched total car and truck sales per AEO and the 

manufacturer breakdowns per CSM. However, the sales splits by market segment would not 

necessarily match those of CSM (shown for 2016 in Table III-2). 

In order to adjust the market segment mix

ed in

specialty and other cars. Since the total sales of cars for each manufacturer were already set

changes in the sales of one car segment had to be compensated by the opposite change in an

segment. For the luxury, specialty and other car segments, it is not clear how changes in sale

would be compensated. For example, if luxury car sales decreased, would sales of full-size ca

increase, mid-size cars, and so on? The agencies have assumed that any changes in the sales of 

cars within these three segments were compensated for by proportional changes in the sales of 

the other four car segments. For example, for 2016, the figures in Table III.A.3-2 indicate that 

luxury car sales in 2016 are 1,548,242 units. Luxury car sales are 1,048,

Howev ter adjusting 2008 car sales by the change in total car sales for 2016 projected by 

EIA and a change in manufacturer market share per CSM, luxury car sales decreased to 

1,523,171 units. Thus, overall for 2016, luxury car sales had to increase by 25,071 units or 6 

percent. The agencies accordingly increased the luxury car sales by each manufacturer by this 

percentage. The absolute decrease in luxury car sales was spread across sales of full-size, midsize, compact and subcompact cars in proportion to each manufacturer’s sales in these segments 

in 2008. The same adjustment process was used for specialty cars and the “other cars” segment 

defined by CSM. 

The agencies used a slightly different approach to adjust for changing sales of the remaining 

car segments. Starting with full-size cars, the agencies again determined the overall percentag

change that needed to occur in future year full-size car sales after 1) adjusting for total sales per 

AEO 2010, 2) adjusting for manufacturer sales mix per CSM and 3) adjusting the luxury, 

specialty and other car segments, in order to meet the segment sales mix per CSM. Sales of each

manufacturer’s large cars were adjusted by this percentage. However, instead of spreading this

er, af

vehicles. The agencies did so because the CSM data followed the trend of increasing volumes 

smaller cars while reducing volumes of larger cars. If a consumer had previously purchased a 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

-size cars 

n opposite change in compact car sales. This process was repeated one more time 

for compact car sales, with changes in sales in this segment being matched by the opposite 

l 

e 

er vehicles to smaller 

vehicles would have been possible. However, the CSM forecasts indicated large changes in total 

er’s 

 left the need to adjust 

truck s es by segment to match the CSM forecast for each model year. 

o 

t 

s 

tion and CSM’s market segment forecast. However, after this step, sales by 

manufa turer no longer met CSM’s forecast. Thus, we repeated step three and adjusted each 

d AEO’s 

full-size car, we thought it unlikely that their next purchase would decrease by two size 

categories, down to a subcompact. It seemed more reasonable to project that they would drop 

one vehicle size category smaller. Thus, the change in each manufacturer’s sales of full

was matched by an opposite change (in absolute units sold) in mid-size cars. 

The same process was then applied to mid-size cars, with the change in mid-size car sales being

matched by a

change in the sales of subcompacts. The overall result was a projection of car sales for mode

years 2012-2016--the reference fleet--which matched the total sales projections of the AEO 

forecast and the manufacturer and segment splits of the CSM forecast. These sales splits can be 

found in Chapter 1 of the Joint TSD for the final rule. 

As mentioned above, the agencies applied a slightly different process to truck sales, because th

agencies could not confidently project how the change in sales from one segment preferentially 

went to or came from another particular segment. Some trend from larg

sport utility vehicle, multi-activity vehicle and cross-over sales which could not be connected. 

Thus, the agencies applied an iterative, but straightforward process for adjusting 2008 truck sales 

to match the AEO and CSM forecasts. 

The first three steps were exactly the same as for cars. EPA and NHTSA broke down each 

manufacturer’s truck sales into the truck segments as defined by CSM. The agencies then 

adjusted all manufacturers’ truck segment sales by the same factor so that total truck sales in 

each model year matched AEO projections for truck sales by model year. The agencies then 

adjusted each manufacturer’s truck sales by segment proportionally so that each manufactur

percentage of total truck sales matched that forecast by CSM. This again

al

In the fourth step, the agencies adjusted the sales of each truck segment by a common factor s

that total sales for that segment matched the combination of the AEO and CSM forecasts. For 

example, projected sales of large pickups across all manufacturers were 1,286,184 units in 2016

after adjusting total sales to match AEO’s forecast and adjusting each manufacturer’s truck sales 

to match CSM’s forecast for the breakdown of sales by manufacturer. Applying CSM’s forecas

of the large pickup segment of truck sales to AEO’s total sales forecast indicated total large 

pickup sales of 1,379,036 units. Thus, we increased each manufacturer’s sales of large pickup

by 7 percent.31 The agencies applied the same type of adjustment to all the other truck segments 

at the same time. The result was a set of sales projections which matched AEO’s total truck 

sales projec

c

manufacturer’s truck sales so that they met CSM’s forecast. The sales of each truck segment (by 

manufacturer) were adjusted by the same factor. The resulting sales projection matche

total truck sales projection and CSM’s manufacturer forecast, but sales by market segment no

 

31 Note: In the NPRM this example showed 29 percent instead of 7 percent. The significant decrease was due to 

using the filtered 4th quarter CSM forecast. Commenters, such as GM, had commented that we had too many fullsize trucks and vans, and this change addresses their comment. 
30

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

e 

.1 percent of our goal, which is well within the needs of this 

nalysis. 

The ne ithin each 

anufacturer-segment combination. In large part, this was based on the characterization of the 

 limited to vehicle models known to satisfy consumer demands in 

tility, performance, safety, and other vehicle attributes. 

otive 

segment. If the combination of AEO 

and CSM forecasts indicated an increase in a given manufacturer’s sales of a particular market 

les 

ct 

e 

average footprint to remain constant. First, as the number of subcompacts increases, so do the 

longer met CSM’s forecast. However, the difference between the sales projections after this fifth 

step was closer to CSM’s market segment forecast than it was after step three. In other words,

the sales projection was converging to the desired result. The agencies repeated these 

adjustments, matching manufacturer sales mix in one step and then market segment in the next a 

total of 19 times. At this point, we were able to match the market segment splits exactly and th

manufacturer splits were within 0

a

xt step in developing the reference fleets was to characterize the vehicles w

m

specific vehicle models sold in 2008 -- i.e., the vehicles comprising the baseline fleet. EPA and 

NHTSA chose to base our estimates of detailed vehicle characteristics on 2008 sales for several 

reasons. One, these vehicle characteristics are not confidential and can thus be published here 

for careful review by interested parties. Two, because it is constructed beginning with actual 

sales data, this vehicle fleet is

light of price, u

As noted above, the agencies gathered most of the information about the 2008 baseline vehicle 

fleet from EPA’s emission certification and fuel economy database. The data obtained from this

source included vehicle production volume, fuel economy, engine size, number of engine 

cylinders, transmission type, fuel type, etc. EPA’s certification database does not include a 

detailed description of the types of fuel economy-improving/CO2-reducing technologies 

considered in this final rule. Thus, the agencies augmented this description with publicly 

available data which includes more complete technology descriptions from Ward’s Autom

Group.32 In a few instances when required vehicle information (such as vehicle footprint) was 

not available from these two sources, the agencies obtained this information from publicly 

accessible internet sites such as Motortrend.com and Edmunds.com.33 

The projections of future car and truck sales described above apply to each manufacturer’s sales 

by market segment. The EPA emissions certification sales data are available at a much finer 

level of detail, essentially vehicle configuration. As mentioned above, the agencies placed each

vehicle in the EPA certification database into one of the CSM market segments. The agencies 

then totaled the sales by each manufacturer for each market 

segment, then the sales of all the individual vehicle configurations were adjusted by the same 

factor. For example, if the Prius represented 30 percent of Toyota’s sales of compact cars in 

2008 and Toyota’s sales of compact cars in 2016 was projected to double by 2016, then the sa

of the Prius were doubled, and the Prius sales in 2016 remained 30 percent of Toyota’s compa

car sales. 

The projection of average footprint for both cars and trucks remained virtually constant over the 

years covered by the final rulemaking. This occurrence is strictly a result of the CSM 

projections. There are a number of trends that occur in the CSM projections that caused th

 

32 Note that WardsAuto.com is a fee-based service, but all information is public to subscribers. 

33 Motortrend.com and Edmunds.com are free, no-fee internet sites. 
31

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

nd in any segment that can be linked to the unchanging footprint, but there is a trend 

that non-pickups’ volumes will move from truck segments that are ladder frame to those that are 

s 

ly 

he proposal discusses many of the advantages and disadvantages of the market forecast 

e 

 this could be advantageous in the development of a reference fleet. First, some 

known changes to the fleet may not be captured by the approach of solely using publicly 

dge 

to 

ing 

em, whose product plans specify which vehicles and 

how many are planned to have this technology. Chrysler Group LLC has announced plans to 

number of 2-wheel drive crossover vehicles (that are regulated as cars). Second, truck volumes

have many segment changes during the rulemaking time frame. There is no specific footprint 

related tre

unibody-type vehicles. A table of the footprint projections is available in the TSD as well as 

further discussion on this topic. 

4. How is the development of the baseline fleet for this rule different from NHTSA’

historical approach, and why is this approach preferable? 

NHTSA has historically based its analysis of potential new CAFE standards on detailed product

plans the agency has requested from manufacturers planning to produce light vehicles for sale in 

the United States. Although the agency has not attempted to compel manufacturers to submit 

such information, most major manufacturers and some smaller manufacturers have voluntari

provided it when requested. 

 

T

approach used by the agencies, including the agencies’ interest in examining product plans as a 

check on the reference fleet developed by the agencies for this rulemaking. One of the primary 

reasons for the request for data in 2009 was to obtain permission from the manufacturers to mak

public their product plan information for model years 2010 and 2011. There are a number of 

reasons that

available information. For example, the agencies’ current market forecast includes some 

vehicles for which manufacturers have announced plans for elimination or drastic production 

cuts such as the Chevrolet Trailblazer, the Chrysler PT Cruiser, the Chrysler Pacifica, the Do

Magnum, the Ford Crown Victoria, the Mercury Sable, the Pontiac Grand Prix, the Pontiac G5 

and the Saturn Vue. These vehicle models appear explicitly in market inputs to NHTSA’s 

analysis, and are among those vehicle models included in the aggregated vehicle types appearing

in market inputs to EPA’s analysis. However, although the agencies recognize that these specific 

vehicles will be discontinued, we continue to include them in the market forecast because they 

are useful as a surrogate for successor vehicles that may appear in the rulemaking time frame 

replace the discontinued vehicles in that market segment.34

Second, the agencies’ market forecast does not include some forthcoming vehicle models, such 

as the Chevrolet Volt, the Ford Fiesta and several publicly announced electric vehicles, includ

the announcements from Nissan regarding the Leaf. Nor does it include several MY 2009 or 

2010 vehicles, such as the Honda Insight, the Hyundai Genesis and the Toyota Venza, as our 

starting point for defining specific vehicle models in the reference fleet was Model Year 2008. 

Additionally, the market forecast does not account for publicly announced technology 

introductions, such as Ford’s EcoBoost syst

offer small- and medium-sized cars using Fiat powertrains. Were the agencies to rely on 

 

34 An example of this is in the GM Pontiac line, which is in the process of being phased out during the course of this 

rulemaking. GM has similar vehicles within their other brands (like Chevy) that will presumable pick up the loss in 

Pontiac share. We model this simply by leaving the Pontiac brand in. 
32

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

e 

duction 

f 

r 

n- and 

intellig ce-sharing agreement with GM that lasts through the introduction of redesigned Saab 9-

sis 

y 

gins. Thus, in fact, the omission only 

reflects e reference fleet, rather than the agencies’ conclusions regarding how stringent the 

at 

 that 

f 

’ analysis, and the counterbalancing aspects of potentially omitted technology in the 

referen fleet, the agencies believe their determination of the stringency of new standards has 

t 

manufacturers’ product plans (that were submitted), the market forecast would account for not 

only these specific examples, but also for similar examples that have not yet been announced 

publicly. 

Additionally, NHTSA acknowledges that Pontiac and Saturn lines are being discontinued. W

also are aware that as of October, General Motors Corp. and Sichuan Tengzhong Heavy 

Industrial Machinery Co., Ltd had tentatively reached an agreement for Tengzhong to acquire 

GM's Hummer truck brand. As we understand it, GM was planning to continue to build the 

trucks and provide business services to the buyer during a transitional period. Two GM 

assembly plants that produce the H2, H3 and H3T models were supposed to continue pro

of those trucks until June 2011, with the option of a one year extension until June 2012. As o

late February, the agencies were made aware that the deal to sell Hummer to Sichuan Tengzhong 

Heavy Industrial Machinery Co., Ltd. had fallen through because Sichuan Tengzhong Heavy 

Industrial Machinery Co., Ltd. failed to win Chinese government approval of the sale. It is 

believed that GM is planning to wind down the Hummer brand, while at the same time being 

open to other potential bidders for Hummer. 

We are also aware that as of late February, GM completed the sale of Saab to Dutch sports ca

maker Spyker Cars NV. The purchase created a new company, called Saab Spyker Automobiles

NV. According to the CEO of Saab Automobile, Jan Ake Jonsson, Saab has a productio

en

3 in 2012. 

Some commenters, such as CBD and NESCAUM, suggested that the agencies’ omission of 

known future vehicles and technologies in the reference fleet causes inaccuracies, which CBD 

further suggested could lead the agencies to set lower standards. On the other hand, CARB 

commented that “the likely impact of this omission is minor.” Because the agencies’ analy

examines the costs and benefits of progressively adding technology to manufacturers’ fleets, the 

omission of future vehicles and technologies primarily affects how much additional technolog

(and, therefore, how much incremental cost and benefit) is available relative to the point at which 

the agencies’ examination of potential new standards be

 th

standards should be. This is discussed further below. The agencies believe the above-mentioned 

comments by CBD, NESCAUM, and others are based on a misunderstanding of the agencies’ 

approach to analyzing potential increases in regulatory stringency. The agencies also note th

manufacturers do not always use technology solely to increase fuel economy, and that use of 

technology to increase vehicles’ acceleration performance or utility would probably make

technology unavailable toward more stringent standards. Considering the incremental nature o

the agencies

ce

not been impacted by any such omissions. 

Moreover, EPA and NHTSA believe that not including such vehicles after MY 2008 does no

significantly impact our estimates of the technology required to comply with the standards. If 

included, these vehicles could increase the extent to which manufacturers are—in the reference 

case—expected to over-comply with the MY 2011 CAFE standards, and could thereby make the 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

rojections of the vehicle fleet generally shift vehicle designs towards those 

more likely to be typic l of newer vehicles. Compared to using product plans that show 

continu fuel

continue to inc nefits of the new standards, as 

the costs and benefits of all fuel economy improvements beyond those required by the MY 2011 

ing 

nology 

o 

urate production intent information in these releases for reasons such as: (a) competitors 

ill closely examine their information for data in their product planning decisions; (b) the press 

overa uncements is not uniform, meaning highly anticipated models 

ave more coverage and materials than models that may be less exciting to the public and 

date 

at 

ir press releases, both on projected date of release of new models and on sales 

al 

new standards appear to cost less and yield less benefit relative to the reference case. However,

in the agencies’ judgment, production of the most advanced technology vehicles, such as the 

Chevy Volt or the Nissan Leaf (for example), will most likely be too limited during MY 2011

through MY 2016 to significantly impact manufacturers’ compliance positions. While we are 

projecting the characteristics of the future fleet by extrapolating from the MY 2008 fleet, the 

primary difference between the future fleet and the 2008 fleet in the same vehicle segment is the 

use of additional CO2-reducing and fuel-saving technologies. Both the NHTSA and EPA models

add such technologies to evaluate means of complying with the standards, and the costs of doing 

so. Thus, our future p

a

ed economy increases planned based on expectations that CAFE standards will 

rease, this approach helps to clarify the costs and be

CAFE standards are being assigned to the final rules. In some cases, the “actual” (vs. projected 

or “modeled”) new vehicles being introduced into the market by manufacturers are done so in 

anticipation of this rulemaking. On the other hand, manufacturers may plan to continue us

technologies to improve vehicle performance and/or utility, not just fuel economy. Our approach

prevents some of these actual technological improvements and their associated cost and fuel 

economy improvements from being assumed in the reference fleet. Thus, the added tech

will not be considered to be free (or having no benefits) for the purposes of this rule. 

In this regard, the agencies further note that manufacturer announcements regarding forward 

models (or future vehicle models) need not be accepted automatically. Manufacturers tend t

limit acc

w

c ge of forward model anno

h

consistency and uniformity cannot be ensured with the usage of press information; and (c) these

market projections are subject to change (sometimes significant), and manufacturers may not 

want to give the appearance of being indecisive, or under/over-confident to their shareholders 

and the public with premature release of information. 

NHTSA has evaluated the use of public manufacturer forward model press information to up

the vehicle fleet inputs to the baseline and reference fleet. The challenges in this approach are 

evidenced by the continuous stream of manufacturer press releases throughout a defined 

rulemaking period. Manufacturers’ press releases suffer from the same types of inaccuracies th

many commenters believe can affect product plans. Manufacturers can often be overly 

optimistic in the

volumes. 

More generally and more critically, as discussed in the proposal and as endorsed by many of the 

public comments, there are several advantages to the approach used by the agencies in this fin

rule. Most importantly, today’s market forecast is much more transparent. The information 

sources used to develop today’s market forecast are all either in the public domain or available 

commercially. Another significant advantage of today’s market forecast is the agencies’ ability

to assess more fully the incremental costs and benefits of the proposed standards. In addition, by
34

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

e 

s final 

rule, the baseline market data comes from actual vehicles (on the road today) which have actual 

fuel economy test data (in contrast to manufacturer estimates of future product fuel economy) – 

so there is no question what is the basis for the fuel economy or CO2 performance of the baseline 

market data as it is. 

5. How is this baseline different quantitatively from the baseline that NHTSA 

used for the MY 2011 (March 2009) final rule? 

As discussed above, the current baseline was developed from adjusted MY 2008 compliance data 

and covers MYs 2011-2016, while the baseline that NHTSA used for the MY 2011 CAFE rule 

was developed from confidential manufacturer product plans for MY 2011. This section 

describes, for the reader’s comparison, some of the differences between the current baseline and 

the MY 2011 CAFE rule baseline. This comparison provides a basis for understanding general 

characteristics and measures of the difference, in this case, between using publicly (and 

commercially) available sources and using manufacturers’ confidential product plans. The 

current baseline, while developed using the same methods as the baseline used for MYs 2012-

2016 NPRM, reflects updates to the underlying commercially-available forecast of manufacturer 

and market segment shares of the future light vehicle market. These changes are discussed 

above. 

Estimated vehicle sales

developing baseline and reference fleets from common sources, the agencies have been able to

avoid some errors—perhaps related to interpretation of requests—that have been observed in 

past responses to NHTSA’s requests. An additional advantage of the approach used for this

proposal is a consistent projection of the change in fuel economy and CO2 emissions across th

various vehicles from the application of new technology. With the approach used for thi

: 

The sales forecasts, based on the Energy Information Administration’s (EIA’s) Annual Energy 

Outlook 2010 (AEO 2010), used in the current baseline indicate that the total number of light 

vehicles expected to be sold during MYs 2011-2015 is 77 million, or about 15.4 million vehicles 

annually. NHTSA’s MY 2011 final rule forecast, based on AEO 2008, of the total number of 

light vehicles likely to be sold during MY 2011 through MY 2015 was 83 million, or about 16.6 

million vehicles annually. Light trucks are expected to make up 41 percent of the MY 2011 

baseline market forecast in the current baseline, compared to 42 percent of the baseline market 

forecast in the MY 2011 final rule. These changes in both the overall size of the light vehicle 

market and the relative market shares of passenger cars and light trucks reflect changes in the 

economic forecast underlying AEO, and changes in AEO’s forecast of future fuel prices.

 

The figures below attempt to demonstrate graphically the difference between the variation of fuel 

economy with footprint for passenger cars under the current baseline and MY 2011 final rule, 

and for light trucks under the current baseline and MY 2011 final rule, respectively. Figures III1 and III-2 show the variation of fuel economy with footprint for passenger car models in the 

current baseline and in the MY 2011 final rule, while Figures III-3 and III-4 show the variation 

of fuel economy with footprint for light truck models in the current baseline and in the MY 2011 

final rule. However, it is difficult to draw meaningful conclusions by comparing figures from 

the current baseline with those of the MY 2011 final rule. In the current baseline the number of 
35

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

make/models, and their associated fuel economy rint, are fixed and do not vary over 

time

compared to the number of data points in the MY 2011 final rule baseline. In contrast, the 

baseline fleet used in the MY 2011 final rule varies over time as vehicles (with different fuel 

economy and footprint characteristics) are added to and dropped from the product mix. 

and footp

—this is why the number of data points in the current baseline figures appears smaller as
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Figure III-1. Planned Fuel Economy vs. Footprint, Passenger Cars in Current Baseline 

10

15

20

25

30

35

40

45

50

55

60

65

70

35 40 45 50 55 60 65 70 75

Footprint (sf)

Fuel Economy(mpg)
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Figure III-2. Planned Fuel Economy vs. Footprint, Passenger Cars in MY 2011 Final Rule

10

15

20

25

30

35

40

45

50

55

60

65

35 40 45 50 55 60 65 70 75 80

Footpri

70

f)

Fuel Economy (mpg)

nt (s
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Figure III-3. Planned Fuel Economy vs. Footprint, Light Trucks in Current Baseline

10

15

20

25

30

35

40

45

50

55

60

65

70

35 40 45 50 55 60 65 70 75 80

Footprint (sf)

Fuel Economy (mpg)
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Figure III-4. Planned Fuel Economy vs. Footprint, Light Trucks in MY 2011 Final Rule 

10

15

20

25

30

35

40

45

50

55

60

65

35

70

50 55 65 70 80

Footpri 

Fuel Economy (mpg)

40 45 60

(sf)

75

nt
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Estimated manufacturer market shares: 

NHTSA’s expectations regarding manufacturers’ market shares (the basis for which is discussed 

below) l rule, given that the agency is relying on 

ifferent sources of material for these assumptions as discussed above and in Chapter 1 of the 

have also changed since the MY 2011 fina

d

joint TSD. These changes are reflected below in Table III-4, which shows the agency’s sales 

forecasts for passenger cars and light trucks under the current baseline and the MY 2011 final 

rule.35

Table III-4. Sales Forecasts (Production for U.S. Sale in MY 2011, Thousand Units) 

Current Baseline MY 2011 Final Rule 

Manufacturer Passenger Nonpassenger Passenger Nonpassenger

Chrysler 326 737 707 1,216

Ford 1,344 792 1,615 1,144

General Motors 1,249 1,347 1,700 1,844

Honda 851 585 1,250 470

Hyundai 382 46 655 221

Kia 306 88 

Nissan 612 331 789 479

Toyota 1,356 888 1,405 1,094

Other Asian 664 246 441 191

European 833 396 724 190

Total 7,923 5,458 9,286 6,849

 Dual-fueled vehicles: 

Manufacturers have also, during and since MY 2008, indicated to the agency that they intend to 

ell more dual-fueled or flexible-fuel vehicles (FFVs) in MY 2011 than indicated in the current 

b

to petroleum-based ga mpliance with 

CAFE standards, the fuel eco to lim

account for this potential.36 However, is precluded from “taki it” for the 

complia by acco bilit d ting 

the leve tandards.”37 Some facturers pl produce siderably gr share 

of FFV earn full credit un CA. The cted avera V share of arket 

in MY 7 percent for the curr seline, versus 17 percent e MY 2011 rule. 

NHTSA at in MY 2008 (the l year prov the vehic pon which 

today’s ased), th e U.S.-bas Ms produ e F offered 

 

s

aseline of adjusted MY 2008 compliance data. FFVs create a potential market for alternatives 

soline and diesel fuel. For purposes of determining co

nomy of a FFV is, subject 

 NHTSA

itations, adjusted upward to

ng cred

nce flexibility unting for manufacturers’ a y to earn an use credits in set

l of the s manu an to a con eater 

s than can der EP proje ge FF the m

2011 is ent ba for th final 

 notes th mode iding le models u

 market forecast is b e thre ed OE ced most of th FVs 

35 As exp although NHTSA n ed each manufacturer’s overal et share to pro 

realistica fleet, the product mix for anufacturer bmitted pro ns was preserved. The 

agency h ed manufacturers’ produ in detail, an rstands that manufacturers do not sell the same 

mix of vehicles in every model year. 

lained below, ormaliz l mark

duct pla

duce a

lly-sized

as review

 each m

ct plans

 that su

d unde

36 See 49 U.S.C. 32905 and 32906. 37 49 U.S.C..32902(h). 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

for sale ., yet these OEMs nt are pro to account for a smaller share of the 

future m he forecast the age s used to d p and an today’s rule in the 

forecas used to develop and analyze the 1 stand 

 achieved fuel eco levels

 in the U.S accou jected

arket in t ncy ha evelo alyze than

t the agency MY 201 ards.

Estimated nomy : 

Becaus ers’ product plans al reflect simultaneous cha in fleet mix and other 

vehicle ristics, the relations tween incr technolo lization and

fuel eco nnot be isolated wit certainty. To do so woul uire an apple apples 

“counte of vehicles th except for ology an economy, i al—

for exam fleet mix an icle perfor and util he current b ne 

arket forecast shows industry-wide average fuel economy levels somewhat lower in MY 2011 

than shown in the MY 2011 final rule and the MYs 2012-2016 NPRM. Under the current 

b

the MY 2011 final rule, and 26 s 2012-2016 NPRM. The 0.3 

mpg change relative to th 6 th s in manufacturer and 

market segment shares o ar

These differences are sh eater detail below able III-5, w ows manufacturerspecific CAFE levels (n ing FFV credits th e manufactu xpect to earn) from 

the current baseline ver Y 2011 final rule ne (from ma turers’ 2008 product 

plans) for passenger car . Table I ows the com averages of these 

planned CAFE levels in ective baseline fle These tables nstrate that, while the 

difference at the industr ot so large, ther significant di ces in CAFE at the 

manufacturer level betw e current baseline an MY 2011 fi le baseline. For 

example, while Volksw is essentially the sam er both, Toyota and Nissan show 

increased combined CA ls under the curren line (by 1.9 and 0.7 mpg respectively), 

while Chrysler, Ford, a ow decreased com d CAFE leve er the current baseline 

(by 1.4, 1.1, and 0.8 mp elative to Y 2011 fina baseline. 

Table III-5. Current B lanned CAFE Le n MY 2011 versus MY 2011 Final Rule 

P AFE Levels (Passenger and Nonpass ) 

e manufactur so nges

 characte hip be eased gy uti increased 

nomy ca h any d req s-torfactual” fleet at are, techn d fuel dentic

ple, in terms of d veh mance ity. T aseli

m

aseline, average fuel economy for MY 2011 is 26.4 mpg, versus 26.5 mpg under the baseline in

.7 mpg under the baseline in the MY

e MYs 2012-201

f the MY 2011 m

 baseline is

ket. 

e result of change

own in gr in T hich sh

ot count at som rers e

sus the M baseli nufac

s and light trucks II-6 sh bined

 the resp ets. demo

y level is n e are fferen

een th d the nal ru

agen e und

FE leve t base

nd GM sh bine ls und

g, respectively) r the M l rule 

aseline P vels i

lanned C enger

rent baseline CAFE 

levels 

MY 2011 planned CAFE 

ls 

Cur

leve

Manufacturer Passenger Nonpas Passen Nonpassenger senger ger

BMW 27.2 0 2 23. 7.0 23.0

Chrysler 27.8 8 2 21. 8.2 23.1

Ford 28.0 21.0 29.3 22.5

Subaru 29.2 26.1 28.6 28.6

General Motors 28.2 21.2 30.3 21.4

Honda 33.5 25.0 32.3 25.2

Hyundai 32.5 24.3 31.7 26.0

Tata 24.6 19.6 24.7 23.9

Kia 31.7 23.7 38

 

38 Again, Kia is not listed in the table for the MY 2011 final rule because it was considered as part of Hyundai f

purposes of that analysis (i.e., Hyundai-Kia). 

or 
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Mazda39 30.6 26.0

Daimler 26.4 21.0 25.2 20.6

Mitsubishi 29.4 23.6 29.3 26.7

Nissan 31.7 21.7 31.3 21.4

Porsche 26.2 20.0 27.2 20.0

Ferrari40 16.2

Maserati41 18.2

Suzuki 30.9 23.3 28.7 24.0

Toyota 35.1 23.7 33.2 22.7

Volkswagen 29.1 20.2 28.5 20.1

Total/Average 30.3 22.2 30.4 22.6

Table III-6. Current Baseline Planned C MY 2011 versus MY 2011 Final Rule 

ed C Lev om

AFE Levels in

Plann AFE els (C bined) 

Manufacturer rren

selin

MY Final 

Rule baseline 

Cu t 

ba e 

2011 

BMW 25.0 26.0

Chrysler 23.3 24.7

Ford 24.9 26.0

Subaru 27.9 28.6

General Motors 24.1 24.9

Honda 29.5 30.0

Hyundai 31.3 30.0

Tata 21.4 24.4

Kia 29.5

Mazda 29.8

Daimler 24.4 23.6

Mitsubishi 27.4 29.1

Nissan 27.3 26.6

Porsche 23.7 22.0

Ferrari 16.2

Maserati 18.2

Suzuki 29.7 27.8

Toyota 29.5 27.6

Volkswagen 27.0 27.1

Total/Average 26.4 26.5

 39 Mazda is not l the MY nal rule it was part of Ford for purposes 

of that analysis. 

40 EPA did not in urrent b based o nclusio ncluding them would not impact 

the results, and t t listed ble for t t base 41 EPA did not in urren ne based conclu t including them would not 

impact the result ti is n d in the t r the cur seline. 

isted in the table for 2011 fi because considered as 

clude Ferrari in the c aseline n the co n that i

herefore Ferrari is no in the ta he curren line. 

clude Maserati in the c

s, and therefore Masera

t baseli

ot liste

 on the 

able fo

sion tha

rent ba
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Tables III-7 through III-9 summarize other differ ces between the current baseline and 

manufacturers’ product plans submitted to NHTSA in 2008 for the MY 2011 final rule. These 

dustry. The 

tables containing product plan data do not identi manufacturers by name, and do not present 

them in

 

Tables III-7a and II at the cu asel ect ht decrease in overall 

average passenger v relative t anu s’ This is a reflection of the 

market segment shif ing the sa cast cu aseline. 

Tabl s ver 2 hicle Footprint 

are F

er 

en

tables present average vehicle footprint, curb weight, and power-to-weight ratios for each 

manufacturer represented in the current baseline and of the seven largest manufacturers 

represented in the product plan data used in that rulemaking, and for the overall in

fy

 the same sequence. 

I-7b show th rrent b ine refl s a slig

ehicle size o the m facturer plans. 

ts underly les fore s of the rrent b

e III-7a. Current Ba eline A age MY 011 Ve

(Squ eet) 

Manufactur PC LT Avg. 

BMW 45.4 49.9 47.5

Chrysler 46.8 52.8 50.9

Daimler 47.1 53.3 49.0

Ford 46.3 56.1 49.9

General 

Motors 46.4 58.2 52.5

Honda 44.3 49.1 46.3

Hyundai 44.4 48.7 44.8

Kia 45.2 51.0 46.5

Mazda 44.4 47.3 44.9

Mitsubishi 43.8 46.5 44.6

Nissan 45.3 53.9 48.3

Porsche 38.6 51.0 42.8

Subaru 43.1 26.6 36.8

Suzuki 40.8 47.2 41.6

Tata 50.3 47.8 48.8

Toyota 44.0 53.0 47.6

Volkswagen .5 43 52.6 45.1

Industry 

Average 45.2 53.5 48.6

Table III-7b. MY 2011 Final Rule A Plan verage ned MY 201 cle Footprint (Square Feet) 1 Vehi

PC LT Avg. 

Manufacturer 1 46.7 58.5 52.8 

Manufacturer 2 46.0 5.4 47.1 

Manufacturer 3 44.9 52.8 48.4 

Manufacturer 4 45.4 55.8 49.3 

Manufacturer 5 45.2 57.5 50.3 

Manufacturer 6 48.5 54.7 52.4 

Manufacturer 7 45.1 49.9 46.4 

Industry Average 45.6 55.1 49.7 
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Tables III-8a and I at the curr selin cts e in overall average 

vehicle weight rela manufacture s. As above, st likely a reflection of 

the market segmen derlying the rec e t baseline. 

Table III-8 ne Av eh rb Weight (Pounds)

facturer P LT A

II-8b show th ent ba e refle a decreas

tive to the rs’ plan this is mo

t shifts un sales fo asts of th curren

a. Current Baseli erage MY 2011 V icle Cu

Manu C vg. 

BMW 3 4 4 ,535 ,648 ,055

Chrysler 3 4 4 ,572 ,469 ,194

Daimler 3 5 4 ,583 ,127 ,063

Ford 3 4 3 ,526 ,472 ,877

General Motors 3 4 4 ,528 ,978 ,281

Honda 3 4 3 ,040 ,054 ,453

Hyundai 3 4 3 ,014 ,078 ,129

Kia 3 4 3 ,035 ,007 ,252

Mazda 3 3 3 ,258 ,803 ,348

Mitsubishi 3 3 3 ,298 ,860 ,468

Nissan 3 4 3 ,251 ,499 ,689

Porsche 3 4 3 ,159 ,906 ,760

Subaru 3,176 2,001 2,727

Suzuki 2,842 3,843 2,965

Tata 3,906 5,171 4,627

Toyota 3,10 321 3,589 9 4,

Vo swagen 3,445 3 lk 5,672 ,839

Industry 

Average 3,313 4 3,7 ,499 97

Table III-8b. le Av lanned MY 2011 le Curb Weight (Pounds) 

P L Avg. 

 MY 2011 Final Ru erage P Vehic

C T 

Manufacturer 1 3, 4, 3 197 329 ,692 

Manufacturer 2 3, 4, 4 691 754 ,363 

Manufacturer 3 3,293 4,038 3,481 

Manufacturer 4 3,254 4,191 3,510 

Manufacturer 5 3,547 5,188 4,401 

Manufacturer 6 3,314 4,641 3,815 

Manufacturer 7 3,345 4,599 3,865 

Industry Average 3,380 4,687 3,935 

ance 

st likely a 

at 

Tables III-9a and III-9b show that the current baseline reflects a decrease in average perform

relative to that of the manufacturers’ product plans. This decreased performance is mo

reflection of the market segment shifts underlying the sales forecasts of the current baseline, th

is, an assumed shift away from higher performance vehicles. 
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Table III-9a. Current Baseline Average MY 2011 Vehicle Power-to-Weight Ratio (hp/lb)

Manufacturer PC LT Avg. 

BMW 0.072 0.061 0.067

Chrysler 0.055 0.052 0.053

Daimler 0.068 0.056 0.064

Ford 0.058 0.054 0.056

General Motors 0.057 0.056 0.056

Honda 0.056 0.054 0.056

Hyundai 0.052 0.055 0.052

Kia 0.050 0.056 0.051

Mazda 0.052 0.055 0.052

Mitsubishi 0.053 0.056 0.054

Nissan 0.059 0.057 0.058

Porsche 0.105 73 4 0.0 0.09

Subaru 0.060 0.030 0.048

Suzuki 0.049 0.062 0.051

Tata 0.077 0 0 .057 .065

Toyota 0.053 0.062 0.056

Volkswagen 0.057 0 0 .052 .056

Industry Average 0.057 0.056 0.056

Table III-9b. MY 2 al Rule Avera lanned 2011 icle Power-to-Weight Ratio 

p/lb)

PC 

011 Fin ge P MY Veh

(h

LT Avg.

Manu 0. facturer 1 065 0.058 60 0.0

Manu 0. facturer 2 061 0.065 62 0.0

Manu 0 facturer 3 .053 0.059 56 0.0

Manu 0 facturer 4 .060 0.058 59 0.0

Manufacturer 5 0.060 0.057 59 0.0

Manufacturer 6 0.063 0.065 65 0.0

Manufacturer 7 0.053 0.055 53 0.0

Industry Average 0.060 0.059 0.060

As discussed above, the agencies’ market forecast for MY 2012-2016 holds the performance and 

other characteristics of individual vehicle models constant, adjusting the size and composition of 

the fleet from one model year to the next. 

Refresh and redesign schedules (for application in NHTSA’s modeling): 

Expected model years in which each vehicle model will be redesigned or freshened constitute 

another important aspect of NHTSA’s market forecast. As discussed in Chapter V below, 

NHTSA’s analysis supporting the current rulemaking times the addition of nearly all 

technologies to coincide with either a vehicle redesign or a vehicle freshening. Product plans 

submitted to NHTSA preceding the MY 2011 final rule contained manufacturers’ estimates of 

vehicle redesign and freshening schedules and NHTSA’s estimates of the timing of the five-year 
46

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

redesign cy e plans. 

In the current baseli contrast, estimates o timing e refresh and redesign cycles 

were based on histo counting fo from k n rede ing in or 

prior to MY 2008 fo the fleet an igning h and ign years 

accordingly. After timates, the s a rers’ senger car and light 

truck estimated to b Y 2011 wer summarized below e current baseline 

and the MY 2011 fi 10 below e es o manufacturer’s 

fleets expected to b Y 2011 for urrent ne. Ta I-11 presents 

corresponding estim rket foreca d by N in th ysis supporting the 

MY 2011 final rule protect confidenti rmation nufac are not identified 

y name). 

cle and the two- to three-year refresh cycle were made with reference to thos

ne, in f the of th

rical dates—i.e., rward now signs occurr

r each vehicle in d ass refres redes

applying these es hares of m nufactu pas

e redesigned in M e as for th

nal rule. Table III- shows the p rcentag f each

e redesigned in M the c baseli ble II

ates from the ma st use HTSA e anal

 (again, to al info , ma turers 

b

Table III-10. Current Baseline, Share of Fleet Redesigned in MY 2011 

Manufacturer PC LT Avg. 

BMW 32% 37% 34%

Chrysler 0% 13% 9%

Daimler 0% 0% 0%

Ford 12% 8% 11%

General Motors 17% 3% 9%

Honda 29% 26% 28%

Hyundai 26% 0% 23%

Kia 38% 83% 48%

Mazda 0% 0% 0%

Mitsubishi 0% 59% 18%

Nissan 5% 25% 12%

Porsche 0% 100% 34%

Subaru 0% 42% 16%

Suzuki 4% 21% 6%

Tata 28% 100% 69%

Toyota 5% 15% 9%

Volkswagen 16% 0% 13%

Industry Average 13% 15% 14%
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PC LT Avg. 

Table III-11. MY 2011 Final Rule, Share of Fleet Redesigned in MY 2011 

Manufacturer 1 19% 0% 11%

Manufacturer 2 34% 27% 29%

Manufacturer 3 5% 0% 3%

Manufacturer 4 7% 0% 5%

Manufacturer 5 19% 0% 11%

Manufacturer 6 34% 28% 33%

Manufacturer 7 27% 28% 28%

Overall 20% 9% 15%

We continue, therefore, to estimate that manufacturers’ redesigns will not be uniformly 

distributed across model years. This is in keeping with standard industry practices, and reflects 

ct 

 MY 

ation that 

advantages. NHTSA plans to consider these advantages and disadvantages further in 

e 

what m nufacturers actually do–NHTSA has observed that manufacturers in fact do redesign 

more vehicles in some years than in others. NHTSA staff have closely examined manufacturers’

planned redesign schedules, contacting some manufacturers for clarification of some plans, and

confirmed that these plans remain unevenly distributed over time. For example, although the 

table above shows that NHTSA expects Company 2 to redesign 34 percent of its passenger car

models in MY 2011, current information indicates that this company will then redesign only (a 

different) 10 percent of its passenger cars in MY 2012. Similarly, although the table above 

shows that NHTSA expects four of the largest seven light truck manufacturers to redesign 

virtually no light truck models in MY 2011, current information also indicates that these four 

manufacturers will redesign 21-49 percent of their light trucks in MY 2012. 

6. How does manufacturer product plan data factor into the baseline used in 

this final rule? 

While the agencies received updated product plans in Spring and Fall 2009 in response to 

NHTSA’s requests, the baseline data used in this final rule is not informed by these produ

plans, except with respect to specific engineering characteristics (e.g., GVWR) of some

2008 vehicle models, because these product plans contain confidential business inform

a

the age cies are legally required to protect from disclosure, and because the agencies have

concluded that, for purposes of this final rule, a transparent baseline is preferable. 

For the NPRM, NHTSA conducted a separate analysis that did make use of these product plans. 

NHTSA performed this separate analysis for purposes of comparison only. For the final rule 

which this FRIA accompanies, NHTSA used the publicly-available baseline for all analysis 

related to the development and evaluation of the new CAFE standards. As discussed above, 

while a baseline developed using publicly and commercially available sources has both 

advantages and disadvantages relative to a baseline developed using manufacturers’ product 

plans, NHTSA has concluded for today’s analysis that the advantages outweigh the 

n

dis

connection with future rulemakings, taking into account changes in the market, changes in th

scope and quality of publicly and commercially available data, and any changes in 

manufacturers’ willingness to make some product planning information publicly available. 
48

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

 wide 

se to comments received in the last round of rulemaking, in our 

March 2009 notice of intent to prepare an environmental impact statement, the agency selected a 

. Thus, 

centage 

ch 

In the N RM, we noted that each of the listed alternatives represents, in part, a different way in 

e 

as 

2 emissions, and fuel savings by consumers, as well as other relevant factors 

such as afety. For example, the 7% Alternative weighs energy conservation and climate change 

e 

ed 

s) will 

ized 

g a 

to 

illustra the similarities and dissimilarities. To that end, we included and analyzed two 

ich total 

spect 

B. Alternatives examined by the agency, and why NHTSA selected the Preferred 

Alternative 

In developing the proposed MY 2012-16 standards, the agency developed and considered a

variety of alternatives. In respon

range of candidate stringencies that increased annually, on average, 3% to 7%.42 That same 

approach has been carried over to this final rule and to the accompanying FEIS and FRIA

the majority of the alternatives considered in this rulemaking are defined as average per

increases in stringency—3 percent per year, 4 percent per year, 5 percent per year, and so on. 

NHTSA believes that this approach clearly communicates the level of stringency of ea

alternative and allows us to identify alternatives that represent different ways to balance 

NHTSA’s statutory requirements under EPCA/EISA. 

P

which NHTSA could conceivably balance different policies and considerations in setting th

standards. We were mindful that the agency needs to weigh and balance many factors, such 

technological feasibility, economic practicability, including lead time considerations for the 

introduction of technologies and impacts on the auto industry, the impacts of the standards on 

fuel savings and CO

 s

considerations more heavily and technological feasibility and economic practicability less 

heavily. In contrast, the 3% Alternative, the least stringent alternative, places more weight on 

technological feasibility and economic practicability. We recognized that the “feasibility” of th

alternatives also may reflect differences and uncertainties in the way in which key economic 

(e.g., the price of fuel and the social cost of carbon) and technological inputs could be assess

and estimated or valued. We also recognized that some technologies (e.g., PHEVs and EV

not be available for more than limited commercial use through MY 2016, and that even those 

technologies that could be more widely commercialized through MY 2016 cannot all be 

deployed on every vehicle model in MY 2012 but require a realistic schedule for more 

widespread commercialization to be within the realm of economically practicability. 

In addition to the alternatives that increase evenly at annual rates ranging from 3% to 7%, 

NHTSA also included alternatives developed using benefit-cost criteria. The agency emphas

benefit-cost-related alternatives in its rulemakings for MY 2008-2011 and, subsequently, MY 

2011 standards. By including such alternatives in its current analysis, the agency is providin

degree of analytical continuity between the two approaches to defining alternatives in an effort 

te

additional alternatives, one that sets standards at the point where net benefits are maximized 

(labeled “MNB” in the table below), and another that sets standards at the point at wh

costs are most nearly equal to total benefits (labeled “TCTB” in the table below).43 With re

 

42 Notice of intent to prepare an EIS, 74 FR 14857, 14859-60, April 1, 2009.

43 The stringency indicated by each of these alternatives depends on the value of inputs to NHTSA’s analysis.

Results presented here for these two alternatives are based on NHTSA’s reference case inputs, which underlie

 

 the 

central analysis of the proposed standards. In the accompanying FRIA, the agency presents the results of that 

n 

ology cost estimates), our analysis often exhausts 

analysis to explore the sensitivity of results to changes in key economic inputs. Because of numerous changes i

model inputs (e.g., discount rate, rebound effect, CO2 value, techn
49

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

at least some 

vehicle , market forecasts and economic assumptions, NHTSA used the Volpe model 

statuto criteria, given the difficulties confronting the industry and the economy, and other 

relevan on 

and achieving a nationally harmonized and coordinated program for regulating fuel economy and 

GHG emissio

Part of that a t c sa

achie both Federal and State GHG emission reduction go specially those of California and 

ates that have adopted its GHG emission standard for motor vehicles. Given that EPCA 

trib as nda HT d E ter the w a nati

G on ndar ld n be ach he s missi

n orn the forni G p m. as by e ting a

e C ir tan for M 16 oul y ac e c y and e 

of emissions reduction which California standards would require for the subset of 

les sold lif nd Ca ia st ds f 2009-2016 ( n as “ y 

n s ncy e C ia P 1 p m w alua ut for

nd Fo mber of rea iscussed in th l ru asse nt wa

oped of national new vehicle fleet-wide CO2 performance standards for model year 2016 

 result in the new light-duty vehicle fleet in the State of California having CO

rmance o rf f e C nia 1 s rds. level

iv to pg if the G and re m clus by conom

nt d t era lt is ode 20 ls o Nat Progr

the of en r the nal am f 25 i C n be m th 

on t e” vem w the G-re on r 

nt h a re ant l e re ns. E st ds, cusse

 t al ru , canno e m impro ents t canno e accoun ed for o e 

 

to the first of those alternatives, we note that Executive Order 12866 focuses attention on an 

approach that maximizes net benefits. Further, since NHTSA has thus far set attribute-based 

CAFE standards at the point at which net benefits are maximized, we believed it would be useful 

and informative to consider the potential impacts of that approach as compared to the new 

approach for MYs 2012-2016. 

After working with EPA in thoroughly reviewing and in some cases reassessing the effectiveness 

and costs of technologies (most of which are already being incorporated in 

s)

extensively to assess the technologies that the manufacturers could apply in order to comply with

each of the alternatives. This allowed us to assess the variety, amount and cost of the 

technologies that could be used to enable the manufacturers to comply with each of the 

alternatives. NHTSA estimated how the application of these and other technologies could 

increase vehicle costs, reduce fuel consumption, and reduce CO2 emissions. 

The agency then assessed which alternative would represent a reasonable balancing of the 

ry

t goals and priorities. Those priorities and goals include maximizing energy conservati

ns. 

ssessment of alternatives entailed an evalua ion of the 

als, e

stringen ies neces ry to 

ve

the St

requires at ute-b ed sta rds, N SA an PA de mined level at hich onal 

attribute-base

 i

d GH emissi s sta d wou eed to set to ieve t ame e on 

reductions

id

Calif

lean A

ia as

 Act s

 Cali

dard 

a GH

Y 20

rogra

that w

This w

d appl

done 

ross th

valua

nationw ountr requir

the levels 

vehic in Ca ornia u er the liforn andar or MY know Pavle

1”). In esse ce, the tringe of th aliforn avley rogra as ev ted, b a 

national sta ard. r a nu sons d e fina le, an ssme s 

devel

which would

perfo

2

equal t the pe ormance rom th alifor Pavley tanda That , 250 

g/mi, is equ alent 35.5 m HG st ard we et ex ively fuel e y 

improveme s – an he ov ll resu the m l year 16 goa f the ional am. 

However, level string cy fo Natio Progr goal o 0 g/m O2 ca et wi

both fuel ec omy “ ailpip impro ents as ell as o r GH ducti elated

improveme

elsewhere in

s, suc

his fin

s A/C

le

friger

t b

eakag

et by

ductio

vem

 CAF

hat 

andar

t b

as dis

t

d 

n th

FTP/HFET tests. Thus, setting CAFE standards at 35.5 mpg would require more tailpipe 

technology (at more expense to manufacturers) than would be required under such a CAA 

 e 

austs all available technologies is considered. 

all available technologies before reaching the point at which total costs equal total benefits. In these cases, th

stringency that exh
50

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

rd. To obtain an equivalent CAFE standard, we determined how much tailpipe technology 

ecess in or et an mpg level if ufactur also loyed w

n ge amount o “cr (lea d enc each 0 

le his ts gure .1 m the pri unte CAFE

erential giv nuf rs th ortu o re 5.5 quiva

under t CAA in ways that would significantly reduce their costs. Were NHTSA instead to 

pg by MY 20

new the 

statutory factors and other relevant considerations. For the reader’s reference, the estimated 

required levels of stringency for each alternative in each model year are presented below: 

Table III-12. Estimated Required Fuel Economy Level for Regulatory Alternatives.44

Alt. 1 Alt. 2 Alt. 3 Alt. 4 Alt. 5 Alt. 6 Alt. 7 Alt. 8 Alt. 9 

standa

would be n

EPA 

ary 

 to be a

der to m

 avera

e of 35.5

edits”

man

kage an

ers 

 effici

emp

y) to r

hat 

deemed the 25

g/mi equiva

f A/C

nt. T resul in a fi of 34 pg as appro ate co rpart 

standard. This diff es ma acture e opp nity t ach 3 mpg e lent 

he 

establis its standard at the same level, manufacturers would need to make substantially greater 

expenditures on fuel-saving technologies to reach 35.5 mpg under EPCA. 

Thus, as part of the process of considering all of the factors relevant under EPCA for setting 

standards, in a context where achieving a harmonized National Program is important, for the 

proposal we created a new alternative whose annual percentage increases would achieve 34.1 

h

m 16. That alternative is one which increases on average at 4.3% annually. This 

 alternative, like the seven alternatives presented above, represents a unique balancing of 

No 

Action 

3%/year 

Increase 

4%/year 

Increase 

~4.3%/year

Increase 

5%/year

Increase

~6.0%/year 

Increase 

MNB 

6%/year

Increase

7%/year 

Increase 

~6.6%/year 

Increase 

 TCTB 

2012 

Passenger 

Cars 30.5 31.7 32.1 33.4 32.4 33.0 32.7 33.0 33.4

Light Trucks 24.4 24.1 24.4 25.3 24.6 26.3 24.9 25.1 26.3

Combined 27.8 28.3 28.6 29.7 28.8 30.0 29.1 29.4 30.3

2013 

Passenger 

Cars 30.5 32.6 33.3 34.2 33.9 36.1 34.5 35.2 36.7

Light Trucks 24.4 24.8 25.3 25.9 25.8 27.7 26.3 26.8 28.0

Combined 27.8 29.1 29.7 30.5 30.3 32.3 30.8 31.4 32.8

2014 

Passenger 

Cars 30.5 33.5 34.5 35.0 35.5 38.1 36.5 37.6 39.2

Light Trucks 24.5 25.5 26.3 26.6 27.0 29.1 27.8 28.6 29.7

Combined 28.0 30.0 30.9 31.3 31.8 34.2 32.7 33.7 35.0

2015 

Passenger 

Cars 30.5 34.4 35.8 36.2 37.1 39.4 38.6 40.1 40.7

Light Trucks 24.4 26.2 27.2 27.5 28.3 30.3 29.4 30.5 30.7

Combined 28.0 31.0 32.2 32.6 33.4 35.6 34.7 36.0 36.5

 

44 Also, the “MNB” and the “TCTB” alternatives depend on the inputs to the agencies’ analysis. The sensitivity 

analysis presented in the Chapter X documents the response of these alternatives to changes in key economic inputs. 

For example, the combined average required fuel economy under the “MNB” alternative is 36.9 mpg under the 

reference case economic inputs presented here, and ranges from 32.0 mpg to 37.2 mpg under the alternative 

economic inputs. 
51

2016 

Passenger 

Cars 30.5 35.4 37.2 37.8 39.0 40.9 40.9 42.9 42.3

Light Trucks 24.4 27.0 28.3 28.7 29.7 31.1 31.1 32.6 31.8

Combined 28.1 32.0 33.6 34.1 35.2 36.9 36.9 38.7 38.0

The following this same inform t in a diff ay, co ing estimated 

average fuel ec required of manufa s under the regula lternatives in 

MYs 2012, 20 levels for 2013 and MY 2015 fall een those for 

MYs 2012 and d 2016, re ively. Req evels f ese interim 

years are not pr following figure si imit the lexity ure. 

Figure III ed onomy ( 012, 2 nd 2016) 

figure presents at u ion b erent w mpar

onomy levels cturer eight tory a

14, and 2016. Required

s 2014 an

 MY betw

 2014 and MY spect uired l or th

esented in the mply to l comp of the fig

-1. Average Estimated Requir Fuel Ec MYs 2 014, a

45 

20 

25 

30 

35 

40 

A

v

e

r

a

g

e

R

e

q

u

i

r

e

d

F

u

e

l

E

c

o

n

o

m

y

(

m

p

g

)

PC, 2012

LT, 2012

Comb., 2012

PC, 2014

LT, 2014

Comb., 2014

PC, 2016

LT, 2016

Comb. 2016

3%/y 4%/y Final 5%/y 6%/y Max

NB

7%/y TC=TB

As this figure illustrates, the final standards involve a “faster start” toward increased stringency 

than do any of the alternatives that increase steadily (i.e., the 3%/y, 4%/y, 5%/y, 6%/y, and 7%/y 

alternatives). However, by MY 2016, the stringency of the final standards reflects an average 

annual increase of 4.3%/y. The final standards, therefore, represent an alternative that could be 

se.” 

s 

d 

referred to as “4.3% per year with a fast start” or a “front-loaded 4.3% average annual increa

For each alternative, including today’s final standards, NHTSA has estimated all corresponding

effects for each model year, including fuel savings, CO2 reductions, and other effects, as well a

the estimated societal benefits of these effects. The accompanying FRIA presents a detaile

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analysis of these results. Table III-13 presents fuel savings, CO2 reductions, and total industry 

cost outlays for model year 2012 – 2016 for the eight alternatives. 

Table III-13. Fuel Savings, CO2 Reductions, and Technology Costs for Regulatory Alternatives

Regulatory Alternative Fuel Savings

(b. gal)

CO2 Reductions

(mmt)

Cost

($b)

3% per Year 34 373 23 

4% per Year 50 539 39 

Final (4.3% per Year) 61 655 52 

5% per Year 68 709 63 

6% per Year 82 840 90 

Maximum Net Benefit 90 925 103 

7% per Year 93 945 111 

Total Cost = Total Benefit 96 986 114 

As noted earlier, NHTSA has used the Volpe model to analyze each of these alternatives based 

on analytical inputs determined jointly with EPA. For a given regulatory alternative, the Volpe 

model estimates how each manufacturer could apply technology in response to the MY 2012 

standard (separately for cars and trucks), carries technologies applied in MY 2012 forward to 

MY 2013, and then estimates how each manufacturer could apply technology in response to the 

MY 2013 standard. When analyzing MY 2013, the model considers the potential to add “extra” 

technology in MY 2012 in order to carry that technology into MY 2013, thereby avoiding the use 

of more expensive technologies in MY 2013. The model continues in this fashion through MY 

2016, and then performs calculations to estimate the costs, effects, and benefits of the applied 

technologies, and to estimate any civil penalties owed based on projected noncompliance. For 

each regulatory alternative, the model calculates incremental costs, effects, and benefits relative 

to the regulatory baseline (i.e., the no-action alternative), under which the MY 2011 CAFE 

standards continue through MY 2016. The model calculates results for each model year, because 

EPCA requires that NHTSA set its standards for each model year at the “maximum feasible 

average fuel economy level that the Secretary decides the manufacturers can achieve in that 

model year” considering four statutory factors. Pursuant to EPCA’s requirement that NHTSA 

not consider statutory credits in establishing CAFE standards, NHTSA did not consider FFV 

credits, credits carried forward and backward, and transferred credits in this calculation45, 46 In 

addition, the analysis incorporates fines for some manufacturers that have traditionally paid fines 

rather than comply with the standards. Because it entails year-by-year examination of eight 

regulatory alternatives for, separately, passenger cars and light trucks, NHTSA’s analysis 

involves a large amount of information. Detailed results of this analysis are presented separately

in Chapter XI below. 

 

45 NHTSA has conducted a separate analysis, discussed in Chapter XI, which accounts for EPCA’s provisions 

regarding FFVs. 

46 For a number of reasons, the results of this modeling differ from EPA’s for specific manufacturers, fleets, a

model years. These reasons include representing every model year explicitly, accounting for estimates of when 

vehicle model redesigns will occur, and not considering those compliance flexibilities where EPCA forbids such 

consideration in setting CAFE standards. It should be noted, however, that these flexibilities in fact provide 

manufacturers significant latitude to manage their compliance obligations. 

nd 
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es 

s for additional technology in 

each model year. The following figure shows cu ulative results for MYs 2012-2016 for 

industry as a whole oyota. This figure 

focuses on these manufacturers as they currently (in MY 2010) represent three large U.S.-

headquartered and three large foreign-headquartered full-line manufacturers. 

Figure III-2. Incremental Technology Outlays (MYs 2012-2016) 

In reviewing the results of the various alternatives, NHTSA confirmed that progressive increas

in stringency require progressively greater deployment of fuel-saving technology and 

corresponding increases in technology outlays and related costs, fuel savings, and CO2 emission 

reductions. To begin, NHTSA estimated total incremental outlay

m

and Chrysler, Ford, General Motors, Honda, Nissan, and T

-

20 

40 

60 

80 

100 

-

5 

10 

15 

20 

25 

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

I

n

c

r

e

m

e

n

t

a

l

T

e

c

h

n

o

l

o

g

y

O

u

t

l

a

y

s

(

$

b

)

30 120 

Chrysler

Ford

General Motors

Honda

Nissan

Toyota

Industry

 

As part of the incremental technology outlays, NHTSA also analyzes which technologies 

manufacturers could apply to meet the standards. In NHTSA’s analysis, manufacturers achieve 

compliance with the fuel economy levels through application of technology rather than through 

anges in the mix of vehicles produced for sale in the U.S. The accompanying FRIA presents 

ailed estimates of additional technology penetration into the NHTSA reference fleet 

ssociated with each regulatory alternative. The following four charts illustrate the results of this 

alysis, considering the application of four technologies by six manufacturers and by the 

ch

det

a

an

industry as a whole. Technologies include gasoline direct injection (GDI), engine turbocharging 

and downsizing, diesel engines, and strong HEV systems (including CISG systems). GDI and 

turbocharging are presented because they are among the technologies that play an important role 
54

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

in achiev d 

strong HEVs are presented because they re ologies involving significant cost and 

related lead time challenges for widespread use through MY 2016. These figures focus on 

Chrysler, Ford, General Motors, Honda, Nissan, and Toyota, as above. For each alternative, the 

figures show additional application of technology by MY 2016. 

Figure III-3. Additional Application of GDI (MY 2016) 

ing the fuel economy improvements shown in NHTSA’s analysis, and diesels an

present techn

0%

20%

40%

60%

80%

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

A

d

d

i

t

i

o

n

a

l

A

p

p

l

i

c

a

t

i

o

n

(

%

P

r

o

d

u

c

t

i

o

n

)

100%

Chrysler

Ford

General Motors

Honda

Nissan

Toyota

Industry
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Figure III-4. Additional Application of Engine Turbocharging & Downsizing 

(MY 2016) 

0%

20%

40%

60%

80%

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

A

d

d

i

t

i

o

n

a

l

A

p

p

l

i

c

a

t

i

o

n

(

%

P

r

o

d

u

c

t

i

o

n

)

100%

Chrysler

Ford

General Motors

Honda

Nissan

Toyota

Industry
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Figure III-5. Additional Application of Diesel Engines (MY 2016) 

0%

20%

40%

60%

80%

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

A

d

d

i

t

i

o

n

a

l

A

p

p

l

i

c

a

t

i

o

n

(

%

P

r

o

d

u

c

t

i

o

n

)

100%

Chrysler

Ford

General Motors

Honda

Nissan

Toyota

Industry
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Figure III-6. Additional Application of CISG and Strong HEV Systems (MY 2016) 

0%

20%

40%

60%

80%

100%

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

A

d

d

i

t

i

o

n

a

l

A

p

p

l

i

c

a

t

i

o

n

(

%

P

r

o

d

u

c

t

i

o

n

)

Chrysler

Ford

General Motors

Honda

Nissan

Toyota

Industry

 

The modeling analysis demonstrates that applying these technologies, of course, results in fuel 

savings. Relevant to EPCA’s requirement that NHTSA consider, among other factors, economic 

practicability and the need of the nation to conserve energy, the following figure compares the 

incremental technology outlays and related cost presented above for the industry to the 

corresponding cumulative fuel savings. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Figure III-7. Incremental Technology Outlays and Fuel Savings (MYs 2012-2016) 

-

20 

40 

60 

80 

100 

120 120 

-

20 

40 

60 

80 

100 

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

F

u

e

l

S

a

v

i

n

g

s

(

b

.

g

a

l

.

)

T

e

c

h

n

o

l

o

g

y

O

u

t

l

a

y

s

(

$

b

)

Cost Fuel Savings
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These incremental technology outlays (and corresponding fuel savings) also result in 

corresponding increases in incremental cost per vehicle, as shown below. The following five 

figures show industry-wide average incremental (i.e., relative to the reference fleet) per-vehicle 

costs, for each model year, each fleet, and the combined fleet. Estimates specific to each 

manufacturer are shown in Chapter VII. 

Figure III-8. Average Incremental Per-Vehicle Costs (MY 2012) 

-

500 

1,000 

1,500 

2,000 

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

A

v

e

r

a

g

e

T

e

c

h

n

o

l

o

g

y

C

o

s

t

(

$

/

V

e

h

i

c

l

e

)

2,500 

PC

LT

Comb.
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Figure III-9. Average Incremental Per-Vehicle Costs (MY 2013) 

-

500 

1,000 

1,500 

2,000 

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

A

v

e

r

a

g

e

T

e

c

h

n

o

l

o

g

y

C

o

s

t

(

$

/

V

e

h

i

c

l

e

)

2,500 

PC

LT

Comb.
61

Figure III-10. Average Incremental Per-Vehicle Costs (MY 2014) 

-

500 

1,000 

1,500 

2,000 

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

A

v

e

r

a

g

e

T

e

c

h

n

o

l

o

g

y

C

o

s

t

(

$

/

V

e

h

i

c

l

e

)

2,500 

PC

LT

Comb.

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62

Figure III-11. Average Incremental Per-Vehicle Costs (MY 2015) 

-

500 

1,000 

1,500 

2,000 

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

A

v

e

r

a

g

e

T

e

c

h

n

o

l

o

g

y

C

o

s

t

(

$

/

V

e

h

i

c

l

e

)

2,500 

PC

LT

Comb.

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63

Figure III-12. Average Incremental Per-Vehicle Costs (MY 2016) 

2,000 

2,500 

i

c

l

e

)

-

500 

1,000 

1,500 

3%/y 4%/y Final 5%/y 6%/y Max. NB 7%/y TC=TB

A

v

e

r

a

g

e

T

e

c

h

n

o

l

o

g

y

C

o

s

t

(

$

/

V

e

h

PC

LT

Com

As discussed in the NPRM, the agency began the process of winnowing the alternatives by 

determining whether any of the lower stringency alternatives should be eliminated from 

consideration. To begin with, the agency needs to ensure that its standards are high enough 

enable the combined fleet of passenger cars and light trucks to achieve at least 35 mpg not later 

than MY 2020, as required by EISA. Achieving that level makes it necessary for the chosen 

alternative to increase at over 3 percent annually. Additionally, given that CO2 and fuel savings 

are very closely correlated, the 3%/y and 4%/y alternative would not produce the reductions in 

fuel savings and CO2 emissions that the Nation needs at this time. Picking either of those 

alternatives would unnecessarily result in foregoing substantial benefits, in terms of fuel savings 

and red ced CO

b.

to 

2 emissions, which would be achievable at reasonable cost. And finally, neither 

 vital 

ent. 

u

the 3%/y nor the 4%/y alternatives would lead to the regulatory harmonization that forms a

core principle of the National Program that EPA and NHTSA are jointly striving to implem

These alternatives would give inadequate weight to other standards of the Government, 

specifically EPA’s and CARB’s. Thus, the agency concluded that alternatives less stringent than

the proposed standards would not yield the emissions reductions required to produce a 

harmonized national program and would not produce corresponding fuel savings, and therefore 

would not place adequate emphasis on the nation’s need to conserve energy. NHTSA has 

therefore concluded that it must reject the 3%/y and 4%/y alternatives. 

DELIBERATIVE DOCUMENT – DO NOT RELEASE 
64

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ion 

e 

SA 

r technologically feasible, and thus concludes that it would result in standards that would be 

beyo

For the ot es, NH t w a t f the 

other mo t alternatives du oncer lead nd ec c prac ity. 

There are ld technological ono on s whi due 

to the sho me available for t ly y his p , in p ar fo 2012 

and 2013. es more st t than nal st s beg ccrue

considera re rapidly than they fue ngs and ons tions, a levels 

that are in ly economically b some cially ering ed to

underlyin tments (e.g., for en ring an ling) adva actual tion. 

As shown s III-2 to III-6 a while nal st s alre e sive 

applicatio hnologies, more s t stan would ire m r 

(includin ubstantial impleme on of ced te gies s s stoichiometric 

gasoline jection engines, di ngines stron s), uld r ious 

issues of y of lead time, no o mee stand t to te s nificant 

changes w nufacturers’ redesig cles. T ency m ains, as s histo , that 

there is a distinction bet onsid ns of logica ibility 

economic bility, both of wh ter int agency termin of th um 

feasible levels of stringency. A given level of pe nce may be technologically feasible (i.e., 

setting aside economic constraints) for a given v icle model. However, it would not be 

econ

vehicle will immediately (i.e., with omulgation) perform at its 

highest te feasib ec fa n li ss to the 

financial or the time requ hire e h eng build ac and 

install en ling. The lead tim sonab ded t capit stme to 

devote th and time to d nd pr r co al p on of fuel 

efficient portant ele that N takes onsid n e hing the 

standards

In additio igures presented ab eveal creasi ingenc ond t l 

standards ail significant ad al app on o ology the more 

stringent ives, the one close tringen the s s be lized is the 

alternativ which combined CA stringe increase an . As i ted 

above, th ative would yield ving O2 r ns ab % an igher, 

respectiv the final standards. wev ared final ds, rnative 

 

NHTSA then considered the “environmentally-preferable” alternative. Based on the informat

provided in the FEIS, the environmentally-preferable alternative would be that involving 

stringencies that increase at 7% annually.47 NHTSA notes that NEPA does not require that 

agencies choose the environmentally-preferable alternative if doing so would be contrary to th

choice that the agency would otherwise make under its governing statute. Given the levels of 

technology and cost required by the environmentally-preferable alternative and the lack of lead 

time to achieve such levels between now and MY 2016, as discussed further below, NHT

concludes that the environmentally-preferable alternative would not be economically practicable 

o

nd the level achievable for MYs 2012-2016. 

her alternativ TSA determined that i ould be in ppropriate o choose any o

re stringen

r

e 

and

to c ns over 

mic tim

ti

st

me a o

ch

nomi ticabil

real-wo

d ti

 ec

r

e c

 t

raint must be considered 

rt lea he ea ears of rogram articul r MYs 

 The alternativ ringen the fi andard in to a costs 

bly mo accrue l savi emissi reduc nd at

creasing urden , espe consid the ne make 

g inves ginee d too well in nce of produc

 in Figure bove, the fi andard ady requir aggres

n of tec tringen dards requ ore widesp ead use

g more s ntati advan chnolo uch a

direct in esel e , and g hybrid and wo aise ser

adequac t only t t the ards bu coordina uch sig

ith ma n cy he ag aint it ha rically

n important ween c eratio techno l feas and 

 practica ich en o the ’s de ation e maxim

rforma

eh

omically practicable to require a level of fleet average performance that assumes every 

in 18 months of the rule’s pr

chnologically le level, b ause manu cturers do ot have un mited acce

resources ired to noug i

o m

neers,

al i

enough f il

nts

ities,

ough too

urces 

e rea ly nee ake nve and 

e reso esign a epare fo mmerci roducti a more

vehicle is an im ment HTSA into c eration i stablis

. 

n, the f ove r

dition

that in

li

ng str y bey he fina

would ent cati f techn . Among

alternat st in s cy to tandard ing fina today 

e under FE ncy s at 5% nually ndica

is altern fuel sa s and C eductio out 11 d 8% h

ely, than Ho er, comp to the standar this alte

47 See, e.g. 2, p. 18, which sh that 7%/y rnative greates lative e n global 

mean temp

, FEIS, figure S-1 ows alte yields t cumu ffect o

erature. 
65

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would increase outlays for new technologies dur MY 2012-2016 by about 22%, or $12b. 

Ave

$1,152 when stringency increases at 5% an s represents a 28% increase in per-vehicle 

cost for o ease in er (o -p sis fuel 

savings ar rtional). Addition he 5% ernativ ly burd e light 

truck flee g a nearly $400 ( rcent) ncrea Y 20 pare e final 

standards llowing three tabl ma imate factu el av

increment 5%/y alter nd erage passe nd lig k fleets: 

Tab verage Increm osts ( icle) the 5% terna FE 

S r enger

MY 2 MY 2 MY MY MY

ing

rage MY 2016 cost increases would, in turn, rise from $903 under the final standards to 

nually. Thi

nly a 3% incr average p formance n a gallon er-mile ba to which

e propo

n

a

4

lly, t /

c

y alt e dispropo

se

r

1

tional ens th

t requiri

fo

2 pe ost i in M 6 com d to th

. The es sum rize est

t

d manu rer-lev erage 

al costs for the native a he av of the nger a ht truc

le III-14. A ental C $/veh under /y Al tive CA

tandards fo Pass Cars 

Manufacturer 012 013 2014 2015 2016 

BMW 3 4 24 184 585 

Chrysler 734 1,303 1,462 1,653 1,727 

Daimler - - 410 801 1,109 

Ford 743 1,245 1,261 1,583 1,923 

General Motors 448 823 1,187 1,425 1,594 

Honda 50 109 271 375 606 

Hyundai 747 877 1,057 1,052 1,124 

Kia 49 128 197 261 369 

Mazda 555 718 1,166 1,407 1,427 

Mitsubishi 534 7 2,534 3,213 3,141 50

Nissan 294 491 965 1,064 1,125 

Porsche 68 (52) (51) (50) (49) 

Subaru 292 324 1,372 1,723 1,679 

Suzuki - 959 1,267 1,316 1,540 

Tata 111 93 183 306 710 

Toyota 31 29 52 129 212 

Volkswagen 145 428 477 492 783 

Average 337 540 726 886 1,053 

Table III-15. Average Incremental Costs ($/vehicle) under the 5%/y Alternative CAFE 

Standards for Light Trucks 

Manufacturer MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 

BMW 169 160 201 453 868 

Chrysler 360 559 1,120 1,216 1,432 

Daimler 60 55 51 52 51 

Ford 1,207 1,663 1,882 2,258 2,225 

General Motors 292 628 866 968 1,136 

Honda 258 234 611 750 1,047 

Hyundai 711 685 1,923 1,909 1,862 

Kia 47 293 556 782 1,157 

Mazda 248 408 419 519 768 

Mitsubishi - - 1,037 1,189 1,556 

Nissan 613 723 2,142 2,148 2,315 

Porsche - (0) (1) 469 469 

Subaru 1,225 1,220 1,365 1,374 1,330 

Suzuki - 1,998 1,895 1,837 2,096 

Tata - - - - 503 

Toyota 63 187 594 734 991 

Volkswagen - - 514 458 441 

Average 415 628 1,026 1,173 1,343 
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MY 2016 

Table III-16. Average Incremental Costs ($/vehicle) under the 5%/y Alternative CAFE 

Standards 

Manufacturer MY 2012 MY 2013 MY 2014 MY 2015 

BMW 72 64 84 265 666 

Chrysler 499 870 1,272 1,414 1,569 

Daimler 20 20 281 554 773 

Ford 914 1,407 1,498 1,838 2,034 

General Motors 371 726 1,033 1,205 1,379 

Honda 135 157 396 518 769 

Hyundai 742 838 1,237 1,186 1,235 

Kia 49 168 273 355 506 

Mazda 500 667 1,053 1,272 1,330 

Mitsubishi 371 352 1,973 2,386 2,506 

Nissan 399 565 1,344 1,387 1,467 

Porsche 52 (39) (35) 130 124 

Subaru 617 628 1,369 1,597 1,553 

Suzuki - 1,134 1,381 1,404 1,630 

Tata 61 56 101 182 629 

Toyota 43 82 239 333 466 

Volkswagen 117 333 486 486 723 

Average 367 573 836 987 1,152 

These cost increases derive from increased application of advanced technologies as stringency 

increases past the levels in the final standards. For example, under the final standards, addition

diesel application rates average 1.6% for the industry and range from 0% to 3% among Chrysler,

Ford, GM, Honda, Nissan, and Toyota. Under standards increasing in combined stringenc

5% annually, these rates more than triple, averaging 6.2% for the industry and ranging fr

to 21% for the same six manufacturers. 

These technology and cost increases are significant, given the amount of lead-time between no

and model years 2012-2016. In order to achieve the levels of technology penetration for the fin

standards, the industry needs to invest significant capital and product de

al 

y at 

om 0% 

w 

al 

velopment resources 

right aw in particular for the 2012 and 2013 model year, which is only 2-3 years from now. 

It is important to note, and as discussed in the final rule, as well as in the Joint Technical Support 

re 

ay, 

For the 2014-2016 time frame, significant product development and capital investments will 

need to occur over the next 2-3 year in order to be ready for launching these new products for 

those model years. Thus a major part of the required capital and resource investment will need 

to occur now and over the next few years, under the final standards. NHTSA believes that the 

final rule requires significant investment and product development costs for the industry, focused 

on the next few years. 

Document and later in this FRIA, the average model year 2016 per-vehicle cost increase of mo

than $900 includes an estimate of both the increase in capital investments by the auto companies

and the suppliers as well as the increase in product development costs. These costs can be 

significant, especially as they must occur over the next 2-3 years. Both the domestic and 

transplant auto firms, as well as the domestic and world-wide automotive supplier base, are 

experiencing one of the most difficult markets in the U.S. and internationally that has been seen 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

d 

The ag y concludes that the levels of technology penetration required by the final standards 

ent 

the most 

approp balance of the various statutory factors. 

at 

” 

osts 

 of 

ld 

d 

in the past 30 years. One major impact of the global downturn in the automotive industry an

certainly in the U.S. is the significant reduction in product development engineers and staffs, as 

well as a tightening of the credit markets which allow auto firms and suppliers to make the nearterm capital investments necessary to bring new technology into production. 

enc

are reasonable. Increasing the standards beyond those levels would lead to rapidly increasing 

dependence on advanced technologies with higher costs—technology that, though perhaps 

technologically feasible for individual vehicle models, would, at the scales involved, pose too 

great an economic burden given the state of the industry, particularly in the early years of the 

rulemaking time frame.48

Therefore, the agency concluded that these more stringent alternatives would give insuffici

weight to economic practicability and related lead time concerns, given the current state of the 

industry and the rate of increase in stringency that would be required. Overall, the agency 

concluded that among the alternatives considered by the agency, the proposed alternative 

contained the maximum feasible CAFE standards for MYs 2012-2016 as they were 

riate

Some commenters argued that the agency should select a more stringent alternative than th

proposed in the NPRM. The Union of Concerned Scientists (UCS) commented that NHTSA 

should set standards to produce the “maximum environmental benefit” available at “reasonable

cost, and at least at the stringency maximizing net benefits. Students from the University of 

California at Santa Barbara commented that the agency should have based standards not just on 

technologies known to be available, but also on technologies that may be available in the 

future—and should do so in order to force manufacturers to “reach” to greater levels of 

performance. Also, the Center for Biological Diversity (CBD) commented that, having 

conducted an unbiased cost-benefit analysis showing benefits three times the magnitude of c

for the proposed alternative, the agency should select a more stringent alternative. CBD also

argued that the agency should have evaluated the extent to which manufacturers could deploy 

technology more rapidly than suggested by a five-year redesign cycle. 

Conversely, other commenters argued that NHTSA should select a less stringent alternative, 

either in all model years or at least in the earlier model years. Chrysler, VW, and the Alliance

Automobile Manufacturers commented that the stringency of NHTSA’s CAFE standards shou

be further reduced relative to that of EPA’s GHG emissions standards, so that manufacturers 

would not be required by CAFE to add any tailpipe technology beyond what they thought would 

be necessary to meet an mpg level of 35.5 minus the maximum possible A/C credits that coul

be obtained under the EPA program. Also, Chrysler, Daimler, Toyota, Volkswagen, and the 

 

48 Although the final standards are projected to be slightly more costly than the 5% alternative in MY 2012, that 

alternati tandard becomes progressively more costly than the final standards in the remaining model years. See 

significantly increased economic burden on the manufacturers in the next few calendar years to prepare for these 

 the 

ve s

Figures III.B.8 through III.B.10 above. Moreover, as discussed above, after MY 2012, the 5% alternative standard 

yields less incremental fuel economy benefits at increased cost (both industry-wide and per vehicle), directionally 

the less desirable result. These increased costs incurred to increase fuel economy through MY 2016 would impose

future model years. In weighing the statutory factors, NHTSA accordingly rejected this alternative in favor of

final standard. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ss 

he 

osed standards, as well as the agencies’ underlying technical analysis and 

weighi of statutory factors. CARB further commented that the stringency increases in the 

e 

 finds 

that alternatives less stringent that the one adopted today would leave too much technology “on 

ference, 

y MY 

 difficulty 

Alliance argued that the agency should reduce the rate of increase in stringency to produce 

steadier and more “linear” increases between MY 2011 and MY 2016. In addition, the Heritage

Foundation commented that the proposed standards would, in effect, force accelerated progre

toward EISA’s “35 mpg by 2020” requirement, causing financially-stressed manufacturers to 

incur undue costs that would passed along to consumers. 

However, most commenters supported the agency’s selection of the proposed standards. T

American Chemical Society, the New York Department of Environmental Conservation, the 

Washington State Department of Ecology, and several individuals all expressed general support 

for the levels of stringency proposed by NHTSA as part of the joint proposal. General Motors 

and Nissan both indicated that the proposed standards are consistent with the National Program 

announced by the President and supported in letters of commitment signed by these companies’ 

executives. Finally, the California Air Resources Board (CARB) strongly supported the 

stringency of the prop

ng 

earlier model years are essential to providing environmental benefits at least as great as would be

achieved through state-level enforcement of CARB’s GHG emissions standards.49 

The agency has considered these comments and all others, and having considered those 

comments, believes the final standards best balance of all relevant factors that the agency 

considers when determining maximum feasible CAFE standards. As discussed below, having 

updated inputs to its analysis and correspondingly updated its definition and analysis of these 

regulatory alternatives, the agency continues to conclude that manufacturers can respond to th

proposed standards with technologies that will be available at reasonable cost. The agency

the shelf” unnecessarily, thereby failing to deliver the fuel savings that the nation needs or to 

yield environmental benefits necessary to support a harmonized national program. In response to

some manufacturers’ suggestion that NHTSA’s CAFE standards should be made even less 

stringent compared to EPA’s GHG emissions standards, NHTSA notes that the dif

consistent with the underlying Notice of Intent, is based on the agencies’ estimate of the average

amount of air conditioning credit earned, not the maximum theoretically available, and that 

NHTSA’s analysis indicates that most manufacturers can achieve the CAFE standards b

2016 using tailpipe technologies. This is fully consistent with the agency’s historical position. 

As NHTSA explained in the NPRM, the Conference Report for EPCA, as enacted in 1975, 

makes clear, and applicable law affirms, “a determination of maximum feasible average fuel 

economy should not be keyed to the single manufacturer which might have the most

achieving a given level of average fuel economy.” CEI-I, 793 F.2d 1322, 1352 (D.C. Cir. 1986). 

Instead, NHTSA is compelled “to weigh the benefits to the nation of a higher fuel economy 

standard against the difficulties of individual automobile manufacturers.” Id. Thus, the law 

permits CAFE standards exceeding the projected capability of any particular manufacturer as 

long as the standard is economically practicable for the industry as a whole. 

While some manufacturers may find greater A/C improvements to be a more cost-effective way 

of meeting the GHG standards, that does not mean those manufacturers will be unable to meet 

 

49 Generally speaking, the cumulative benefits (in terms of fuel savings and GHG reductions) of front-loaded 

standards will be greater than standards that increase linearly. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

gies. 

“Econo ic practicability” means just that, practicability, and need not always mean what is 

s. 

TSA 

e 

aking 

ed to 

dards. Therefore, the agency believes that alternatives less 

stringent than the one adopted today would not give sufficient emphasis to the nation’s need to 

t 

ent 

ndence on the most expensive 

logies and those which are technically more demanding to implement, with 

are not ec racticab th e di ie e. The 

agency al rees with CBD’s a on th SA a A hav overl

conserva suming an averag sign f 5 y ere e m urers 

who appl cycles (such as man ers d d abo ere ar s who 

have shor ome of the ucts, ere a e pro g., c ans) that 

tend to be gned on longer cycl HTSA eves th re are ll line 

manufact o can maintain sig nt red s of ve (with ve larg s) in 1 

or 2 year BD has provided n ence ting th uld be icable. mplete 

redesign e U.S. light-dut t by m year 2 clear asible HTSA 

and EPA at several mode additi ad t ces orde e 

manufact meet the most strin and e gr ed incr the cy of 

 

the CAFE standards with tailpipe technologies. NHTSA’s analysis has demonstrated a feasible

path to compliance with the CAFE standards for most manufacturers using those technolo

m

“cheapest” or “most cost-effective” for a specific manufacturer. Moreover, many of the A/C 

improvements on which manufacturers intend to rely for meeting the GHG standards will reduce 

GHG emissions, specifically HFC emissions, but they will not lead to greater fuel saving 50

The core purpose of the CAFE standards under EPCA is to reduce fuel consumption. NH

believes that less stringent standards would allow tailpipe fuel economy technologies to be left 

on the table that can be feasibly and economically applied, and failing to apply them would lead 

to a loss in fuel savings. This would not place appropriate emphasis on the core CAFE purpos

of conserving fuel. For this reason, we decline to reduce the stringency of our standards as 

requested by some manufacturers. Similarly, we decline to pursue with EPA in this rulem

the suggestion by one commenter that that agency’s calculation authority under EPCA be us

provide A/C credits. 

With respect to some manufacturers’ concerns regarding the increase in stringency through MY

2013, the agency notes that stringency increases in these model years are especially important in

terms of the accumulation of fuel savings and emission reductions over time. In addition, a 

weakening would risk failing to produce emission reductions at least as great as might be

achieved through CARB’s GHG stan

conserve energy. The requirement to set standards that increase ratably between MYs 2011 and

2020 must also be considered in the context of what levels of standards would be maximum 

feasible. The agency believes that the rate of increase of the final standards is reasonable. 

On the other hand, the agency disagrees with comments by UCS, CBD, and others indicating tha

more stringent standards would be appropriate. As discussed above, alternatives more string

than the one adopted today would entail a rapidly increasing depe

techno

commensurately rapid increases in costs. In the agency’s considered judgment, these alternatives 

onomically p le, nor do ey provid correspon ngly suffic nt lead tim

so disag ss

e r

erti at NHT

 cycl

nd

ea

 EP e

 a

 been y

tive in as

er

ede e o rs. Th re som anufact

y long smaller

i

ufactur escribe ve), th e other

ter cycles for s r prod and th re som ducts (e. argo v

 redesi es. N beli at the no fu

urers wh nifica esign hicles relati e sale

s, and C o evid indica is wo pract A co

of the entir

 th

y flee odel 012 is

im

ly infe

s

, and N

believe l years onal le e is ne ary in r for th

urers to gent st ards. Th aduat ease in stringen

50 This is n TSA means, in ay, to d anufacturers from emp A/C tec ies to 

meet EPA’ t simply to say th A’s i ndent ob n to set um feas AFE 

standards t rough application of e techn alone m fulfille recogn the 

flexibilities offered in another regulatory program. 

ot to say that NH

s standards, bu at NHTS

any w e

ndepe

ter m loying hnolog

ligatio maxim ible C

o be met th tailpip ologies ust be d, while izing 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

the standards from MYs 2012 through 2016 acco ts for the economic necessity of timing the 

a

In contra alysis of the ative r shown e, as w e omplete 

and detail s presented in thi ysis, N A has ed th fina rds are 

technolog asible and econom prac e. The and ill re

manufact siderabl tional ology, ng wit signif 

investme hnology design, de ment apital i ment c for in t xt few 

years. A HTSA cannot pr how m e respo he fi rds, 

the agenc lysis indicates that andards could lead gnifica reate f 

advanced d transmission t logies hown e, the a y’s an shows 

considera eases in the applic of SGDI systems a gine hargi

downsizi ugh not presented ab , the a y’s anal also sh ilar e 

increases se of dual-clutch ted m trans ns (A How he 

agency’s s does not suggest tha e ad app th nol 

response nal standards woul nd be levels achievable b indust hese 

technolog to be applied t least so xtent in the ce of n AFE 

standards tion, the agency’ s in s that manufa u ly 

to a limited extent on the most costly technologi ch as diesel engines and advanced 

technologies, such as strong HEVs. 

As shown i t t an ld l era ental 

costs rang $303 per vehicle light tru in MY ) to $9 r veh r light 

trucks in ), increasing stea rom $ er vehi r all hicle 2012 

to $903 f ht vehicle in MY NH timat these woul

considera nufacturer ould excee 00 p cle. wing 

three tabl arize estimated m cturer averag ent sts for nal 

standards average of the pas r and ruck f

Table III ge Incremental ($/ve under Final Pass ar C tandards 

MY 2 MY 2 MY 2 MY MY

un

pplication of many major technologies to coincide with scheduled model redesigns. 

st, through an

t

illustr esults abov ell as th m

l st

ore c

ed resul

y fe

s anal HTS conclud at the anda

icall ically ticabl final st ards w quire 

urers to apply con e addi techn starti h very icant

nt in tec velop and c nvest alled he ne

lthough N edict anufactur rs will nd to t nal standa

y’s ana the st

ech

 to si ntly g r use o

 engine an no . As s abov genc alysis 

ble incr ation nd en turboc ng and 

ng. Tho ove genc ysis ows sim ly larg

in the u automa anual missio MTs). ever, t

 analysi t th ditional lication of ese tech ogies in

to the fi d exte yond

m

y the ry. T

ies are likely o at e e even absen ew C

. In addi s analysi dicate most cturers wo ld rely on

es, su

 below, NHTSA est mates tha he final st dards cou ead to av ge increm

ing from

6

 (for cks 2012 47 pe ic

s 

le (fo

MY 201

lig

dily f 396 p cle fo light ve in MY

or all 2016. 

s

TSA es es that costs d vary 

bly among ma , but w rarely d $1,8 er vehi The follo

es summ anufa -level e increm al co the fi

and the senge light t leets: 

-17. Avera

turer 

 Costs hicle) enger C

 2

AFE S

Manufac 012 013 014 015 2016 

BMW 3 4 24 184 585 

Chrysler 734 1,043 1,129 1,270 1,358 

Daimler - - 410 801 1,109 

Ford 1, 1 619 ,537 1,533 1,713 1,884 

General Motors 448 1 896 ,127 1,302 1,323 

Honda 33 98 205 273 456 

Hyundai 559 591 768 744 838 

Kia 110 4 14 177 235 277 

Mazda 555 6 799 854 923 65

Mitsubishi 534 460 1,588 1,875 1,831 

Nissan 119 323 707 723 832 

Porsche 68 (52) (51) (50) (49) 

Subaru 292 324 988 1,385 1,361 

Suzuki - 625 779 794 1,005 

Tata 111 93 183 306 710 

Toyota 31 29 41 121 126 

Volkswagen 145 428 477 492 783 

Average 455 552 670 774 880 
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Table III-18. Average Incremental Costs ($/vehicle) under Final Light Truck CAFE Standards 

Manufacturer MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 

BMW 252 239 277 281 701 

Chrysler 360 527 876 931 1,170 

Daimler 60 51 51 52 51 

Ford 465 633 673 1,074 1,174 

General Motors 292 513 749 807 986 

Honda 233 217 370 457 806 

Hyundai 693 630 1,148 1,136 1,113 

Kia 400 467 582 780 1,137 

Mazda 144 241 250 354 480 

Mitsubishi - - 553 686 1,371 

Nissan 398 489 970 1,026 1,362 

Porsche - (1) (1) 469 469 

Subaru 1,036 995 1,016 1,060 1,049 

Suzuki - 1,797 1,744 1,689 1,732 

Tata - - - - 503 

Toyota 130 150 384 499 713 

Volkswagen - - 514 458 441 

Average 303 411 615 741 947 

Table III-19. Average Incremental Costs ($/vehicle) under Final CAFE Standards 

Manufacturer MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 

BMW 106 94 110 213 618 

Chrysler 499 743 989 1,084 1,257 

Daimler 20 18 281 554 773 

Ford 1,195 1,187 1,205 1,472 1,622 

General Motors 371 705 946 1,064 1,165 

Honda 116 144 266 343 585 

Hyundai 577 599 847 805 879 

Kia 176 221 263 334 426 

Mazda 482 587 716 778 858 

Mitsubishi 371 319 1,200 1,389 1,647 

Nissan 211 376 792 813 984 

Porsche 52 (39) (35) 130 124 

Subaru 551 552 998 1,267 1,248 

Suzuki - 823 954 946 1,123 

Tata 61 56 101 182 629 

Toyota 67 70 159 248 317 

Volkswagen 117 333 486 486 723 

Average 396 498 650 762 903 

In summary, NHTSA has considered eight regulatory alternatives, including the final standards, 

examining technologies that could be applied in response to each alternative, as well as 

corresponding costs, effects, and benefits. The agency has concluded that alternatives less 

stringent than the final standards would not produce the fuel savings and CO2 reductions 

necessary at this time to achieve either the overarching purpose of EPCA, i.e., energy 

conservation, or an important part of the regulatory harmonization underpinning the National 

Program, and would forego these benefits even though there is adequate lead time to implement 

reasonable and feasible technology for the vehicles. Conversely, the agency has concluded that 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

 s

uld provide inadequate lead time, 

ustry, would not be economically 

erefore, having considered these eight regulatory alternatives, and the statutorilyotor 

more tringent standards would involve levels of additional technology and cost that would be

economically impracticable and, correspondingly, wo

considering the economic state of the automotive ind

practicable. Th

relevant factors of technological feasibility, economic practicability, the effect of other m

vehicle standards of the Government on fuel economy, and the need of the United States to 

conserve energy, along with other relevant factors such as the safety impacts of the final 

standards, NHTSA concludes that the final standards represent a reasonable balancing of all of 

these concerns, and are the maximum feasible average fuel economy levels that the 

manufacturers can achieve in MYs 2012-2016. 
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V. IMPACT OF OTHER MOTOR VEHICLE STANDARDS OF THE 

troduction

I

GOVERNMENT ON FUEL ECONOMY 

In

The Energy Policy and Conservation Act ( Act) requires that fuel economy 

standards be set a eria: (1) 

tec ibility, (2) e impact of o t 

stan on fuel economy, and (4) n to con

as a ne, this section discusses overnme

(M 2-2016 passenger car and . Th

inc the Volpe model at this on MY 

EPCA or the

t the maximum feasible level after considering the following crit

hnological feas conomic practicability, (3) the ther Governmen

dards the need of the Natio serve energy. Using MY 2008 

 baseli the effects of other g nt regulations on model year 

Y) 201 light truck fuel economy ese effects have not been 

luded in time, which is based 2008 vehicles. 

The Impact on Weight of Safety Standards and Voluntary Safety Improvements 

The fuel economy impact of safety improvements will typically take the form of increased 

vehicle weight, which reduces the fuel economy of the vehicle. The agency’s estimates are 

ased on cost and weight tear-down studies of a few vehicles and cannot possibly cover all the 

variations in the manufacturers’ fleets. NH ted, and various manufacturers provided, 

confidential estimates in 2009 o safety improvements. Those 

incr ases are shown in subsequent ta

We wn our analysis of the i of safety standards that mig ct the MY 

201 to three parts: 1) those N final rules with known effec ates, 2) 

rop r soon to be proposed rule HTSA, without final effectiv tes, and 3) 

urrently voluntary safety improvements planned by the manufacturers. 

b

TSA reques

f increases in weight resulting from

e bles. 

 have broken do mpact ht affe

2-16 fleets in

osed rules o

HTSA

s by N

tive d

p e da

c

Weight Impacts of Required Safety Standards (Final Rules)

The National Highway Traffic Safety Administration (NHTSA) has issued several safety 

standards that become effective for passenger cars and light trucks between MY 2009 and MY 

2016. We will examine the potential impact on passenger car and light truck weights for MY 

2012-2016, using MY 2008 as a baseline. 

1. FMVSS 126, Electronic Stability Control 

2. FMVSS 206, Door Latches for Sliding Doors 

3. FMVSS 208, 35 mph Belted Testing of 5th Female 

4. FMVSS 214, Side Impact Oblique Pole Test 

5. FMVSS 216, Roof Crush 
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FMVSS 126, Electronic Stability Control

The phase-in schedule for vehicle manufacturers is: 

Electronic Stability Control Effective Dates Phase-in Schedule 

Table IV-1 

Model Year Production Beginning Date Requirement 

2009 September 1, 2008 55% with carryover credit 

2010 September 1, 2009 75% with carryover credit 

2011 September 1, 2010 95% with carryover credit 

2012 September 1, 2011 All light vehicles 

The final rule requires all light vehicles to meet the ESC requirements by MY 2012. In 

nce was estimated as shown in Table IV-2. All 

Tab

comparison, the MY 2008 voluntary complia

light vehicles must meet the requirements by MY 2012. 

le IV-2 

MY 2008 Voluntary Compliance 

Passenger Cars Light Trucks 

ABS and ESC 36% 64% 

ABS alone 46% 35%

No systems 18% 1%

Th 51 f .8 lbs. 

pe 2 ry 

in 2 nt 

wo h enger 

ca s. (0.82

Th t fo line is 

3.0 cars lbs.) for 

th 

MVSS 206, Door locks

e agency’s analysis o

r vehicle for a total of 1

stallation of ESC in M

 weight impacts found that ABS adds 10.7 lbs. and ESC adds 1

.5 lbs. Based on confidential manufacturers’ plans for volunta

Y

uld have ESC. Thus, t

rs would be 9.42 lb

008, 82 percent of passenger cars would have ABS and 36 perce

e MY 2008 weight added by the manufacturers’ plans for pass

*10.7 + 0.36*1.8). 

e incremental weigh r the period of MY 2012-2016 compared to the MY 2008 base

8 lbs. for passenger 

e ESC requirements. 

 (12.5 – 9.42 lbs) and 0.75 lbs. for light trucks (12.5 – 11.75

F

s 

 were 13.2 percent of light truck 

sales in MY 2007, it is estimated that in MY 2009, average light truck weight would be increased 

 for 

 

A new door lock test for sliding doors took effect in MY 2009. This test was expected to force 

those sliding doors that used a latch/pin mechanism to change to two latches to help keep sliding

doors closed during crashes. The increase in weight is estimated to be 1.0 lbs. Several van 

models had two sliding doors. Out of 1.4 million MY 2003 vans an estimated 1.2 million door

needed to be changed to the two latch system. Given that vans

by 0.11 lbs. for sliding door latches (1.2/1.4 million * 0.132 * 1 lb.). The incremental weight

 

51 “Final Regulatory Impact Analysis, FMVSS 126, Electronic Stability Control Systems”, March 2007, NHTSA, 

Docket No. 2007-27662-2. 
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each year of MY 2012-2016 compared to the MY 2008 baseline is 0 lbs. for passenger cars and 

0.11 lbs. for light trucks for the sliding door latch requirements. 

 

FMVSS 208, Occupant Crash Protection – 35 mph belted 50th percentile male and 5th percentile

female testing 

The agency phased-in requirements for 35 mph belted testing with the 50th percentile male w

35 percent for MY 2008, 65 percent for MY 2009

ere 

, and 100 percent for MY 2010. The agency 

phased-in requirements for 35 mph belted testing with the 5th percentile female were 35 percent 

for MY 2010, 65 percent for MY 2011, and 100 percent for MY 2012. Several different 

technologies could be used to pass this test, but the agency’s analysis of these countermeasures 

showed no increase in weight was needed. Only one of the manufacturers’ confidential 

submissions showed a small weight increase for FMVSS 208. 

 

FMVSS 214, Oblique Pole Side Impact Test

The phase-in requirements for the side impact test are as shown below in Table IV-3: 

Table IV-3 

FMVSS 214 Final Rule Phase-In Schedule 

Phase-in Date Percent of each man ight vehicles that must comply ufacturer’s l

during the production period 

Septemb

Aug

er 1, 2010 to 

ust 31, 2011 

20 percent (excluding vehicles GVWR > 8,500 lbs.) 

September 1, 2011 to 

August 31, 2012 

40 percent vehicles (excluding vehicles GVWR > 8,500 lbs.) 

September 1, 2012 to 

August 31, 2013 

60 percent vehicles (excluding vehicles GVWR > 8,500 lbs.) 

September 1, 2013 to 

August 31, 2014 

80 percent vehicles (excluding vehicles GVWR > 8,500 lbs.) 

On or after 

September 1, 2014 

All vehicles 

GVWR > 8,5

including limited line vehicles, except vehicles with 

00 lbs., alterers, and multi-stage manufacturers 

On or after 

September 1, 2015 

All vehicles, including vehicles with GVWR > 8,500 lbs., 

excluding alterers and multi-stage manufacturers 

On or after All vehicles, including vehicles with GVWR > 8,500 lbs., alterers 

September 1, 2016 and multi-stage manufacturers 

A teardown study of five thorax air bags resulted in an average weight increase per vehicle of 

4.77 pounds (2.17 kg).52 A second study53 performed teardowns of 5 window curtain systems. 

One of the window curtain systems was very heavy (23.45 pounds). The other four window 

curtain systems had an average weight increase per vehicle of 6.78 pounds (3.08 kg), a figure 

which is assumed to be average for all vehicles in the future. 

 

52 Khadilkar, et al. “Teardown Cost Estimates of Automotive Equipment Manufactured to Comply with Motor 

Vehicle Standard – FMVSS 214(D) – Side Impact Protection, Side Air Bag Features”, April 2003, DOT HS 809 

809. 

53 Ludtke & Associates, “Perform Cost and Weight Analysis, Head Protection Air Bag Systems, FMVSS 201”, page 

4-3 to 4-5, DOT HS 809 842. 
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t of passenger cars and 85.4 percent of light 

ucks and torso protection was projected at 92.1 percent of passenger cars and 50.1 percent of 

rmation indicates that on average the MY 2012 phase-in 

Based on MY 2008 Buying a Safer Car data supplied by the manufacturers, the projected number 

of side air bags with head protection was 98.5 percen

tr

light trucks. Combined this info

requirement would be already be met voluntarily in MY 2008 and that the weight increases for 

MY 2013 would be 0 for passenger cars and 0.47 lbs. for light trucks, MY 2014 would be 0 for 

passenger cars and 1.43 lbs. for light trucks, MY 2015 and MY 2016 would be 0.48 lbs. for 

passenger cars and 3.37 lbs. for light trucks. 

FMVSS 216, Roof Crush

On May 12, 2009, NHTSA issued a final rule amending the roof crush standard from 1.5 times 

the vehicle weight to 3.0 times the vehicle weight for passenger cars and light trucks of 6,000 

lbs. GVWR or less.54 Vehicles over 6,000 lbs. and less than 10,000 lbs. GVWR will be requir

to meet the same test bu

ed 

t at 1.5 times the vehicle weight. In the FRIA, the average passenger car 

nd light truck weight was estimated to increase weight by 7.9 to 15.4 lbs. The average weight 

-4 

 lbs. 

-4. 

Table IV-4 

FMVSS 216 Final Rule Phase-In Schedule 

a

of 11.65 lbs. will be used in later tables and will be multiplied by the percentages in Table IV

to get incremental weights by model year (2.91 lbs. in MY 2013, 5.83 lbs. in MY 2014, 8.74

in MY 2015, and 11.65 lbs. in MY 2016). The final rule effective dates are shown in Table IV

 

Phase-in Date Percent of each manufacturer’s light vehicles that must comply 

during the production period 

September 1, 2012 to 

August 31, 2013 

25 percent 

September 1, 2013 to 

August 3

50 percent 

1, 2014 

September 1, 2014 to 75 percent 

August 31, 2015 

On or after All vehicles 

September 1, 2015 

FMVSS 301 Fuel System Integrity

t test procedure to a 50 mph offset test. The 

, 70 percent for MY 2008, and 100 percent 

r MY 2009. Thus, an incremental 30 percent of the fleet needs to meet the standard in 

omparison to the MY 2008 baseline. Several di ferent countermeasures could be used to meet 

the standard. Averaging the most likely two res ed55 in an estimated 3.7 lbs. to passenger cars 

 

NHTSA issued a final rule changing the rear impac

phase-in effective dates are 40 percent for MY 2007

fo

c f

ult

54 Final Regulatory Impact Analysis, FMVSS 216 Upgrade Roof Crush Resistance, (Docket No. 2009-0093-4) (May 

12, 2009) (74 FR 22347) 

55 Improvements in the fuel filler neck and redesigning areas around the fuel tank shield, for example a deformed 

gusset plate punctured the fuel tank wall. 
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and light trucks. Assuming an incremental f the fleet for MY 2009 at 3.7 lbs., results 

in an increase of 1.11 lbs. for the average vehicle. 

NPRM on Ejection M

 30 percent o

itigation

56 The agency has published an NPRM on ejection mitigation . The likely result of the planned 

pro is for window curtai bags (li e used to meet the FM

pol es) to b for a sor d. cy 

esti ere will incre und c

pounds for light trucks (wh acc ut 50 f ligh

third row of seats that need d). T effect s and the phase-in 

schedule are 20% in MY 2014 in MY 201 5% in resulting in weight 

incr of 0.34 lbs. in MY 2 68 lb. in M 5, and 1.2 MY 2016 enger 

car eight increases of 0. . in MY 2014 3 lb. in M , and 3.24 MY 

201 ght trucks. 

In a n, advanced glazing lternative anufactur t pursue fo fic 

win pplications for eject gation (po for fixed w for third r

app r more broadly. nced glazin ely to hav ht implicat he 

age made an estim he likeliho advanced g might be r its 

we ns. 

NH on Pedestrian Protection

posal n side air

e larger and 

be a weight 

h takes int

kely to b

 rollover sen

ase of 1.7 po

ount that abo

VSS 214 oblique

e test in all vehicl Preliminary agen

mates are that th

to be installe

s for passenger 

 percent o

ars and 4.32 

ic o t trucks have a 

 to be covere

, 40%

he proposed 

5, and 7

ive date

MY 2016,

eases 014, 0.

8 s

Y 201

.7

8 lbs. in for pass

s and w

6 for li

6 lb , 1 Y 2015 lbs. in 

dditio is one a

i i

that m ers migh

s

r speci

dow a

licatio

on mit

 Adva

ssibly 

g is lik

indow

e weig

ow 

ns) o ions. T

ncy has not

ight implicatio

ate of t od that glazin used o

TSA initiative

The has started to anal costs and of a Gl hnical Reg on 

edestrian protection. The effective dates have not been decided, however, it is possible that a 

ule on pedestrian protection could start to be phased in by the end of the period of this proposed 

rulemaking. Potential weight increases for pedestrian head and leg protection have not yet been 

identified. 

Summary – Overview of Anticipated Weight Increases

 agency yze the benefits obal Tec ulation 

p

r

Table IV-5 summarizes estimates made by NHTSA regarding the weight added by the above 

discussed standards or likely rulemakings. NHTSA estimates that weight additions required by 

final rules and likely NHTSA regulations effective by MY 2016, compared to the MY 2008 fleet, 

will increase passenger car weight by at least 17.59 lbs. and light truck weight by at least 20.23 

lbs. 

Table IV-6 shows the distribution by model year. 

 

56 74 FR 63180, December 2, 2009, (Docket No. NHTSA-2009-0183.0002.1) 
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Table IV-5 

Weight Additions Due to Final Rules or Likely NHTSA Regulations 

Comparing MY 2016 to the MY 2008 Baseline fleet 

Standard No. 

Added 

Weight in

pounds 

Passenger 

Car

Added 

Weight in 

kilograms 

Passenger 

Car

Added 

Weight in

pounds 

Light 

Trucks

Added Weight 

in kilograms 

Light trucks

126 3.08 1.40 0.75 0.34 

206 0 0 0.11 0.05 

214 0.48 0.22 3.37 1.53 

216 11.65 5.28 11.65 5.28 

301 1.11 0.50 1.11 0.50 

Ejection 

Mitigation

1.28 0.58 3.24 1.47 

Pedestrian 

Protection 

? ? ? ? 

Total 17.59 7.98 20.23 9.18 
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Table IV-6 

Weight Additions by Model Year 

Due to Final Rules or Likely NHTSA Regulations 

Compared to a MY 2008 Baseline 

Added 

Weight in 

pounds 

Passenger 

Car

Added 

Weight in 

kilograms 

Passenger 

Car

Added 

Weight in 

pounds 

Light 

Trucks

Added Weight 

in kilograms 

Light trucks

MY 2012 4.19 1.90 1.97 0.89 

MY 2013 7.10 3.22 5.35 2.43 

MY 2014 10.36 4.70 10.09 4.58 

MY 2015 14.09 6.39 15.81 7.17 

MY 2016 17.59 7.98 20.23 9.18 

nomy algorithms, a 3-4 pound increase in weight 

of 3.5 pounds increase in 

s the results for final 

Based on NHTSA’s weight-versus-fuel-eco

equates to a loss of 0.01 mpg in fuel economy. Assuming an average 

weight equates to a loss of 0.01 mpg in fuel economy, Table IV-7 show

rules or likely future safety standards. 
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 Table IV-7 

Estimated mpg Impact of Weight Additions by Model Year 

Due to Fin gulations 

C to Ba

al Rules or Likely NHTSA Re

ompared a MY 2008 seline 

MPG 

Impact of 

Added 

Weight 

Passenger 

Car

MPG 

Impact of 

Added 

Weight 

Light 

Trucks

MY 2012 0.012 0.006 

MY 2013 0.020 0.015 

MY 2014 0.030 0.029 

MY 2015 0.040 0.045 

MY 2016 0.050 0.058 

CONFIDENTIAL SUBMISSIONS 

Weight Impacts of Potential Future Voluntary Safety Improvements 

At the time the agency requested information about fuel economy plans and capabilities for the 

future, the agency also requested information on weight increases that could occur due to safety 

improvements. Several manufacturers provided confidential information in 2009 about plans 

they had to meet final rules, proposed safety standards, or to voluntarily increase safety for the 

years 2012-2016. The plans are compared to a MY 2008 baseline fleet. The areas covered 

above and the regulatory areas described as final and proposed, and voluntary safety initiatives 

from manufacturers that have confidential increases for the period after MY 2008 are shown in 

the following tables. [
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GM Estimates o Impact on mp

MY 2012 Y 2015 

Table IV-8 

f g 

M 2013 MY 2014 MY MY 2016 

Domestic 

PC 

 

Import PC 

Trucks 
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[Table IV-9a 

Confidential Submissions of Weight Impacts compared to a 

Baseline of MY 2008 

Ford

Car MY Light Truck MY

Final and Proposed 

2012 2013 2014 2015 2016 2012 201320142015 2016 

12 6 ESC 

2

th Female 

08 Belted 

5

214 Side Impact 

216 Roof Crush 

2

n 

26 itigation 

Ejectio

M

301 Fuel System 

Total Final and

Rule Increme

 Proposed 

nts 

Voluntary and Other Ru s le 

202a Head Restraints 

TBD Ped. Protection 

TBD Compatibility 

 EDR part 563 

N/A Other Voluntary 

T ry an

Rule Incremen

otal Volunta d Othe

ts 

r 

Total by Year 
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[Table IV-9b 

Confidential Submissions of Weight Impacts compared to a 

Bas 08 

 otors 

eline of MY 20

General M

 Car MY Light Truck MY 

Final and Proposed 

2012 2013 2014 

15 

2016 202013 

014 

15 16 

20

12 

22020

126 ESC 

208 B 

5th Female 

e d lte

2 S 14 ide Impact 

2 R 16 oof Crush 

2

E

26 M 

jection 

itigation 

3 F 01 uel System 

Tot

P

a

 

l Final and 

roposed Rule 

Increments 

Vol

 

untary and Other

Rules 

202a H traints ead Res 

TBD Ped. Protection 

TBD Compatibility 

 EDR part 563 

N/A Voluntary 

Other 

Total V d 

Ot 

oluntary an

her Rule Increments 

Total by Year 
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[Table IV-9c 

Confidential Submissions of Weight Impacts compared to a 

 

Baseline of MY 2008 

Chrysler 

 Car MY Light Truck MY 

Final and Proposed 

2012 2013 2014 2015 2016 2012 2013 2014 2015 2016 

126 ESC 

208 

5

B

th Female 

elted 

214 Side Impact 

216 Roof Crush 

226 

Ejection 

Mitigation 

301 Fuel System 

Total Final and 

Proposed Rule 

Increments 

Voluntary and Other 

Rules 

202a 

Head 

Restraints 

TBD Ped. Protection 

TBD Compatibility 

 EDR part 563 

N/A 

Other 

Voluntary 

Total Voluntary and 

Other Rule 

Increments 

 Total by Year 
DELI O NOT RELEASE 

85

Fue

The ehicles 

and

(MS

GV s 

in M

imp

duri

new on 

fuel

BERATIVE DOCUMENT – D

l Economy Impacts of Government Emission Standards 

 only program EPA has that has been finalized but is not yet in-force for light-duty v

 MDPVs is the new cold hydrocarbon standard finalized under the Mobile Source Air Toxics 

AT) rule. For <6,000 lb. vehicles the standard begins in MY 2010. But for 6,000-8,500 lb. 

WR vehicles and for MDPVs, the standard has a phase-in that starts with MY 2012 and end

Y 2015. EPA estimated the new standard could have a small, but unquantified, impact on 

roving fuel consumption during cold start conditions. However, in the temperature range 

ng which the CAFE test procedures are performed (68 - 86 deg. F), EPA does not believe the 

 cold hydrocarbon standard will have any impact on fuel economy. Therefore, the impact 

 economy is expected to be zero for both passenger cars for light trucks. 
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on do the agencies use, and why? 

eased CO2 standards. 

 

, 

turers to 

 the 

phasized the impact of this non-harmonization on manufacturers who sell 

vehicles globally, and asked the agencies to consider these effects. NADA supported the 

in 

account 

agencies to consider a multi-attribute approach incorporating curb weight, maximum 

engine power or torque, and/or engine displacement, as it had requested in the previous 

dual, Mr. Kenneth Johnson, commented that 

V. FUEL ECONOMY ENHANCING TECHNOLOGIES AND THE 

VOLPE MODEL 

A. What attribute and mathematical functi

In the NPRM, NHTSA and EPA proposed to set attribute-based CAFE and CO2

standards that are defined by a mathematical function for MYs 2012-2016 passenger cars 

and light trucks. EPCA, as amended by EISA, expressly requires that CAFE standards 

for passenger cars and light trucks be based on one or more vehicle attributes related to

fuel economy, and be expressed in the form of a mathematical function.57 The CAA has 

no such requirement, though in past rules, EPA has relied on both universal and attribut

based standards (e.g., for nonroad engines, EPA uses the attribute of horsepower). 

However, given the advantages of using attribute-based standards and given the goal of

coordinating and harmonizing CO2 standards promulgated under the CAA and CAFE 

standards promulgated under EPCA. EPA also proposed to issue standards that are 

attribute-based and defined by mathematical functions. There was consensus in the 

public comments that EPA should develop attribute-b

Comments received in response to the agencies’ decision to base standards on vehicle 

footprint were largely supportive. Several commenters (BMW, NADA, NESCAUM) 

expressed support for attribute-based (as opposed to flat or universal) standards generally

and agreed with EPA’s decision to harmonize with NHTSA in this respect. Many 

commenters (Aluminum Association, BMW, ICCT, NESCAUM, NY DEC, Schade, 

Toyota) also supported the agencies’ decision to continue setting CAFE standards, and 

begin setting GHG standards, on the basis of vehicle footprint, although one commenter 

(NJ DEP) opposed the use of footprint due to concern that it encourages manufac

upsize vehicles and undercut the gains of the standard. Of the commenters supporting

use of footprint, several focused on the benefits of harmonization—both between EPA 

and NHTSA, and between the U.S. and the rest of the world. BMW commented, for 

example, that many other countries use weight-based standards rather than footprintbased. While BMW did not object to NHTSA’s and EPA’s use of footprint-based 

standards, it em

use of footprint, but cautioned that the agencies must be careful in setting the footprint 

curve for light trucks to ensure that manufacturers can continue to provide functionality 

like 4WD and towing/hauling capacity. 

 

Some commenters requested that the agencies consider other or more attributes 

addition to footprint, largely reiterating comments submitted to the MYs 2011-2015 

CAFE NPRM. Cummins supported the agencies using a secondary attribute to 

for towing and hauling capacity in large trucks, for example, while Ferrari asked the 

round of CAFE rulemaking. An indivi

 

57 49 U.S.C. 32902(a)(3)(A). 
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 does not 

necessa ily guarantee safety the way the agencies say it does, and because weight-based 

standards would be fairer to manufacturers. 

In response, EPA and NHTSA continue to believe that the benefits of footprint-attributeed standards outweigh any potential drawbacks raised by commenters, and that 

ization between the two agencies should be the overriding goal on this issue. As 

ed by NHTSA in the MY 2011 CAFE final rule,58 the agencies believe that the 

ossibi s, 

as oppo

that inc pability, and/or off-road capability in 

additio ntly more complex, but by providing 

degrees e it 

less cer

CO2 le

2016 C

The ag manufacturers if 

ere w harmonization of fuel economy and GHG standards, but 

 attributes appropriate for basing standards, depending on the 

particular challenges they face – from fuel prices, to family size and land use, to safety 

concerns, to fleet composition and consumer preference, to other environmental 

challenges besides climate change. Given differences in fleet composition, identical 

attribute-based standards would produce different levels of compliance burden in 

different countries. The agencies anticipate working more closely with other countries 

and regions in the future to consider how to mitigate these issues in a way that least 

burdens manufacturers while respecting each country’s need to meet its own particular 

challenges. 

Under an attribute-based standard, every vehicle model has a performance target (fuel 

economy and CO2 emissions for CAFE and CO2 emissions standards, respectively), the 

level of which depends on the vehicle’s attribute (for this rule, footprint). The 

manufacturers’ fleet average performance is determined by the production-weighted59

average (for CAFE, harmonic average) of those targets. NHTSA and EPA are 

promulgating CAFE and CO2 emissions standards defined by constrained linear functions 

and, equivalently, piecewise linear functions.60 As a possible option for future 

rulemakings, the constrained linear form was introduced by NHTSA in the 2007 NPRM 

 

weight-based standards would be preferable to footprint-based ones, because weight 

correlates better with fuel economy than footprint, because the use of footprint

r

bas

harmon

discuss

p lity of gaming attribute-based standards is lowest with footprint-based standard

sed to weight-based or multi-attribute-based standards. Specifically, standards

orporate weight, torque, power, towing ca

n to footprint would not only be significa

 of freedom with respect to more easily-adjusted attributes, they would mak

tain that the future fleet would actually achieve the average fuel economy and 

vels projected by the agencies. The agencies are therefore finalizing MYs 2012-

AFE GHG standards based on footprint. and

encies also recognize that there could be benefits for a number of

th as greater international 

this is largely a question of how stringent standards are and how they are enforced. It is 

entirely possible that footprint-based and weight-based systems can coexist 

internationally and not present an undue burden for manufacturers. Different countries or 

regions may find different

58 See 74 Fed. Reg. at 14359 (Mar. 30, 2009). 59 Production for sale in the United States. 

60 The equations are equivalent but are specified differently due to differences in the agencies’ respective 

models. 
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proposing CAFE standards for MY 2011-2015. Described mathematically, the proposed 

constrained linear function was defined according to the following formula:61

1 TAR

where 

TARGET = the fuel economy target (in mpg) applicable to vehicles of a given 

footprint (FOOTPRINT, in square feet), 

a = the function’s upper limit (in mpg), 

b = the function’s lower limit (in mpg), 

c = the slope (in gpm per square foot) of the sloped portion of the function, 

d = the intercept (in gpm) of the sloped portion of the function (that is, the value 

the sloped portion would take if extended to a footprint of 0 square feet, and 

the MIN and MAX functions take the minimum and maximum, respectively, of the 

included values; for example, MIN(1,2) = 1, MAX(1,2) = 2, and 

MIN[MAX(1,2),3)]=2. 

Because the format is linear on a gallons-per-mile basis, not on a miles-per-gallon basis, 

it is plotted as fuel consumption below. Graphically, the constrained linear form appears 

as shown in Figure V-1. 

 

1 1

, ,

GET

MIN MAX c FOOTPRINT d

a b

= ⎡ ⎤ ⎛ ⎞ ⎜ ⎟ × + ⎢ ⎥ ⎣ ⎦ ⎝ ⎠

61 This function is linear in fuel consumption but not in fuel economy. 
89

70

0.0

55 60 65

Figure V-1 The Shape of the Constrained Linear Form 

IMIT UPPER

DELIBERATIVE DOCUMENT – DO NOT RELEASE 504540353025

2015100500

35

0.00.00.00.00.00.00.00.00.00.0

Footp f)

1/L

40 45 50

rint (s

Fuel Consumption (gpm) 1/LIMIT LOWER SLOPE

INTERCEPT
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del 

g 

1 

e form 

) 

ng 

all 

etter 

In fittin the curves, NHTSA and EPA also continued to fit the sloped portion of the 

ued 

e 

e 

afety 

conside ations that support the provision of a disincentive for downsizing as a 

consistent with safety considerations. 

nd 

the footprint ranges covering most vehicle 

models, but that the single (as opposed to piecewise) linear form does not perform well in 

 

The specific form and stringency for each fleet (passenger car and light trucks) and mo

year are defined through specific values for the four coefficients shown above. 

For purposes of the final rules, NHTSA and EPA developed the basic curve shapes usin

methods similar to those applied by NHTSA in fitting the curves defining the MY 201

standards. The first step involved defining the relevant vehicle characteristics in th

used by NHTSA’s CAFE model (e.g., fuel economy, footprint, vehicle class, technology

described in Section II.B of the Preamble and in Chapter 1 of the joint TSD. However, 

because the baseline fleet utilizes a wide range of available fuel saving technologies, 

NHTSA used the CAFE model to develop a fleet to which all of the technologies 

discussed in Chapter 3 of the joint TSD62 were applied, except dieselization and stro

hybridization. This was accomplished by taking the following steps: (1) treating 

manufacturers as unwilling to pay civil penalties rather than applying technology, (2) 

applying any technology at any time, irrespective of scheduled vehicle redesigns or 

freshening, and (3) ignoring “phase-in caps” that constrain the overall amount of 

technology that can be applied by the model to a given manufacturer’s fleet. These steps 

helped to increase technological parity among vehicle models, thereby providing a b

basis (than the baseline or reference fleets) for estimating the statistical relationship 

between vehicle size and fuel economy. 

g

function to vehicle models between the footprint values at which the agencies contin

to apply constraints to limit the function’s value for both the smallest and largest 

vehicles. Without a limit at the smallest footprints, the function—whether logistic or 

linear—can reach values that would be unfairly burdensome for a manufacturer that 

elects to focus on the market for small vehicles; depending on the underlying data, an 

unconstrained form, could result in stringency levels that are technologically infeasibl

and/or economically impracticable for those manufacturers that may elect to focus on th

smallest vehicles. On the other side of the function, without a limit at the largest 

footprints, the function may provide no floor on required fuel economy. Also, the s

r

compliance strategy apply weakly, if at all, to the very largest vehicles. Limiting the 

function’s value for the largest vehicles leads to a function with an inherent absolute 

minimum level of performance, while remaining 

Before fitting the sloped portion of the constrained linear form, NHTSA and EPA 

selected footprints above and below which to apply constraints (i.e., minimum a

maximum values) on the function. The agencies believe that the linear form performs

well in describing the observed relationship between footprint and fuel consumption or 

CO2 emissions for vehicle models within 

62 The agencies excluded diesel engines and strong hybrid vehicle technologies from this exercise (and only 

this exercise) because the agencies expect that manufacturers would not need to rely heavily on these 

technologies in order to comply with the proposed standards. NHTSA and EPA did include diesel engines 

and strong hybrid vehicle technologies in all other portions of their analyses. 
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describing this relationship for the smallest and largest vehicle models. For passenger 

cars, the agency noted that several manufacturers offer small, sporty coupes below 41 

square feet, such as the BMW Z4 and Mini, Honda S2000, Mazda MX-5 Miata, Porsche 

Carrera and 911, and Volkswagen New Beetle. Because such vehicles represent a small 

portion (less than 10 percent) of the passenger car market, yet often have performance, 

utility, and/or structural characteristics that could make it technologically infeasible 

and/or economically impracticable for manufacturers focusing on such vehicles to 

achieve the very challenging average requirements that could apply in the absence of a 

constraint, EPA and NHTSA proposed to “cut off” the linear portion of the passenger car 

function at 41 square feet. For consistency, the agency proposed to do the same for the 

light truck function, although no light trucks are currently offered below 41 square feet. 

The agencies further noted that above 56 square feet, the only passenger car model 

present in the MY 2008 fleet were four luxury vehicles with extremely low sales 

volumes—the Bentley Arnage and three versions of the Rolls Royce Phantom. NHTSA 

and EPA therefore also proposed to “cut off” the linear portion of the passenger car 

function at 56 square feet. Finally, the agencies noted that although public information is 

limited regarding the sales volumes of the many different configurations (cab designs and 

bed sizes) of pickup trucks, most of the largest pickups (e.g., the Ford F-150, GM 

Sierra/Silverado, Nissan Titan, and Toyota Tundra) appear to fall just above 66 square 

feet in footprint. EPA and NHTSA therefore proposed to “cut off” the linear portion of 

the light truck function at 66 square feet. 

Having developed a set of vehicle emissions and footprint data which represent the 

benefit of all non-diesel, non-hybrid technologies, we determined the initial values for 

parameters c and d were determined for cars and trucks separately. c and d were initially 

set at the values for which the average (equivalently, sum) of the absolute values of the 

differences was minimized between the “maximum technology” fleet fuel consumption 

(within the footprints between the upper and lower limits) and the straight line of the 

function defined above at the same corresponding vehicle footprints. That is, c and d 

were determined by minimizing the average absolute residual, commonly known as the 

MAD (Mean Absolute Deviation) approach, of the corresponding straight line. 

Finally, NHTSA calculated the values of the upper and lower parameters (a and b) based 

on the corresponding footprints discussed above (41 and 56 square feet for passenger 

cars, and 41 and 66 square feet for light trucks). 

The result of this methodology is shown below in Figures V-2 and V-3 for passenger cars 

and light trucks, respectively. The fitted curves are shown with the underlying 

“maximum technology” passenger car and light truck fleets. For passenger cars, the 

mean absolute deviation of the sloped portion of the function was 14 percent. For trucks, 

the corresponding MAD was 10 percent. 
92

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0.0200.0150.0100.0050.000

35 40 45 50 55 60 65 70 75 80

Footprint (sf)

Fuel Consumption (gpm)

Figure V-2 “Maximum Technology” Passenger Fleet with Fitted Constrained Linear Function 

0.060
93

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0.0200.0150.0100.0050.000

Fuel Consumption (gpm)

0.060

50 60 80

re V-3 imum Technology” Light Truck with Fitt Constra e ar Function 

75 65 70

ed in d Line

55

Footprint (sf)

35 40 45

Figu “Max
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rd) 

 light 

ari 

rt for the application of limits on the functions’ values, support for a 

generally less steep passenger car curve compared to MY 2011, and support for the 

supported 

thods 

n 

, students from UC Santa Barbara commented that the 

passeng nd light truck curves should be flatter and should converge over time in 

), 

idual 

to 

 of 

e 

e 

point defining the smallest 10 percent of the fleet, both for consistency with the passenger 

car cut-off point, and to provide a greater incentive for manufacturers to downsize the 

ger 

ssed 

The agencies used these functional forms as a starting point to develop mathematical 

functions defining the actual proposed standards as discussed above. The agencies then 

transposed these functions vertically (i.e., on a gpm or CO2 basis, uniformly downwa

to produce the same fleetwide fuel economy (and CO2 emission levels) for cars and

trucks described in the NPRM. 

A number of public comments generally supported the agencies’ choice of attributebased mathematical functions, as well as the methods applied to fit the function. Ferr

indicated support for the use of a constrained linear form rather than a constrained 

logistic form, suppo

inclusion of all manufacturers in the analysis used to fit the curves. ICCT also 

the use of a constrained linear form. Toyota expressed general support for the me

and outcome, including a less-steep passenger car curve, and the application of limits on 

fuel economy targets applicable to the smallest vehicles. The UAW commented that the 

shapes and levels of the curves are reasonable. 

Other commenters suggested that changes to the agencies’ methods and results would

yield better outcomes. GM suggested that steeper curves would provide a greater 

incentive for limited-line manufacturers to apply technology to smaller vehicles. GM 

argued that steeper and, in their view, fairer curves could be obtained by using salesweighted least-squares regression rather than minimization of the unweighted mea

absolute deviation. Conversely

er car a

order to encourage the market to turn, as the agencies’ analysis assumes it will, away 

from light trucks and toward passenger cars. 

NADA commented that there should be no “cut-off” points (i.e., lower limits or floors

because these de facto “backstops” might limit consumer choice, especially for light 

trucks—a possibility also suggested by the Alliance. The Alliance and several indiv

manufacturers also commented that the cut-off point for light trucks should be shifted 

72 square feet (from the proposed 66 square feet), arguing that the preponderance

high-volume light truck models with footprints greater than 66 square feet is such that a 

72 square foot cut-off point makes it unduly challenging for manufacturers serving th

large pickup market and thereby constitutes a de facto backstop. Also, with respect to the 

smallest light truck models, Honda commented that the cut-off point should be set at th

smallest light truck models (which provide greater functionality than passenger cars). 

Other commenters focused on whether the agencies should have separate curves for 

different fleets or whether they should have a single curve that applied to both passen

cars and light trucks. This issue is related, to some extent, to commenters who discu

whether car and truck definitions should change. CARB, Ford, and Toyota supported 

separate curves for cars and trucks, generally stating that different fleets have different 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ing the current 

definitions of car and truck the same. CBD, ICCT, and NESCAUM supported a single 

 have made 

is decision considering that, while EISA mandates that CAFE standards be defined by a 

r 

 a 

erations, as discussed below and in the Joint 

Techni cument. 

ares 

n the 

l 

relationship between fuel economy and footprint, given comparable levels of technology, 

and this supports weighting discrete vehicle models equally. On the other hand, sales 

functional characteristics and these characteristics are appropriately addressed by 

separate curves. Likewise, AIAM, Chrysler, and NADA supported leav

curve, based on concerns about manufacturers gaming the system and reclassifying 

passenger cars as light trucks in order to obtain the often-less stringent light truck 

standard, which could lead to lower benefits than anticipated by the agencies. 

In addition, the students from UC Santa Barbara reported being unable to reproduce the 

agencies’ analysis to fit curves to the passenger car and light truck fleets, even when 

using the model, inputs, and external analysis files posted to NHTSA’s web site when the

NPRM was issued. 

Having considered public comments, NHTSA and EPA have re-examined the 

development of curves underlying the standards proposed in the NPRM, and are 

promulgating standards based on the same underlying curves. The agencies

th

mathematical function in terms of one or more attributes related to fuel economy, neithe

EISA nor the CAA require that the mathematical function be limited to the observed or 

theoretical dependence of fuel economy on the selected attribute or attributes. As a 

means by which CAFE and GHG standards are specified, the mathematical function can 

and does properly play a normative role. Therefore, NHTSA and EPA have concluded 

that, as supported by comments, the mathematical function can reasonably be based on

blend of analytical and policy consid

cal Support Do

With respect to GM’s recommendation that NHTSA and EPA use weighted least-squ

analysis, the agencies find that the market forecast used for analysis supporting both the 

NPRM and the final rule exhibits the two key characteristics that previously led NHTSA 

to use minimization of the unweighted Mean Absolute Deviation (MAD) rather than 

weighted least-squares analysis. First, projected model-specific sales volumes i

agencies’ market forecast cover an extremely wide range, such that, as discussed in 

NHTSA’s rulemaking for MY 2011, while unweighted regression gives low-selling 

vehicle models and high-selling vehicle models equal emphasis, sales-weighted 

regression would give some vehicle models considerably more emphasis than other 

vehicle models.63 The agencies’ intention is to fit a curve that describes a technica

 

63 For example, the agencies’ market forecast shows MY 2016 sales of 187,000 units for Toyota’s 2WD 

Sienna, and shows 27 model configurations with MY 2016 sales of fewer than 100 units. Similarly, th

agencies’ market forecast shows MY 2016 sales of 268,000 for the Toyota Prius, and shows 29 model 

configurations with MY 2016 sales of fewer than 100 units. Sales-weighted analysis would give the 

Toyota Sienna and Prius more than a thousand times the consideration of many vehicle model 

configurations. Sales-weighted analysis would, therefore, cause a large number of vehicle model 

configurations to be virtually ignored. See discussion in NHTSA’s final rule for MY 2011 passenger ca

and light truck CAFE standards, 74 FR 14368 (Mar. 30, 2009), and in NHTSA’s NPRM for that 

rulemaking, 73 FR 24423-2442

e 

r 

9 (May 2, 2008).
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

gical 

 is a 

on, 

energy savings and environmental benefits 

would be lower than projected, because the steeper curves would provide a greater 

les. 

the range of 

d 

at 

weighted regression would allow the difference between other vehicle attributes to be 

reflected in the analysis, and also would reflect consumer demand. 

Second, even after NHTSA’s “maximum technology” analysis to increase technolo

parity of vehicle models before fitting curves, the agencies’ market forecast contains 

many significant outliers. As discussed in NHTSA’s rulemaking for MY 2011, MAD

statistical procedure that has been demonstrated to produce more efficient parameter 

estimates than least-squares analysis in the presence of significant outliers.64 In additi

the agencies remain concerned that the steeper curves resulting from weighted leastsquares analysis would increase the risk that 

incentive to increase sales of larger vehicles with lower fuel economy levels. Based on

these technical considerations and these concerns regarding potential outcomes, the 

agencies have decided not to re-fit curves using weighted least-squares analysis, but note 

that they may reconsider using least-squares regression in future analysis. 

NHTSA and EPA have considered GM’s comment that steeper curves would provide a 

greater incentive for limited-line manufacturers to apply technology to smaller vehic

While the agencies agree that a steeper curve would, absent any changes in fleet mix, 

tend to shift average compliance burdens away from GM and toward companies that 

make smaller vehicles, the agencies are concerned, as stated above, that steeper curves 

would increase the risk that induced increases in vehicle size could erode projected 

energy and environmental benefits. 

NHTSA and EPA have also considered the comments by the students from UC Santa 

Barbara indicating that the passenger car and light truck curves should be flatter and 

should converge over time. The agencies conclude that flatter curves would reduce the 

incentives intended in shifting from “flat” CAFE standards to attribute-based CAFE and 

GHG standards—those being the incentive to respond to attribute-based standards in 

ways that minimize compromises in vehicle safety, and the incentive for more 

manufacturers (than primarily those selling a wider range of vehicles) across 

the attribute to have to increase the application of fuel-saving technologies. With regar

to whether the agencies should set separate curves or a single one, NHTSA also notes th

EPCA requires NHTSA to establish standards separately for passenger cars and light 

trucks, and thus concludes that the standards for each fleet should be based on the 

 

64 Id. In e case of a dataset not drawn from a sample with a Gaussian, or normal, distribution, there is 

l 

, 

e 

2, 

MIT Press, Cambridge, MA). 

th

often a need to employ robust estimation methods rather than rely on least-squares approach to curve 

fitting. The least-squares approach has as an underlying assumption that the data are drawn from a norma

distribution, and hence fits a curve using a sum-of-squares method to minimize errors. This approach will

in a sample drawn from a non-normal distribution, give excessive weight to outliers by making their 

presence felt in proportion to the square of their distance from the fitted curve, and, hence, distort the 

resulting fit. With outliers in the sample, the typical solution is to use a robust method such as a minimum

absolute deviation, rather than a squared term, to estimate the fit (see, e.g., ‘‘AI Access: Your Access to 

Data Modeling,’’ at http://www.aiaccess.net/English/Glossaries/GlosMod/e_gm_O_Pa.htm#Outlier). Th

effect on the estimation is to let the presence of each observation be felt more uniformly, resulting in a 

curve more representative of the data (see, e.g., Peter Kennedy, A Guide to Econometrics, 3rd edition, 199
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d 

cs 

ends 

d was more apparent when 

car-like WD SUVs were classified as light trucks, it seems likely to diminish for the 

 suggestion that there should be no 

such cut-off points, the agencies conclude that curves lacking maximum fuel economy 

targets (i.e., minimum CO2 targets) would result in average fuel economy and GHG 

requirements that would not be technologically feasible or economically practicable for 

manufacturers concentrating on those market segments. In addition, minimum fuel 

economy targets (i.e., maximum CO2 targets) are important to mitigate the risk to energy 

and environmental benefits of potential market shifts toward large vehicles. The agencies 

also disagree with comments by the Alliance and several individual manufacturers that 

the cut-off point for light trucks should be shifted to 72 square feet (from the proposed 66 

square feet) to ease compliance burdens facing manufacturers serving the large pickup 

market. Such a shift would increase the risk that energy and environmental benefits of 

the standards would be compromised by induced increases in the sales of large pickups, 

in situations where the increased compliance burden is feasible and appropriate. Also, 

the agencies’ market forecast suggests that most of the light trucks models with footprints 

larger than 66 square feet have curb weights near or above 5,000 pounds. This suggests, 

in turn, that in terms of highway safety, there is little or no need to discourage downsizing 

of light trucks with footprints larger than 66 square feet. Based on these energy, 

environmental, technological feasibility, economic practicability, and safety 

considerations, the agencies conclude that the light truck curve should be cut off at 66 

square feet, as proposed, rather than at 72 square feet. The agencies also disagree with 

Honda’s suggestion that the cut-off point for the smallest trucks be shifted to a larger 

footprint value, because doing so could potentially increase the incentive to reclassify 

vehicles in that size range as light trucks, and could thereby increase the possibility that 

energy and environmental benefits of the rule would be less than projected. 

Finally, considering comments by the UC Santa Barbara students regarding difficulties 

reproducing NHTSA’s analysis, NHTSA reexamined its analysis, and discovered some 

erroneous entries in model inputs underlying the analysis used to develop the curves 

proposed in the NPRM. These errors are discussed in NHTSA’s final Regulatory Impact 

Analysis (FRIA) and have since been corrected. They include the following: incorrect 

valvetrain phasing and lift inputs for many BMW engines, incorrect indexing for some 

Daimler models, incorrectly enabled valvetrain technologies for rotary engines and 

Atkinson cycle engines, omitted baseline applications of cylinder deactivation in some 

characteristics of vehicles in each fleet. In other words, the passenger car curve shoul

be based on the characteristics of passenger cars, and the light truck curve should be 

based on the characteristics of light trucks—thus to the extent that those characteristi

are different, an artificially-forced convergence would not accurately reflect those 

differences. However, such convergence could be appropriate depending on future tr

in the light vehicle market, specifically further reduction in the differences between 

passenger car and light truck characteristics. While that tren

 2

model year vehicles subject to these rules as the truck fleet will be more purely “trucklike” than has been the case in recent years. 

NHTSA and EPA have also considered comments on the maxima and minima that the 

agencies have applied to “cut off” the linear function underlying the proposed curves for

passenger cars and light trucks. Contrary to NADA’s
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Honda nd GM engines, incorrect valve phasing codes for some 4-cylinder Chrysler 

engines, omitted baseline applications of advanced transmissions in some VW models, 

incorrectly enabled advanced electrification technologies for several hybrid vehicle 

models, and incorrect DCT effectiveness estimates for subcompact passenger cars. These 

errors, while not significant enough to impact the overall analysis of stringency, did 

affect the fitted slope for the passenger car curve and would have prevented precise 

replication of NHTSA’s NPRM analysis by outside parties. 

After correcting these errors and repeating the curve development analysis presented

the NPRM, NHTSA obtained the curves shown below in Figures V-4 and V-5 for 

passenger cars and light trucks, respectively. The fitted curves are shown with the 

underlying “maximum technology” passenger car and light truck fleets. For passeng

cars, the mean absolute deviation of the sloped portion of the function was 14 percen

For trucks, the corresponding MAD was 10 percent. 

a

 in 

er 

t. 
99

0.0600.0550.0500.0450.0400.0350.0300.0250.0200.0150.0100.0050.000

35 40 45 50 55 60 65 70 75 80

Footprint (sf)

Fuel Consumption (gpm)

Figure V-4 Revised “Maximum Technology” Passenger Fleet with Fitted Constrained Linear Function 

DELIBERATIVE DOCUMENT – DO NOT RELEASE 
100

0.0600.0550.0500.0450.0400.0350.0300.0250.0200.0150.0100.0050.000

35 40 45 50 55 60 65 70 75 80

 Function 

)mpg(noitpmusnoCleuF

Footprint (sf)

 

Figure V-5 Revised “Maximum Technology” Light Truck with Fitted Constrained Linear

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This refitted passenger car curve is similar to that presented in the NPRM, and the refitted 

light truck curve is nearly identical the corresponding curve in the NPRM. However, the 

slope of the refitted passenger car curve is about 27 percent steeper (on a gpm per sf 

basis) than the curve presented in the NPRM. For passenger cars and light trucks, 

respectively, Figures V-6 and V-7 show the results of adjustment—discussed in the t 

section—of the above curves to yield the average required fuel economy levels 

corresponding to the final standards. 

 nex
102

454035302520

35 40 45 50 55 60 65 70 75 80

)gpm(tegraT

Footprint (sf)

NPRMFinalRe-Fitted

Figure V-6 MY 2016 Passenger Car Targets: NPRM, Final Rule, and if Using Re-Fitted Curve 

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DE

103

75 80

LIBERATIVE DOCUMENT – DO NOT RELEASE 45403530

2520

)gpm(tegraT

35 55 70 40 45 50 60

Footprint (sf)

65

NPRMFinalRe-Fitted

Cu Figu 7 argets: NPRM, Final Ru ing Re-Fitted rve le, and if Us re V- MY 2016 Light Truck T
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se 

lso, the agencies note that the refitted passenger car curve produces only a slightly 

 

rt the 

. 

e 

ions may merit updating or 

vision in future analysis to support CAFE and CO2 standards or for other purposes. 

functions in the context of future rulemakings. 

prices could 

is is often described as a 

While the resultant light truck curves are visually indistinguishable from one another, the 

refitted curve for passenger cars would increase stringency for the smallest cars, decrea

stringency for the largest cars, and provide a greater incentive to increase vehicle size

throughout the range of footprints within which NHTSA and EPA project most passenger

car models will be sold through MY 2016. The agencies are concerned that these 

changes would make it unduly difficult for manufacturers to introduce new small 

passenger cars in the United States, and unduly risk losses in energy and environmental 

benefits by increasing incentives for the passenger car market to shift toward larger 

vehicles. 

A

closer fit to the corrected fleet than would the curve estimated in the NPRM; with respect

to the corrected fleet (between the “cut off” footprint values, and after the “maximum 

technology” analysis discussed above), the mean absolute deviation for the refitted curve 

is 13.887 percent, and that of a refitted curve held to the original slope is 13.933 percent.

In other words, the data support the original slope very nearly as well as they suppo

refitted slope. 

Considering NHTSA’s and EPA’s concerns regarding the change in incentives that 

would result from a refitted curve for passenger cars, and considering that the data 

support the original curves about as well as they would support refitted curves, the 

agencies are finalizing CAFE and GHG standards based on the curves presented in the 

NPRM. 

 

Finally, regarding some commenters’ inability to reproduce the agencies’ NPRM

analysis, NHTSA believes that its correction of the errors discussed above and its release

(on NHTSA’s web site) of the updated Volpe model and all accompanying inputs and 

external analysis files should enable outside parties to independently reproduce the 

agencies’ analysis. If outside parties continue to experience difficulty in doing so, we 

encourage them to contact NHTSA, and the agency will do its best to provide assistance

Thus, in summary, the agencies’ approach to developing the attribute-based mathematical

functions for MY 2012-2016 CAFE and CO2 standards represents the agencies’ best 

technical judgment and consideration of potential outcomes at this time, and we are 

confident that the conclusions have resulted in appropriate and reasonable standards. Th

agencies recognize, however, that aspects of these decis

re

Consistent with best rulemaking practices, the agencies will take a fresh look at all 

assumptions and approaches to curve fitting, appropriate attributes, and mathematical 

The agencies also recognized in the NPRM the possibility that lower fuel 

lead to lower fleetwide fuel economy (and higher CO2 emissions) than projected in this 

rule. One way of addressing that concern is through the use of a universal standard—that 

is, an average standard set at a (single) absolute level. Th
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

, but 

e 

nt 

beyond 

ssociation, 

alifornia Air Resources Board (CARB), Environment America, Environment Defense 

private citizens. Commenters in favor of additional backstop standards for all fleets for 

65

ize, and 2) lower 

enger cars encourage manufacturers to find ways to 

rers 

r 

“backstop standard.” The agencies explained that under the CAFE program, EISA 

requires such a minimum average fuel economy standard for domestic passenger cars

is silent with regard to similar backstops for imported passenger cars and light trucks, 

while under the CAA, a backstop could be adopted under section 202(a) assuming it 

could be justified under the relevant statutory criteria. NHTSA and EPA also noted that 

the flattened portions of the curves at the largest footprints directionally address the issu

of a backstop (i.e., the mpg “floor” or gpm “ceiling” applied to the curves provides a 

universal and absolute value for that range of footprints). The agencies sought comme

on whether backstop standards, or any other method within the agencies’ statutory 

authority, should and can be implemented in order to guarantee a level of CO2 emissions 

reductions and fuel savings under the attribute-based standards. 

The agencies received a number of comments regarding the need for a backstop 

NHTSA’s alternative minimum standard. Comments were divided fairly evenly between 

support for and opposition to additional backstop standards. The following organizations

supported the need for EPA and NHTSA to have explicit backstop standards: American 

Council for an Energy Efficient Economy (ACEEE), American Lung A

C

Fund, Massachusetts Department of Environmental Protection, Natural Resources 

Defense Council (NRDC), Northeast States for Coordinated Air Use Management 

(NESCAUM), Public Citizen and Safe Climate Campaign, Sierra Club, State of 

Washington Department of Ecology, Union of Concerned Scientists, and a number of 

both NHTSA and EPA generally stated that the emissions reductions and fuel savings

expected to be achieved by MY 2016 depended on assumptions about fleet mix that 

might not come to pass, and that various kinds of backstop standards or “ratchet 

mechanisms”66 were necessary to ensure that those reductions were achieved in fact. In 

addition, some commenters67 stated that manufacturers might build larger vehicles or 

more trucks during MYs 2012-2016 than the agencies project, for example, because 1) 

any amount of slope in target curves encourages manufacturers to ups

targets for light trucks than for pass

reclassify vehicles as light trucks, such as by dropping 2WD versions of SUVs and 

offering only 4WD versions, perhaps spurred by NHTSA’s reclassification of 2WD 

SUVs as passenger cars. Both of these mechanisms will be addressed further below. 

Some commenters also discussed EPA authority under the CAA to set backstops,68

agreeing with EPA’s analysis that section 202 (a) allows such standards since EPA has 

wide discretion under that section to craft standards. 

The following organizations opposed a backstop: Alliance of Automobile Manufactu

(AAM), Association of International Automobile Manufacturers (AIAM), Ford Moto

 

65 ACEEE, American Lung Association, CARB, Christopher Lish, Environment America, EDF, MA 

DEP, NRDC, NESCAUM, Public Citizen, Sierra Club et al., SCAQMD, UCS, WA DE 66 Commenters generally defined a “ratchet mechanism” as an automatic re-calculation of stringency to 

ensure cumulative goals are reached by 2016, even if emissions reductions and fuel savings fall short in the 

earlier years covered by the rulemaking. 

67 CBD, MA DEP, NJ DEP, Public Citizen, Sierra Club et al., UCS 68 CARB, Public Citizen, Sierra Club et al.
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ps 

ess’ silence regarding backstops 

r imported passenger cars and light trucks should be construed as a lack of authority for 

ia, 

dard 

ld 

eet 

Company, National Automobile Dealers Association (NADA), Toyota Motor Company, 

and the United Auto Workers Union. Commenters stating that additional backsto

would not be necessary disagreed that upsizing was likely,69 and emphasized the antibacksliding characteristics of the target curves. Others argued that universal absolute 

standards as backstops could restrict consumer choice of vehicles. Commenters making 

legal arguments under EPCA/EISA70 stated that Congr

fo

NHTSA to create further backstops. Commenters making legal arguments under the 

CAA71 focused on the lack of clear authority under the CAA to create multiple GHG 

emissions standards for the same fleets of vehicles based on the same statutory criter

and opposed EPA taking steps that would reduce harmonization with NHTSA in stan

setting. Furthermore, AIAM indicated that EISA’s requirement that the combined (car 

and truck) fuel economy level reach at least 35 mpg by 2020 itself constitutes a 

backstop.72 One individual73 commented that while additional backstop standards might 

be necessary given optimism of fleet mix assumptions, both agencies’ authorities wou

probably need to be revised by Congress to clarify that backstop standards (whether for

individual fleets or for the national fleet as a whole) were permissible. 

In response, EPA and NHTSA remain confident that their projections of the future fl

mix are reliable, and that future changes in the fleet mix of footprints and sales are not 

likely to lead to more than modest changes in projected emissions reductions or fuel

savings.74 Both agencies thus remain confident in these fleet projections and the 

 

69 For example, the Alliance and Toyota said that upsizing would not be likely because (1) it would not 

necessarily make compliance with applicable standards easier, since larger vehicles tend to be heavier and 

heavier vehicles tend to achieve worse fuel economy/emissions levels; (2) it may require expensive 

platform changes; (3) target curves become increasingly more stringent from year to year, which redu

the benefits of upsizing; and (4) the mpg floor and gpm ceiling for the largest vehicles (the point at which 

the curve is “cut off”) discourages manufacturers from continuing to upsize beyond a point because doing 

so makes it increasingly difficult to meet the flat standard at that part of the curve. 

70 AIAM, Alliance, Ford, NADA, Toyota 

71 Alliance, Ford, NADA, UAW 

72 NHTSA and EPA agree with AIAM that the EISA 35 mpg requirement in MY 2020 has a backstop-like

function, in that it requires a certain level of achieved fleetwide fuel economy by a certain date, although it 

is not literally a backstop standard. Considering that NHTSA’s MY 2011 CAFE standards increased 

projected average fuel economy requirements (relative to the MY 2010 standards) at a significantly faster 

rate than would be required to achieve the 35-in-2020 requirement, and considering that the standards being

finalized today would increase projected average combined fuel economy requirements to 34.1 mpg in MY 

2016, four years before MY 2020, the agencies believe that the U.S. vehicle market would have to shift in 

highly unexpected ways in order to put the 35-in-2020 requirement at risk, even despite the fact that due to 

the attribute-based standards, average fuel economy requirements will vary depending on the mix of 

vehicles produced for sale in the U.S. in each model year. The agencies further emphasize that both 

NHTSA and EPA plan to conduct and document retrospective analyses to evaluate how the market’s 

ces 

evolution during the rulemaking timeframe compares with the agencies’ forecasts employed for this 

rulemaking. Additionally, we emphasize that both agencies have the authority, given sufficient lead time, 

e 45.6 square feet (sf) and 55.1 sf, respectively, such that 

, respectively, for passenger 

to revise their standards upwards if necessary to avoid missing the 35-in-2020 requirement. 

73 Schade 

74 For reference, NHTSA’s March 2009 final rule establishing MY 2011 CAFE standards was based on a 

forecast that passenger cars would represent 57.6 percent of the MY 2011 fleet, and that MY 2011 

passenger cars and light trucks would averag

average required CAFE levels would be 30.2 mpg, 24.1 mpg, and 27.3 mpg
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 the 

sistent 

the 

g 

ssenger 

between the two flattened portions of the corresponding 

curve, the actual slope of fuel economy with respect to footprint, if fit to that data by 

t the same time, adding another backstop standard would have virtually no effect if the 

ore 

y 

r 

for 

ile. 

 

resulting emissions reductions and fuel savings from the standards. As explained in 

Section II.B of the Preamble, the agencies’ projections of the future fleet are based on

most transparent information currently available to the agencies. In addition, there are 

only a relatively few model years at issue. Moreover, market trends today are con

with the agencies’ estimates, showing shifts from light trucks to passenger cars and 

increased emphasis on fuel economy from all vehicles. 

Finally, the shapes of the curves, including the “flattening” at the largest footprint values, 

tend to avoid or minimize regulatory incentives for manufacturers to upsize their fleet to 

change their compliance burden. Given the way the curves are fit to the data points 

(which represent vehicle models’ fuel economy mapped against their footprint), 

agencies believe that there is little real benefit to be gained by a manufacturer upsizin

their vehicles. As discussed above, the agencies’ analysis indicates that, for pa

car models with footprints falling 

itself, is about 27 percent steeper than the curve the agencies are promulgating today. 

This difference suggests that manufacturers would, if anything, have more to gain by 

reducing vehicle footprint than by increasing vehicle footprint. For light trucks, the 

agencies’ analysis indicates that, for models with footprints falling between the two 

flatted portions of the corresponding curve, the slope of fuel economy with respect to 

footprint is nearly identical to the curve the agencies are promulgating today. This 

suggests that, within this range, manufacturers would typically have little incentive to 

either incrementally increase or reduce vehicle footprint. 

A

standard was weak, but a more stringent backstop could compromise the objectives 

served by attribute-based standards – that they distribute compliance burdens m

equally among manufacturers, and at the same time encourage manufacturers to appl

fuel-saving technologies rather than simply downsizing their vehicles, as they did in past

decades under flat standards. This is why Congress mandated attribute-based CAFE 

standards in EISA. This compromise in objectives could occur for any manufacture

whose fleet average was above the backstop, irrespective of why they were above the 

backstop and irrespective of whether the industry as a whole was achieving the emissions 

and fuel economy benefits projected for the final standards, the problem the backstop is

supposed to address. For example, the projected industry wide level of 250 gm/mile 

MY 2016 is based on a mix of manufacturer levels, ranging from approximately 205 to

315 gram/mile75 but resulting in an industry wide basis in a fleet average of 250 gm/m

Unless the backstop was at a very weak level, above the high end of this range, then some 

percentage of manufacturers would be above the backstop even if the performance of the

entire industry remains fully consistent with the emissions and fuel economy levels 

cars, light trucks, and the overall light-duty fleet. Based on the agencies’ current market forecast, even as 

soon as MY 2011, passenger cars will comprise a larger share (59.2 percent) of the light vehicle market; 

passenger cars and light trucks will, on average, be smaller by 0.5 sf and 1.3 sf, respectively; and average 

ndards presented in tables III.B.1-1 and III.B.1-2. 

required CAFE levels will be higher by 0.2 mpg, 0.3 mpg, and 0.3 mpg, respectively, for passenger cars, 

light trucks, and the overall light-duty fleet. 

75 Based on estimated sta
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ers 

 be 

pose 

to be imposed on 

manufacturers only when there is a failure to achieve the projected reductions across the 

 about 

e new 

Given 

r of model years covered by this rulemaking and the short lead-time 

lready before the 2012 model year, a ratchet mechanism in this rulemaking that would 

utomatically tighten the standards at some point after model year 2012 is finished and 

would fail to 

provide equate lead time for any new, more stringent standards 

be more expensive and, other 

ings being equal, have inherently lower fuel economy than their 2WD equivalent 

models ere

might shift fro les if 4WD becomes available at little or no 

extra c an

concern ou

many manufac

models. Additi rm changes, 

which lly r urs on 

average once every 5 years for most models). Alternatively, turning many 2WD SUVs 

r 

projected for the final standards. For these manufacturers and any other manufactur

who were above the backstop, the objectives of an attribute based standard would

compromised and unnecessary costs would be imposed. This could directionally im

increased costs for some manufacturers. It would be difficult if not impossible to 

establish the level of a backstop standard such that costs are likely 

industry as a whole. An example of this kind of industry wide situation could be when 

there is a significant shift to larger vehicles across the industry as a whole, or if there is a 

general market shift from cars to trucks. The problem the agencies are concerned

in those circumstances is not with respect to any single manufacturer, but rather is based 

on concerns over shifts across the fleet as a whole, as compared to shifts in one 

manufacturer's fleet that may be more than offset by shifts the other way in another 

manufacturer's fleet. However, in this respect, a traditional backstop acts as a 

manufacturer specific standard. 

The concept of a ratchet mechanism recognizes this problem, and would impose th

more stringent standard only when the problem arises across the industry as a whole. 

While the new more stringent standards would enter into force automatically, any such 

standards would still need to provide adequate lead time for the manufacturers. 

the limited numbe

a

a

apply the new more stringent standards for model years 2016 or earlier, 

 ad

Additionally, we do not believe that the risk of vehicle upsizing or changing vehicle 

offerings to “game” the passenger car and light truck definitions is as great as 

commenters imply for the model years in question.76 The changes that commenters 

suggest manufacturers might make are neither so simple nor so likely to be accepted by

consumers. For example, 4WD versions of vehicles tend to 

th

. Th fore, although there is a market for 4WD vehicles, and some consumers

m 2WD vehicles to 4WD vehic

ost, m y consumers still may not desire to purchase 4WD vehicles because of 

s ab t cost premium and additional maintenance requirements; conversely, 

turers often require the 2WD option to satisfy demand for base vehicle 

onally, increasing the footprint of vehicles requires platfo

usua equires a product redesign phase (the agencies estimate that this occ

into 2WD light trucks would require manufacturers to squeeze a third row of seats in o

significantly increase their GVWR, which also requires a significant change in the 

 

76 We note that NHTSA’s recent clarification of the light truck definitions has significantly reduced the 

potential for gaming, and resulted in the reclassification of over a million vehicles from the light truck to 

the passenger car fleet. 
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t lead time is provided. 

 MY 2016 fleet emissions and fuel economy goals of 

250 g/mi and 34.1 mpg for EPA and NHTSA respectively are estimates and not standards 

economy and emissions goals exists, but is not likely Given this, and given the potential 

re 

ards 

s, 

 developing today’s final CAFE standards, NHTSA has made significant use of results 

produc th

CAFE nsportation 

System nte he 

model, which 

CAFE standar

(1) estimating how manufacturers could apply technologies in response to 

new fuel economy standards, 

, 

vehicle.77 The agencies are confident that the anticipated increases in average fuel 

economy and reductions in average CO2 emission rates can be achieved without 

backstops under EISA or the CAA. As noted above, the agencies plan to conduct 

retrospective analysis to monitor progress. Both agencies have the authority to revise

standards if warranted, as long as sufficien

The agencies acknowledge that the

(the MY 2012-2016 curves are the standards). Changes in fuel prices, consumer 

preferences, and/or vehicle survival and mileage accumulation rates could result in either 

smaller or larger oil and GHG savings. As explained above and elsewhere in the rule, the

agencies believe that the possibility of not meeting (or, alternatively, exceeding) fuel 

complexities in designing an appropriate backstop, the agencies believe the balance he

points to not adopting additional backstops at this time for the MYs 2012-2016 stand

other than NHTSA’s finalizing of the ones required by EPCA/EISA for domestic 

passenger cars. If, during the timeframe of this rule, the agencies observe a significant 

shift in the manufacturer’s product mix resulting in a relaxation of their estimated target

NHTSA and EPA will reconsider options, both for MYs 2012-2016 and future 

rulemakings. 

B. How does NHTSA use the assumptions in its modeling analysis? 

In

ed by e CAFE Compliance and Effects Model (commonly referred to as “the 

model” or “the Volpe model”), which DOT’s Volpe National Tra

s Ce r developed specifically to support NHTSA’s CAFE rulemakings. T

has been constructed specifically for the purpose of analyzing potential 

ds, integrates the following core capabilities: 

(2) estimating the costs that would be incurred in applying these technologies

(3) estimating the physical effects resulting from the application of these 

technologies, such as changes in travel demand, fuel consumption, and 

emissions of carbon dioxide and criteria pollutants, and 

(4) estimating the monetized societal benefits of these physical effects. 

An overview of the model follows below. Separate model documentation provides a 

detailed explanation of the functions the model performs, the calculations it performs in

 

77 Increasing the GVWR of a light truck (assuming this was the only goal) can be accomplished in a 

number of ways, and must include consideration of: (1) redesign of wheel axles; (2) improving the vehicle 

suspension; (3) changes in tire specification (which will likely affect ride quality); (4) vehicle dynamics 

development (especially with vehicles equipped with electronic stability control); and (5) brake redesig

Depending on the vehicle, some of these changes may be easier or more difficult than others. 

n. 
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doing s , and how to install the model, construct inputs to the model, and interpret the 

ource 

on is 

m 

perate? 

IV.C.3 of the Preamble and Chapter 

4 of the ) inputs defining baseline and potential new CAFE standards. For 

s the 

technology.

o

model’s outputs. Documentation of the model, along with model installation files, s

code, and sample inputs are available at NHTSA’s web site. The model documentati

also available in the docket for today’s final rule, as are inputs for and outputs fro

analysis of today’s final CAFE standards. 

1. How Does the Model O

As discussed above, the agency uses the Volpe model to estimate how manufacturers 

could attempt to comply with a given CAFE standard by adding technology to fleets that 

the agency anticipates they will produce in future model years. This exercise constitutes 

a simulation of manufacturers’ decisions regarding compliance with CAFE standards. 

This compliance simulation begins with the following inputs: (a) the baseline market 

forecast discussed in Section IV.C.1 of the Preamble and Chapter 1 of the TSD, (b) 

technology-related estimates discussed in Section IV.C.2 of the Preamble and Chapter 3 

of the TSD, (c) economic inputs discussed in Section 

 TSD, and (d

each manufacturer, the model applies technologies in a sequence that follows a defined 

engineering logic (“decision trees” discussed in the MY 2011 final rule and in the model 

documentation) and a cost-minimizing strategy in order identify a set of technologie

manufacturer could apply in response to new CAFE standards. The model applies 

technologies to each of the projected individual vehicles in a manufacturer’s fleet, until 

one of three things occurs: 

(1) the manufacturer’s fleet achieves compliance with the applicable standard; 

(2) the manufacturer “exhausts”78 available technologies; or 

(3) for manufacturers estimated to be willing to pay civil penalties, the 

manufacturer reaches the point at which doing so would be more costeffective (from the manufacturer’s perspective) than adding further 

79

 

78 In a given model year, the model makes additional technologies available to each vehicle model within 

several constraints, including (a) whether or not the technology is applicable to the vehicle model’s 

technology class, (b) whether the vehicle is undergoing a redesign or freshening in the given model year, 

(c) whether engineering aspects of the vehicle make the technology unavailable (e.g., secondary axle 

an 

ce enough technology is added to a given manufacturer’s fleet in a 

udes the possibility of 

he agency believes is 

disconnect cannot be applied to two-wheel drive vehicles), and (d) whether technology application remains 

within “phase in caps” constraining the overall share of a manufacturer’s fleet to which the technology c

be added in a given model year. On

given model year that these constraints make further technology application unavailable, technologies are 

“exhausted” for that manufacturer in that model year. 

79 This possibility was added to the model to account for the fact that under EPCA/EISA, manufacturers 

must pay fines if they do not achieve compliance with applicable CAFE standards. 49 U.S.C. 32912(b). 

NHTSA recognizes that some manufacturers will find it more cost-effective to pay fines than to achieve 

compliance, and believes that to assume these manufacturers would exhaust available technologies before

paying fines would cause unrealistically high estimates of market penetration of expensive technologies 

such as diesel engines and strong hybrid electric vehicles, as well as correspondingly inflated estimates of 

both the costs and benefits of any potential CAFE standards. NHTSA thus incl

manufacturers choosing to pay fines in its modeling analysis in order to achieve what t
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technologies 

between model years. CAFE model accounts explicitly for each model year because 

year determination of the appropriate level 

of strin ency and then set the standard at that level, while ensuring ratable increases in 

s 

applying 

.C.2 of the Preamble, and by 

accounting for the number of affected vehicles. It accounts for effects such as changes in 

vehicle teria 

on 

ying 

s 

evelopment of a CAFE 

standar . It can be used to fit a mathematical function forming the basis for an attributebased C

 

As discussed below, the model has also been modified in order to apply additional 

technology in early model years if doing so will facilitate compliance in later model 

years. This is designed to simulate a manufacturer’s decision to plan for CAFE 

obligations several years in advance, which NHTSA believes better replicates 

manufacturers’ actual behavior as compared to the year-by-year evaluation which EPCA 

would otherwise require. 

The model accounts explicitly for each model year, applying most technologies when 

vehicles are scheduled to be redesigned or freshened, and carrying forward 

 The 

EPCA requires that NHTSA make a year-byg

average fuel economy.80 The multi-year planning capability mentioned above increases 

the model’s ability to simulate manufacturers’ real-world behavior, accounting for the 

fact that manufacturers will seek out compliance paths for several model years at a time, 

while accommodating the year-by-year requirement. 

The model also calculates the costs, effects, and benefits of technologies that it estimate

could be added in response to a given CAFE standard.81 It calculates costs by 

the cost estimation techniques discussed in Section IV

 travel, changes in fuel consumption, and changes in greenhouse gas and cri

pollutant emissions. It does so by applying the fuel consumption estimation techniques 

also discussed in Section IV.C.2 of the Preamble, and the vehicle survival and mileage 

accumulation forecasts, the rebound effect estimate and the fuel properties and emissi

factors discussed in Section IV.C.3 of the Preamble. Considering changes in travel 

demand and fuel consumption, the model estimates the monetized value of accompan

benefits to society, as discussed in Section IV.C.3 of the Preamble. The model calculate

both the undiscounted and discounted value of benefits that accrue over time in the 

future. 

The Volpe model has other capabilities that facilitate the d

d

AFE standard, following the steps described below. It can also be used to 

 

bilities. 

20. 81 As for all of its other rulemakings, NHTSA is required by Executive Order 12866 and DOT regulations 

to analyze the costs and benefits of CAFE standards. Executive Order 12866, 58 FR 51735 (Oct. 4, 1993); 

olicies and Procedures,” 1979, available at

gov/rulemakingrequirements.htm (last accessed February 21, 2010). 

a more realistic simulation of manufacturer decision-making. Unlike flex-fuel and other credits, NHTSA is 

not barred by statute from considering fine-payment in determining maximum feasible standards under 

EPCA/EISA. 49 U.S.C. 32902(h). 

80 49 U.S.C. 32902(a) states that at least 18 months before the beginning of each model year, the Secretary 

of Transportation shall prescribe by regulation average fuel economy standards for automobiles 

manufactured by a manufacturer in that model year, and that each standard shall be the maximum feasible

average fuel economy level that the Secretary decides the manufacturers can achieve in that year. NHTSA

has long interpreted this statutory language to require year-by-year assessment of manufacturer capa

49 U.S.C. 32902(b)(2)(C) also requires that standards increase ratably between MY 2011 and MY 20

DOT Order 2100.5, “Regulatory P

http://regs.dot.
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d 

stringe which net benefits to society are maximized, the stringency at which a 

specifie

nt 

re 

ecified probability distributions, such that the uncertainty 

of key ures (e.g., fuel consumption, costs, benefits) can be evaluated. 

uld 

final 

ility to 

e Volpe 

t and evaluation of potential CAFE 

standar s. Also, although some observers have criticized analyses the agency has 

ficiently transparent. 

However, in NHTSA’s view, the complexity of the Volpe model has evolved in response 

model transparency relate to the use of confidential business information, not to the 

as discussed below in Section V.B.5, NHTSA and the Volpe Center 

evaluate many (e.g., 200 per model year) potential levels of stringency sequentially, an

identify the stringency at which specific criteria are met. For example, it can identify the 

ncy at 

d total cost is reached, or the stringency at which a given average required fuel 

economy level is attained. This allows the agency to compare more easily the impacts in 

terms of fuel savings, emissions reductions, and costs and benefits of achieving differe

levels of stringency according to different criteria. The model can also be used to 

perform uncertainty analysis (i.e., Monte Carlo simulation), in which input estimates a

varied randomly according to sp

meas

2. Has NHTSA Considered Other Models? 

Nothing in EPCA requires NHTSA to use the Volpe model. In principle, NHTSA co

perform all of these tasks through other means. For example, in developing today’s 

standards, the agency did not use the Volpe model’s curve fitting routines; rather, as 

discussed in Section II of the Preamble, the agency fitted curves outside the model (as for

the NPRM) but elected to retain the curve shapes defining the proposed standards. In 

general, though, these model capabilities have greatly increased the agency’s ab

rapidly, systematically, and reproducibly conduct key analyses relevant to the 

formulation and evaluation of new CAFE standards. 

During its previous rulemaking, which led to the final MY 2011 standards 

promulgated earlier this year, NHTSA received comments from the Alliance and CARB 

encouraging NHTSA to examine the usefulness of other models. As discussed in that 

final rule, NHTSA, having undertaken such consideration, concluded that th

model is a sound and reliable tool for the developmen

82 d

conducted using the Volpe model, those criticisms have largely concerned inputs to the

model (such as fuel prices and the estimated economic cost of CO2 emissions), not the

model itself. In comments on the NPRM preceding today’s final rule, one of these 

observers, the Center for Biological Diversity (CBD), suggested that the revisions to such 

inputs have produced an unbiased cost-benefit analysis.83

One commenter, the International Council on Clean Transportation (ICCT) 

suggested that the Volpe model is excessively complex and insuf

to the complex analytical demands surrounding very significant regulations impacting a 

large and important sector of the economy, and ICCT’s own comments illustrate some of 

the potential pitfalls of model simplification. Furthermore, ICCT’s assertions regarding 

Volpe model itself; 

have taken pains to make the Volpe model transparent by releasing the model and 

 

82 74 FR 14372 (Mar. 30, 2009). 

83 CBD, p. 2. 
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 comments. 

el 

PCA, NHTSA has traditionally assessed 

the ann al costs and benefits of the standards. The first (2002) version of DOT’s model 

 

technology in 

MY 2007. GM (and other manufacturers) argued that this completely failed to represent 

allowed 

e recent rulemaking for MY 2011 passenger cars and light trucks, DOT further 

modified the CAFE model to account for cost reductions attributable to “learning effects” 

supporting documentation, along with the underlying source code and accompanying 

model inputs and outputs. Therefore, the agency disagrees with these ICCT

In reconsidering and reaffirming this conclusion for purposes of this rule, NHTSA

notes that the Volpe model not only has been formally peer-reviewed and tested through 

three rulemakings, but also has some features especially important for the analysis of 

CAFE standards under EPCA/EISA. Among these are the ability to perform year-byyear analysis, and the ability to account for engineering differences between specific 

vehicle models. 

EPCA requires that NHTSA set CAFE standards for each model year at the level 

that would be “maximum feasible” for that year.84 Doing so requires the ability to 

analyze each model year and, when developing regulations covering multiple mod

years, to account for the interdependency of model years in terms of the appropriate

levels of stringency for each one.85 Also, as part of the evaluation of the economic 

practicability of the standards, as required by E

u

treated each model year separately, and did not perform this type of explicit accounting.

Manufacturers took strong exception to these shortcomings. For example, GM 

commented in 2002 that “although the table suggests that the proposed standard for MY 

2007, considered in isolation, promises benefits exceeding costs, that anomalous outcome 

is merely an artifact of the peculiar Volpe methodology, which treats each year 

independently of any other...” In 2002, GM also criticized DOT’s analysis for, in some 

cases, adding a technology in MY 2006 and then replacing it with another 

true manufacturer product-development cycles, and therefore could not be 

technologically feasible or economically practicable. 

In response to these concerns, and related concerns expressed by other manufacturers, 

DOT modified the CAFE model in order to account for dependencies between model 

years and to better represent manufacturers’ planning cycles, in a way that still 

NHTSA to comply with the statutory requirement to determine the appropriate level of 

the standards for each model year. This was accomplished by limiting the application of 

many technologies to model years in which vehicle models are scheduled to be 

redesigned (or, for some technologies, “freshened”), and by causing the model to “carry 

forward” applied technologies from one model year to the next. 

During th

related to volume (i.e., economies of scale) and the passage of time (i.e., time-based 

 

84 49 U.S.C. 32902(a). 

85 For example, the CAFE model “carries forward” technologies applied in earlier model years and, when 

evaluating standards in later model years, evaluates the potential to add “extra” technology in earlier mode

years if doing so will sufficiently facilitate compliance in later model years. However, because EPCA doe

not allow NHTSA to consider manufacturers’ potential use of CAFE credits, NHTSA’s analysis does no

attempt to account for manufacturers’ ability to earn credits in one ye

l 

s 

t 

ar and apply them toward compliance 

in a different model year, even though this is an important flexibility actually allowed by EPCA. 
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learnin , both of which evolve on year-by-year basis. These changes were implemented 

s 

ers are most likely to broadly apply generic 

technology “packages,” and the Volpe model does tend to form “packages” dynamically, 

s, and schedules for increases in CAFE 

standar s. For example, under the final CAFE standards for passenger cars, the CAFE 

 with 

Y 

rbochargers. 

el-byces 

reliable means of predicting when the driver will change gears. By retaining cylinder 

s 

ultimately present at the conclusion of modeling. For each vehicle, the same file shows 

resultant changes in vehicle weight, fuel economy, and cost. This provides for efficient 

g)

in response to comments by environmental groups and other stakeholders. 

The Volpe model is also able to account for important engineering differences between 

specific vehicle models, and to thereby reduce the risk of applying technologies that may

be incompatible with or already present on a given vehicle model. Some commenter

have previously suggested that manufactur

based on vehicle characteristics, redesign schedule

d

model estimated that manufacturers could apply turbocharged SGDI engines mated

dual-clutch AMTs to 2.4 million passenger cars in MY 2016, about 22 percent of the M

2016 passenger car fleet. Recent modifications to the model, discussed below, to 

represent multi-year planning, increase the model’s tendency to add relatively costeffective technologies when vehicles are estimated to be redesigned, and thereby increase 

the model’s tendency to form such packages. 

On the other hand, some manufacturers have indicated that especially when faced with 

significant progressive increases in the stringency of new CAFE standards, they are likely 

to also look for narrower opportunities to apply specific technologies. By progressively 

applying specific technologies to specific vehicle models, the CAFE model also produces

such outcomes. For example, under the final CAFE standards for passenger cars, the 

CAFE model estimated that in MY 2012, some manufacturers could find it advantageous 

to apply SIDI to some vehicle models without also adding tu

By following this approach of combining technologies incrementally and on a mod

model basis, the CAFE model is able to account for important engineering differen

between vehicle models and avoid unlikely technology combinations. For example, the 

model does not apply dual-clutch AMTs (or strong hybrid systems) to vehicle models 

with 6-speed manual transmissions. Some vehicle buyers prefer a manual transmission; 

this preference cannot be assumed away. The model’s accounting for manual 

transmissions is also important for vehicles with larger engines: for example, cylinder 

deactivation cannot be applied to vehicles with manual transmissions, because there is no 

deactivation as a specific technology rather than part of a pre-determined package and by

retaining differentiation between vehicles with different transmissions, DOT’s model i

able to target cylinder deactivation only to vehicle models for which it is technologically 

feasible. 

The Volpe model also produces a single vehicle-level output file that, for each vehicle 

model, shows which technologies were present at the outset of modeling, which 

technologies were superseded by other technologies, and which technologies were 

identification, analysis, and correction of errors, a task with which the public can now 

assist the agency, since all inputs and outputs are public. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

s, as well as those related to the efficiency with which the Volpe 

model is able to analyze attribute-based CAFE standards and changes in vehicle 

el analysis such as stringency estimation (to meet 

predetermined criteria), sensitivity analysis, and uncertainty analysis, lead the agency to 

e 

plexity 

pe model, each model year is 

parately and explicitly, the model could not be modified to add this 

s, 

duces more realistic estimates of the costs and benefits of such standards. 

amount 

ot 

e 

Such consideration

classification, and to perform higher-lev

conclude that the model remains the best available to the agency for the purposes of 

analyzing potential new CAFE standards. 

3. What Changes Has DOT Made to the Model? 

As discussed in the NPRM preceding today’s final rule, the Volpe model has been 

revised since the 2011 CAFE rule to make some minor improvements, and to add one 

significant new capability: the ability to simulate manufacturers’ ability to engage in

“multi-year planning.” Multi-year planning refers to the fact that when redesigning or 

freshening vehicles, manufacturers can anticipate future fuel economy or CO2 standards, 

and add technologies accounting for these standards. For example, a manufacturer might 

choose to over-comply in a given model year when many vehicle models are scheduled 

for redesign, in order to facilitate compliance in a later model year when standards will b

more stringent yet few vehicle models are scheduled for redesign.86 Prior comments 

have indicated that the Volpe model, by not representing such manufacturer choices,

tended to overestimate compliance costs. However, because of the technical com

involved in representing these choices when, as in the Vol

accounted for se

capability prior to the statutory deadline for the MY 2011 final standards. 

The model now includes this capability, and NHTSA has applied it in conducting 

analysis to support the NPRM and in analyzing the standards finalized today. 

Consequently, this new capability often produces results indicating that manufacturers 

could over-comply in some model years (with corresponding increases in costs and 

benefits in those model years) and thereby “carry forward” technology into later model 

years in order to reduce compliance costs in those later model years. NHTSA believes

this better represents how manufacturers would actually respond to new CAFE standard

and thereby pro

The Volpe model has also been modified to accommodate inputs specifying the 

of CAFE credit to be applied to each manufacturer’s fleet. Although the model is n

currently capable of estimating manufacturers’ decisions regarding the generation and use

of CAFE credits, and EPCA does not allow NHTSA, in setting CAFE standards, to tak

into account manufacturers’ potential use of credits, this additional capability in the 

Volpe model provides a basis for more accurately estimating costs, effects, and benefits 

that may actually result from new CAFE standards. Insofar as some manufacturers 

actually do earn and use CAFE credits, this provides NHTSA with some ability to 

 

86 Although a manufacturer may, in addition, generate CAFE credits in early model years for use in later 

model years (or, less likely, in later years for use in early years), EPCA does not allow NHTSA, when 

setting CAFE standards, to account for manufacturers’ use of CAFE credits. 
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xamine outcomes more realistically than EPCA allows for purposes of setting new 

ards are set. Although the 

model has been programmed in previous rulemakings to estimate at what stringency net 

it 

erned 

 sets 

econom cability, the effect of other standards of the Government on fuel 

actors, 

nd 

form and contribute to the agency’s 

conside ation of the “need of the United States to conserve energy,” as well as the other 

what standards to propose and finalize, but the model does not determine the standards. 

e

CAFE standards. 

4. Does the Model Set the Standards? 

Since NHTSA began using the Volpe model in CAFE analysis, some commenters have

interpreted the agency’s use of the model as the way by which the agency chooses the 

maximum feasible fuel economy standards. This is incorrect. Although NHTSA 

currently uses the Volpe model as a tool to inform its consideration of potential CAFE 

standards, the Volpe model does not determine the CAFE standards that NHTSA 

proposes or promulgates as final regulations. The results it produces are completely 

dependent on inputs selected by NHTSA, based on the best available information and 

data available in the agency’s estimation at the time stand

benefits are maximized, it was not the model’s decision to seek that level of stringency, 

was the agency’s, as it is always the agency’s decision what level of CAFE stringency is 

appropriate. Ultimately, NHTSA’s selection of appropriate CAFE standards is gov

and guided by the statutory requirements of EPCA, as amended by EISA: NHTSA

the standard at the maximum feasible average fuel economy level that it determines is 

achievable during a particular model year, considering technological feasibility, 

ic practi

economy, and the need of the nation to conserve energy. 

 

NHTSA considers the results of analyses conducted by the Volpe model and analyses

conducted outside of the Volpe model, including analysis of the impacts of carbon 

dioxide and criteria pollutant emissions, analysis of technologies that may be available in

the long term and whether NHTSA could expedite their entry into the market through

these standards, and analysis of the extent to which changes in vehicle prices and fuel 

economy might affect vehicle production and sales. Using all of this information—not 

solely that from the Volpe model—the agency considers the governing statutory f

along with environmental issues and other relevant societal issues such as safety, a

promulgates the standards based on its best judgment on how to balance these factors.

 

This is why the agency considered eight regulatory alternatives, only one of which 

reflects the agency’s final standards, based on the agency’s determinations and 

assumptions. Others assess alternative standards, some of which exceed the final 

standards and/or the point at which net benefits are maximized.87 These comprehensive 

analyses, which also included scenarios with different economic input assumptions as 

presented in the FEIS and FRIA, are intended to in

r

statutory factors. 49 U.S.C. 32902(f). Additionally, the agency’s analysis considers the 

need of the nation to conserve energy by accounting for economic externalities of 

petroleum consumption and monetizing the economic costs of incremental CO2 emissions

in the social cost of carbon. NHTSA uses information from the model when considering 

 

87 See Section IV.F of the Preamble for a detailed discussion of the alternatives. 
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Model documentation, which is publicly available in the rulemaking docket and on 

 model inputs (all of 

hich are available to the public) and outputs are structured, and how the model is 

ft 

ng 

 in 

lties 

ia at Santa Barbara, though successful in 

installing and running the model, reported being unable to reproduce NHTSA’s results 

y 

tation notes that some of the 

develop ent and operating environment used by the Volpe model (e.g., the software 

is, 

 errors 

5. How Does NHTSA Make the Model Available and Transparent? 

NHTSA’s web site, explains how the model is installed, how the

88

w

used. The model can be used on any Windows-based personal computer with Microso

Office 2003 or 2007 and the Microsoft .NET framework installed (the latter available 

without charge from Microsoft). The executable version of the model and the underlyi

source code are also available at NHTSA’s web site. The input files used to conduct the 

core analysis documented in this final rule are available in the public docket. With the 

model and these input files, anyone is capable of independently running the model to 

repeat, evaluate, and/or modify the agency’s analysis. 

NHTSA is aware of two attempts by commenters to install and use the Volpe model

connection with the NPRM. James Adcock, an individual reviewer, reported difficu

installing the model on a computer with Microsoft® Office 2003 installed. Also, 

students from the University of Californ

underlying the development of the shapes of the passenger car and light truck curves. 

Regarding the difficulties Mr. Adcock reported encountering, NHTSA staff is aware of 

no attempts to contact the agency for assistance locating supporting material related to 

the MYs 2012-2016 CAFE rulemaking. Further, the model documentation provides 

specific minimum hardware requirements and also indicates operating environment 

requirements, both of which have remained materially unchanged for more than a year. 

Volpe Center staff members routinely install and run the model successfully on new 

laptops, desktops, and servers as part of normal equipment refreshes and interagenc

support activities. We believe, therefore, that if the minimum hardware and operating 

environment requirements are met, installing and running the model should be 

straightforward and successful. The model documen

m

environment rather than the hardware on which that software environment operates), 

particularly the version of Microsoft® Excel used by the model, is Microsoft® Office 

2003. We recognize that some users may have more recent versions of Microsoft® 

Office. However, as in the case of other large organizations, software licensing 

decisions, including the version of Microsoft® Office, is centralized in the Office of the

Chief Information Officer. Nonetheless, the Volpe Model is proven on both Microsoft®

Office version 2003 and the newer 2007 version. 

As discussed in Section II.C of the Preamble to today’s final rule, considering comments 

by the UC Santa Barbara students regarding difficulties reproducing NHTSA’s analys

NHTSA reexamined its analysis, and discovered some erroneous entries in model inputs 

underlying the analysis used to develop the curves proposed in the NPRM. These

 

88 We note, however, that files from any supplemental analysis conducted that relied in part on confidential 

manufacturer product plans cannot be made public, as prohibited under 49 CFR Part 512. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

re discussed in the FRIA and have since been corrected. Updated inputs and outputs 

ave been posted to NHTSA’s web site, and should enable outside replication of the 

ce. 

egarding the possible effects of potential new CAFE standards. An 

er that 

estimat uel 

econom low. However, 

NHTSA has ing such a 

model. 

sensitiv lues of 

these c n published studies. 

 the N ways to improve 

S, 

n 

 this 

omments received in connection 

 earlier experimental version of the Volpe model included a 

at estimated changes in sales resulting from CAFE-induced 

 the model. The 

tter does not have the capabilities discussed below. 

a

h

analysis documented in today’s noti

6. Estimating Market Effects Induced by New CAFE Standards 

In comments on recent NHTSA rulemakings, some reviewers have suggested that the 

Volpe model should be modified to estimate the extent to which new CAFE standards 

would induce changes in the mix of vehicles in the new vehicle fleet. NHTSA agrees 

that a “market shift” model, also called a consumer vehicle choice model, could provide 

useful information r

earli experimental version of the Volpe model included a multinomial logit model

ed changes in sales resulting from CAFE-induced increases in new vehicle f

y and prices. A fuller description of this attempt can be found be

 thus far been unable to develop credible coefficients specify

 In addition, as discussed in Section II.H.4 of the Preamble, such a model is 

e to the coefficients used in it, and there is great variation over some key va

oefficients i

In PRM preceding today’s final rule, NHTSA sought comment on 

on this earlier work and develop this capability effectively. Some comments implied that

the agency should continue work to do so, without providing specific recommendations. 

The Alliance of Automobile Manufacturers identified consumer choice as one of several 

factors outside the industry’s control yet influential with respect to the agencies’ analysis. 

Also, the University of Pennsylvania Environmental Law Project suggested that the rule 

would change consumers’ vehicle purchasing decisions, and the California Air Resources

Board expressed support for continued consideration of consumer choice modeling. On 

the other hand, citing concerns regarding model calibration, handling of advanced 

technologies, and applicability to the future light vehicle market, ACEEE, ICCT, UC

and NRDC all expressed opposition to the possibility of using consumer choice models i

estimating the costs and benefits of new standards. 

Notwithstanding comments on this issue, NHTSA has been unable to further develop

capability in time to include it in the analysis supporting decisions regarding final CAFE 

standards. The agency will, however, continue efforts to develop and make use of this 

capability in future rulemakings, taking into account c

with today’s final rule. An

multinomial logit model th

increases in new vehicle fuel economy and prices, as well as an accompanying cost 

allocation algorithm to estimate how manufacturers might allocate compliance costs. 

However, the agency has thus far been unable to develop credible coefficients specifying

such a model. The agency intends to continue seeking to develop such methods, and

documents its prior attempts here in the interest of providing an overview of how they

might be formulated and applied. The following description applies to an earlier 

experimental version of the Volpe model, not to the current version of

la
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a. Cost Alloc

s 

r 

As-Incurred

ation Assumptions 

At the compliance simulation’s conclusion, each represented vehicle model has some 

incurred technology cost (potentially zero), and each represented manufacturer has some

zero or positive incurred CAFE fines (i.e., civil penalties). We consider several cost 

allocation assumptions to distribute these compliance costs across each manufacturer’

product line, following one of the following four strategies as specified as a user input fo

each manufacturer: 

: Based on the total technology costs incurred by each vehicle. 

Price-Based: Based on the initial price (MSRP) of each vehicle. 

Elasticity-Based: Based on the inverse of each vehicle’s price elasticity of 

demand. 

Uniform: Based on uniform allocation across all vehicles. 

A review of relevant literature did not reveal published studies that focus specifically on 

the relationship between CAFE compliance costs and vehicle prices. However, this 

review did reveal studies that generically address automotive price elasticities of demand 

and their influence on pricing decisions, as well as production costs and pricing strategies 

r some categories of automotive powertrain components. Interviews with selected 

experts suggest that m iance costs between vehicle 

odels in order to maintain or improve competitiveness in profitable market segments. 

n 

 and 

 influencing 

their choices to purchase a new vehicle during a specific model year. 

fo

industry anufacturers may shift compl

m

Specific information regarding the pricing strategies followed by individual 

manufacturers is unavailable. The pricing strategies provided by the cost allocation 

assumption portion of the model are intended to realistically bracket the potential range 

of strategies. 

At the conclusion of the cost allocation assumption part of the system, each vehicle 

model is assigned a regulatory cost, which is reported as a price increase and used whe

applying the market share model discussed below. 

b. Market Share Model 

To provide the capability to analyze the market response to changes in vehicle prices

other attributes resulting from manufacturers’ efforts to comply with CAFE regulation, 

we developed a statistical model to analyze the factors influencing new car buyers’ 

choices among vehicle models. Our model focuses on buyers’ decisions to choose 

specific vehicle types individual models, but does not analyze the factors
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i. Market Share Model Structure 

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

two-step process. First, a 

onsumer chooses a type of vehicle, for example, a mid-size premium automobile, a 

mall pickup r a large sport-utility vehicle.89 Conditioned on that decision, a 

uyer then selects an individual vehicle model from among those making up the chosen 

The model uses a nested logit model to represent buyers’ decisions about the type of 

vehicle to purchase and their choices among competing models of that type. As Figure 

V-8 illustrates, buyers are assumed to make decisions using a 

c

s truck, o

b

“market segment”. 

Buyer

Small - Budget Midrange - Standard SUV - Midrange Other Market Segments

GMC Trailblazer Toyota 4Runner Isuzu Trooper Other Midrange SUVs

Choice of Segment:

Choice of model:

Figure V

Other Midrange SUVs

-8. Nested Logit Model 

, 

al 

 make individual vehicle models attractive to potential buyers have 

f 

similar body type or style, overall size, luxury level, and performance. 

This model relies on several underlying assumptions; most important, that buyers derive 

utility from the attributes offered by different vehicle models, including characteristics

such as its passenger- and cargo-carrying capacity, driving performance, fuel economy

comfort level, transmission and drive type (two- versus four-wheel drive). Individu

buyers are assumed to choose the specific vehicle model whose purchase price and 

combination of attributes offers the maximum level of utility. Many of the attributes or 

characteristics that

been well documented, and some of these can be readily measured and compared. 

However, other characteristics that lead buyers to view particular models as closely 

competitive may be difficult to quantify, or may simply be unknown. The presence of 

these unobserved attributes means that vehicles are likely to form groups or market 

segments, and that models within each segment compete more closely with one another 

than with models belonging to other market segments. Our model uses the common 

assumption in automotive marketing that market segments consist of vehicle models o

 

89 Our model employs the market segmentation presented in 2002 Automotive News Car Market 

Classifications, [need website address] 
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ii. Factors Affecting Vehicle Buyer’s Behavior 

se 

Using the subscript s to designate market segments, k to designate individual vehicle 

models, and n to designate buyers, the probability that a representative buyer will choo

a vehicle of type and luxury or performance level s is simply 

Pn (s) (0.1) 

In turn, the probability that buyer n will choose to purchase a specific brand and model k

from within market segment, or Pn(sk), is 

Pn nn (sk P k s P s ) = ( ) ( ) (0.2) 

Here, Pn(k|s) represents the conditional probability that the representative buyer will 

elect model o purchase a vehicle of the body type and luxury 

or perfor segment s. 

In choosing a market segment and a specific vehicle model, the probability that a buyer 

ill choose a specific alternative depends on how the utility or benefits it provides 

or example, the probability uyer will select a specific vehicle model from a given 

market segment depends on how the utility its attributes offer compares to the utility 

vels offered by other vehicle models within that same market segment. Similarly, a 

 choice of the vehicle type, size, luxury, and performance level to shop for 

ends on how the composite utility of the various models making up that market 

egment compares to the composite offered by the vehicles included in the other 

arket segments. 

able or measu

l 

k, having already decided t

mance level represented by 

s

w

compare to those supplied by the competing choices. Since buyers are assumed to 

choose the alternative that offers the maximum utility, the likelihood that any specific 

alternative will be chosen depends on the probability that it offers the maximum utility 

level among the choices available. 

F that a b

le

buyer’s

dep

s utility 

m

The observ rable component of utility offered by each vehicle model 

depends on the particular features or attributes it provides, such as its driving 

performance, fuel economy, and seating or luggage-carrying capacity, as well as on its 

purchase price.90 The unobserved component of utility that each model offers arises 

partly from uncertainty about which observable attributes are important to buyers, as wel

as about the relationship between a vehicle’s combination of attributes and the utility it 

offers to prospective buyers. Other sources of unobserved utility include errors in 

 

90 It may also be affected by characteristics of the buyers who choose the market segment containing tha

model, since certain characteristics of buyers may affect their preferences for or valuation of specific 

vehicle attributes. 

t 
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ttp://www.epa.gov/QUALITY/informationguidelines/ 

ply 

likely to 

erred 

icle 

nction of its 

measuring or describing these attributes, and the potential existence of attributes that, 

though valued by buyers, are unknown or difficult to measure. 

h

By making a specific assumption about the probability distribution of these unobserved 

components of utility, the probability that a representative buyer will select a specific 

vehicle model can be expressed as a function of the utility it’s measured attributes sup

and of how it compares to the utility levels offered by competing models.91 One 

common assumption is that the unobserved components of utility follow a specific 

probability distribution in which large values are rare (a Type I extreme value 

distribution, which somewhat resembles a normal distribution), and are thus un

be sufficiently large to offset any difference in observed utilities between the pref

model and other competing choices. 

Under this assumption, the probability that a representative buyer will purchase a veh

model (k) from among those within a market segment (s) is an exponential fu

utility as well as those offered by the other models in that market segment: 

sk

( ) sk

n

k s

P ks U

e ′

′∈

=

∑ (0.3) 

U

e

where Usk represents the level of utility provided by the attributes of vehicle model k. In 

turn, the probability that a representative buyer will decide to purchase a vehicle from 

market segment s can be expressed as 

( )

s

s

s

s

n

s s

U

P s

U

e

e

μ

μ ′

′∈

=

∑

 (0.4) 

where 

( ) log U sk U s = ∑ ′ k s ′∈ e (0.5) 

he term U T sk ∑ e , often referred to as the expected maximum utility provided by 

that market es that the probability a buyer will 

k s ′∈

the choices available in market segment s, is a measure of the composite utility – i.e., the 

overall attractiveness to potential buyers – offered by all of the vehicle models making up

′

segment. Thus, Equation (0.4) stat

purchase a vehicle from market segment s – say a small economy car – depends on how

the composite utility (or combined attractiveness) of the models making up that category 

 

91 The specific probability distribution assumed for the unobserved utility components determines the form 

of the expression for the probability that an individual model will be chosen, because it determines the 

probability that a vehicle model offering the maximum observed or measured level of utility to a buyer 

lected in the decision. 

would still represent that buyer’s utility-maximizing choice if the unobserved component of utility were 

also ref
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is 

f 

me market segment relative to that of the remaining 

nobserved component of utility, which differs for each vehicle model. This parameter 

e 

ur model assumes that the utility offered by an individual vehicle model is a linear 

function of the offers, including its driving 

erformance, seating capacity, fuel economy, transmission and drive type, and its 

compares to the composite utility measures for each of the other market segments (sports

cars, large automobiles, midsize sport-utility vehicles, etc.), the sum of which appears in

the denominator. 

Equation (0.4) also shows that the expected maximum utility of each market segment 

scaled by the parameter μs

, which measures the variance in the unobserved component o

utility shared by models in the sa

u

(sometimes referred to as the nesting coefficient) has the convenient property that th

value of [1 - (μs

)

2

] measures how similarly buyers view the various vehicle models 

included within each market segment, thus indicating how closely the market 

segmentation used in the model matches shoppers’ views of model groupings or 

segmentation in the new vehicle market.92 

O

 levels of various attributes that it

p

purchase price. Denoting these attributes X1, X2, ..., Xn, vehicle model k within market 

segment s provides a utility level 

1 2 1 2 U sk s β XX X kk n β β n k ε ε sk = + ++ + + K (0.6) 

where, for example, X1k denotes the level of attribute 1 – say, the ratio of horsepower to 

weight, a widely used index of driving performance – provided by vehicle model k.

93

The relative importance or weight that buyers attach to each vehicle attribute is 

s d component of utility that is 

red by all vehicle models in market segments, that implies the hierarchical structure of 

buyers’ decisions. 

iii. Statistical Estimation of Model Parameters 

 in an input file define this model based on any of several candidate 

summarized by the value of its coefficient (β1, β2, ...βn), while the terms εs and εsk

respectively represent the unobserved components of utility shared by all vehicles in 

market segment s and unique to vehicle model k. As discussed previously, it is the 

presence of the term ε , which represents the unobserve

sha

Parameters specified

attributes. These parameters can be estimated statistically by using the market shares of 

 

92 Specifically, [1- (μs

)

2

] measures the correlation between the utility levels offered by any two vehicle 

models that are included in the same market segment. The value of μs

 is theoretically restricted to the 

nge from 0 to 1; values close to 0 indicate that the utilities offered by models in the same m

re closely correlated, and thus that the market segmentation used in the model accurately re

views about how closely different vehicle types and models compete with one another. In contrast, values 

loser to 1 indicate that the utilities of models in the same segment are not closely correlated, and thus that 

ra arket segment 

a flects buyers’ 

c

the market segmentation may be inaccurate. 

93 Thus in this model, the parameter μs

 in Equation (0.4) measures the variance in εs relative to the variance 

in εsk. 
DELIBERA

124

. 

d 

e assembled data on suggested retail and actual sales prices, horsepower, vehicle 

tics 

Using the Market Share Model 

escribing the attributes and prices of vehicles that manufacturers will offer for sale 

during re m be used to simulate how sales 

r market shares in future years would change in response to changes in attributes or 

( )

total sales accounted for by each individual vehicle model during a recent model year to 

approximate the probabilities that a “typical” vehicle buyer would choose each model

We estimated the model’s parameters, including the coefficients (β1, β2, ...βn) in 

Equation (0.6) and the nesting parameter μs

, using market share and attribute data for the 

approximately 1,300 automobile and light truck models that were produced and sol

during model year 2002. Total automobile and light truck sales during that model year 

were about 17 million vehicles. 

W

weight, seating capacity, fuel economy, fuel tank capacity, transmission and drive type, 

continent of origin, and brand name for each vehicle model produced and sold during 

model year 2002. These attributes were used to define additional vehicle characteris

such as the ratio of horsepower to vehicle weight and refueling range, and the resulting 

set of attributes was used to test a variety of different specifications for Equation (0.6). 

iv.

With a sufficiently large number of new vehicle sales, the model’s predicted probabilities

that a representative buyer will choose each vehicle model can be interpreted as the share 

or fraction of total sales it is likely to account for. Thus the model can be used to 

estimate how the market shares of individual vehicle models would have differed during 

that period if one or more attributes of a specific model had been different. If data

d

futu odel years are available, this model can also

o

prices for some models. 

The change in the probability that an individual vehicle model k would have been chosen 

by a representative buyer – or in the aggregate, its market share of total new vehicle sales

– in response to a change in one of its attributes Xi,k is: 

TIVE DOCUMENT – DO NOT RELEASE 

( ) ( )

( ) ( ) ( ) ( ) () ()

, ,,

2

i k i k i k

s ( )

P ks P sk n n n P s

X XX

1 1 i n P n n in n n n =− + − β μ ks P ks P s P ks P s P s P β ⎡ ⎤ ⎣ ⎦ ⎣ ⎦

(0.7) 

s

∂ ∂ ∂

Normalizing

vehicle’s m

the elasticity

= +

∂ ∂∂

⎡ ⎤

 Equation (0.7) to measure the proportional (rather than absolute) change in a 

arket share in response to a proportional change in one of its attributes gives 

 of its market share: 

( )

( ) ( ) ( ) ( ) ,

, , 1 1 i k si ik n i ik n n

P sk X

X P ks X P ks P s

X P sk β μ β ⎡ ⎤

=− + − ⎡ ⎤

,

n

ik n

∂ ⎢ ⎥ ⎡ ⎤ ⎣ ⎦ ⎣ ⎦ (0.8) ∂ ⎣ ⎦

The computed values of these elasticities, which depend on the estimated parameters (the 

βis), the values of the attributes that change (the Xi,ks), and the initial market shares of 
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individual vehicles ( the elasticities of 

vehicle models’ market shares with respect to their own selling prices can be used to 

implement the cost-sharing calculation that apportions a manufacturer’s technology costs 

for improving the fuel economy of its fleet in inverse proportion to the price elasticity of 

demand for each of its models. Second, they can be used to estimate the resulting 

changes in market shares for individual models that results when these technology costs 

are “spread” among a manufacturer’s fleet using this or any other cost allocation 

assumption. 

However, certain attributes of at least some vehicle models – notably fuel economy, and 

possibly weight and performance – will also change as part of manufacturers’ efforts to 

comply with stricter fuel economy standards. When prices and other attributes of a 

ber of vehicle models change simultaneously, it is often simpler to estimate t e new 

eflected in vehicle prices. This revised CAFE level 

and 

le 

sing price and four other attributes. Other NML formulations may be specified, 

the values of Psk), can be used in two ways. First,

num

m

h

arket shares that will result by inserting the changed prices and attribute values in the 

utility expression for these models and recalculate the new market shares of all models 

directly. 

These new market shares can then be used to recalculate how each manufacturer’s salesweighted CAFE level would have changed once the technology costs for improving some 

of its models’ fuel economy were r

can then be used to assess each manufacturer’s compliance with the revised standard, 

thus its need to apply additional fuel economy technology to its vehicle models. 

v. NML (Market Share) Model Specification 

The system uses a 2-level nested multinomial logit (NML) model to recalculate market 

shares and sales volumes of different vehicle models after compliance costs have been 

estimated and allocated. Table V-1 lists the attributes accommodated by the system, and 

shows the inclusive value parameter the coefficients used in Equation (0.6) for a samp

model u

subject to the following constraints: 

• The inclusive value parameter must be between 0 and 1. 

• Coefficients must apply to attributes measured in the indicated units. 

• The number of market segments must correspond to the vehicles input file. 
126

Table V-1. Market Share Model Coefficients (Sample) 

Inclusive Value Parameter 0.579638

Attribute Units Coefficient

Effective Price dollars ( -0.000061

Fuel Economy mpg

Seating Capacity (Max.) number of seat belts 0.175729

2003)

Curb Weight pounds

4 Wheel Drive 1=present 0.075382

Automatic Transmission 1=present

Power horsepower

Power/Weight horsepower/pound 10.046800

Range miles

Weight-Specific Fuel Economy pound-miles per gallon

When developing an input file defining the initial state of the MY2002 fleet based on the 

th 

ng the resulting data file was missing some or all attribute 

ata for certain vehicle models. Wherever possible, we filled these gaps by collecting 

racteristics and related data 

uch as Edmunds.com. As part of this process, we also obtained the Manufacturer’s 

Suggested Retail Price (MSRP) for each vehicle model produced during model year 

2002. 

Because actual purchase prices for most vehicle models typically differ significantly from 

their suggested retail process, we adjusted each vehicle model’s MSRP for model year 

2002 by the ratio of its nationwide average “True Market Value” (TMV) during model 

year 2004, as estimated by Edmunds.com, to its MSRP during model year 2004.94 This 

adjustment provided an estimate of its nationwide average actual selling price during 

model year 2002. For vehicle models produced in model year 2002 but no longer offered 

for sale during model year 2004, we used the ratio of Edmunds’ estimated TMV to 

MSRP for the vehicle model in the same market segment we judged to be most similar 

(and where possible, produced by the same manufacturer). 

To calculate an “effective price” that takes into account fuel costs, we combined this with 

the estimated value to the consumer of fuel outlays during a specific payback period. We 

 

structure shown in Table V-1 we estimated the annual sales volumes for the 1,355 

individual vehicle models produced during model year 2002 using production data 

reported to NHTSA by manufacturers for the purpose of determining their CAFE 

compliance, supplemented with confidential and commercial data regarding vehicles wi

curb weights over 8,500 pounds. 

As discussed above, we developed the vehicle attribute, price, and other data used to 

estimate the market share model using several sources. We initially obtained some 

vehicle attribute data through information requests to the automotive manufacturers, but 

because of inconsistent reporti

d

supplemental information from online sources of vehicle cha

s

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ket share model. 

94 Edmunds’ estimates of vehicles True Market Values for model year 2002 were no longer available at the 

time we developed the mar
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calculated this value using the same methodology used in the compliance simulation 

model. The model-specific form applied here is as follows: 

( ) 0 0.5 (1 ) 1 FUEL v v LUE

FE gap r

v PB v v MY v SURV MI FUELPRICE VA = +

= + = − +

∑ (0.9) 

where MIv is the number of miles driven during the year when a vehicle produced in 

model year MY reaches age v, SURVv is the probability that a vehicle of that vintage 

(model year) will remain in service through age v, FE is the vehicle’s fuel economy, 

FUELPRICEMY+v is the price of fuel in year MY+v, and PB is a “payback period”, or 

number of years in the future the consumer is assumed to take into account when 

considering fuel savings. Payback periods of three and five years produced similar 

results. 

Table V-2 lists the vehicle attributes for which we were able to obtain complete data 

using the combination of sources discussed above. We used the estimated market shares 

and attribute data for individual vehicle models to develop a two-level nested logit model 

of each vehicle model’s market share. In this model, buyers first choose one of the 23 

ury 

ls 

 

market segments developed by Automotive News to represent the new vehicle market, 

each of which represents one combination of vehicle type (automobile versus light truck), 

style (e.g., sedan, pickup, or utility vehicle), size (small, mid-size, or large), and lux

level (standard, “upscale,” etc.). Table V-2 gives examples of vehicles that fall into each 

of these segments.95 Buyers then choose to purchase one of the specific vehicle mode

within that market segment. 

Table V-2. NML Market Segments and Example Vehicles 

ne 95 When using forward-looking product plans, it will be necessary to assign each new vehicle model to o

of these market segments. 
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Segment Name Examples

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1 Small - Budget

Small - Econ

Hyundai Accent, Toyota Echo

omy urn S Series, Toyota Corolla

ouring yota MR2 Spyder, Mini Cooper

remium che (all), BMW Z3

Exotic prit, Dodge Viper

ge - Lowe alibu, Honda Civic, VW Golf

 - Standa ota Camry, Honda Accord

rem axima, Saab 9-3

ria, Toyota Avalon

 Lu 70 Series, Chrysle 30

ry Jaguar XJ, Mercedes-Be ss

Upscale - Premium Mercedes-Benz CL600, Rolls-Royce

13 Pickups - Small Chevrolet S, Dodge Dakota, Mazda B-Series

Dodge Ram, Ford F-Series, Toyota Tundra

Honda Odyssey, Toyota Sienna, Dodge Caravan

16 Vans - Full-Sized Chevrolet Express, Dodge Ram Van, Ford Econoline

ator

2 Dodge Neon, Sat

3 Sporty - T o

- P

Mazda Miata, T

4 Sporty 

5 Sporty - 

Audi TT Coupe, Pors

Ferrari (all), Lotus Es

6 Mid-Ran r Chevrolet M

7 Mid-Range rd Buick Century, Toy

8 Mid-Range - P

itional

ium Audi A4, Nissan M

9 Trad Buick LeSabre, Ford Crown Victo

10 Upscale - Near , Volvo

11 Upscale - Luxu

xury Acura TL, BMW 3-Series

Acura RL, BMW 5-Series,

r 

nz E Cla

0M

12 Bentley (all), 

14 Pickups - Full-Sized

15 Vans - Mini

17 SUV - Standard Sport Wagon Honda CRV, Ford Escape, Toyota Highlander

18 SUV - Premium Sport Wagon Acura MDX, BMW X5, Mercedes-Benz M-Class

19 SUV - Small Chevrolet Tracker, Jeep Liberty, Nissan Xterra

20 SUV - Mid-Range Chevrolet Trailblazer, Dodge Durango, Honda Passport

21 SUV - Large Chevrolet Suburban, Ford Expedition, Toyota Sequoia

22 SUV - Premium Cadillac Escalade, Land Rover Range Rover, Mercedes-Benz G Class, Lincoln Navig

23 SUV - Sport-utility pickups Chevrolet Avalanche, Lincoln Blackwood, Cadillac Escalade EXT

24 Hybrid Toyota Prius, Honda Insight

We used the Gauss Mathematical and Statistical System produced by APTECH System

Inc., to estimate the parameters of the nested logit model of vehicle market shares 

escrib

s, 

ed previously in the report. This system uses a conventional maximum-likelihood 

rocedure to estimate the parameter values for the utility function and the associated 

inclusive value parameter. As indicated as previously in the text, the value of this 

parameter provides some indication of how accurately the nesting structure used in the 

model (the Automotive News market segmentation) reflects buyers’ views of the new 

vehicle market. 

We experimented with a large number of alternative specifications of the utility function 

shown in Equation (0.6) for individual vehicle models, each using different combinations 

of the vehicle attributes shown in the table. We selected the combination of attributes to 

include in the final model on the basis of the reasonableness of the signs and relative 

magnitudes of their estimated coefficients, the model’s ability to replicate actual market 

shares for individual models, and the estimated value of the nesting coefficient or 

inclusive value parameter.96 Table V-3 indicates the subset of attributes that were 

included in final model, and reports the estimated values of their coefficients. 

Table V-3. NML Model Attributes and Coefficients 

Best Model Specification 

d

p

Attribute Measure Coefficient t-statistic 

Equivalent Price Est. sale price plus est. fuel value over 5 years -0.0000556 -847 

Performance Ratio of horsepower to curb weight 9.605 285 

Weight Curb weight 

 

96 The wide variation in the orders of magnitude of the estimated coefficients for the different attributes 

reflects similarly wide variation in their measurement scales. 
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Seating Capacity Number of adults seated 0.171 688 

Towing Capacity Maximum trailer weight 

Payload Maximum cargo weight 

Luggage Space Enclosed cargo volume 

Fuel Economy EPA combined MPG rating 

Fuel Tank Size Capacity in gallons 

Refueling Range Fuel tank capacity * MPG 

Transmission Type Automatic =1; manual = 0 

Drive Type 2—wheel drive = 0; 4-wheel drive =1 0.054 81 

Continent of Origin Asia, Europe, or North America 

Brand Manufacturer identity 

c. Model Convergence 

After the market share model has concluded, the sales volumes of different vehicle 

models will typically have changed relative to values used to determine compliance with 

CAFE standards. Because this can cause changes in CAFE levels, the revised sales 

volumes are used to repeat the compliance simulation, cost allocation, and market share 

models. This process is repeated until the model converges, as determined by the 

magnitude of changes in CAFE levels and market share specific to each manufacturer 

and regulatory class. The process, for which Figure V-9 provides an overview, 

terminates if such changes are all less than 1% or if the sequence has been repeated 10 

times.97,98

 

97 This cycling currently leads to “overcompliance” in some cases, which we are attempting to minimize by 

developing code to selectively “remove” technologies between iterations. 

98 A limit of 10 iterations is imposed to guard against indefinite repetition. The system typically converges 

within 5-6 iterations to changes smaller than 1%. 
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Cost Allocation

Market Share

Model

Convergence?

Compliance

Simulation

No

Yes Calculate

Effects

Figure V-9. Model Convergence Process
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ten 

tions. 

ts 

nical Report and supplemented the review 

with updated information from the FEV tear-down studies contracted by EPA, more 

current rature, new product plans and EPA certification testing data. 

e fol ness estimates 

ompleted for technologies deemed to be appropriate in the rulemaking timeframe. The 

estimates are d he 

analysis was conducte rs from DOT and EPA and represents what the 

agencies believe to be the best available estimates for the MY 2012-2016 rulemaking 

timefra

el 

el saving technologies can be added to the baseline fleet, NHTSA researches 

and dev logies that 

 input into 

fleet in 

t to 

ology 

“availability” is not determined based simply on whether the technology exists, but 

depends also on whether the technology has achieved a level of technical viability that 

C. Technologies – Costs and Effectiveness 

Technology assumptions, i.e., assumptions about their availability, cost, 

effectiveness, and the rate at which they can be incorporated into new vehicles, are of

very controversial as they have a significant impact on the levels of the standards. 

Agencies must, therefore, take great care in developing and justifying these assump

In developing technology inputs for MY 2012-2016 standards, NHTSA and EPA 

reviewed, as requested by President Obama in his January 26 memorandum, the 

technology assumptions that NHTSA used in setting the MY 2011 standards, the 

comments that NHTSA received in response to its May 2008 NPRM and the commen

received in response to the NPRM for this rule. In addition, the agencies reviewed the 

technology input assumptions identified in EPA’s July 2008 Advanced Notice of

Proposed Rulemaking and 2008 Staff Tech 99

 lite

Th lowing section details the availability, cost and effective

c

rawn from an analysis conducted between NHTSA and EPA in 2009. T

d by enginee

me. 

A. NHTSA analyzes what technologies can be applied beyond those in 

the baseline vehicle fleet 

One of the key statutory factors that NHTSA must consider in setting maximum 

feasible CAFE standards for each model year is the availability and feasibility of fu

saving technologies. The baseline vehicle fleet identifies the technologies already 

deployed for each vehicle model. The agency uses the baseline vehicle fleet data to

ascertain the “baseline” capabilities and average fuel economy of each manufacturer. 

Given the agency’s need to consider economic practicability in determining how quickly

additional fu

elops, based on the best available information and data, a list of techno

the agencies believe will be ready for implementation during the model years covered by 

the rulemaking. This includes developing estimates of the costs and effectiveness of each 

technology and lead time needs. The resultant technology assumptions form an

the Volpe model. The model simulates how manufacturers can comply with a given 

CAFE level by adding technologies beyond those included in the baseline vehicle 

a systematic, efficient and reproducible manner. 

 CBD commented that because many of the technologies considered in the NPRM

are currently available, manufacturers should be able to attain mpg levels equivalen

the MY 2016 standards in MY 2009. In response, as discussed below, techn

 

99 EPA Staff Technical Report: Cost and Effectiveness Estimates of Technologie

Duty Vehicle Carbon Dioxide Emissions. EPA420-R-08-008, March 2008. 

s Used to Reduce Light-
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

makes ent 

en if a technology is available for 

applica

ne or 

Final Rule

In two of the a blished light truck 

AFE standards for MYs 2005-2007 and MYs 2008-2011, NHTSA relied on the 2002 

Nation erage 

 of 

f Congress, in order to provide independent and peer 

viewed estimates of cost and effectiveness numbers. The NAS list was determined by a 

ational Academy of Sciences, and was then peerreview

er 

 economy 

technologies that will be available and their costs and effectiveness values. To aid the 

agency

 

it appropriate for widespread application. This depends in turn on compon

supplier constraints, capital investment and engineering constraints, and manufacturer 

product cycles, among other things. Moreover, ev

tion, it may not be available for every vehicle. Some technologies may have

considerable fuel economy benefits, but present significant technical changes related to 

NVH and drivability issues when applied to some vehicles within the model years 

covered by this rule – for example, applying cylinder deactivation to 4-cylinder engi

on vehicles with manual transmissions. The agencies have provided for increases over 

time to reach the mpg level of the MY 2016 standards precisely because of these types of 

constraints, because they have a real effect on how quickly manufacturers can apply 

technology to vehicles in their fleets. The following sections describe NHTSA’s fuelsaving technology assumptions and methodology for estimating them, and their 

applicability to MY 2012-2016 vehicles. 

 

 

 B How NHTSA decides which technologies to include

1. How NHTSA did this historically, and how for the MY 2011

gency’s past CAFE rulemakings, which esta

C

al Academy of Sciences’ report, “Effectiveness and Impact of Corporate Av

Fuel Economy Standards”100 (“the 2002 NAS Report”) for estimating potential fuel 

economy effectiveness values and associated retail costs of applying combinations

technologies in 10 classes of production vehicles. The NAS study was commissioned by 

the agency, at the direction o

re

panel of experts formed by the N

ed by individuals chosen for their diverse perspectives and technical expertise in 

accordance with procedures approved by the Report Review Committee of the National 

Research. 

In the 2008 NPRM, NHTSA explained that there has been substantial 

advancement in fuel-saving automotive technologies since the publication of the 2002 

NAS Report. New technologies, i.e., ones that were not assessed in the NAS report, have

appeared in the market place or are expected to appear in the timeframe of the 

rulemaking. Also, new studies have been conducted and reports issued by several oth

organizations providing new or different information regarding the fuel

 in assessing these developments, NHTSA contracted with the NAS to update the

fuel economy section, Chapter 3, of the 2002 NAS Report. However, as NHTSA 

explained, the NAS update was not available in time for this rulemaking. 

 

100 National Research Council, “Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) 

 11, 2008). 

Standards,” National Academy Press, Washington, DC (2002). Available at

http://www.nap.edu/openbook.php?isbn=0309076013 (last accessed October
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Accordingly, NHTSA worked with EPA staff to update the technology 

s NPRM. EPA staff published a related 

report a

cal 

believed that the assumptions of availability and 

applica

e 

e 

e more information can be found 

on thes

assumptions, and used the results as a basis for it

nd submitted it to the NAS committee.101

For the MY 2011 final rule, NHTSA hired an international consulting firm, 

Ricardo, to aid the agency in analyzing the comments the agency received in response to 

its 2008 NPRM. Ricardo’s role was as a technical advisor to NHTSA staff. In this 

capacity, Ricardo helped NHTSA undertake a comprehensive review of the NPRM 

technology assumptions and all comments received on those assumptions, based on both 

old and new public and confidential manufacturer information. Relying on the techni

expertise of Ricardo and taking into consideration all the information available, NHTSA 

revised its estimates of the availability and applicability of many technologies. While 

NHTSA sought Ricardo’s expertise and relied significantly on their assistance as a 

neutral expert in developing its technical assumptions, it retained responsibility for the 

final assumptions. The agency 

bility for the MY 2011 final rule were more accurate than those used in the 

NPRM, and were the best available for purposes of that rulemaking. 

 

C. What technology assumptions has NHTSA used for the final rule? 

1. How do NHTSA’s technology assumptions in the final rul

differ from those used in the NPRM? 

In developing this final rule, and in working in conjunction with the EPA, 

NHTSA has revised some of the inputs used by the Volpe model to assess the appropriat

stringency for future CAFE standards. The following section discusses the more 

important changes and revisions, and also advises wher

e and other changes. 

Baseline and Market Data File:

As described in detail above in Section III.b. of the Preamble, the agencies relied 

on CSM forecast data to assist us with establishing the baseline and the market data file. 

After the NPRM had been published, the agencies noticed that the standard CSM forecast

included heavy duty class 2b and class 3 vehicles. These vehicles are unregulate

CAFE (e.g., Ford F-350). The forecast from CSM used in the NPRM was from

quarter of 2009. The agencies requested that CSM to make a custom 4th quarter forecast

with these vehicles removed for the final rule making. The customized forecast from

CSM has allowed the agencies to correct this error and we now believe the estimates 

included in the baseline fleet to be accurate for all classes of vehicles. 

 

More information on the advantages and disadvantages of the current approach 

d by 

 the 2nd 

and the agencies’ decision to follow it is available in Section II.B.3 of the Preamble, and 

Section I of the joint TSD describes in greater detail the process the agencies used in 

sourcing the data for the baseline fleet and developing it into a representation of a future 

fleet. 

 

101 EPA Staff Technical Report: Cost and Effectiveness Estimates of Technologies Used to Reduce LightDuty Vehicle Carbon Dioxide Emissions, EPA 420-R-08-008, March 2008. 
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Revisions to Technologies and Their Estimates:

Specific to its modeling, NHTSA has revised two technologies used in the final 

rule analysis from those considered in the NPRM. These revisions were based on 

omments received in response to the NPRM and the identification of area to improve 

accuracy. In th PR not available for 

small v hicles because it did not appear to be a cost-effective option. However, based on 

comme r 

tion 

ss 

 and 

ess 

 a great extent, the agencies, in reconsidering information from many 

sources

Lift 

al 

08 

logies 

. Thus, NHTSA corrected these effectiveness 

estimat

HTSA 

c

e N M, a diesel engine option (DSLT or DSLC) was 

e

nts received in response to the NPRM, the agency added a diesel engine option fo

small vehicles. Additionally, in the NPRM, the mass reduction/material substitu

technology, MS1, assumed engine downsizing. However, for purposes of the final rule, 

engine downsizing is no longer assumed for MS1, thus slightly lowering the effectivene

estimate, to better reflect how manufacturers might implement small amounts of mass 

reduction/material substitution. These changes are discussed in greater detail below and

Chapter 3 of the joint TSD. 

Building on NHTSA’s estimates developed for the MY 2011 CAFE final rule

EPA’s Advanced Notice of Proposed Rulemaking, which relied on EPA’s 2008 Staff 

Technical Report,102 the agencies took a fresh look at technology cost and effectiven

values and incorporated FEV tear-down study results for purposes of this joint final rule

under the National Program. Generally speaking, while NHTSA found that much of the 

cost information used in the MY 2011 final rule and EPA’s 2008 Staff Report was 

consistent to

, revised the component costs of several major technologies including: 

turbocharging/downsizing, mild and strong hybrids, diesels, SGDI, and Valve Train 

Technologies for purposes of the NPRM. In addition, based on FEV tear-down studies, 

the costs for turbocharging/downsizing, 6-, 7-, 8-speed automatic transmissions, and du

clutch transmissions were revised for this final rule. 

Most effectiveness estimates used in both the MY 2011 final rule and the 20

EPA Staff Report were determined to be accurate and were carried forward without 

significant change into this rulemaking. When NHTSA and EPA’s estimates for 

effectiveness diverged slightly due to differences in how the agencies apply techno

to vehicles in their respective models, we report the ranges for the effectiveness values 

used in each model. For purposes of the final rule analysis, NHTSA made only a couple 

of changes to the effectiveness estimates. Specifically, in reviewing the NPRM 

effectiveness estimates for this final rule NHTSA discovered that the DCTAM 

effectiveness value for Subcompact and Compact subclasses was incorrect; the (lower) 

wet clutch effectiveness estimate had been used instead of the intended (higher) dry 

clutch estimate for these vehicle classes 103

es. Additionally, as discussed above, the effectiveness estimate for MS1 was 

revised (lowered) to better represent the impact of reducing mass at a refresh. These 

revisions are discussed at length in the joint TSD and in this document below. N

 

102 EPA Staff Technical Report: Cost and Effectiveness Estimates of Technologies Used to Reduce Li

Duty Vehicle Carbon Dioxide Emissions. EPA420-R-08-008, March 2008. 

103 A dry clutch DCTAM is more efficient and cheaper than a wet clutch DCTAM because it doesn’t 

require a wet clutch type hydraulic system, which is used to cool the clutches. However, due to this lack 

of cooling, a dry clutch DCTAM has a lower torque capacity. Dry clutch DCTAM’s are ideal for smaller 

ghtvehicles (i.e. Subcompact and Compact) with lower engine torque ratings.
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e 

2. How are technologies applied in the model? 

s has its 

w the 

ented 

before 

l 

particu s 

ology are 

ness 

ose 

 other 

technol

evaluated in an “apples-to-apples” comparison with those used by the CAFE model, since 

t 

and EPA are confident that the thorough review which has been conducted has led to th

best available conclusion regarding technology costs and effectiveness estimates for the 

current rulemaking and resulted in excellent consistency between the agencies’ respective 

analyses for developing the CAFE and CO2 standards. 

As in the MY 2011 final rule and NPRM, each technology is assigned to one of 

the five following categories based on the system it affects or impacts: engine, 

transmission, electrification/accessory, hybrid or vehicle. Each of these categorie

own decision tree that the CAFE model uses to apply technologies sequentially during 

the compliance analysis. The decision trees were designed and configured to allo

CAFE model to apply technologies in a cost-effective, logical order that also considers 

ease of implementation. For example, software or control logic changes are implem

replacing a component or system with a completely redesigned one, which is 

typically a much more expensive option. In some cases, and as appropriate, the mode

may combine the sequential technologies shown on a decision tree and apply them 

simultaneously, effectively developing dynamic technology packages on an as-needed 

basis. For example, if compliance demands indicate, the model may elect to apply LUB, 

EFR, and ICP on a dual overhead cam engine, if they are not already present, in one 

single step. 

Each technology within the decision trees has an incremental cost and an 

incremental effectiveness estimate associated with it, and estimates are specific to a 

lar vehicle subclass. Each technology’s incremental estimate takes into account it

position in the decision tree path. If a technology is located further down the decision 

tree, the estimates for the costs and effectiveness values attributed to that techn

influenced by the incremental estimates of costs and effectiveness values for prior 

technology applications. In essence, this approach accounts for “in-path” effective

synergies, as well as cost effects that occur between the technologies in the same path. 

When comparing cost and effectiveness estimates from various sources and th

provided by commenters, it is important that the estimates evaluated are analyzed in the 

proper context, especially as concerns their likely position in the decision trees and

ogies that may be present or missing. Not all estimates available in the public 

domain or offered for the agencies’ consideration during the comment period can be 

in some cases the order of application, or included technology content, is inconsisten

with that assumed in the decision tree. 

In the MY 2011 final rule, significant revisions had been made to the sequence of 

technology applications within the decision trees, and in some cases the paths themselves 

had been modified and additional paths had been added. These revisions were 

maintained for this final rule analysis. The additional paths allow for a more accurate 

application of technology, insofar as the model now considers the existing configuration 

of the vehicle when applying technology. In this analysis, single overhead camshaft 

(SOHC), dual overhead camshaft (DOHC) and overhead valve (OHV) configured 

engines now have separate paths that allow for unique path-dependent versions of certain 

engine technologies. Thus, the cylinder deactivation technology (DEAC) now consists of
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ve 

properly account for 

technology effec path, the 

increm al effe g loss 

reductions have already been accomplished by the preceding technology, CCPS, which 

reduces or diminishes the effectiveness estimate for DVVLS because part of the 

efficiency gain associated with the reduction of the pumping loss mechanism has already 

occurred. This accounting approach resolves this potential double-counting issue. 

To address any potential confusion, NHTSA would like to draw attention to the 

retention of previously applied technologies when more advanced technologies (i.e., 

those further down the decision tree) were applied. In both the MY 2011 final rule and 

this final rule, as appropriate and feasible, previously-applied technologies are retained in 

combination with the new technology being applied, but this is not always the case. For 

instance, one exception to this would be the application of diesel technology, where the 

entire engine is assumed to be replaced, so gasoline engine technologies cannot carry

over. This exception for diesels, along with a few other technologies, is documented

below es. 

sts 

ject, 

, 

three unique versions that depend on whether the engine being evaluated is an SOHC, 

DOHC or OHV design; these technologies are designated by the abbreviations DEACS, 

DEACD and DEACO, respectively, to designate which engine path they are located on. 

Similarly the last letter for the Coupled Cam Phasing (CCP) and Discrete Variable Val

Lift (DVVL) abbreviations are used to identify which path the technology is applicable 

to. 

Use of separate valvetrain paths and unique path-dependent technology variations 

also ensures that the incremental cost and effectiveness estimates 

ts so as not to “double-count.” For example, in the SOHC

ent ctiveness estimate for DVVLS assumes that some pumpin

in the detailed discussion of each decision tree and corresponding technologi

As the Volpe model steps through the decision trees and applies technologies, it 

accumulates total or “NET” cost and effectiveness values. Net costs are accumulated 

using an additive approach while net effectiveness estimates are accumulated 

multiplicatively. As with the MY 2011 final rule, the decision trees have been expanded

so that NHTSA is better able to track the incremental and net/cumulative cost and 

effectiveness of each technology, which substantially improves the “accounting” of co

and effectiveness for this final rule.104 To help readers better understand the 

accumulation process, and in response to comments expressing confusion on this sub

the following examples demonstrate how the Volpe model calculates net values. 

Accumulation of net cost is explained first as this is the simpler process. This 

example uses the Electrification/Accessory decision tree sequentially applying the EPS

 

104 In addition to the (simplified) decision trees, as published in this document, NHTSA also utilized 

“expanded” decision trees in this final rule analysis. Expanded decision trees graphically represent each 

unique path, considering the branch points available to the Volpe model, which can be utilized for applyin

fuel saving technologies. For instance, the engine decision tree shown in this document has 20 boxes 

representing engine technologies, whereas the expanded engine decision tree requires a total of 45 boxe

accurately represent all available application variants. Expanded decision trees presented a signi

improvement in th

staff to a urately

g 

s to 

ficant 

e overall assessment and tracking of applied technologies since they allowed NHTSA 

 view and assess both the incremental and the accumulated, or net cost and effectiveness 

at any st e of technology application in a decision tree. Because of the large format of the expanded 

decision s, they could not be included in the Federal Register, so NHTSA refers the reader to Docket 

No. NHTSA-2009-0059. Expanded decision trees for the engine, 

electrification/transmission/hybridization, and the vehicle technologies (three separate decision trees) were 

ket for 

cc

ag

 tree

developed for each of the 12 vehicle technology application classes and have been placed in the doc

the reader’s information. 
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IACC, MH cost and 

effectiv ness estimates from its input sheet. As seen in Table V-4 below, the input sheet 

cost estimates have a lower and upper value which may be the same or a different value 

(i.e., a single value or a range) as shown in columns two and three. The Volpe model 

first averages the values (column 4), and then sums the average values to calculate the net 

cost of applying each technology (column 5). Accordingly, the net cost to apply the 

MHEV technology for example would be ($106.00+ $128.00 + $288.00 = $522.00). Net 

costs are calculated in a similar manner for all the decision trees. 

Table V-4 Sample Volpe Model Net Cost Calculation 

EV, BISG and CISG technologies to a subcompact vehicle using the

e

Tech. Abrev.

Lower INCR 

Cost

Upper INCR 

Cost

Avg. INCR 

Cost NET Cost

EPS $ 106.00 $ 106.00 $ 106.00 $ 106.00

IACC $ 128.00 $ 128.00 $ 128.00 $ 234.00

MHEV 288.00 $ $ 288.00 $ 288.00 $ 522.00

BISG $ 286.00 $ 286.00 $ 286.00 $ 808.00

CISG 2,791.00 $ $ 2,791.00 $ 2,791.00 $ 3,599.00

Example Net Cost Calculation: 

Elect./Acc. Path, Subcompact Vehicle Subclass

The same decision tree, technologies, and vehicle are used for the example 

demonstrating the model’s net effectiveness calculation. Table V-5 below shows averag

incremental effectiveness estimates in column two; this value is calculated in the same 

manner as the cost estimates above (average of lower and upper value taken from the 

input sheet). To calculate the change in fuel consumption due to application of the EPS 

technology with incremental effectiveness of 1.5 percent (or 0.015 in decimal form, 

column 3), when applied multiplicatively, means that the vehicle’s current fuel 

consumption ‘X’ would be reduced by a factor of (1 – 0.015) = 0.985,

e 

02, or a net 2.98 

percent eness, as shown in the table. Net effectiveness is calculated in a similar 

manner the all decision trees. It should be noted that all incremental effectiveness 

estimat were derived with this multiplicative approach in mind; calculating the net 

effectiv ness using an additive approach will yield a different and incorrect net 

105 or 

mathematically 0.985*X. To represent the changed fuel consumption in the normal 

fashion (as a percentage change), this value is subtracted from 1 (or 100%) to show the 

net effectiveness in column 5. 

As the IACC technology is applied, the vehicle’s fuel consumption is already 

reduced to 0.985 of its original value. Therefore the reduction for an additional 

incremental 1.5 percent results in a new fuel consumption value of 0.97

 effectiv

 for 

es

e

effectiveness. 

 

105 A decrease in fuel consumption (FC) means the fuel economy (FE) will be increased since fuel 

consumption and economy are related by the equation FC = 1/FE. 
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Ta -5 ble V Sample Volpe Model Net Effectiveness Calculation 

Tech. 

Abrev.

INCR 

Eff. %

Avg. INCR 

Eff. (decimal)

Mu

Cu

Avg. 

ltiplicative FC Reduction

rrent FC * (1-Avg INCR)

Net Effect.

(1 - Red)

18.00%

EPS 1.50% 0.0150 1 * (1 - 0.015) = 0.985 1.50%

IACC 1.50% 0.0150 0.985 * (1 - 0.015) = 0.9702 2.98%

MHEV 2.50% 0.0250 0.9702 * (1 - 0.0250) = 0.9459 5.41%

BISG 5.00% 0.0500 0.99459* (1 - 0.0500) = 0.8986 10.14%

CISG 8.75% 0.0875 0.8986 * (1 - 0.0875) = 0.8200

Example Net Effectiveness Calculation: 

Elect./Acc. Path, Subcompact Vehicle Subclass

To improve the accuracy of accumulating net cost and effectiveness estimate

“path-dependent corrections” were employed in the MY 2011 final rule and are being 

utilized in this final rule. The prior NPRM analysis (2008) had the potential to

overestimate or underestimate net cost and effectiveness depending on which decision 

tree path the Volpe model followed when applying the technologies. For example, i

the 2008 NPRM analysis a diesel technology was applied to a vehicle that followed

OHV path, the net cost and effectiveness could be different from the net estimates

vehicle that followed the OHC path even though the intention was to have the same ne

cost and effectiveness. In order to correct this issue path-dependent correction ta

were added to

s, 

 either 

f in 

 the 

 for a 

t 

bles 

 the input sheets. The model uses these tables to correct net cost and 

effectiv single 

which 

re for 

e 

l 

is 

 into the strong hybrids, the 

correction tables are used to adjust the estimates from the CVT path. 

 

eness estimate differences that occur when multiple paths lead into a 

technology that is intended to have the same net cost and effectiveness no matter 

path was followed.106 Path-dependent corrections were used when applying cylinder 

deactivation (on the DOHC path), turbocharging and downsizing, diesel and strong

hybrids. For the engine technologies listed in the preceding sentence, the fuel 

consumption and cost estimates stated in following sections and the input sheets a

an SOHC engine. The correction tables discussed above are then used to adjust th

estimates for the different paths (i.e. DOHC or OHV). Similarly, all strong hybrid fue

consumption and cost estimates stated in the following section and the input sheets are

relative to a vehicle that is following the CVT path, discussed in the 

Electrification/Accessory Technology Decision Tree section below. For a vehicle that 

following the 6-, 7- and 8-speed automatic transmission path

106 The correction tables are used for path deviations within the same decision tree. However, there is one 

exception to this rule, specifically that the tables are used to keep the model from double-counting cost and 

effectiveness estimates when both the CBRST and MHEV are applied to the same vehicle. Both 

technologies try to accomplish the same goal of reducing fuel consumption, by limiting idle time, but 

through different means. If either of these technologies exists on a vehicle and the Volpe model applies the 

other, the correction tables are used to remove the cost and effectiveness estimates for CBRST, thus 

ensuring that double-counting does not occur. 
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3. Technology application decision trees 

The following paragraphs explain, in greater detail, the decision tree logic and 

revisions to the decision trees from the MY 2011 final rule that have been incorporated 

for this final rule. 

Engine Technology Decision Tree 

For the NPRM and this final rule, NHTSA reviewed the engine decision tree 

and the model’s technology application logic used in the MY 2011 final rule, and 

concluded that no revisions were necessary to the engine tree at this time. Figure V10 below shows the decision tree for the engine technology category. 

As in the MY 2011 final rule, NHTSA does not show Camless Valve 

Actuation (CVA), Lean-Burn GDI (LBDI), and Homogenous Charge Compression 

Ignition (HCCI) on the decision trees because these technologies were determined to 

be in the research phase of development; no new information to suggest these 

technologies are under development has been received at this time. As also discussed 

in the MY 2011 final rule, SOHC, DOHC and OHV engines have separate paths to 

allow the model to apply unique path-dependent valvetrain technologies (Variable 

Valve Timing, Variable Valve Lift, and cylinder deactivation) that are tailored to 

those specific engine types. This approach also improves the accuracy of accounting 

for net cost and effectiveness compared to that used in the 2008 NPRM or prior 

rulemakings.

Also as in the MY 2011 final rule, the Turbocharging and Downsize 

technology (TRBDS) is considered to be a completely new engine that has been 

converted to DOHC (if not already a DOHC in the baseline vehicle) with LUB, EFR, 

DCP, SGDI and CBRST applied. Similarly, the conversion to Diesel (DSLC and 

DSLT) is considered to be a completely new engine that replaces the gasoline engine 

(although it carries over the LUB and EFR technologies). We note that the pathdependent variations of these three technologies (TRBDS, DSLC, and DSLT) all 

result in the same technology state for the modified vehicle regardless of the path the 

model followed to achieve it. Therefore, in conducting the analysis, the net cost and 

effectiveness estimates for the different engine paths are considered to be the same 

(regardless of path), and the incremental cost and effectiveness estimates are adjusted 

as appropriate to account for the path-dependent variations 
DE

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FigureV-10. Engine Technology (EngMod) Decision Tree 

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ing this decision tree, NHTSA made some revisions from the version 

used in ) has 

 Figure V-11. Electric Power Steering (EPS) is the first technology in this 

decision tree, since it is a primary enabler for both mild and strong hybrids, and is 

followe as in the MY 2011 final rule. Micro-Hybrid 

(MHEV , a 12-volt system that offers basic idle stop/start functionality only, continues to 

follow ge 

ents a higher voltage, 

. 

is 

 example 

ially realized version of this technology. CISG, which is the most capable 

of the mild hybrid options, is the final step necessary in order to convert the vehicle to a 

(full) strong hybrid; it replaces BISG when it is applied, but again, the final vehicle state 

contains both EPS and IACC. All Electrification/Accessory technologies can be applied 

to both automatic and manual transmission vehicles. 

Transmission Technology Decision Tree 

For the NPRM and this final rule, NHTSA reviewed the transmission technology 

decision tree and the model’s technology application logic used in the MY 2011 final 

rule, and concluded that no revisions to the transmission tree were necessary at this time. 

This decision tree, shown in Figure V-11, contains two paths: one for automatic 

transmissions and one for manual transmissions, that are identical to those used in the 

MY 2011 final rule. 

On the automatic path, the decision tree first optimizes the current transmission 

by improving the control system via the Improved Automatic Transmissions Controls and 

other Externals (IATC) technology before applying more expensive technologies. After 

IATC, the decision tree splits into a “Unibody only” and “Unibody or Ladder Frame” 

path, both of which result in conversion to new and fully optimized transmission designs. 

The Unibody only path contains the Continuously Variable Transmission (CVT) 

technology, while the Unibody or Ladder Frame path has 6/7/8-Speed Automatic 

Transmission with Improved Internals (NAUTO). The NAUTO technology is followed 

by Dual Clutch Transmission/Automated Manual Transmission (DCTAM) technology. 

Dual Clutch Transmission (DCT) designs do not suffer torque interrupt when shifting; a 

Electrification/Accessory Technology Decision Tree 

After review

 the MY 2011 final rule. Specifically, one of the 2011 technologies (HVIA

been incorporated into a new mild hybrid technology (BISG), which allows the model to 

choose from a broader range of mild hybrid options before conversion to a strong hybrid,

as shown in

d by Improved Accessories (IACC),

)

as the first of the mild hybrid technologies. However, while the Higher Volta

and Improved Alternator (HVIA) technology followed MHEV in the MY 2011 final rule, 

for purposes of the NPRM and this final rule, HVIA has been incorporated into the next 

technology, Belt Integrated Starter Generator (BISG). BISG repres

such as 42 volts, mild hybrid system with idle stop/start functionality, but with higher 

capability than MHEV including limited energy recovery through regenerative braking

BISG represents a mid-point option between MHEV and the next level of mild hybrid. 

BISG replaces the MHEV technology when it is applied, but EPS and IACC remain on 

the vehicle. Crank Integrated Starter Generator (CISG), the last of the mild hybrids, 

also a higher voltage system with regenerative braking and limited motive power, 

primarily launch assist. Honda’s Integrate Motor Assist (IMA) system is a good

of a commerc
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charact

ments from manufacturers expressing concern that torque interrupt will 

not be acceptable to consumers, the DCTAM technology is intended to use a DCT-type 

transmission only. 

The manual transmission path again has only one technology application; 

conversion to a 6-Speed Manual with Improved Internals (6MAN). NHTSA anticipates 

limited use of manual transmissions with more than 6 speeds within the MY 2012-2016 

timeframe. 

Hybrid Technology Decision Tree 

NHTSA also reviewed the hybrid technology decision tree and the model’s 

technology application logic used in the MY 2011 final rule, and concluded that no 

revisions were necessary for the hybrid tree for the NPRM and this final rule. The model 

continues to only apply strong hybrid technologies when both the 

Electrification/Accessory and Transmission (automatic transmissions only) technologies 

have been fully added to the vehicle, as seen in Figure V-11. When the CAFE model 

applies strong hybrids it takes into account that some of the fuel consumption reductions 

have already been included when technologies like EPS or IACC have been previously 

applied. When strong hybrids are required, the model chooses the most appropriate 

application of the Two Mode (2MHEV), Power Split (PSHEV) or Plug-in Hybrid 

Vehicle (PHEV), based on the vehicle’s subclass and/or the most cost-effective 

application. 

eristic associated with automated manual transmission (AMT) designs. In 

response to com
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gy 

Vehicle Te

After re

technology tree fro

utilized three Materi

Technology Deci

the NPRM and this final rule as Mass Reduction and are discussed in greater detail 

below. As shown in Figure V-12, this rule uses two technologies, (MS1) and (MS2), and 

a dedicated path in the Vehicle Technology Decision Tree. Both have a different 

definition than was used in the prior rule. The Mass Reduction 1 (MS1) technology now 

represents a 1.5 percent (of vehicle curb weight) weight decrease that can be applied to 

any subclass of vehicle at the Refresh or Redesign cycle. The MS2 technology defines a 

3.5 percent to 8.5 percent subclass-dependent mass reduction, which can only be applied 

at the Redesign cycle, with the lower reductions occurring in the smaller/lighter vehicles. 

MS2 is incremental to MS1, which means that the model may, subject to subclass and 

cycle constraints, potentially reduce vehicle weight by a total of 5 to 10 percent (of curb 

weight) within the rulemaking time frame. To allow manufacturers lead time to 

Figure V-11. Electrification/Accessory, Transmission and Hybrid Technolo

Decision Tree

chnology Decision Tree 

ing this decision tree, NHTSA made some revisions to the vehicle 

m the version used in the MY 2011 final rule. The MY 2011 final rule 

al Substitution (MS) technologies in a dedicated path in the Vehicle 

sion tree. These technologies have been reconsidered for purposes of 

view
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implement larger mas uct

2014. Low Rolling Resistanc B) and Secondary 

Axle Disconnect (SAX) all ha e the same definition and path as used in the MY 2011 

final ru

s red ions, the MS2 technology is made unavailable until MY 

e Tires (ROLL), Low Drag Brakes (LD

v

le, with SAX applied to 4WD vehicles only. Aerodynamic Drag Reduction 

(AERO) remains a separate path. 

Figure V-12. Vehicle Technology Decision Tree 

 
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logy 

on using ten vehicle “classes” (4 cars classes and 6 truck classes),107

but did not det lass. NAS’s 

purpos n sep ” vehicles, 

i.e., veh cles similar in size, powertrain configuration, weight, and consumer use, and for 

which similar technologies are applicable. NHTSA similarly differentiates vehicles, 

referring to each grouping as a “subclass,” for the purpose of applying technologies to 

vehicles and assessing their incremental costs and effectiveness. These technology 

subclasses should not be confused with the regulatory classifications pursuant to 49 CFR 

Part 523. 

For this final rule as for the MY 2011 final rule, the CAFE model divides the 

vehicle fleet into subclasses based on model inputs, and applies subclass-specific 

estimates, also from model inputs, of the applicability, cost, and effectiveness of each 

fuel-saving technology. Therefore, the model’s estimates of the cost to improve the fuel 

economy and the amount of fuel economy improvement of each vehicle model depend 

upon the subclass to which the vehicle model is assigned. 

NHTSA’s analysis for the MY 2005-2007 and MY 2008-2011 light truck CAFE 

standards used the same vehicle classes defined by NAS in its 2002 Report. The 2008 

NPRM for MY 2011-2015 also used those same vehicle classes, but included some 

differentiation in cost and effectiveness numbers between the various classes to account 

for differences in technology costs and effectiveness that are observed when technologies 

are applied on to different classes and subclasses of vehicles. The agency found it 

important to make that differentiation because it estimated that, for example, engine 

turboch

016 

vehicles under consideration. The methodology is as follows: 

NHTSA examined the car and truck segments separately. First, for the car 

segment, NHTSA plotted the footprint distribution of vehicles in the baseline vehicle 

fleet and divided that distribution into four equivalent footprint range segments. The 

footprint ranges were named Subcompact, Compact, Midsize, and Large classes in 

ascending order. Cars were then assigned to one of these classes based on their specific 

footprint size. Vehicles in each range were then manually reviewed by NHTSA staff to 

 

4. Division of vehicles into subclasses based on techno

applicability, cost and effectiveness 

As part of its consideration of technological feasibility, the agency evaluates 

whether each technology could be implemented on all types and sizes of vehicles, and 

whether some differentiation is necessary in applying certain technologies to certain 

types and sizes of vehicles, and with respect to the cost incurred and fuel consumption 

and CO2 emissions reduction achieved when doing so. GM commented as to the 

applicability of technologies based on size and classification of vehicles, NHTSA agrees 

and applied technologies with this approach. The 2002 NAS Report differentiated 

technology applicati

ermine how cost and effectiveness values differ from class to c

e i arating vehicles into these classes was to create groups of “like

i

arging and downsizing would have different implications for large vehicles than 

for smaller vehicles. However, for purposes of the NPRM and this final rule, NHTSA 

closely re-examined the subclasses used for the MY 2011 final rule and found that the 

methodology and subclasses used then, which had been developed in response to 

comments arguing insufficient differentiation, remain appropriate for the MY 2012-2

107 The NAS classes included subcompact cars, compact cars, midsize cars, large cars, small SUVs, midsize 

SUVs, large SUVs, small pickups, large pickups, and minivans. 
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ity of size, 

weight, powertrains, consumer use, etc. However, each group contained some vehicles 

that orts or high-perform different technologies and cost and 

effe ates may be a TSA employed a 

perf ss within eac e the accuracy of technology 

appl rmine which specific cars would be assigned to the performance 

subc TSA graphed (in t ratio for each 

veh mp lass plot is shown below in Figure 

V-1 bpopulation was th ine an 

appropriate transition point betw e” and “non-performance” models 

with

Figure V-13. Power/Weight R lass 

evaluate and confirm that they represented a fairly reasonable homogene

 were sp ance models. Since

ctiveness estim ppropriate for these type vehicles, NH

ormance subcla

ication. To dete

h car subclass to maximiz

lasses, NH ascending rank order) the power-to-weigh

icle in a subclass. An exa le of the Compact subc

3. The su en manually reviewed by NHTSA staff to determ

een “performanc

in each class. 

atio for Compact Subc

Compact Subclass - P/W Ratio in Ascending Order

P

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

ower (HP) / Curb Wght. (Lbs)

Compact

Transition Area

Normal Perf. High Perf.

A total of eight classes (including performance subclasses) were identified for the 

car segment: Subcompact, Subcompact Performance, Compact, Compact Performance

Midsize, Midsize Performance, Large and

, 

 Large Performance. In total, the number of 

ars that were ultimately assigned to a performance subclass was less than 10 percent. 

Table V-6 ss. 

c

 provides examples of the types of vehicles assigned to each car subcla
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Table V-6 Passenger Car Subclasses Example (MY 2008) Vehicles 

Class Example vehicles 

Subcompact Chevy Aveo, Hyundai Accent 

Subcompact 

Performance 

Mazda MX-5, BMW Z4 

Compact Chevy Cobalt, Nissan Sentra and Altima 

Compact Performance Audi S4, Mazda RX8 

Midsize Chevy Impala, , Toyota Camry, Honda Accord, 

Hyundai Azera 

Midsize Performance Chevy Corvette, Ford Mustang (V8), Nissan G37 

Coupe 

Large Audi A8, Cadillac CTS and DTS 

Large Performance Bentley Arnage, Daimler CL600 

For light trucks, as in the MY 2011 final rule, NHTSA found less of a distinction 

in the anticipated vehicle fleet during the model years covered by the rulemaking 

between SUVs and pickup trucks than appeared to exist in earlier rulemakings. We 

anticipate fewer ladder-frame and more unibody pickups, and that many pickups wil

share common powertrains with SUVs. Thus, SUVs and pickups are grouped in the same

subclasses. Additionally, it made sense to carry forward NHTSA’s decision from the 

MY 2011 final rule to employ a separate minivan class, because minivans (e.g., th

Honda Odyssey) are more car-like and differ significantly in terms of structural and other 

engineering characteristics as compared to other vans (e.g., Ford’s E-Series—also known

as Econoline—vans) intended for more passengers and/or heavier cargo and which are 

more truck-like. 

Thus, the remaining vehicles (other vans, pickups, and SUVs) were then 

segregated into three footprint ranges and assigned a class of Small Truck/SUV, Midsize 

Truck/SUV, and Large Truck/SUV based on their footprints. 

l 

e 

NHTSA staff then 

manually reviewed each population for inconsistent vehicles based on engine cylinder 

count, weight (curb and/or gross), or intended usage, since these are important 

considerations for technology application, and reassigned vehicles to classes as 

appropriate. This system produced four truck segment subclasses—minivans and small, 

medium, and large SUVs/Pickups/Vans. Table V-7 provides examples of the types of 

vehicles assigned to each truck subclass. 

Table V-7. Light Truck Subclasses Example (MY 2008) Vehicles 

Class Example vehicles 

Minivans Dodge Caravan, Toyota Sienna 

Small 

SUV/Pickup/Van 

Ford Escape & Ranger, Nissan Rogue 

Midsize Chevy Colorado, Jeep Wrangler, Toyota Tacoma 

SUV/Pickup/Van 

Large Chevy Silverado, Ford E-Series, T

SUV/Pickup/Van 

oyota Sequoia 
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e 

rulema

e 

the 

A’s 

l 

r 

M, in 

 the 

etermine its components and what they cost. 

icle 

technologies, upon further joint review and for purposes of the MY 2012-2016 standards, 

the agencies decided that some of the costing information in that report was no longer 

accurate due to downward trends in commodity prices since the publication of that report. 

ents 

nt 

 

As mentioned above, NHTSA employed this method for assigning vehicle 

subclasses for this final rule after reviewing the process used in the MY 2011 final rul

and concluding that it continued to be a reasonable approach for purposes of this 

king. NHTSA believes that this method substantially improves the overall 

accuracy of the results as compared to systems employed previously, due to the close 

manual review by NHTSA staff to ensure proper assignments, the use of performanc

subclasses in the car segment, and the condensing of subclasses in the truck segment, all

of which further refine the system without overly complicating the CAFE modeling 

process. Nevertheless, NHTSA invites comments on the method of assigning vehicles to 

subclasses for the purposes of technology application in the CAFE model, and on 

issue of technology-application subclasses generally. 

5. How did NHTSA develop technology cost and effectiveness 

estimates for this final rule? 

Building on NHTSA’s estimates developed for the MY 2011 final rule and EP

Advanced Notice of Proposed Rulemaking, which relied on the 2008 Staff Technica

Report,108 the agencies took a fresh look at technology cost and effectiveness values fo

purposes of the joint final rule under the National Program. For costs, the agencies 

reconsidered both the direct or “piece” costs and indirect costs of individual components 

of technologies. For the direct costs, the agencies followed a bill of materials (BOM) 

approach employed by NHTSA in NHTSA’s MY 2011 final rule based on 

recommendation from Ricardo, Inc. Ricardo was hired by NHTSA, as discussed 

previously, to aid in the analysis of public comments on its proposed standards for MYs 

2011-2015 because of its expertise in the area of fuel economy technologies A BO

a general sense, is a list of components that make up a system—in this case, an item of

fuel economy-improving technology. The BOM approach is similar in concept to the 

approach used in tear down studies In order to determine what a system costs, one of

first steps is to d

NHTSA and EPA estimated these components and their costs based on a number 

of sources for cost-related information. The objective was to use those sources of 

information considered to be most credible for projecting the costs of individual veh

technologies. For example, while NHTSA and Ricardo engineers had relied considerably

in the MY 2011 final rule on the 2008 Martec Report for costing contents of some 

The agencies reviewed, revalidated or updated cost estimates for individual compon

based on new information. Thus while NHTSA and EPA found that much of the cost 

information used in NHTSA’s MY 2011 final rule and EPA’s staff report was consiste

to a great extent, the agencies, in reconsidering information from many sources,109

 teport, the 2004 study done by NESCCAF, the California Air Resources Board (CARB) 

 (EEA) for the Department of Energy, a study done by Martec for the Alliance of 

108 EPA Staff Technical Report: Cost and Effectiveness Estimates of Technologies Used to Reduce Ligh

Duty Vehicle Carbon Dioxide Emissions. EPA420-R-08-008, March 2008. 

109 The 2002 NAS R

Initial Statement of Reasons in support of their carbon rulemaking a 2006 study done by Energy and 

Environmental Analysis
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sels, SGDI, Valve Train Lift Technologies, 6 speed automatic 

transm

e 

 for additional engine 

and tra

e 

 

revised component costs of several major technologies (turbocharging downsizing, mild

and strong hybrids, die

ission and dual clutch transmission). These are discussed at length below. 

For some technologies such as turbocharging/downsizing, SGDI, 6 speed 

automatic transmission and dual clutch transmission, the agencies relied, to the extent 

possible, on the tear down data available and scaling methodologies used in EPA’s 

ongoing study with FEV Inc., an independent engine and powertrain systems research, 

design and development company. This study consists of complete system tear-down to 

evaluate technologies down to the nuts and bolts to arrive at very detailed estimates of th

costs associated with manufacturing them.110 For the NPRM, the agencies used a 

completed analysis to estimate costs of turbocharging with downsizing for I4 engines 

only. The NPRM stated that tear-down cost estimates from FEV

nsmission technologies became available shortly before the release of the NPRM,

but not in time to be incorporated into the agencies’ cost analysis of the proposed 

standards. These preliminary results were made available for review and the agencies 

stated they would consider this information for use in the final rule analysis.111 The 

NPRM also stated that a detailed report would be submitted to the docket on these 

additional technologies during the public comment period for this rule. That deadline

was not met but all additional technologies for which cost study tear downs have been 

completed from this study with FEV (studies have now been completed on turbocharging 

and downsizing for V6 and V8 engines, stoichiometric gasoline direct injection, 6/7/8-

speed automatic transmission and dual clutch transmission technologies) have been 

considered for the final rule and details are contained in two reports placed in the 

docket.112 113 EPA and NHTSA reviewed all of the above information in order to 

develop the best estimates of availability, cost and effectiveness of these fuelsaving/CO2-reducing technologies. The confidential information provided by 

manufacturer under their product plan submissions to the agencies or discussed in 

meetings between the agencies and the manufacturers and suppliers served largely as a 

check on publicly-available data. 

For the other technologies, because tear down studies were not yet available, th

agencies decided to pursue the (BOM) approach considering all sources of information. 

The agencies worked together intensively during the summer of 2009 to determine 

component costs for each of the technologies and build up the costs accordingly. Where 

estimates differ between sources, we have used engineering judgment to arrive at what 

 Automobile Man acturers and the 2008 Martec Report which updated that study, and vehicle fuel 

economy arch 2009 

ty Technology Cost Analysis Pilot 

Study,” Contract No. EP-C-07-069, Work Assignment 1-3, September 3, 2009, Docket EPA-HQ-OAR2009-0472-0149. 

uf

 certification data and confidential data submitted by manufacturers in response to the M

request for product plans. 

110 “Draft Report – Light-Duty Technology Cost Analysis Pilot Study,” U.S. Environmental Protection 

Agency, Contract No. EP-C-07-069, Work Assignment 1-3, September 3, 2009 

111 Memorandum from Don Kopinski, U.S. EPA, Docket No. EPA-HQ-OAR-2009-0472-0217, dated 

September 11, 2009. 

112 U.S. Environmental Protection Agency, “Draft Report – Light-Du

113 Insert docket info for the FEV final report on additional case studies beyond the I4 to I4 (should be 

available in mid-Feb). 
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we beli at 

fferent for 

th 

o reexamined the estimates from NHTSA’s MY 2011 CAFE final rule and EPA’s 

ANPRM

2 

re to 

ns and other vehicle attributes such as performance, 

refinem

s 

icant 

ir 

n 

each m

eve to be the best cost estimate available today, and explained the basis for th

exercise of judgment. 

Once costs were determined, they were adjusted to ensure that they were all 

expressed in 2007 dollars using a ratio of GDP values for the associated calendar 

years,114 and indirect costs were accounted for using the new approach developed by 

EPA for this rulemaking and explained in the joint TSD, rather than using the traditional 

Retail Price Equivalent (RPE) multiplier of 1.5. This report can be found in the docket 

for this notice. NHTSA and EPA also considered how costs should be adjusted by 

modifying or scaling content assumptions to account for differences across the range of 

vehicle sizes and functional requirements, and adjusted the associated material cost 

impacts to account for the revised content, although these adjustments were di

each agency due to the different vehicle subclasses used in their respective models. 

Regarding estimates for technology effectiveness, NHTSA in coordination wi

EPA als

 and Staff Technical Report, which largely mirrored NHTSA’s NPRM estimates 

in the 2008 proposed rule. The agencies also reconsidered other sources such as the 200

NAS Report, the 2004 NESCCAF report and recent CAFE compliance data. Using the 

BOM framework utilized in MY 2011 CAFE final rule, NHTSA and EPA engineers 

reviewed effectiveness information from the multiple sources for each technology. 

Together, they compared the multiple estimates and assessed their validity, taking ca

ensure that common BOM definitio

ent, and drivability were taken into account. However, because the agencies’ 

respective models employ different numbers of vehicle subclasses and use different 

technology decision trees to arrive at the standards, direct comparison of technologie

was somewhat more complicated. To address this and to assure an apples-to-apple 

comparison, NHTSA and EPA developed mapping techniques, devising technology

packages and corresponding incremental technology estimates. This approach helped 

compare incremental and packaged estimates and derive results that are consistent and 

could be translated into the respective models of the agencies. In general, most 

effectiveness estimates used in both the MY 2011 CAFE final rule and the 2008 EPA 

staff report were determined to be accurate and were carried forward without signif

change into this rulemaking. When NHTSA and EPA’s estimates for effectiveness 

diverged slightly due differences in how agencies apply technologies to vehicles in the

respective models, the agencies will report the ranges for the effectiveness values used i

odel, as well as the reasons the range is reasonable. 

6. Learning curves 

In the MY 2011 CAFE final rule and its related 2008 proposal, NHTSA 

accounted for the cost reductions manufacturers realized through experiential learning

achieved through applying technologies. NHTSA continues to account for these cost 

reductions in this final rule through the use of two mutually exclusive learning types, 

“volume-based” and “time-based,” as discussed below. 

 

114 NHTSA examined the use of the CPI multiplier instead of GDP for adjusting these dollar values, but 

found the difference to be exceedingly small – only $0.14 over $100. 
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using 

, 

e 

e 2008 NPRM, NHTSA applied 

a learn e 

 (thus 

as 

rring 

es. 

 the 

he MY 2011 final rule. 

Comm n 

me 

olumes that were on the extended, 

flatter p

ns if 

fic, 

creases as the current time- and volume-based learning curves 

appear 

 be 

st 

le 

In the 2008 NPRM, working in conjunction with the EPA, NHTSA applied 

learning factors to technology costs for the first time. The factors were developed 

the three parameters of learning threshold, learning rate, and the initial technology cost

and were based on the “experience curve” concept which describes reductions in 

production costs as a function of accumulated production volume. The typical curv

shows a relatively steep initial decline in cost which flattens out to a gentle downwardly

sloping line as the volume increase to large values. In th

ing rate discount of 20 percent for each successive doubling of production volum

(on a per manufacturer basis), and a learning threshold of 25,000 units was assumed

a technology was viewed as being fully learned out at 100,000 units). The factor was 

only applied to certain technologies that were considered emerging or newly 

implemented on the basis that significant cost improvements would be achieved 

economies of scale were realized (i.e., the technologies were on the steep part of the 

curve). 

In the MY 2011 final rule, NHTSA continued to use this learning factor, refe

to it as volume-based learning since the cost reductions were determined by production 

volume increases, and again only applied it to low volume, emerging technologi

However, and in response to comments, NHTSA revised its assumptions on learning 

threshold, basing them instead on an industry-wide production basis, and increasing

threshold to 300,000 units annually (and thus a technology is considered to be fully 

learned out at 1.2M annual units). 

However commenters to the 2008 NPRM also described another type of learning

factor which NHTSA, working in conjunction with its contractor Ricardo, Inc who 

assisted in finalizing the rule, adopted and implemented in t

enters described a relatively small negotiated cost decrease that occurred on a

annual basis through contractual agreements with first tier component and systems 

suppliers. These agreements were generally only applicable to readily available, high 

volume technologies that were commonly in use by multiple OEMs. Based on the sa

experience curve principal, however at production v

art of the curve (and thus the types of volumes that more accurately represent an 

annual industry-wide production volume), NHTSA adopted this type learning and 

referred to it as time-based learning. An annual cost reduction of 3 percent in the second

and each subsequent year, which was consistent with estimates from commenters and

supported by work Ricardo conducted for NHTSA, was used in the 2011 final rule. 

NHTSA received comments from ICCT and Ferrari related to learning curves. 

ICCT stated the agencies could improve the accuracy of the learning curve assumptio

they used a more dynamic or continuous learning curve that is more technology-speci

rather than using step de

to do. ICCT also commented on the appropriate application of volume- versus 

time-based learning, and stated further that worldwide production volumes should

taken into account when developing learning curves. Ferrari commented that is more 

difficult for small-volume manufacturers to negotiate cost decreases from things like co

learning effects with their suppliers, implying that learning effects may not be applicab

equally for all manufacturers. 

NHTSA agrees that a continuous curve, if implemented correctly, could 

potentially improve the accuracy of modeling cost-learning effects. To implement a 
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el 

 of this 

sis, however, 

NHTSA

hat 

ard to ICCT’s comments on the appropriate application of volumeersus time-based learning, however, it seems as though ICCT is referencing a study that 

defines volume- and time-based learning in a different manner than the current 

definitions used by the agencies. The agencies use “volume-based” learning for nonmature technologies that have the potential for significant cost reductions through 

learning, while “time-based” learning is used for mature technologies that have already 

had significant cost reductions and only have the potential for smaller cost reductions. 

For “time-based” learning, the agencies chose to emulate the small year-over-year cost 

reductions manufacturers realize through defined cost reductions, approximately 3 

percent per year, negotiated into contracts with suppliers. 

And finally, in response to Ferrari’s comment, NHTSA recognizes that cost 

negotiations can be different for different manufacturers, but believes that on balance, 

cost learning at the supplier level will generally impact costs to all purchasers. Thus, if 

cost reductions are realized for a particular technology, all entities that purchase the 

technology will benefit from these cost reductions. 

In developing this final rule, NHTSA, taking into account comments received, has 

reviewed both types of learning factors, and the thresholds (300,000) and cost reduction 

rates (20 percent for volume, 3 percent for time-based) they rely on, as implemented in 

the MY 2011 final rule and the NPRM, and has concluded that both learning factors 

continue to be accurate and appropriate. NHTSA therefore continues to implement both 

time- and volume-based learning in the analyses that supports this final rule. Noting that 

only one type of learning can be applied to any single technology, if any learning is 

applied at all, NHTSA reviewed each technology to determine which if any learning 

factor was appropriate. 

Working under the principal that volume-based learning is applicable to lower 

volume, higher complexity, emerging technologies while time-based learning is 

appropriate for high volume, established and readily available technologies, NHTSA 

determined the learning factors shown in Table V-8 below. These factors, which were 

used in this analysis, closely resemble the settings used in the 2011 final rule with the 

exception of PSHEV which has been revised from time-based to volume-based learning. 

Note that no learning is applied to technologies which are potentially affected by 

commodity costs (LUB, ROLL) or that have loosely-defined BOMs (EFR, LDB) in the 

continuous curve, however, NHTSA would need to develop a learning curve cost mod

to be integrated into the agency’s existing model for CAFE analysis. Due to time 

constraints the agencies were not able to investigate fully the use of a continuous costlearning effects curve for each technology, but we will investigate the applicability

approach for future rulemakings. For purposes of the final rule analy

 believes that while more detailed cost learning approaches may eventually be

possible, the approach taken for this final rule is valid. 

Additionally, while the agencies agree that worldwide production volumes can 

impact learning curves, the agencies do not forecast worldwide vehicle production 

volumes in addition to the already complex task of forecasting the U.S. market. T

said, the agencies do consider current and projected worldwide technology proliferation 

when determining the maturity of a particular technology used to determine the 

appropriateness of applying time- or volume-based learning, which helps to account for 

the effect of globalized production. 

With reg

v
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lumebased learning has been applied, NHTSA has taken great care to ensure that the initial 

costs (before learning is applied) properly reflect low volume, unlearned cost estimates 

(i.e., any high volume cost estimates used in the analysis have been appropriately 

“reverse learned” so as not to underestimate the final learned costs). 

Regarding these initial volume-based learning costs, ICCT commented that it 

would be helpful to clarify the assumed production volumes to better interpret the costs 

of technologies, which are eligible for “volume-based” learning. The agencies have not 

defined the specific cumulative production volume for technologies that are eligible for 

volume-based learning. When developing the costs for these technologies it was 

assumed that cumulative production volumes have not exceeded 300,000 but the agencies 

did not try to specify the exact production volume. Due to the uncertainty of projected 

production volumes the agencies did not believe it advantageous to define costs based on 

a finer level detail and believe the costs developed are the most appropriate for this 

rulemaking. 

this analysis, as was also the case in the MY 2011 final rule analysis. Where vo
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Table V-8 Application of learning-related cost reductions for technologies 
DE

155

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Model Learning Learning 

ate

Speed

3%

3%

Mode Hybrid 2MHEV VOLUME 20%

AERO TIME 3%

Technology Abbreviation Type R

Low Friction Lubricants LUB

Engine Friction Reduction EFR

VVT - Coupled Cam Phasing (CCP) on SOHC CCPS TIME 3%

Discrete Variable Valve Lift (DVVL) on SOHC DVVLS TIME 3%

Cylinder Deactivation on SOHC DEACS TIME 3%

VVT - Intake Cam Phasing (ICP) ICP TIME 3%

VVT – Dual Cam Phasing (DCP) DCP TIME 3%

Discrete Variable Valve Lift (DVVL) on DOHC DVVLD TIME 3%

Continuously Variable Valve Lift (CVVL) CVVL TIME 3%

Cylinder Deactivation on DOHC DEADD TIME 3%

Cylinder Deactivation on OHV DEACO TIME 3%

VVT - Coupled Cam Phasing (CCP) on OHV CCPO TIME 3%

Discrete Variable Valve Lift (DVVL) on OHV DVVLO TIME 3%

Conversion to DOHC with DCP CDOHC TIME 3%

Stoichiometric Gasoline Direct Injection (GDI) SGDI TIME 3%

Combustion Restart CBRST TIME 3%

Turbocharging and Downsizing TRBDS TIME 3%

Exhaust Gas Recirculation (EGR) Boost EGRB TIME 3%

Conversion to Diesel following CBRST DSLC TIME 3%

Conversion to Diesel following TRBDS DSLT TIME 3%

 Manual/Improved Internals 6MAN TIME 3%

Improved Auto. Trans. Controls/Externals IATC TIME 

Continuously Variable Transmission CVT TIME 3%

6/7/8-Speed Auto. Trans with Improved Internals NAUTO TIME 

Dual Clutch or Automated Manual Transmission DCTAM TIME 3%

Electric Power Steering EPS TIME 3%

Improved Accessories IACC TIME 3%

12V Micro-Hybrid MHEV TIME 3%

Belt Integrated Starter Generator BISG VOLUME 20%

Crank Integrated Starter Generator CISG VOLUME 20%

Power Split Hybrid PSHEV VOLUME 20%

Plug-in Hybrid PHEV VOLUME 20%

Mass Reduction 1 (1.5%) MS1

Mass Reduction 2 (3.5% – 8.5%) MS2

Low Rolling Resistance Tires ROLL

Low Drag Brakes LDB

Secondary Axle Disconnect 4WD SAX TIME 3%

Aero Drag Reduction
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e 

5

 

, 

on 

reased fuel consumption reduction). An example of a positive synergy 

might b r 

hicle 

e 

ping 

ere pumping losses are less significant, leaving less opportunity for 

the com

lumped 

s 

s with an 

e 

f 

c. However, 

regardl

7. Technology synergies

When two or more technologies are added to a particular vehicle model to 

improve its fuel efficiency, the resultant fuel consumption reduction may sometimes b

higher or lower than the product of the individual effectiveness values for those items.11

This may occur because one or more technologies applied to the same vehicle partially 

address the same source (or sources) of engine, drivetrain or vehicle losses. Alternately

this effect may be seen when one technology shifts the engine operating points, and 

therefore increases or reduces the fuel consumption reduction achieved by another 

technology or set of technologies. The difference between the observed fuel consumpti

reduction associated with a set of technologies and the product of the individual 

effectiveness values in that set is referred to as a “synergy.” Synergies may be positive 

(increased fuel consumption reduction compared to the product of the individual effects) 

or negative (dec

e a vehicle technology that reduces road loads at highway speeds (e.g., lowe

aerodynamic drag or low rolling resistance tires), that could effectively extend the ve

operating range over which cylinder deactivation may be employed, thus allowing a 

greater fuel consumption reduction than anticipated or predicted by analysis. An exampl

of a negative synergy might be a variable valvetrain technology, which reduces pum

losses by altering the profile of the engine speed/load map, and a six-speed automatic 

transmission, which shifts the engine operating points to a portion of the engine 

speed/load map wh

bined technologies to decrease fuel consumption. As the complexity of the 

technology combinations is increased, and the number of interacting technologies grows

accordingly, it becomes increasingly important to account for these synergies. 

NHTSA determined synergistic impacts for this rulemaking using EPA’s “

parameter” analysis tool, which EPA described at length in its March 2008 Staff 

Technical Report.116 The lumped parameter tool is a spreadsheet model that represent

energy consumption in terms of average performance over the fuel economy test 

procedure, rather than explicitly analyzing specific drive cycles. The tool begin

apportionment of fuel consumption across several loss mechanisms and accounts for th

average extent to which different technologies affect these loss mechanisms using 

estimates of engine, drivetrain and vehicle characteristics that are averaged over the EPA

fuel economy drive cycle. Results of this analysis were generally consistent with those o

full-scale vehicle simulation modeling performed in 2007 by Ricardo, In

ess of a generally consistent set of results for the vehicle class and set of 

technologies studied, the lumped parameter tool is not a full vehicle simulation and 

 

115 More specifically, the resultant is calculated as the products of the differences between the numeric 

alue one (i.e., 1.0) and the technology-specific levels of effectiveness in reducing fuel consumption 

(expressed as a numeric value also, i.e., 10% = 0.10). For example, not accounting for interactions, if 

technologies A and B are estimated to reduce fuel consumption by 10% (i.e., 0.1) and 20% (i.e., 0.2) 

respectively, the “product of the individual effectiveness values” would be (1 – 0.1) times (1 – 0.2), or 0.9 

times 0.8, which equals 0.72, corresponding to a combined effectiveness of (1 - .72 = .28) or 28% rather 

ghtoxide Emissions; EPA420-R-08-008, March 2008.

v

than the 30% obtained by adding 10% to 20%. The “synergy factors” discussed in this section further 

adjust these multiplicatively combined effectiveness values. 

116 EPA Staff Technical Report: Cost and Effectiveness Estimates of Technologies Used to Reduce Li

duty Vehicle Carbon Di
157

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

cannot replicat

Because NHTSA applies technologies individually in its modeling analysis, 

NHTSA incorporates synergistic effects between pairings of individual technologies. 

The use of discrete technology pair incremental synergies is similar to that in DOE’s 

National Energy Modeling System (NEMS).117 Inputs to the Volpe model incorporate 

NEMS-identified pairs, as well as additional pairs from the set of technologies considered 

in the Volpe model. For this final rule, as was the case in the 2011 final rule, NHTSA 

used the lumped parameter tool to evaluate accurate synergy values. During the 2011 

final rule analysis, and with the assistance of Ricardo, NHTSA modified the lumped 

parameter tool by updating the list of technologies and their associated effectiveness 

values, and expanding the list of synergy pairings based on further consideration of the 

technologies for which a competition for losses would be expected, for the purposes of 

evaluating appropriate synergy values. Table V-9 below presents the types of losses that 

were analyzed. 

NHTSA notes that synergies that occur within a particular decision tree are 

already accounted for within the incremental effectiveness values assigned for each 

technology, and therefore additional synergy pairs for these technologies are not required. 

For example, all engine technologies take into account the synergies that occur with the 

preceding/existing engine technologies, and all transmission technologies take into 

account synergies of preceding transmission technologies, etc. These synergy factors are 

accounted for in the fuel consumption improvement estimates in the input files used by 

the Volpe model. 

For applying incremental synergy factors in separate path technologies, i.e., 

between two or more decision trees, the Volpe model uses an input table (see Tables V10 a-d) which lists technology pairings and incremental synergy factors associated with 

those pairings (most of which are between engine technologies and transmission/ 

electrification/hybrid technologies). When a technology is applied to a vehicle by the 

Volpe model, all instances of that technology in the incremental synergy table which 

match technologies already applied to the vehicle (either pre-existing or previously 

applied by the Volpe model) are summed and applied to the fuel consumption 

improvement factor of the technology being applied. Synergies for the strong hybrid 

technology fuel consumption reductions are included in the incremental value for the 

specific hybrid technology since the model applies technologies in the order of the most 

effectiveness for least cost and also applies all available electrification and transmission 

technologies before applying strong hybrid technologies. 

NHTSA received only one comment regarding synergies, from MEMA, who 

commented that NHTSA’s Volpe model adequately addressed synergistic effects. 

Having received no information to the contrary, NHTSA finalized the synergy approach 

and values for the final rule. 

 

e the physics of such a simulation. 

117 U.S. partment of Energy, Energy Information Administration, Transportation Sector Module of the 

ationa ergy Modeling System: Model Documentation 2007, May 2007, Washington, DC, DOE/EIAM070(2007), at 29-30. Available at http://tonto.eia.doe.gov/ftproot/modeldoc/m070(2007).pdf (last 

accessed Jul. 6, 2009). 

De

N l En
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Table V alysis 

 

VEHICLE TRANS ENGINE ENGINE ENGINE ENGINE

Tractive Drivetrain Mechanical Pumping Accessory Indicated

Effort Losses Friction Losses Losses Efficiency

ENGINE

Low Friction Lubricants +

Engine Friction Reduction +

VVT - Coupled Cam Phasing (CCP) on SOHC -+ +

Discrete Variable Valve Lift (DVVL) on SOHC - +

Cylinder Deactivation on SOHC + +

VVT - Intake Cam Phasing (ICP) -+ +

VVT - Dual Cam Phasing (DCP) -+ +

Discrete Variable Valve Lift (DVVL) on DOHC - +

Continuously Variable Valve Lift (CVVL) - +

Cylinder Deactivation on DOHC + +

Cylinder Deactivation on OHV + +

VVT - Coupled Cam Phasing (CCP) on OHV -+ +

Discrete Variable Valve Lift (DVVL) on OHV - +

Conversion to DOHC with DCP -+ +

Stoichiometric Gasoline Direct Injection (GDI) +

Combustion Restart + ++

Turbocharging and Downsizing - +

Exhaust Gas Recirculation (EGR) Boos

-9 Loss Factors Considered in Synergy An

t +

Conversion to Diesel + +

TRANSMISSION (MANUAL)

6-Speed Manual/Improved Internals + +

TRANSMISSION (AUTOMATIC)

Improved Auto. Trans. Controls/Externals + +

Continuously Variable Transmission - +

6/7/8-Speed Auto. Trans with Impr. Internals + +

Dual Clutch/Automated Manual Transmission +

ELECTRIFICATION/ACCESSORY

Electric Power Steering +

Improved Accessories +

12V Micro-Hybrid + ++

Belt Integrated Starter Generator + ++

Crank Integrated Starter Generator + ++

(STRONG) HYBRID

Power Split Hybrid + + ++

2-Mode Hybrid + + ++

Plug-in Hybrid + + ++

VEHICLE 

Mass Reduction 1 (1.5%) +

Mass Reduction 2 (3.5% - 8.5%) +

Low Rolling Resistance Tires +

Low Drag Brakes +

Secondary Axle Disconnect - 4WD +

Aero Drag Reduction +

+ Technology has a positive effect on fuel consumption

- Technology has a negative effect on fuel consumption

Lumped Parameter Synergy Analysis
DE

159

Tec

DV

DV

DV

DV

DV

DV

DE

DE

DE

DE

DE

DE

IC

IC

IC

IC

IC

IC

DC

DC

DC

DC

DC

DC

DV

DV

DV

DV

DV

DV

DE

DE

DE

DE

DE

DE

CVV

CVV

CVV

CVV

CVV

CVV

DE

DE

DE

DE

DE

DE

Synergies Fuel Consumption Improvement Synergy values by Vehicle Subclass

Table V-10a Synergy pairings and values 

LIBERATIVE DOCUMENT – DO NOT RELEASE 

hnology A Technology B Subcompact 

PC

Subcompact 

Perf. PC Compact PC Compact Perf. PC Midsize PC Midsize Perf. PC

CCPS 6MAN -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

CCPS IATC -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

CCPS CVT -0.8% -0.8% -0.8% -0.8% -0.8% -0.8%

CCPS NAUTO -0.4% -0.4% -0.4% -0.4% -0.4% -0.4%

CCPS MHEV -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

CCPS BISG -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

VLS 6MAN -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

VLS IATC -0.5% -0.5% -0.5% -0.5% -0.5% -0.5%

VLS CVT -1.4% -1.4% -1.4% -1.4% -1.4% -1.4%

VLS NAUTO -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

VLS MHEV -0.8% -0.8% -0.8% -0.8% -0.8% -0.8%

VLS BISG -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

ACS 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

ACS IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

ACS CVT -1.7% -1.7% -1.7% -1.7% -1.7% -1.7%

ACS NAUTO -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

ACS MHEV -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

ACS BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

P 6MAN -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

P IATC -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

P CVT -0.8% -0.8% -0.8% -0.8% -0.8% -0.8%

P NAUTO -0.4% -0.4% -0.4% -0.4% -0.4% -0.4%

P MHEV -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

P BISG -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

P 6MAN -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

P IATC -0.4% -0.4% -0.4% -0.4% -0.4% -0.4%

P CVT -1.3% -1.3% -1.3% -1.3% -1.3% -1.3%

P NAUTO -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

P MHEV -0.8% -0.8% -0.8% -0.8% -0.8% -0.8%

P BISG -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

VLD 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

VLD IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

VLD CVT -1.8% -1.8% -1.8% -1.8% -1.8% -1.8%

VLD NAUTO -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

VLD MHEV -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

VLD BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

ACD 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

ACD IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

ACD CVT -1.8% -1.8% -1.8% -1.8% -1.8% -1.8%

ACD NAUTO -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

ACD MHEV -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

ACD BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

L 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

L IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

L CVT -1.8% -1.8% -1.8% -1.8% -1.8% -1.8%

L NAUTO -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

L MHEV -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

L BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

ACO 6MAN -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

ACO IATC -0.5% -0.5% -0.5% -0.5% -0.5% -0.5%

ACO CVT -1.4% -1.4% -1.4% -1.4% -1.4% -1.4%

ACO NAUTO -0.8% -0.8% -0.8% -0.8% -0.8% -0.8%

ACO MHEV -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

ACO BISG -1.2% -1.2% -1.2% -1.2% -1.2% -1.2%

Positive values are positive synergies, negative values are dissynergies.
DE

160

Tec

CCP

CCP

CCP

CCP

CCP

CCP

CB

CB

CB

CB

CB

CB

CB

TR

TR

TR

TR

TR

TR

DS

DS

DS

DS

DS

DS

DS

DS

DS

DS

DS

DS

CCP

IC

DCP

CCP

CB

TR

DS

DS

Fuel Consumption Improvement Synergy values by Vehicle Subclass

Table V-10b Synergy pairings and values 

LIBERATIVE DOCUMENT – DO NOT RELEASE 

hnology A Technology B Subcompact 

PC

Subcompact 

Perf. PC Compact PC Compact Perf. PC Midsize PC Midsize Perf. PC

O 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

O IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

O CVT -1.7% -1.7% -1.7% -1.7% -1.7% -1.7%

O NAUTO -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

O MHEV -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

O BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DVVLO 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

DVVLO IATC -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

DVVLO CVT -2.0% -2.0% -2.0% -2.0% -2.0% -2.0%

DVVLO NAUTO -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DVVLO MHEV -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

DVVLO BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CDOHC 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

CDOHC IATC -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

CDOHC CVT -2.0% -2.0% -2.0% -2.0% -2.0% -2.0%

CDOHC NAUTO -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CDOHC MHEV -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

CDOHC BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

RST 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

RST IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

RST CVT -1.8% -1.8% -1.8% -1.8% -1.8% -1.8%

RST NAUTO -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

RST BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

RST EPS -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

RST IACC -0.4% -0.4% -0.4% -0.4% -0.4% -0.4%

BDS 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

BDS IATC -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

BDS CVT -2.4% -2.4% -2.4% -2.4% -2.4% -2.4%

BDS NAUTO -1.3% -1.3% -1.3% -1.3% -1.3% -1.3%

BDS MHEV -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

BDS BISG -1.3% -1.3% -1.3% -1.3% -1.3% -1.3%

LC 6MAN -0.3% -0.3% -0.3% -0.3% -0.3% -0.3%

LC IATC 2.5% 2.5% 2.5% 2.5% 2.5% 2.5%

LC CVT -2.9% -2.9% -2.9% -2.9% -2.9% -2.9%

LC NAUTO -1.7% -1.7% -1.7% -1.7% -1.7% -1.7%

LC MHEV -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

LC BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

LT 6MAN -0.3% -0.3% -0.3% -0.3% -0.3% -0.3%

LT IATC 2.5% 2.5% 2.5% 2.5% 2.5% 2.5%

LT CVT -2.9% -2.9% -2.9% -2.9% -2.9% -2.9%

LT NAUTO -1.7% -1.7% -1.7% -1.7% -1.7% -1.7%

LT MHEV -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

LT BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

S CISG -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

DVVLS CISG -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

DEACS CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

P CISG -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

CISG -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

DVVLD CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DEACD CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CVVL CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DEACO CISG -1.2% -1.2% -1.2% -1.2% -1.2% -1.2%

O CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DVVLO CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CDOHC CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

RST CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

BDS CISG -1.3% -1.3% -1.3% -1.3% -1.3% -1.3%

LC CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

LT CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

Synergies Positive values are positive synergies, negative values are dissynergies.
DE

161

Tec

CCP

CCP

CCP

CCP

CCP

CCP

DEA

DEA

DEA

DEA

DEA

DEA

IC

IC

IC

IC

IC

IC

DCP

DCP

DCP

DCP

DCP

DCP

DEA

DEA

DEA

DEA

DEA

DEA

CVV

CVV

CVV

CVV

CVV

CVV

DEA

DEA

DEA

DEA

DEA

DEA

Fuel Consumption Improvement Synergy values by Vehicle Subclass

Table V-10c Synergy pairings and values 

LIBERATIVE DOCUMENT – DO NOT RELEASE 

hnology A Technology B Large PC Large Perf. 

PC Minivan LT Small LT Midsize LT Large LT

S 6MAN -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

S IATC -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

S CVT -0.8% -0.8% -0.8% -0.8% -0.8% -0.8%

S NAUTO -0.4% -0.4% -0.4% -0.4% -0.4% -0.4%

S MHEV -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

S BISG -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

DVVLS 6MAN -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

DVVLS IATC -0.5% -0.5% -0.5% -0.5% -0.5% -0.5%

DVVLS CVT -1.4% -1.4% -1.4% -1.4% -1.4% -1.4%

DVVLS NAUTO -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

DVVLS MHEV -0.8% -0.8% -0.8% -0.8% -0.8% -0.8%

DVVLS BISG -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

CS 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

CS IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

CS CVT -1.7% -1.7% -1.7% -1.7% -1.7% -1.7%

CS NAUTO -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

CS MHEV -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

CS BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

P 6MAN -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

P IATC -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

P CVT -0.8% -0.8% -0.8% -0.8% -0.8% -0.8%

P NAUTO -0.4% -0.4% -0.4% -0.4% -0.4% -0.4%

P MHEV -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

P BISG -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

6MAN -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

IATC -0.4% -0.4% -0.4% -0.4% -0.4% -0.4%

CVT -1.3% -1.3% -1.3% -1.3% -1.3% -1.3%

NAUTO -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

MHEV -0.8% -0.8% -0.8% -0.8% -0.8% -0.8%

BISG -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

DVVLD 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

DVVLD IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

DVVLD CVT -1.8% -1.8% -1.8% -1.8% -1.8% -1.8%

DVVLD NAUTO -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

DVVLD MHEV -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

DVVLD BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CD 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

CD IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

CD CVT -1.8% -1.8% -1.8% -1.8% -1.8% -1.8%

CD NAUTO -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

CD MHEV -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

CD BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

L 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

L IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

L CVT -1.8% -1.8% -1.8% -1.8% -1.8% -1.8%

L NAUTO -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

L MHEV -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

L BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CO 6MAN -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

CO IATC -0.5% -0.5% -0.5% -0.5% -0.5% -0.5%

CO CVT -1.4% -1.4% -1.4% -1.4% -1.4% -1.4%

CO NAUTO -0.8% -0.8% -0.8% -0.8% -0.8% -0.8%

CO MHEV -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

CO BISG -1.2% -1.2% -1.2% -1.2% -1.2% -1.2%

Synergies Positive values are positive synergies, negative values are dissynergies.
DELIBE

162

and values 

DS

DE

Fuel Consumption Improvement Synergy values by Vehicle Subclass

Table V-10d Synergy pairings 

RATIVE DOCUMENT – DO NOT RELEASE 

-1.1% -1.1% -1.1% -1.1%

1%

1%

ACO CISG -1.2% -1.2% -1.2% -1.2% -1.2% -1.2%

1%

-1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

Synergies s.

Technology A Technology B Large PC Large Perf. 

PC Minivan LT Small LT Midsize LT Large LT

CCPO 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

CCPO IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

CCPO CVT -1.7% -1.7% -1.7% -1.7% -1.7% -1.7%

CCPO NAUTO -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

CCPO MHEV -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

CCPO BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DVVLO 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

DVVLO IATC -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

DVVLO CVT -2.0% -2.0% -2.0% -2.0% -2.0% -2.0%

DVVLO NAUTO -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DVVLO MHEV -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

DVVLO BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CDOHC 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

CDOHC IATC -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

CDOHC CVT -2.0% -2.0% -2.0% -2.0% -2.0% -2.0%

CDOHC NAUTO -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CDOHC MHEV -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

CDOHC BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CBRST 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

CBRST IATC -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

CBRST CVT -1.8% -1.8% -1.8% -1.8% -1.8% -1.8%

CBRST NAUTO -1.1% -1.1%

CBR

Positive values are positive synergies, negative values are dissynergie

ST BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CBRST EPS -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

CBRST IACC -0.4% -0.4% -0.4% -0.4% -0.4% -0.4%

TRBDS 6MAN -0.2% -0.2% -0.2% -0.2% -0.2% -0.2%

TRBDS IATC -0.7% -0.7% -0.7% -0.7% -0.7% -0.7%

TRBDS CVT -2.4% -2.4% -2.4% -2.4% -2.4% -2.4%

TRBDS NAUTO -1.3% -1.3% -1.3% -1.3% -1.3% -1.3%

TRBDS MHEV -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

TRBDS BISG -1.3% -1.3% -1.3% -1.3% -1.3% -1.3%

DSLC 6MAN -0.3% -0.3% -0.3% -0.3% -0.3% -0.3%

DSLC IATC 2.5% 2.5% 2.5% 2.5% 2.5% 2.5%

DSLC CVT -2.9% -2.9% -2.9% -2.9% -2.9% -2.9%

DSLC NAUTO -1.7% -1.7% -1.7% -1.7% -1.7% -1.7%

DSLC MHEV -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DSLC BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DSLT 6MAN -0.3% -0.3% -0.3% -0.3% -0.3% -0.3%

DSLT IATC 2.5% 2.5% 2.5% 2.5% 2.5% 2.5%

DSLT CVT -2.9% -2.9% -2.9% -2.9% -2.9% -2.9%

DSLT NAUTO -1.7% -1.7% -1.7% -1.7% -1.7% -1.7%

LT MHEV -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DSLT BISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CCPS CISG -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

DVVLS CISG -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

DEACS CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

ICP CISG -0.9% -0.9% -0.9% -0.9% -0.9% -0.9%

DCP CISG -1.0% -1.0% -1.0% -1.0% -1.0% -1.0%

DVVLD CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DEACD CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.

CVVL CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.

CCPO CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

DVVLO CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CDOHC CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

CBRST CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%

TRBDS CISG -1.3% -1.3% -1.3% -1.3% -1.3% -1.3%

DSLC CISG -1.1% -1.1% -1.1% -1.1% -1.1% -1.

DSLT CISG
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o terms that describe when technology changes to 

vehicle

a 

n or at least two years before a scheduled redesign. For the majority of 

technol

vel 

 rates at 

 model 

year, an ign 

Even within the context of the phase-in caps discussed below, NHTSA considers 

ery year. In reality, 

 

9. Refresh and redesign schedule

Because of the complexities of the automobile manufacturing process, 

manufacturers are generally only able to add new technologies to vehicles on a specific 

schedule; just because a technology exists in the marketplace, does not mean that it is 

immediately available for application on all of a manufacturer’s vehicles. In the 

automobile industry there are tw

s occur: redesign and refresh (i.e., freshening). Vehicle redesign usually refers to

significant changes to a vehicle’s appearance, shape, dimensions, and powertrain. 

Redesign is traditionally associated with the introduction of “new” vehicles into the 

market, often characterized as the “next generation” of a vehicle, or a new platform. 

Vehicle refresh usually refers to less extensive vehicle modifications, such as minor 

changes to a vehicle’s appearance, a moderate upgrade to a powertrain system, or small 

changes to the vehicle’s feature or safety equipment content. Refresh is traditionally 

associated with mid-cycle cosmetic changes to a vehicle, within its current generation, to 

make it appear “fresh.” Vehicle refresh generally occurs no earlier than two years after 

vehicle redesig

ogies discussed today, manufacturers will only be able to apply them at a refresh 

or redesign, because their application would be significant enough to involve some le

of engineering, testing, and calibration work.118

Thus, in addition to developing methods that address limitations on the

which new technologies can feasibly penetrate manufacturers’ fleets, which NHTSA 

refers to as phase-in caps, the agency has also developed methods to address the feasible

scheduling of changes to specific vehicle models. In the Volpe model, which the agency 

used to support this final rule, these scheduling-related methods were first applied in 

2003, in response to concerns that an early version of the model would sometimes add 

and then subsequently remove some technologies.119 By 2006, these methods were 

integrated into a new version of the model, one which explicitly “carried forward” 

technologies added to one vehicle model to succeeding vehicle models in the next

d which timed the application of many technologies to coincide with the redes

or freshening of any given vehicle model.120 In the 2008 NPRM and subsequent final 

rule for the MY 2011 CAFE standards, NHTSA tied the application of the majority of

technologies to a vehicle’s refresh/redesign cycle. 

these model-by-model scheduling constraints necessary in order to produce an analysis 

that reasonably accounts for the need for a period of stability following the redesign of 

any given vehicle model. If engineering, tooling, testing, and other redesign-related 

resources were unlimited, every vehicle model could be redesigned ev

however, every vehicle redesign consumes resources simply to address the redesign, and 

thus cost expenditures occur. Phase-in caps, which are applied at the level of a 

 

e 

118 For example, applying material substitution through weight reduction, or even something as simple as 

low rolling-resistance tires, to a vehicle will likely require some level of validation and testing to ensure 

that the vehicle may continue to be certified as compliant with NHTSA’s Federal Motor Vehicle Safety 

Standards (FMVSS). Weight reduction might affect a vehicle’s crashworthiness; low rolling-resistanc

tires might change vehicle’s braking characteristics or how it performs in crash avoidance tests. 

119 68 FR 16874 (Apr. 7, 2003). 120 71 FR 17582 (Apr. 6, 2006). 
164

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ar basis, 

in the analysis that supported 

the MY

ted 

sis 

e 

in how 

TSA 

t with 

cycle for the majority of light trucks. A fuller discussion of NHTSA’s justification and 

125

ould 

manufacturer’s entire fleet, do not, by themselves, constrain the scheduling of changes to

any particular vehicle model. Conversely, scheduling constraints to address vehicle 

freshening and redesign do not necessarily yield realistic overall penetration rates for a 

particular technology type (e.g., for strong hybrids), while phase-in caps do. Thus, the 

two constraints work together in the model to ensure that the timing and application rate 

for various fuel-saving technologies is feasible for manufacturers on a year-by-ye

as required by EPCA/EISA.121

For purposes of the analysis supporting this final rule, NHTSA has employed, as

inputs to the Volpe model, a redesign cycle of 5 years for all manufacturers, with a 

refresh cycle of 2-3 years. This is the schedule employed 

 2011 final rule, and is consistent with the most recent manufacturer product plans 

received in response to NHTSA’s March 2009 and September 2009 requests for upda

plans. However, the application of the refresh/redesign cycle in the modeling analy

has changed in this final rule from the MY 2011 final rule due to the characteristics of th

new joint approach for establishing the baseline fleet. The paragraphs below expla

NHTSA developed the refresh/redesign cycle, and how its application has changed for 

this final rule. 

In the MY 2011 final rule NHTSA developed the redesign and refresh schedules 

based on a combination of manufacturers’ confidential product plans and NHTSA’s 

engineering judgment. In most instances, NHTSA reviewed manufacturers’ planned 

redesign and refresh schedules as stated in their confidential submissions and 

incorporated them into the market data file, as done in past rulemakings. If companies 

did not provide product plan data, NHTSA used publicly available data to estimate the 

redesign and refresh schedules for the vehicles produced by these companies.122 Unless a 

manufacturer submitted plans for a more rapid redesign and refresh schedule, NH

assumed that passenger cars would normally be redesigned every 5 years, consisten

industry trends over the last 10-15 years.123 NHTSA also projected a 5-year redesign 

124

rationale for the 5-year redesign cycle can be found in the MY 2011 final rule.

Some manufacturers commented in the last round of CAFE rulemaking, even 

before the economic crisis had reached today’s levels that their vehicle redesign cycles 

take at least five years for cars and 6 years and longer for trucks because they rely on 

those later years to recover investments and earn a profit. They argued that they w

 

121 49 U.S.C. § 32902(a) requires that NHTSA set CAFE standards at the maximum feasible level for each 

fleet, for each model year. 

122 Sources included but were not limited to manufacturers’ web sites, industry trade publications (e.

Automotive News), and commercial data sources (e.g., Ward’s Automotive, etc.). 123 Exceptions were made for high performance vehicles and other vehicles that traditionally had longer 

than average design cycles due to their unique design characteristics and their evolutionary, as opposed to

revolutionary product development practices (e.g., the Porsche 911 has remained the same basic vehicle for

many years). 

124 NHTSA recognized in the MY 2011 CAFE rulemaking that light trucks are currently redesigned every

5 to 7 years, with some vehicles (like full-size vans) having longer redesign periods. However, in the most 

competitive SUV and crossover vehicle segments, the redesign cycle currently averages slightly above 5 

years. NHTSA concluded that the light truck redesign schedule will be shortened in the future due to 

competitive market forces. Thus, for almost all light trucks scheduled for a redesign in the early portions o

the rulemaking period, NHTSA projected a 5-year redesign cycle. 

125 74 FR 14265 (Mar. 30, 2009) 

g., 

f 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

n 

uing to 

market will 

5 

ri 

e 

g analysis. NHTSA has 

conside

nt 

not be able to sustain their businesses if forced by CAFE standards to a shorter redesig

cycle. Expecting that those concerns may be magnified in the current economic climate, 

NHTSA recognizes that some manufacturers are severely stressed and may be delaying

or hoping to delay planned vehicle redesigns in order to conserve financial resources. 

However, manufacturers must balance this concern against their interest in contin

provide vehicles that the public wishes to purchase, which may be redesigned or 

refreshed vehicles. Consistent with its forecast of the overall size of the light vehicle 

 from MY 2011 on, the agency tentatively expects that the industry’s status

improve and that manufacturers will typically redesign both car and truck models every 

years in order to be competitive in the market. 

NHTSA received comments from the Center for Biological Diversity (CBD) and

Ferrari regarding redesign cycles. CBD stated that manufacturers do not necessarily 

adhere to the agencies’ assumed five-year redesign cycle, and may add significant 

technologies by redesigning vehicles at more frequent intervals, albeit at higher costs. 

CBD argued that NHTSA should analyze the costs and benefits of manufacturers 

choosing to redesign vehicles more frequently than a 5-year average. Conversely, Ferra

agreed with the agencies that major technology changes are introduced at vehicle 

redesigns, rather than at vehicle freshenings, stating further that as compared to full-lin

manufacturers, small-volume manufacturers in fact may have 7 to 8-year redesign cycles. 

In response, NHTSA recognizes that not all manufacturers follow a precise five-year 

redesign cycle for every vehicle they produce,126 but continues to believe that the fiveyear redesign cycle assumption is a reasonable estimate of how often manufacturers can 

make major technological changes for purposes of its modelin 127

red attempting to quantify the increased cost impacts of setting standards that rise 

in stringency so rapidly that manufacturers are forced to apply “usual redesign” 

technologies at non-redesign intervals, but such an analysis would be exceedingly 

complex and is beyond the scope of this rulemaking given the timeframe and the curre

 

126 In prior NHTSA rulemakings, the agency was able to account for shorter redesign cycles on some 

models (e.g., some sedans), and longer redesign cycles on others (e.g., cargo vans), but has standardized t

redesign cycle in this analysis using the transparent baseline. 

127 In the MY 2011 final rule, NHTSA noted that the CAR report submitted by the Alliance, prepared by 

the Center for Automotive Research and EDF, stat

concepti

he 

ed that “For a given vehicle line, the time from 

o 

ated 

pdf). 

ferent 

s), 

o

John Murphy, Research Analyst, Bank of America/Merrill Lynch research paper, July 15, 2009. 

on to first production may span two and one-half to five years,” but that “The time from first 

production (“Job#1”) to the last vehicle off the line (“Balance Out”) may span from four to five years t

eight to ten years or more, depending on the dynamics of the market segment,” The CAR report then st

that “At the point of final production of the current vehicle line, a new model with the same badge and 

similar characteristics may be ready to take its place, continuing the cycle, or the old model may be 

dropped in favor of a different product.” See NHTSA-2008-0090-0170.1, Attachment 16, at 8 (393 of 

NHTSA explained that this description, which states that a vehicle model will be redesigned or dropped 

after 4-10 years, was consistent with other characterizations of the redesign and freshening process, and 

supported the 5-year redesign and 2-3 year refresh cycle assumptions used in the MY 2011 final rule. See 

id., at 9 (394 of pdf). Given that the situation faced by the auto industry today is not so wholly different 

from that in March 2009, when the MY 2011 final rule was published, and given that the commenters did 

not present information to suggest that these assumptions are unreasonable (but rather simply that dif

manufacturers may redesign their vehicles more or less frequently, as the range of cycles above indicate

NHTSA believes that the assumptions remain reasonable for purposes of this final rule analysis. See als

“Car Wars 2009-2012, The U.S. automotive product pipeline”, John Murphy, Research Analyst, Merrill 

Lynch research paper, May 14, 2008 and “Car Wars 2010-2013, The U.S. automotive product pipeline”, 
166

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ve 

feasibil

s. 

 in the modeling analysis 

for this

t 

lable, 

ly available. The 

advanta

cts 

ar 

prior to or 

ced 

M’s Chevy Volt and Chrysler’s 

anticip

t 

e 

baselin Y 2008 vehicles, using publicly-available data and its own engineering 

judgment, which required finding the date of most recent redesign for each vehicle. 

Next, the agency applied 5-year redesign cycles to obtain new redesign dates for each 

vehicle, starting with the date of most recent redesign and working forward. Thus, a 

vehicle that was determined to have been last redesigned in MY 2008 would be projected 

to be redesigned again in MY 2013. The assumption here is that future vehicles that are 

replacements for vehicles currently in the market will tend to follow the same cycles as 

their predecessors, so it is appropriate to reflect the MY 2013 date in the market data file. 

NHTSA tried to ensure that most if not all vehicles had a redesign scheduled in the 

analysis during the rulemaking time frame, consistent with the industry’s response in 

confidential product plans to the estimated levels of stringency announced in the joint 

NOI preceding the NPRM and this final rule . Manufacturers appear to be redesigning 

condition of the industry. NHTSA emphatically disagrees that the redesign cycle is a 

barrier to increasing penetration of technologies as CBD suggests, but we also belie

that standards so stringent that they would require manufacturers to abandon redesign 

cycles entirely would be beyond the realm of economic practicability and technological 

ity, particularly in this rulemaking timeframe given lead time and capital 

constraints. Manufacturers can and will accomplish much improvement in fuel economy 

and GHG reductions while applying technology consistent with their redesign schedule

NHTSA has concluded that the 5-year redesign is still appropriate and is 

retaining the 5-year redesign with 2-3 year refresh cycle assumptions for the final rule, 

noting that, for the most part, the cycle times are supported by manufacturer’s 

confidential responses to NHTSA’s March and September 2009 product plan requests. 

With regard to how the refresh/redesign cycle was implemented

 final rule given the new joint baseline approach, as discussed in Section I of the 

Preamble.], NHTSA previously used confidential manufacturer product plan information 

and the refresh and redesign dates contained therein for formulating the market data inpu

file used by the Volpe model, or relied on other sources of information where that data 

did not exist. For purposes of this final rule, in contrast, the agencies developed a 

baseline vehicle fleet data file from MY 2008 CAFE certification data. As discussed 

above, the certification data represents an historical data source that is publicly avai

which allows NHTSA to make the baseline market data file itself public

ge to this approach is the greater transparency provided with a publicly-available 

baseline market data file as compared to one based on confidential manufacturer data, as 

also discussed at greater length in Section I of the Preamble. 

However, using adjusted historical data rather than estimated future data impa

how NHTSA is able to model the refresh/redesign cycle in its analysis of year-by-ye

maximum feasible CAFE standards. For example, some vehicles that exist in the MY 

2008 certification-data based fleet manufacturers have indicated (either publicly or in 

their product plans) they will be discontinued (i.e., no longer produced or sold) 

within the rulemaking period. Conversely, some vehicle models will be first introdu

to the market during the rulemaking time frame, like G

ated new models based on Fiat platforms. Since these vehicles were not sold 

(unavailable) in 2008, they do not exist in the MY 2008 certification data, and thus do no

exist in the final rule’s market data file. 

To address this problem, NHTSA first determined redesign schedules for th

e M
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

the vas ajority of today’s vehicles, or replacing them with new models, between now 

and the end of ilar 

fashion, based on those of the baseline fleet and using the 2 to 3 year cycle, also working 

to ensure that all derwent a refresh h ram

akings, NHTSA used manufacturers’ confidential information 

e arket file for each unique vehicle model, including new models 

( troduced. For the new appro h, which does 

n ation to produce the base e vehicle fleet 

a ic vehicle that manufactur rrently intend

t time frame, the ag cy had to develop a new method 

f and subtraction of ve cles during that time frame from 

t 2008 ba ne fleet. 

the v cle fleet as follows. While each 

e file, by definition, is a vehicle th was sold in MY

2 certification data), for purposes of projecting that vehicle 

m e fleet in the rulemaking period, each ent so be used

t arket segm t (e.g., subcomp t, SUV/CUV, 

p eet. The particular vehicle model shown in the

f n the future vehicle fleet, and in fact som odels are 

e Y 2016, as discussed above

HTSA believes that it is reasona e to expect that anufacturer 

w e, or some group of sim r vehicles, to compete in the same

m facturer will of the same vehicl model, a fully 

r rsion of that mo , or an entirely n w vehicle or 

g del or nameplate of a similar type. his is how 

N e GM Volt: altho es not app r in the baseline 

m as one of the e isting GM models of similar type 

a nce it becomes av able. NHTSA also used 

m this app nd t m fairly 

c et data fi

le on NHTSA’s website, ntains the refresh 

a veloped by NHTSA for this fi l rule. Table V-1 elow provides 

w chnologies are “anytime” tech ogies, “redesign only” 

t ign” technologies, for purposes of th inal rule. 

t m

MY 2016. Finally, the agency determined refresh dates in a sim

vehicles un cycle within t e rulemaking time f e. 

In previous rulem to 

stablish entries in the m

such as the GM Volt) when they were in ac

ot rely on confidential manufacturer inform

 of the specif

lin

nd which does not model all s ers cu

o produce during the rulemaking en

or accounting for the addition hi

he pool of vehicles that makes up the MY

NHTSA accounts for these changes in 

seli

ehi

ntry in the new baseline market data at

008 (based on the MY 2008 

odel forward into the futur ry can al

o represent a vehicle in that particular m en ac

ickup, etc.) of a manufacturer’s future fl

ile may or may not be sold i e m

xpected to be discontinued well before M . 

However, N bl the m

ill produce a similar vehicl ila

arket segment—whether the manu fer e 

edesigned but otherwise similar ve del e

roup of vehicles, sold as a new mo T

HTSA addresses the issue of th ugh it do ea

arket data file, it will be considered x

nd in the same market segment o ail

anufacturers’ product plans as a check on roach, and fou he

onsistent with the resulting baseline mark

arket data file, availab

le. 

The baseline m co

nd redesign dates de

hether particular te

na 1 b

nol

echnologies, or “refresh or redes is f
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

y Refresh and Redesign Application 

me 

Table V-11 Technolog

Technology Redesign only Redesign or Refresh Anyti

Low Friction Lubricants X 

Engine Friction Reduction X 

VVT - Coupled Cam Phasing (CCP) on SOHC X 

Discrete Variable Valve Lift (DVVL) on SOHC X 

Cylinder Deactivation on SOHC X 

VVT - Intake Cam Phasing (ICP) X 

VVT – Dual Cam Phasing (DCP) X 

Discrete Variable Valve Lift (DVVL) on DOHC X 

Continuously Variable Valve Lift (CVVL) X 

Cylinder Deactivation on DOHC X 

Cylinder Deactivation on OHV X 

VVT - Coupled Cam Phasing (CCP) on OHV X 

Discrete Variable Valve Lift (DVVL) on OHV X 

Conversion to DOHC with DCP X 

Stoichiometric Gasoline Direct Injection (GDI) X 

Combustion Restart X 

Turbocharging and Downsizing X 

Exhaust Gas Recirculation (EGR) Boost X 

Conversion to Diesel following CBRST X 

Conversion to Diesel following TRBDS X 

6-Speed Manual/Improved Internals X 

Improved Auto. Trans. Controls/Externals X 

Continuously Variable Transmission X 

6/7/8-Speed Auto. Trans with Improved Internals X 

Dual Clutch or Automated Manual Transmission X 

Electric Power Steering X 

Improved Accessories X 

12V Micro-Hybrid X 

Belt Integrated Starter Generator X 

Crank Integrated Starter Generator X 

Power Split Hybrid X 

2-Mode Hybrid X 

Plug-in Hybrid X 

Mass Reduction 1 (1.5%) X 

Mass Reduction 2 (3.5% – 8.5%) X 

Low Rolling Resistance Tires X 

Low Drag Brakes X 

Secondary Axle Disconnect 4WD X 

Aero Drag Reduction X 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

rate of t

rer 

nel and 

mited 

vailable resources during the rulemaking time frame, especially in years where 

many m

roposed 

to the 

he agency’s 

analysi

ps 

h 

s 

10. Phase-in caps

Besides the refresh/redesign cycles used in the Volpe model, which constrain the 

echnology application at the vehicle level so as to ensure a period of stability 

following any modeled technology applications, the other constraint on technology 

application employed in NHTSA’s analysis is “phase-in caps.” Unlike vehicle-level 

cycle settings, phase-in caps constrain technology application at the vehicle manufactu

level.128 They are intended to reflect a manufacturer’s overall resource capacity available 

for implementing new technologies (such as engineering and development person

financial resources) thereby ensuring that resource capacity is accounted for in the 

modeling process. At a high level, phase-in caps and refresh/redesign cycles work in 

conjunction with one another to avoid the modeling process out-pacing an OEM’s li

pool of a

odels may be scheduled for refresh or redesign. This helps to ensure 

technological feasibility and economic practicability in determining the stringency of the 

standards. 

NHTSA has been developing the concept of phase-in caps for purposes of the 

agency’s modeling analysis over the course of the last several CAFE rulemakings, as 

discussed in greater detail in the MY 2011 final rule.129 In 2002, when NHTSA p

MY 2005-2007 standards for light trucks using a predecessor modeling algorithm 

Volpe model, manufacturers commented extensively on the issue of lead time and the 

potential for the rapid and widespread application of new technologies in t

s. Specifically, GM’s comment pointed to the most significant manufacturer 

concern, the algorithm’s “application of technologies to all truck lines in a single model 

year.”130 In response, NHTSA modified the algorithm to moderate the rates at which 

technologies were estimated to penetrate manufacturers’ fleets in the MY 2005-2007 

CAFE standards. The modeling changes produced more realistic estimates of the 

technologies manufacturers could apply in response to new standards, and more realistic 

estimates of the costs of those standards. 

Explicit phase-in caps were included in the Volpe model analysis for the next 

rulemaking, establishing standards for MY 2008-2011 light trucks. These phase-in ca

constrained the rates at which each technology would be estimated to penetrate eac

manufacturer’s fleet in response to new CAFE standards. The agency’s final standard

for those model years used phase-in caps of up to 25 percent (corresponding to full 

penetration of the fleet within 4 years) for most technologies, and up to 10 percent (full

penetration of the fleet within 10 years) for more advanced technologies such as hybrid 

 

128 While phase-in caps are expressed as specific percentages of a manufacturer’s fleet to which a 

technology may be applied in a given model year, phase-in caps cannot always be applied as precise limits, 

and the Volpe model in fact allows “override” of a cap in certain circumstances. When only a small 

portion of a phase-in cap limit remains, or when the cap is set to a very low value, or when a manufacturer 

has a very limited product line, the cap might prevent the technology from being applied at all since any 

ceeded. Therefore, the Volpe model evaluates and enforces each 

y the application of the technology (as opposed to 

ich can result in the described overriding of the cap. 

) 

application would cause the cap to be ex

phase-in cap constraint after it has been exceeded b

evaluating it before application), wh

129 74 FR 14268–14271 (Mar. 30, 2009 130 68 FR 16874 (Apr. 7, 2003). 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

es “that 

er.”132

 as 

nditions and technology developments. The agency concluded that 

many t

of 

-in 

, b) 

nal 

 not consider the 

resourc

r of 

, 

phasized that the MY 

2011 p

r individual 

years 

le 

for some 

 

electric vehicles.131 The agency based these rates on consideration of comments and on 

the 2002 NAS Committee’s findings that “widespread penetration of even existing 

technologies will probably require 4 to 8 years” and that for emerging technologi

require additional research and development, this time lag can be considerably long

In its 2008 NPRM proposing new CAFE standards for passenger cars and light 

trucks sold during MYs 2011-2015, NHTSA considered manufacturers’ planned product 

offerings and estimates of technology availability, cost, and effectiveness, as well

broader market co

echnologies could be deployed more rapidly than it had estimated during the prior

rulemaking133 and increased some of the estimates as it determined appropriate. 

However, as in its earlier CAFE rulemakings, the agency continued to recognize that 

myriad constraints prohibit most technologies from being applied across an entire fleet 

vehicles within a single year, even if those technologies are readily available in the 

market. 

The comments NHTSA received in response to the 2008 proposal asserted three 

basic concerns with the agency’s adjustments to phase in caps; a) that the hybrid phase

caps were much lower than manufacturer announcements would otherwise suggest

that the phase-ins were too high in the early years of the rulemaking and did not reflect 

the very small (from a manufacturing perspective) amount of lead-time between the fi

rule and the standards taking effect, and/or were too low in the later years of the 

rulemaking given the increased lead-time, or c) that NHTSA did

es (either in terms of capital or engineering) required to implement the number 

(quantities) of technologies implied by the phase-in caps simultaneously. 

NHTSA responded to these comments in the final rule,134 noting that a numbe

factors potentially impact a manufacturer’s ability to implement new technologies

including commercial viability, infrastructure requirements, and resource and lead-time 

considerations.135 The agency explained that evaluating all the factors involved would

require an extraordinary effort and that the analysis would likely involve significant 

uncertainties that would raise questions about its accuracy and usefulness. Nevertheless, 

the agency concluded that its use of phase-in caps was still appropriate “to apply the 

agency’s best judgment of the extent to which such factors combine to constrain the rates 

at which technologies may feasibly be deployed.” NHTSA em

hase-in caps were based on assumptions for the full five year period of the 

proposal (2011-2015), and stated that it would reconsider the phase-in settings for all 

years beyond 2011 in future rulemaking analysis. Some phase-in caps fo

technologies were raised and some were lowered, and the Volpe model was revised to 

add the ability to define unique phase-in caps for each model year, allowing non-linear 

technology application rates throughout the rulemaking period (lower in the early 

and increased in later, or vice-versa) if required. 

Table V-12 below outlines the phase-in caps for the technologies used in this ru

by model year. As in the MY 2011 final rule, NHTSA combines phase-ins caps 

ar. 30, 2009) 

131 71 FR 17572, 17679 (Apr. 6, 2006). 132 Id. at. 17572. See also 2002 NAS Report, at 5. 133 73 FR 24387-88 (May 2, 2008). 134 74 FR 14268-69 (Mar 30, 2009) 135 74 FR 14268 (M
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 from 

o 

technol

ule, 

nd 

ke 

e 

tation 

A 

ent, for the most part, a significant departure from the vehicle 

archite e 2011 rule, 

 Volpe 

nce the 

e NPRM analysis (as 

compar

t 

groups of similar technologies, such as valve phasing technologies that are applicable to 

different forms of engine design (SOHC, DOHC, OHV), since they are very similar

an engineering and implementation standpoint. When the phase-in caps for tw

ogies are combined, the maximum total application of either or both to any 

manufacturers’ vehicle fleet is limited to the value of the cap.136 In contrast to the phasein caps used in the MY 2011 final rule, NHTSA has increased the phase-in caps for most 

of the technologies, except those for diesels and stronger hybrid technologies, as

discussed below. 

In developing phase-in cap values for purposes of the NPRM and this final r

NHTSA initially considered the fact that many of the technologies commonly applied by

the model, those placed near the top of the decision trees, such as low friction lubes, 

valve phasing, electric power steering, improved automatic transmission controls, a

others, have been commonly available to manufacturers for several years now. Many 

technologies, in fact, precede the 2002 NAS Report, which estimated that such 

technologies would take 4 to 8 years to penetrate the fleet. Since this final rule will ta

effect in MY 2012, nearly 10 years beyond the NAS report, and extends to MY 2016, 

NHTSA determined that higher phase-in caps were likely justified. Additionally, 

NHTSA considered the fact that manufacturers, as part of the agreements supporting th

National Program, appear to be anticipating higher technology application rates than 

those used in the MY 2011 final rule. This also supported higher phase-in caps of 

commonly applied technologies for purposes of this final rule. 

However, for a few of the more complex and intrusive (from an implemen

perspective) technologies, specifically dieselization and stronger hybridization, NHTS

has retained the more stringent phase-in levels used in the 2011 final rule since these 

technologies repres

ctures commonly utilized by most OEMs today. As was the case in th

these more stringent phase-in caps limit technology application, i.e., due to the

modeling process, to 3 percent per annum up to a maximum of 15 percent by the 2016 

model year.137 Additionally, for some technologies that are not available in certain 

model years, a phase-in cap of 0 percent is shown for those model years, such as the 

combustion restart technology that is not determined to be available until 2014; he

values of 0 percent for MYs 2012 and 2013 shown in Table V-12 below. 

NHTSA received comments from the Alliance and ICCT relating to phase-in 

caps. The Alliance commented that the higher phase-in caps in th

ed to the MY 2011 final rule) “ignore OEM engine architecture 

differences/limitations,” arguing that the agency must consider manufacturing investmen

and lead time implications when defining phase-in caps. The Alliance also commented 

that it seems the combining of technologies “isn’t being considered” due to most 

technologies be “phased in at 85%/100% rates by the mid-decade”. ICCT did not raise 

the issue of phase-in caps directly, but commented that the agencies had not provided 

information in the proposal documents explaining when each manufacturer can 

 

136 See 74 FR 14270 (Mar 30, 2009) for further discussion and examples. 137 A 15 percent maximum application rate should not be confused with the overall penetration of the 

technology, i.e., the amount of the technology applied by the modeling process plus that which existed in 

the baseline or was installed at the discretion of the manufacturer. Penetration rates typically exceed 

application rates. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

o spread 

develop

011 

 of 

ements supporting the National Program, appear to be anticipating higher 

technology application rates during the rulemaking timeframe. Additionally, the agencies 

did not receive any comments from manufacturers indicating a concern with the proposed 

application rates after reviewing the detailed manufacturer level model outputs. The 

agencies believe that as manufacturers focus their resources (i.e., engineering, capital 

investment, etc.) on fuel economy-improving technologies, many of which have been in 

production for many years, the application rates being modeled are appropriate for the 

timeframe being analyzed. Regarding the Alliance’s comments about the consideration of 

technology combinations, the 85%/100% phase-in caps do not dictate the level of applied 

technologies. As stated above, phase-in caps are one of the constraints, in combination 

with other constraints, used to limit technology applications, they are not used to 

prescribe technology application rates. The model applies different combinations of 

technologies at differing rates, however most technologies never approach the levels of 

the phase-in caps. 

In response to ICCT’s comments, the combination of phase-in caps, 

refresh/redesign cycles, engineering constraints, etc., are intended to simulate 

manufacturers’ technology application decisions, and ultimately define the technology 

application/implementation rates for each manufacturer. NHTSA notes that the PRIA 

and the FRIA do contain manufacturer-specific application/implementation rates for 

prominent technologies, and that manufacturer-specific technology application as 

employed in the agency’s analysis is available in full in the Volpe model outputs 

available on NHTSA’s website. The model outputs present the resultant application of 

technologies at the industry, manufacturer, and vehicle levels. 

Theoretically, significantly higher phase-in caps, such as those used in the NPRM 

and this final rule as compared to those used in the MY 2011 final rule, should result in 

higher levels of technology penetration in the modeling results. Reviewing the modeling 

output does not, however, indicate unreasonable levels of technology penetration as 

shown in Tables V-48 and V-49. NHTSA believes that this is due to the interaction of 

the various changes in methodology applied for the NPRM analysis and carried into this 

final rule--changes to phase-in caps are but one of a number of revisions to the Volpe 

model and its inputs that could potentially impact the rate at which technologies are 

applied in the NPRM and this final rule as compared to prior rulemakings. Other 

revisions that could impact application rates include the use of transparent CAFE 

certification data in baseline fleet formulation and the use of other data for projecting it 

implement the different technologies and how long it will take the technologies t

across the fleet. ICCT argued that this information was crucial to considering how 

quickly the stringency of the standards could be increased, and at what cost. 

In response to the Alliance comments, the phase-in cap constraint is, in fact, 

exactly intended to account for manufacturing investment and lead time implications, as

discussed above: phase-in caps are intended to reflect a manufacturer’s overall resource 

capacity available for implementing new technologies (such as engineering and 

ment personnel and financial resources), to help ensure that resource capacity is 

accounted for in the modeling process. Although the phase-in caps for the analysis 

supporting these standards are higher than the phase-in caps employed in the MY 2

final rule, as stated above, the agencies considered the fact that manufacturers, as part

the agre
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

rward,138 or the use of a multi-year planning programming technique to apply 

technology retroactively to earlier-MY vehicles, both of which may have a direct impact 

on the m ther 

areas that also could impact technology appl ation, such as in the refresh/redesign cycle 

settings, or the eff s used for chno

largely unchang Y 2011 final ru e cha toget ficul

t n caps should be expec cti he n del ces

wing the output files, N A be hat her

c tion rates produc the e mo bo

t propriate for th l rul ievi

s ing un istic o hiev e 

r

 

fo

odeling process. Conversely the model and inputs remain unchanged in o

ic

ectiveness estimate

ed from the M

 the te

e. The

logies, both of which remain 

l s ke it dif

ted to fun

nges

on in t

her ma

ew mo

t 

o predict how phase-i ing pro s. 

Thus, after revie HTS lieves t the hig phase-in 

aps, and the resulting technology applica ed by Volp del, at th 

he industry and manufacturer level, are ap

ithout requir

is fina e, ach ng a 

uitable level of stringency w real r unac able pen tration

ates. 

 138 The baseline fleet sets the starting point, from a te logy point of view, for where the model begins 

the technology application process, so changes have a irect impact on the net application of technology. 

chno

 d
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Tabl nt Rule 

 Final Rule Phase-In Caps by Model 

Year * 

e V-12 Phase-in Caps from 2011 Final Rule and Curre

Final 

Rule 

2012-2016

Techno

015 2016 

logy 

MY 2011 2012 2013 2014 2

Low Friction Lubricants 50% 100% 100% 100% 100% 100% 

Engine Friction Reduction 20% 85% 85% 85% 100% 100% 

VVT - Coupled Cam Phasing (CCP) on SOHC 15% 85% 85% 85% 100% 100% 

Discrete Variable Valve Lift (DVVL) on SOHC 15% 85% 85% 85% 100% 100% 

Cylinder Deactivation on SOHC 9% 85% 85% 85% 85% 85% 

VVT - Intake Cam Phasing (ICP) 15% 85% 85% 85% 100% 100% 

VVT – Dual Cam Phasing (DCP) 15% 85% 85% 85% 100% 100% 

Discrete Variable Valve Lift (DVVL) on DOHC 15% 85% 85% 85% 100% 100% 

Continuously Variable Valve Lift (CVVL) 15% 85% 85% 85% 100% 100% 

Cylinder Deactivation on DOHC 9% 85% 85% 85% 85% 85% 

Cylinder Deactivation on OHV 9% 85% 85% 85% 85% 85% 

VVT - Coupled Cam Phasing (CCP) on OHV 15% 85% 85% 85% 100% 100% 

Discrete Variable Valve Lift (DVVL) on OHV 15% 85% 85% 85% 100% 100% 

Conversion to DOHC with DCP 9% 85% 85% 85% 85% 85% 

Stoichiometric Gasoline Direct Injection (GDI) 3% 85% 85% 85% 85% 85% 

Combustion Restart 0% 0% 0% 85% 85% 85% 

Turbocharging and Downsizing 9% 85% 85% 85% 85% 85% 

Exhaust Gas Recirculation (EGR) Boost 0% 0% 85% 85% 85% 85% 

Conversion to Diesel following CBRST 3% 3% 6% 9% 12% 15% 

Conversion to Diesel following TRBDS 3% 3% 6% 9% 12% 15% 

6-Speed Manual/Improved Internals 33% 85% 85% 85% 100% 100% 

Improved Auto. Trans. Controls/Externals 33% 85% 85% 85% 100% 100% 

Continuously Variable Transmission 5% 85% 85% 85% 85% 85% 

6/7/8-Speed Auto. Trans with Improved Internals 50% 85% 100% 100% 100% 100% 

Dual Clutch or Automated Manual Transmission 20% 85% 100% 100% 100% 100% 

Electric Power Steering 10% 85% 85% 85% 100% 100% 

Improved Accessories 10% 85% 85% 85% 100% 100% 

12V Micro-Hybrid 3% 85% 85% 85% 85% 85% 

Belt mounted Integrated Starter Generator n/a 85% 85% 85% 85% 85% 

Crank mounted Integrated Starter Generator n/a 3% 6% 9% 12% 15% 

Power Split Hybrid 0% 3% 6% 9% 12% 15% 

2-Mode Hybrid 0% 3% 6% 9% 12% 15% 

Plug-in Hybrid 0% 3% 6% 9% 12% 15% 

Mass Reduction (1.50%) 5% 85% 85% 85% 85% 100% 

Mass Reduction (5% to 10% Cum) 5% 0% 0% 85% 85% 100% 

Low Rolling Resistance Tires 20% 85% 85% 85% 100% 100% 

Low Drag Brakes 20% 85% 85% 85% 100% 100% 

Secondary Axle Disconnect - Ladder Frame 17% 85% 85% 85% 100% 100% 

Aero Drag Reduction 17% 85% 85% 85% 100% 100% 

* - a phase-in cap of 0% is shown for the years the technology is unavailable 
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s 

ornia 

vehicle fuel economy certification data. Both agencies also reviewed the published 

technic nomy, 

such as ers published by the Society of Automotive Engineers and the American 

Society of M

manufacturers for product plans, and confidential 

information

and NHTSA a 

cross check 

lemaking. 

s a contracted study ongoing with FEV that consists of complete 

ystem tear-downs to evaluate technologies down to the nuts and bolts to arrive at very 

NHTSA and EPA believe the best way to derive technology cost estimates is to 

conduct real-world tear down stu sitio d s

ICCT an ed no comm tra tu to 

ns of vehicle stems th ploy the n chnolog

 or system new te ies. Ana with ex 

 

D. Specific technologies considered for application and NHTSA’

estimates of their incremental costs and effectiveness 

1. What data sources did NHTSA evaluate? 

NHTSA and EPA have done extensive research in identifying the most credible 

sources of information. These sources included: the 2002 NAS report on the effectiveness 

and impact of CAFE standards;139 the 2004 study done by NESCCAF;140 the Calif

Air Resources Board (CARB) Initial Statement of Reasons in support of their carbon 

rulemaking;141 a 2006 study done by Energy and Environmental Analysis (EEA) for the 

Department of Energy;142 a study done by the Martec Group for the Alliance of 

Automobile Manufacturers, and an update by the Martec Group to that study;143 and 

al literature which addressed the issue of CO2 emission control and fuel eco

pap

echanical Engineers. In addition, confidential data submitted by vehicle 

in response to NHTSA’s request 144

 shared by automotive industry component suppliers in meetings with EPA 

 staff held during the second half of the 2007 calendar year were used as 

of the public data mentioned above and not as a significant basis for this 

ru

EPA also ha

s

detailed estimates of the costs associated with manufacturing them.145 As a general 

matter, 

dies. This po

ents to the con

n is supporte

ry.146 These s

 by commenters

dies are based

uch as 

d we receiv a large

degree on tear dow s or vehicle sy at em ew te ies, 

and of similar vehicles s without the chnolog lysts pertise

 d Impact of Cor Econo FE) Standard ational Re 

ien

1

 “Staff eport: Initial Statement of Reasons for Proposed Rulemaking,” California Environmental 

Protectio gency, Air Resources Board, Regulations to Control Greenhouse Gas Emissions from Motor 

Vehicles

139 “Effectiveness an porate Average Fuel my (CA s,” N search

Council, National Academy of Sc

140

ces, 2002. 

 “Reducing Greenhouse Gas Emissions from Light-Duty Motor Vehicles,” Northeast States Center f

lean Air Future, September 2004. 

or a 

C

14 R

n A

, August 6, 2004. 142 “Technology to Improve the Fuel Economy of Light Duty Trucks to 2015,” Energy and Environmental

Analysis, Inc., May 2006. 

143 “Variable Costs of Fuel Economy Technologies,” prepared for The Alliance of Automobile 

Manufacturers, June 1, 2008; and, “Variable Costs of Fuel Economy Technologies,” prepared for The 

Alliance of Automobile Manufacturers, June 1, 2008, Amended December 10, 2008. 

144 74 FR 9185 (Mar. 3, 2009) 145 “Draft Report – Light-Duty Technology Cost Analysis Pilot Study,” U.S. Environmental Protection 

Agency, Contract No. EP-C-07-069, Work Assignment 1-3, September 3, 2009 

146 See comments from ICCT (EPA-HQ-OAR-2009-0472-7156), CARB (EPA-HQ-OAR-2009-0472-

7189), NESCAUM (EPA-HQ-OAR-2009-0472-7235) 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

dividual 

n studies 

y. 

, four technologies (downsizing and turbocharging, stoichiometric gasoline directocket. 

hese recently completed tear-downs include the following technologies: 

o GDI 

n 

in automotive design, materials, and manufacturing then compare the tear down 

components and evaluate the differences. Using databases for materials, labor, 

manufacturing overhead, and mark-up costs, the overall costs to manufacture in

parts are calculated and summed into final results. However, as such, tear dow

require a significant amount of time and are very costly. EPA has begun conducting tear 

down studies to assess the costs of 4-5 technologies under a contract with FEV Inc., an

independent engine and powertrain systems research, design and development compan

To date

injection, dual clutch transmission and 6-speed automatic transmission) have been 

evaluated. The tear down study has been peer-reviewed and the report for these tear

down studies and the peer-review report have been made public in the rulemaking d

The agencies have considered these studies and the comments received on them, as 

practicable and appropriate, in developing technology cost assumptions for this final rule. 

T

1. 3.0L V6 port fuel-injected (PFI) downsized and turbocharged to a 2.0L I4 

gasoline direct injection (GDI) 

2. 5.4L V8 PFI downsized and turbocharged to a 3.0L V6 twin-turb

3. 5-speed automatic transmission to 6-speed automatic transmission 

4. 6-speed automatic transmission to 6-speed wet dual-clutch transmission

A comparison between costs reported in the NPRM and the final rule can be found in 

Table V-13 below. 

Table V-13. A comparison of NPRM costs and the final rule for five updated technologies ($2007 i

2012). 

Technology Incremental To 

NPRM Direct 

Manufacturing 

Cost 

Final Rule Direct 

Manufacturing 

Cost 

Change

2.0L I4 Turbo GDI 3.0L V6 MPFI $248 $152 -$96 

3.0L V6 twin-turbo GDI 5.4L V8 MPFI $1,081 $964 -$117 

5-speed auto trans 4-speed auto trans $91 $91 $0 

6-speed auto trans 4-speed auto trans $153 $101 -$52 

6-speed auto trans 5-speed auto trans $62 * $9 -$53 

6-speed dual-clutch trans (wet) 6-speed auto trans $126 -$11 -$137 

* Calculated as the difference between the 4 to 6 speed trans ($153) and the 4 to 5 speed trans ($91). 

 

FEV tear down cost analysis studies were conducted based on the assumption that 

the analyzed technologies and the manufacturing for those technologies were both fully 

“mature,” in that designs and manufacturing processes have been reasonably optimized. 

The studies also assumed that manufacturing facilities have annual production levels of 

450,000 units. EPA and NHTSA recognize that in early implementation years, designs 

and manufacturing processes may not be optimized to that extent, and investment cost 

may ex ed those of fully matu ce re technologies. To account for higher cost in th

e

e earlier 

implem ntation years of the rulemaking period, NHTSA and EPA estimated MY 2012 

costs as the average of the FEV tear down study cost and the NPRM cost for technologies 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

for whi udies. Time-based learning is used to 

reflect st in later years. This approach is applied to downsizing and turbocharging for 

V6 and

on 

f 

 to the best 

vailable conclusion regarding technology costs and effectiveness estimates for the 

current rulemaking and resulted in excellent consistency between the agencies’ respective 

analyses for dev

tal benefits 

and cos

n, in which such interactions are 

analyze ehicle 

ailable for this rulemaking. The agencies look forward to considering the results 

ch there were completed FEV tear down st

co

 V8, stoichiometric gasoline direct-injection for V6 and V8, dual clutch 

transmission and 6-speed automatic transmission. In the NPRM, the costs for 

turbocharging, downsizing and SGDI for I4 engines were based on an FEV teardown cost 

study that was completed prior to release of the NPRM. For the final rule, these costs 

were carefully reviewed and updated to better account for early year implementati

costs. 

EPA and NHTSA reviewed all this information in order to develop the best estimates o

availability, cost and effectiveness of these fuel-saving/CO2-reducing technologies. 

NHTSA and EPA are confident that the thorough review conducted, led

a

eloping the CAFE and CO2 standards. 

The agencies would also like to note that per the Energy Independence and 

Security Act (EISA), the National Academies of Sciences is conducting an updated study 

to update chapter 3 of their 2002 NAS Report, which presents technology effectiveness 

estimates. The update will take a fresh look at that list of technologies and their 

associated cost and effectiveness values. Some of specific tasks that NAS will undertake 

in updating the technology chapter are to define and document specific methodologies 

and input parameters to account for the sequential application and incremen

ts of technologies, including the methods used to account for variations in vehicle 

characteristics (e.g., size, weight, engine characteristics). Some methodologies might 

involve simple mathematical relationships (e.g., cost per cylinder). Others might involve 

matrices (e.g., of effectiveness versus vehicle category or versus the presence of other 

technologies) or more complex structural representations (e.g., decision trees). In 

addition, NAS will identify and assess leading computer models for projecting vehicle 

fuel economy as a function of additional technology. These models would include both 

lumped-parameter (or Partial Discrete Approximation) type models, where interactions 

between technologies are represented using energy partitioning and/or scalar adjustment 

factors (aka “synergy” factors), and full vehicle simulatio

d using explicit drive cycle and engine cycle simulation, based on detailed v

engineering characteristics (e.g., including engine maps, transmission shift points, etc.). 

Finally, NAS will examine the effectiveness and impacts of vehicle weight and engine 

size/horsepower reductions which will be limited to advances in structural design and 

lightweight materials. 

The updated NAS report was expected to be available on September 30, 2009, but 

has not been completed and released to the public. The updated report is currently 

undergoing various levels of required review. It is anticipated that the final report will be 

published after the publication of this final rule, thus the results from this study thus are 

unav

from this study as part of the next round of rulemaking for CAFE standard. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

or 

em at 

the aut

se, 

tor 

anufacturing costs, recovers total revenue147. This 

multipl n is accurate only in the aggregate; it does not in reality apply to any specific 

technology. The RPE is a way to estimate indirect costs on the assumption that indirect 

costs are constant across all technologies and processes in a company. In the MY 2011 

CAFE final rule NHTSA utilized a 1.5 RPE multiplier. 

 

In fact, however, the indirect costs of new technologies vary, both with the 

complexity of the technology and with the time frame. For instance, a hybrid-electric 

engine is likely to involve greater research and development and marketing costs per 

dollar of direct costs than low-rolling-resistance tires; the research and development costs 

of any technology are likely to decrease over time. In recognition of this concern, EPA 

contracted with RTI International to provide a current estimate of the RPE multiplier and 

to examine whether the indirect costs of new technologies are likely to vary across 

technologies. The report “Automobile Industry Retail Price Equivalent and Indirect Cost 

Multipliers,” by Alex Rogozhin, Michael Gallaher, and Walter McManus,148 calculates 

 

The Indirect Cost Methodology (ICM) 

Indirect costs include production-related costs (research, development, and other 

engineering), business-related costs (corporate salaries, pensions and manufacturer 

profits), and retail-sales-related costs (dealer support, marketing and dealer profits). F

this analysis, direct cost estimates were first developed for each technology or syst

o manufacturer level, i.e., the price paid by the manufacturer to a Tier 1 

component supplier. To these costs, an indirect cost markup factor was then applied that

varied by the best estimate of the particular technology’s complexity. This section 

describes the approach to determining the indirect cost multipliers (ICM) used in this 

analysis and the specific multipliers used for each piece of technology. 

Concept behind and development of indirect cost multipliers 

If all desirable data were available, when a new technology is implemented, the 

costs of that technology would include the direct and indirect costs particular to that 

technology. For instance, some changes may involve new tooling, while others may not; 

some may affect the way the car is marketed, while others are of limited interest to 

consumers. In a world of full information, the indirect costs of a new technology would 

be calculated specifically for that technology. In practice, though, it is often difficult, if

not impossible, to identify the indirect costs specific to a new technology. 

The automotive industry, EPA, and NHTSA have commonly used retail price 

equivalent (RPE) multipliers to approximate the indirect costs associated with a new 

technology. The RPE is a ratio of total revenues to direct manufacturing costs. Becau

by definition, total revenues = direct costs + indirect costs + profit, the RPE is the fac

that, w multiplied by direct m hen

icatio

147 Note that unlike the RPE, the ICM does not include profits. 148 Rogozhin, Alex, Michael Gallaher, and Walter McManus, “Automobile Industry Retail Price Equivalent 

and Indirect Cost Multipliers,” EPA 420-R-09-003, February 2009, http://epa.gov/otaq/ldhwy/420r09003.pdf. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

the RPE multiplier as 1.46 i ndirect cost (IC) 

multipliers ry with the complexity frame. While any 

multiplier an appro tio ue ect co f a ol e IC 

multipliers in this report m aw the ass mption th the propo n of indirect 

costs t across al nolo and ta to acc some e variation in 

these lie velo n this rt are p ted ble V

The agencies received comments from The National Automobile Dealers 

Associ ati at all cost assoc with costs-of sales uding 

consumer financ be accounted f “deal ” e agen have 

included dealer cos f-sal sellin ts) in t indirect st mu er (ICM which 

makes up part of t lo sts—a e ent. e is no

compelling reason t clude those s in the aler pro elem f the I . As 

for the finance cos id nsu it is i tant to that a soc

persp h e ar ec g sts selve d do not de 

the f s. While those costs are incurred by consumers, they are merely transfer 

costs fr m the perspective of regulatory cost analysis. We have included financing costs 

l 

n 2007. The report then develops i

that va

 is only 

of technology and the time

xima

ove 

n of th

ay from

e tr indir

u

sts o

at

new tec

rtio

hn ogy, th

 is constan l tech gies ke in ount of th

 costs. The multip rs de ped i repo resen in Ta -1. 

ation (NADA) st ng th iated dealer , incl

e costs, should 

ts-o

or in

he

er profits

co

. Th

ltipli

cies 

es ( g cos )—

he final techno gy co s a uniqu elem Ther

o in

ts pa

cost

mers,

 “de

mpor

fit” 

 note

ent o

from

CM

by co ial 

ective, the costs of t

ina ce cost

e rul e the t hnolo y co them s an inclu

n

o

in our consumer welfare analysis since costs there are not social costs but rather persona

costs. 

The indirect cost multipliers used adjustment factors, developed by a team of EPA 

engineers with expertise in the auto industry, which accounted for the differences in 

complexity of the specific technologies under study. To examine the sensitivity of the 

results to different technologies of the same complexity, and to provide more detailed 

documentation of the development of the adjustment factors, EPA convened a second 

panel,149 with NHTSA’s input, to develop adjustment factors for three different 

technologies. This latter process allowed for estimates of the variation in adjustment 

factors, and thus in the variation of indirect cost multipliers. These results are also 

presented in Table V-14. 

 

 

149 “Memorandum: Documentation of the Development of Indirect Cost Multipliers for Thre

Technologies,” Gloria Helfand and Todd Sherwood, Office of Transportation and Air Quality, U.S. 

Environmental Protection Agency 

e Automotive 
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Table V-14. Indirect Cost Multipliers 

TECHNOLOGY COMPLEXITY 

STUDY Short Run Long Run 

Low Medium High Low Medium High 

RTI Report 1.05 1.20 1.45 1.02 1.05 1.26 

EPA Memo: Average 1.16 1.29 1.64 1.12 1.20 1.39 

Standard Deviation 0.14 0.15 0.21 0.14 0.13 0.15 

Median 1.12 1.26 1.66 1.06 1.20 1.40 

Max 1.43 1.53 2.15 1.42 1.45 1.69 

Min 1.00 1.02 1.37 1.00 1.01 1.12 

Multipliers Used in 

this Analysis 1.11 1.25 1.45 1.64 1.07 1.13 1.26 1.39 

The table shows minor differences in the multipliers for low- and medium-complexity 

technologies (roughly 0.1), but larger differences in the high-complexity technologies. 

The EPA and NHTSA engineers who reviewed the results believed that the differences 

reflected actual differences in the technologies under study. In particular, for low 

complexity, low-rolling-resistance tires (the application in the RTI Report) would involve 

lower indirect costs than aerodynamic improvements (the application in the EPA memo); 

and, for medium complexity, dual-clutch transmissions (the application in the RTI 

Report) should have a smaller multiplier than engine downsizing done in conjunction 

with turbocharging (the application in the EPA Memo). For these two cases, EPA and 

NHTSA considered these technologies to span the range of technologies assigned to 

those classes; the costs in this study, then, use the averages of the values of the two 

reports, as shown in the last line of Table V-1. For high complexity technologies, the 

agencies felt the technologies assigned to these categories—hybrid-electric vehicles in 

the RTI Report; plug-in hybrid electric vehicles in the EPA Memo—were sufficiently 

different that each deserved a different category. This is discussed in more detail in the 

next section which highlights the multipliers used for each specific technology.

Application of specific indirect cost multipliers to each technology

As noted in the previous section and in the NPRM a different ICM was applied to 

each technology’s direct cost to arrive at its compliance cost. These different ICMs were 

chosen based on the complexity of integrating the technology into the vehicle in the 

opinions of staff engineers at EPA and NHTSA, most of whom have several years of 

experience in the auto industry. As shown in Table V-1, ICMs were developed via two 

separate processes: that presented in the RTI report; and that presented in the EPA 

Memo. While all of the ICMs generated via these two processes were in general 

agreement, some differences did exist. In determining how to deal with these differences, 

EPA and NHTSA agreed that, for the low and medium complexity technologies, a simple 

average of the two values would be used. However, for the high complexity 

technologies, it was decided that two separate high-multipliers should be used. The 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

wer multiplier, deemed high, would be applied to those technologies of high 

complexity but with some level of use in the marketplace today. Such technologies 

would . The higher multiplier, deemed 

high+, would be applied to those technologies of high complexity but with no, or 

essen current flee hnolog h

. 

lo

be power-split and 2-mode hybrid electric vehicles

tially no, use in the t. Such tec ies would be plug-in ybrids and 

full electric vehicles
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able V-1 shows the complexity level for each technology considered in this 

analysi

T

s. 
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Table V-15 Complexity Levels of Technologies 

LOW COMPLEXITY MEDIUM 

COMPLEXITY HIGH COMPLEXTIY HIGH+ COMPLEXITY 

Low friction lubes (LUB) Combustion Restart 

(CBRST) 

Continuously variable 

valve lift (CVVL) 

Plug-in hybrid 

Engine friction reduction (EFR) Exhaust gas recirculation 

boost (EGRB) 

2-mode hybrid 

(2MHEV) 

Full electric vehicle 

Intake cam phasing (ICP) Belt integrated starter 

generator (BISG) 

Power-split hybrid 

(PSHEV) 

Coupled cam phasing (CCPO) and 

(CCPS) 

Turbocharge with Crankshaft integrated 

downsize (TRBDS) starter generator (CISG) 

Dual cam phasing (DCP) Conversion to diesel 

(DSLC) and (DSLT) 

 

Cylinder deactivation (DEACS), 

(DEACD), and (DEACO) 

Dual clutch transmission 

(DCTAM) 

 

Discrete variable valve lift (DVVLS), 

(DVVLO) and (DVVLD) 

Continually variable 

transmission (CVT) 

 

Stoichiometric gasoline direct 

injection (SGDI) 

12 volt micro hybrid 

(MHEV) 

 

Conversion to DOHC with DCP 

(CDOHC) 

6/7/8-speed

(NAUTO) 

 auto transmission 

Improved auto transmission (IATC) 

6-speed manual transmission (6MAN) 

Improved accessories (IACC) 

Electric power steering (EPS) 

Low rolling resistance tires (ROLL) 

Low drag brakes (LDB) 

Secondary axle disconnect 

(SAXU/SAXL)) 

 

Improved aerodynamics (AERO) 

Mass reduction (MS1) 1.5% 

Mass reduction (MS2) 3.5 - 8.5% 

ICCT commented that the integration aspect of a technology needs to be 

considered when defining technology complexity levels for purposes of ICM 

applications. While assigning ICM complexity levels to each technology used in the 

NPRM the agencies took into account the integration challenges with each technology. 

After considering the comments and evaluating the complexity levels of each technology 

relative to assigned complexity levels of other technologies the agencies still believe the 

complexity levels assigned in the NPRM to be valid. Thus for purposes of this final rule 

the complexity level assignments will be the same as those in the NPRM. For future 

rulemakings that agencies will re-evaluate the current list of technologies and emerging 

technologies to determine the appropriate technology complexity levels. 

The estimates of vehicle compliance costs cover the years of implementation of 

the PA’s analysis, compliance costs have also been 

stimated for the years following implementation to shed light on the long term – 2022 

and later – cost impacts of the rule. The year 2022 is used by EPA because the shortterm and long-term markup factors described above are applied in five year increments 

 program – 2012 through 2016. In E

e
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ith th

ty analyses performed by NHTSA for this final rule was to 

valuate the effects of using the Retail Price Equivalent (RPE) multiplier employed in the 

MY 20 TSA rulemakings, instead of using the 

Indirec Cost Multiplier (ICM) developed for this rulemaking. The RPE methodology 

ultipl

ed 

e 

er 

2. Individual technology descriptions and cost/effectiveness 

he end of the section. Related 

to costs the Volpe Model handles learning effects within the model itself so that 

odel year would be lower than those in previous 

ears. The costs in this section and the summary tables are for model year 2012 vehicles 

d, th

olumeg the 

echanical work output as shaft torque and 

ower delivered to the transmission and to the vehicle’s driving wheels. Vehicle fuel 

economy is directly proportional to the efficiency of the engine. Two common terms are 

used to define the efficiency of an engine are (1) Brake Specific Fuel Consumption 

 

w e 2012 through 2016 implementation span and the 2017 through 2021 span both

representing the short-term. 

One of the sensitivi

e

11 CAFE final rule and in other NH

t 

m ies variable costs by 1.5 to estimate consumer costs. The 1.5 multiplier is a 

general increase that is applied consistently to every technology and consists of fix

costs and profits for the manufacturer and automobile dealers. The indirect cost 

multiplier is estimated depending upon the complexity of the technology and in the 

aggregate for the technologies utilized in the model results in a multiplier in the 1.2 to 

1.25 range and does not include profits. The sensitivity analysis indicates that using th

1.5 RPE multiplier would result in noticeably higher costs compared to the final rule 

costs incorporating the ICM multiplier, although we note that even with those high

costs the 1.5 RPE analysis still resulted in significant net benefits for the rulemaking as a 

whole150. The agency plans to investigate this issue further for future rulemakings. 

estimates 

The technology cost and effectiveness estimates used in the Volpe Model are 

defined in this section and are summarized in the tables at t

individual technology costs in the 2016 m

y

an erefore, represent fully learned costs in the context of EPA’s analysis. For 

technologies added in years prior to 2016, EPA has backed out the learning effects 

relative to the costs shown in the tables. For example, the small car stop-start vehicle 

cost is $351 in 2016. In the 2012 model year, this cost would be higher since the v

based learning reflected in the 2016 cost would not have occurred yet. Backing out two 

volume-based learning steps (i.e., dividing $351 by 80% twice) would result in a 2012 

cost estimate of $548. 

(a) Gasoline Engine Technologies 

(i) Overview 

Most passenger cars and light trucks in the U.S. have gasoline-fueled spark 

ignition internal combustion engines. These engines move the vehicle by convertin

chemical energy in gasoline fuel to useful m

p

150 See Section X. below for the results of the sensitivity analyses. 
DELIBE

185

(BSFC), which fuel used to the output mechanical energy; and 

(2) Bra ciency (BTE), which is the ratio of the fuel chemical energy, 

known

with 

50 

) and typically between 70-85 percent of 

aximum torque output at that speed. At this operating condition, BTE is typically 33-

36 percent. However, at low gine speeds engine 

operates in most consumer vehicle use and on standardized drive cycles, BTE typically 

drops t

rk. 

gine 

tion 

ion 

9

Eng

VV

Co

 is the ratio of the mass of

ke Thermal Effi

 as calorific value, to the output mechanical energy. 

The efficiency of an automotive spark ignition engine varies considerably 

the rotational speed and torque output demanded from the engine. The most efficient 

operating condition for most current engine designs occurs around medium speed (30-

percent of the maximum allowable engine rpm

m

er en and torque outputs, at which the 

o 20-25 percent. 

Spark ignition engine efficiency can be improved by reducing the energy losses

that occur between the point of combustion of the fuel in the cylinders to the point where 

that energy reaches the output crankshaft. Reduction in this energy loss results in a 

greater proportion of the chemical energy of the fuel being converted into useful wo

For improving engine efficiency at lighter engine load demand points, which are most 

relevant for CAFE fuel economy, the technologies that can be added to a given en

may be characterized by which type of energy loss is reduced, as shown in Table V-16 

below. 

Table V-16 Technology Characterization by Type of Loss Reduced 

Technology

 Heat Loss 

Reduction 

Exhaust 

Energy 

Reduction

Gas 

Exchange 

Reduction

 Fric

Reduct

Low Friction Lubricants

RATIVE DOCUMENT – DO NOT RELEASE 

9

C 9

9

s Recirculation (EGR) Boost 999

n

ine Friction Reduction

VVT - Coupled Cam Phasing (CCP) on SOHC 9

Discrete Variable Valve Lift (DVVL) on SOHC 9

Cylinder Deactivation on SOH

T - Intake Cam Phasing (ICP) 9

VVT - Dual Cam Phasing (DCP) 9

Discrete Variable Valve Lift (DVVL) on DOHC 9

Continuously Variable Valve Lift (CVVL) 9

Cylinder Deactivation on DOHC 9

Cylinder Deactivation on OHV 9

VVT - Coupled Cam Phasing (CCP) on OHV 9

Discrete Variable Valve Lift (DVVL) on OHV 9

Conversion to DOHC with DCP 9

Stoichiometric Gasoline Direct Injection (GDI) 9

Combustion Restart

Turbocharging and Downsizing 9 9

Exhaust Ga

version to Diesel 9 99

9 Represents area of primary influence 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

y are exhaust energy losses, engine friction 

losses, gas exchange losses. Converting the gasoline engine to a diesel engine can 

also reduce heat losses. 

 three 

e cycle 

io. The 

latter is

issipated through the cooling system in the form of heat. Besides 

via dire e 

stion 

cylinde

 lift. 

king it 

arget reduced pumping loss will have little additional 

ffectiveness. Thus, in the revised decision trees, the effectiveness value shown for 

additional technologies targeting pumping loss depends on the existing technology 

combination already present on the engine. 

 As Table V-16 shows, the main types of energy losses that can be reduced in 

gasoline engines to improve fuel econom

and

Exhaust Energy Loss Reduction 

 Exhaust energy includes the kinematic and thermal energy of the exhaust gases,

as well as the wasted chemical energy of unburned fuel. These losses represent 

approximately 32 percent of the initial fuel chemical energy and can be reduced in

ways: first, by recovering mechanical or electrical energy from the exhaust gases;

second, by improving the hydrocarbon fuel conversion; and third, by improving th

thermodynamic efficiency. The thermodynamic efficiency can be improved by either 

increasing the engine’s compression ratio or by operating with a lean air/fuel rat

 not considered to be at the emerging technology point yet due to the nonavailability of lean NOx aftertreatment, as discussed below. However, the compression 

ratio may potentially be raised by 1 to 1.5 ratios using stoichiometric direct fuel injection. 

Engine Friction Loss Reduction 

Friction losses can represent a significant proportion of the global losses at low

load. These losses are d

ct reduction measures, friction can also be reduced through downsizing the engin

by means of increasing the engine-specific power output. 

Gas Exchange Loss Reduction 

 The energy expended while delivering the combustion air to the cylinders and 

expelling the combustion products is known as gas exchange loss, commonly referred to

as pumping loss. The main source of pumping loss in a gasoline engine is the use of an 

inlet air throttle, which regulates engine output by controlling the pre-combu

r air pressure, but is an inefficient way to achieve this pressure control. A more 

efficient way of controlling the cylinder air pressure is to modify the valve timing or

Another way to reduce the average pumping losses is to “downsize” the engine, ma

run at higher loads or higher pressures. 

 Several different technologies target pumping loss reduction, but it is important to

note that the fuel consumption reduction from these technologies is not necessarily 

cumulative. Once most of the pumping work has been eliminated, adding further 

technologies that also t

e
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a. Engine Techn es 

 

rces 

er 

., 

 

aft, rod and main bearings and changes to 

the me ability 

wer 

at low 

friction lubricants could have an effectiveness value between 0 to 1 percent. For 

purpos

ng a 

st 

e that the $3 cost estimate is appropriate and 

independent of vehicle class since the eng apply to any 

engine size. Apply ect cost m complexity 

technology

Neither volume-based cost reductions nor time-based cost reductions are applied 

ologi

NHTSA and EPA have reviewed the engine technology estimates used in 

NHTSA’s MY 2011 CAFE final rule and EPA’s 2008 Staff Report and available 

comments to the NPRM. In doing so NHTSA and EPA reconsidered all available sou

and updated estimates as appropriate. The section below describes each of the engine 

technologies considered for this rulemaking. 

(1) Low Friction Lubricants (LUB)

One of the most basic methods of reducing fuel consumption in gasoline engines 

is the use of lower viscosity engine lubricants. More advanced multi-viscosity engine 

oils are available today with improved performance in a wider temperature band and with 

better lubricating properties. This can be accomplished by changes to the oil base stock 

(e.g., switching engine lubricants from a Group I base oils to lower-friction, low

viscosity Group III synthetic) and through changes to lubricant additive packages (e.g

friction modifiers and viscosity improvers). The use of 5W-30 motor oil is now 

widespread and auto manufacturers are introducing the use of even lower viscosity oils,

such as 5W-20 and 0W-20, to improve cold-flow properties and reduce cold start friction.

However, in some cases, changes to the cranksh

chanical tolerances of engine components may be required. In all cases, dur

testing would be required to ensure that durability is not compromised. The shift to lo

viscosity and lower friction lubricants will also improve the effectiveness of valvetrain 

technologies such as cylinder deactivation, which rely on a minimum oil temperature 

(viscosity) for operation. 

Several manufacturers have previously commented confidentially, th

es of this final rule, NHTSA is using an effectiveness estimate within this range. 

Therefore 0.5 percent is used. 

The 2002 NAS study estimated the low friction lubricant RPE at $8 to $11 usi

1.4 markup factor. The NESCCAF study showed an RPE of $5 to $15 with a 1.4 

markup. The EEA report to DOE showed manufacturer costs of $10 to $20 with no 

markup. Confidential Business Information (CBI) data estimates an average incremental

cost of $3 for the use of low friction lubricants. EPA’s 2008 Staff Report also confirms 

this $3 cost (2006$). NHTSA believes that manufacturer’s estimates are the mo

accurate, and thus continues to believ

ineering work required should 

ing an indir ultiplier (ICM) of 1.11, for a low

, results in a compliance cost of $3.33 per vehicle (2007$) for a MY 2012 

through MY 2016 vehicle. The costs developed for low friction lubricants reflect the 

costs associated with any engine changes that would be required as well as any durability 

testing. 

to low friction lubricants. This technology is presumed to be significantly dependent on 

commodity raw material prices and to be priced independent of particular design or 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

nd 

proving the design of engine components and 

subsyst

ples 

ce 

mprove, 

more o

orts as 

ness for engine 

friction n to be between 1 to 3 percent. NHTSA continues to believe that this 

range is accurate. B f the increm ded 

to continue to use the narrower range of 1-2 percent, which was also used in the MY 

2011 C

r 

ce 

s cost is multiplied by the number of engine cylinders 

for Vol

ufacturers’ comments, NHTSA has maintained 

s it did n 

le 

manufacturing savings. This technology can be applied to any vehicle class with a phasein of 100 percent starting in MY 2012. 

 

(2) Engine Friction Reduction (EFR)

In addition to low friction lubricants, manufacturers can also reduce friction a

improve fuel consumption by im

ems. Approximately 10 percent of the energy consumed by a vehicle is lost to 

friction, and just over half is due to frictional losses within the engine.151 Exam

include improvements in low-tension piston rings, piston skirt design, roller cam 

followers, improved crankshaft design and bearings, material coatings, material 

substitution, more optimal thermal management, and piston and cylinder surfa

treatments. Additionally, as computer-aided modeling software continues to i

pportunities for evolutionary friction reductions may become available. 

All reciprocating and rotating components in the engine are potential candidates

for friction reduction, and minute improvements in several components can add up to a 

measurable fuel economy improvement. The 2002 NAS, NESCCAF and EEA rep

well as confidential manufacturer data suggested a range of effective

 reductio

ecause o ental nature of the Volpe model, NHTSA nee

AFE final rule. 

In the MY 2011 CAFE final rule, NHTSA estimated a range from $13 to $49 

using a 1.5 RPE on a per cylinder basis, or $9 to $33 without RPE (2007$). In the 2008 

NPRM engine friction reduction was estimated to cost up to $14 without RPE on a per 

cylinder basis. After review, NHTSA believes that the cost estimate is closer to the lowe

end of the MY 2011 CAFE final rule range and thus for this rulemaking has a complian

cost of $13 per cylinder (2007$), including the low complexity ICM markup value of 

1.11, for a MY 2012 vehicle. Thi

pe modeling purposes. Thus a cost of $50 was used for a 4-cylinder engine, $75 

for a 6-cylinder engine and $101 for an 8-cylinder engine for this final rule. 

Engine friction-reducing technologies may be applied to all vehicle classes. No

learning factors were applied to costs as the technology has a loosely defined BOM 

which may in part consist of materials (surface treatments, raw materials) that are 

commodity based. As confirmed by man

a in the MY 2011 final rule, that engine friction reduction may only be applied i

conjunction with a refresh or redesign cycle. Engine friction has phase-in cap of 85 

percent from MY 2012 to 2014 and then increases to 100 percent for the rest of this ru

making period. 

 

151 “Impact of Friction Reduction Technologies on Fuel Economy,” Fenske, G. Presented at the March 

2009 Chicago Chapter Meeting of the ‘Society of Tribologists and Lubricated Engineers’ Meeting, March 

18th, 2009. Available at: http://www.chicagostle.org/program/2008-

2009/Impact%20of%20Friction%20Reduction%20Technologies%20on%20Fuel%20Economy%20-

%20with%20VGs%20removed.pdf (last accessed July 9, 2009). 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Variable va (VVT) clas designs that alter 

the timing of the intake valve, exhaust valve, or both, primarily to reduce pumping losses, 

increas

e timing is in production on most of its engine families. 

Manufa h 

y the level of valvetrain technology already 

implem et file is 

e 

a solenoid that controls the oil pressure supplied to the phaser. 

e 

ming or variable valve lift. NHTSA 

judges 

s each of these factors is addressed prior to production 

implem ntation of the technologies. 

(a) Inta

(3) Variable Valve Timing (VVT)

lve timing sifies a family of valve-train

e specific power, and control the level of residual gases in the cylinder. VVT 

reduces pumping losses when the engine is lightly loaded by controlling valve timing 

closer to the optimum needed to sustain horsepower and torque. VVT can also improve

volumetric efficiency at higher engine speeds and loads. Additionally, VVT can be used 

to alter (and optimize) the effective compression ratio where it is advantageous for 

certain engine operating modes (e.g., in the Atkinson Cycle). 

VVT has now become a widely adopted technology: in MY 2007, over half of all 

new cars and light trucks had engines with some method of variable valve timing.152 GM

has commented that variable valv

cturers are currently using many different types of variable valve timing, whic

have a variety of different names and methods. Therefore, the degree of further 

improvement across the fleet is limited b

ented on the vehicles. Information found in the 2008 baseline vehicle fle

used to determine the degree to which VVT technologies have already been applied to 

particular vehicles to ensure the proper level of VVT technology, if any, is applied. Th

three major types of VVT are listed below. 

Each of the three implementations of VVT uses a cam phaser to adjust the 

camshaft angular position relative to the crankshaft position, referred to as “camshaft

phasing.” The phase adjustment results in changes to the pumping work required by the 

engine to accomplish the gas exchange process. The majority of current cam phaser 

applications use hydraulically-actuated units, powered by engine oil pressure and 

managed by 

In response to the NPRM, NHTSA received comments from GM that included a 

description of technical considerations, concerns, limitations and risks that need to b

considered when implementing variable valve ti

that the expressed technical considerations, concerns, limitations and risks are 

well recognized within the industry and it is standard industry practice to address each 

during the design and development phases of applying variable valve timing or variable 

valve lift technologies. Cost and effectiveness estimates used in the final rule are based 

on analysis that assume

e

ke Cam Phasing (ICP)

Valvetrains with ICP, which is the simplest of the cam phasing technologies, can 

modify the timing of the inlet valves by phasing the intake camshaft while the exhaust 

valve timing remains fixed. This requires the addition of a cam phaser on each bank o

 

f 

152 “Light-Duty Automotive Technology and Fuel Economy Trends: 1975 Through 2007”, EPA420-S-07-

001, September 2007. Available at http://www.epa.gov/oms/cert/mpg/fetrends/fetrends-archive.htm (last 

accessed July 9, 2009). 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

d so have continued to 

employ it for this rulemaking. 

As for costs, NH ($41 nonRPE) c

er 

d 

bined phase-in cap is 85 percent from MY 2012 to 2014 and then 

increas

intake valves on the engine. An in-line 4-cylinder engine has one bank of intake valves,

while V-configured engines have two banks of intake valves. 

NHTSA’s MY 2011 CAFE final rule and EPA 2008 Staff Report estimated an

effectiveness of 1 to 2 percent for ICP, which was supported by the NESCCAF report and 

a majority of confidential manufacturer comments. NHTSA has found no additional 

sources to suggest strongly that this estimate is inaccurate, an

TSA’s MY 2011 CAFE final rule estimated a $61 RPE

ost per cam phaser, based on the 2008 Martec Report and confidential 

manufacturer data. NHTSA believes that this number remains accurate. Using the new 

indirect cost multiplier of 1.11, for a low complexity technology, the compliance cost p

cam phaser would be $45 per bank, yielding a $45 cost for and in-line engine 

configurations and $90 for V-engine configurations for a MY 2012 vehicle. 

ICP is applicable to all vehicle classes, can be applied at the refresh or redesign 

cycles and is eligible for time-based learning. For this rulemaking and as it did for the 

MY 2011 final rule, NHTSA has combined the phase-in caps for ICP, CCPS, CCPO an

DCP. This com

es to 100 percent for the rest of this rule making period. 

 

(b) Coupled Cam Phasing (CCPS and CCPO)

Valvetrains with coupled (or coordinated) cam phasing can modify the timing of 

both the inlet valves and the exhaust valves an equal amount by phasing the camshaft

single overhead cam (SOHC) engine or an overhead valve (OHV) engine. For overhead 

cam engines, this requires the addition of a cam phaser on each bank of th

 of a 

e engine. Thus, 

an in-li

 and 

ess for CCPS to be 1 to 3 

percent

. 

 

ne 4-cylinder engine has one cam phaser, while SOHC V-engines have two cam 

phasers. For overhead valve (OHV) engines, which have only one camshaft to actuate

both inlet and exhaust valves, CCP is the only VVT implementation option available

requires only one cam phaser.153

Based on NHTSA’s MY 2011 CAFE final rule, previously-received confidential 

manufacturer data, and the NESCCAF report, NHTSA estimated the effectiveness of 

CCP to be between 1 to 4 percent. NHTSA reviewed this estimate for purposes of the

NPRM, and continue to find it accurate. Due to the incremental nature and decision tree

logic of the Volpe model, NHTSA estimated the effectiven

 and 1 to 1.5 percent for CCPO. 

 The same cam phaser has been assumed for ICP and CCP applications, thus 

CCP’s cost per cam phaser is identical to ICP’s. This results in a cost of $45 for in-line

SOHC and OHV engines and $90 for SOHC V-engine configurations for a MY 2012 

vehicle with time-based learning applied. 

CCP is applicable to all vehicle classes and can be applied at refresh or redesign

For purposes of this rulemaking as in the MY 2011 final rule, NHTSA has combined the 

phase-in caps for ICP, CCPS, CCCPO and DCP. This combined phase-in cap is 85 

 153 It is a o noted that coaxial camshaft developments would allow other VVT options to be applied to 

OHV en nes. However, since they would potentially be adopted on a limited number of OHV engines 

NHTSA did not include them in the decision tree. 

ls

gi
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

percent from MY 2 nt for the rest of this rule 

making

012 to 2014 and then increases to 100 perce

 period. 

(c) Dual Cam Phasing (DCP)

The most flexible VVT design is dual (independent) cam phasing, where the 

intake and exhaust valve opening and closing events are controlled independently. This 

option allows the option of controlling valve overlap, which can be used as an inte

EGR strategy. At low engine loads, DCP creates a reduction in pumping losses, resulting 

in improved fuel consumption. Increased i

rnal 

nternal EGR also results in lower engine-out 

OX em

at 

P’s cost per cam phaser is identical to ICP’s. DCP requires two 

cam ph

percent

ng 

cesses. Variable valve lift control can also be 

used to induce in-cylinder mixture motion, which improves fuel-air mixing and can result 

N issions. The amount by which fuel consumption is improved depends on the 

residual tolerance of the combustion system. Additional improvements are observed 

idle, where low valve overlap could result in improved combustion stability, potentially 

reducing idle fuel consumption. 

In the MY 2011 final rule, NHTSA estimated the effectiveness of DCP to be 

between 2 to 3 percent relative to an engine with ICP. NHTSA believes that this estimate

remains applicable for this rulemaking. 

As with CCP, the same cam phaser has been assumed for ICP and DCP 

applications. Thus, DC

asers per cylinder bank, one to control the intake valves and one to control the 

exhaust valves. This results in a cost of $90, relative to an engine without ICP, or $45 

relative to an engine with ICP, minus $6 for the removal of the EGR valve, ultimately 

yielding costs of $84 and $39 respectively for in-line DOHC configurations. For Vconfiguration engines, the cost is $180 relative to an engine without ICP, or $90 relative

to an engine with ICP, minus $6 for the removal of the EGR valve, ultimately yielding 

costs of $174 and $84, respectively. These costs are appropriate for a MY 2012 vehicle 

application. 

DCP can be applied to all of the vehicle classes at vehicle refresh. Time-based 

leaning is applied and NHTSA has combined the phase-in caps of ICP, CCPS, CCPO and

DCP with a combined cap of 85 percent for MY 2012 to 2014 and increases to 100 

 for the rest of this rule making period. 

In response to the NPRM, NHTSA received comments from a manufacturer that 

included confidential business information related to the effectiveness of variable valve 

timing technology. Analysis of the data, that used assumptions similar to those used in 

the NPRM and final rule, showed that effectiveness values are similar to those used in the 

NPRM and final rule. 

(4) Variable Valve Lift (VVL)

Controlling the lift of the valves provides a potential for further efficiency 

improvements. By optimizing the valve-lift profile for specific engine operating regions, 

the pumping losses can be reduced by reducing the amount of throttling required to 

produce the desired engine power output. By moving the throttling losses further 

downstream of the throttle valve, the heat transfer losses that occur from the throttli

process are directed into the fresh charge-air mixture just prior to compression, delaying

the onset of knock-limited combustion pro
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

in impr tially 

Discrete Variable Valve Lift (DVVLS, DVVLD, DVVLO) 

s 

gine. These cam profiles consist of a low and a high-lift lobe, and 

may in e an inert or blank lobe to incorporate cylinder deactivation (in the case of a 3-

step DVVL system). DVVL is normally applied together with VVT control. DVVL is 

also known as Cam Profile Switchi

technical risk. 

he 

n inline 4-cylinder engine, $306 for a V6 engine and $396 for a V8 

engine , 

is 

cylinder 

ne cylinder head. In the NPRM and final rule, NHTSA limits 

applica the 

ass 

oint penetration allowed 

at 85 p

oved thermodynamic efficiency. Variable valve lift control can also poten

reduce overall valvetrain friction. At the same time, such systems may also incur

increased parasitic losses associated with their actuation mechanisms. A number of 

manufacturers have already implemented VVLT into their fleets (Toyota, Honda, and 

BMW), but overall this technology is still available for most of the fleet. There are two 

major classifications of variable valve lift, described below: 

DVVL systems allow the selection between two or three discrete cam profiles by 

means of a hydraulically-actuated mechanical system. By optimizing the cam profile for

specific engine operating regions, the pumping losses can be reduced by reducing the 

amount of throttling required to produce the desired engine power output. This increase

the efficiency of the en

clud

ng (CPS). DVVL is a mature technology with low 

NHTSA’s MY 2011 CAFE final rule, previously-received confidential 

manufacturer data, and the NESCCAF report, all estimate the effectiveness of DVVL to 

be between 1 to 4 percent above that realized by VVT systems. NHTSA believes this 

estimate continues to be applicable for the final rule. Taking into account the incremental 

nature and decision tree logic of Volpe modeling, NHTSA has estimated an incremental 

reduction in fuel consumption for DVVLS and DVVLD of 1 to 3 percent. On OHV 

engines, DVVLO is applied following both VVT and cylinder deactivation, therefore t

effectiveness estimate is at a slightly lower range of 0.5 to 2.5 percent. 

In the MY 2011 CAFE final rule, NHTSA estimated an RPE (1.5 markup factor)

cost of $201 for a

or without RPE $134, $204, $264, respectively (all in 2007$). After review

NHTSA, in consultation with EPA, has chosen to use the NESCCAF report as the basis 

for the discrete variable valve lift cost. The NESCCAF estimates were converted to 2007 

dollars, updated for a MY 2012 application, increased by $25 for additional controls

hardware and multiplied by the low complexity ICM markup factor or 1.11. For th

final rule, NHTSA is using a compliance cost estimate of $141 for an inline 4-

engine, $205 for a V6 engine and $293 for a V8 engine. 

In response to the NPRM, NHTSA received comments from GM that 

implementation of either 2-step or continuously variable lift must be timed to coincide 

with changes to the engi

tion of these technologies to vehicle redesign, which is judged to approximate 

frequency of engine cylinder head changes. This technology may be applied to any cl

of vehicles. NHTSA has combined the phase-in caps for DVVLS, DVVLD, DVVLO 

and CVVL, as it did in the MY 2011 final rule, and capped the j

ercent in MY 2012 to 2014 and increases to 100 percent for the rest of this rule 

making period with time-based learning applied. 

 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ry 

m. 

 intake valve opening reduction, which improves engine 

efficien eam 

 to 

1.5 

h as 

VL 

ere based on the NESCCAF report, in 

which 

y 

facturers’ 

product lans confirmed that this technology will not be applied by most manufacturers. 

In the MY 11 CAFE fin

continuously variable valve lift to be $ for a V6 

engine d $582 for a V8 engine or without RPE $204, $287, $388, respectively. After 

review the 

s 

 a 

-based learning applied. 

y 

LS, 

penetration allowed at 85 percent in MY 2012 to 2014 and the increases to 100 percent 

for the rest of this rule making period. 

1. Continuously Variable Valve Lift (CVVL) 

In CVVL systems, valve lift is varied by means of a mechanical linkage, driven 

by an actuator controlled by the engine control unit. The valve opening and phasing va

as the lift is changed and the relation depends on the geometry of the mechanical syste

BMW has considerable production experience with CVVL systems and has sold portinjected “Valvetronic” engines since 2001. CVVL allows the airflow into the engine to 

be regulated by means of

cy by reducing pumping losses from throttling the intake system further upstr

as with a conventionally throttled engine. 

 Variable valve lift gives a further reduction in pumping losses compared to that 

which can be obtained with cam phase control only, with CVVL providing greater 

effectiveness than DVVL, since it can be fully optimized for all engine speeds and loads,

and is not limited to a two or three step compromise. There may also be a small 

reduction in valvetrain friction when operating at low valve lift, resulting in improved 

low load fuel consumption for cam phase control with variable valve lift as compared

cam phase control only. Most of the fuel economy effectiveness is achieved with 

variable valve lift on the intake valves only. CVVL is only applicable to double overhead

cam (DOHC) engines. 

NHTSA’s MY 2011 CAFE final rule estimated the effectiveness for CVVL at 

to 3.5 percent over an engine with DCP, but also recognized that it could go up as hig

5% above and beyond DCP to account for the implementation of more complex CV

systems such as BMW’s “valvetronic” engines. This coincides with EPA Staff Report

estimates of the contribution of CVVL, which w

CVVL could improve effectiveness by 4 percent (minivans) and up to 6 percent 

(large cars) over dual cam phasing. For this rulemaking, NHTSA has continued to use the 

1.5 to 3.5 percent range from the MY 2011 final rule. However, due to the complexit

and cost of this technology, the Volpe model projected very limited applications of this

technology (i.e., 2 out of 1100 vehicles). The most recent submission of manu

 p

 20 al rule, NHTSA estimated and RPE (1.5) cost of 

306 for an inline 4-cylinder engine, $432

an

, NHTSA in consultation with EPA has chosen to use the NESCCAF report as

basis for the discrete variable valve lift cost. The NESCCAF estimates were converted to

2007 dollars, updated for a MY 2012 application, increased by $25 for additional controls

hardware and multiplied by the low complexity ICM markup factor or 1.45 For thi

rulemaking, NHTSA estimated a cost of $277 for an inline 4-cylinder engine, $509 for

V6 engine and $554 for a V8 engine with time

There are no class specific applications of this technology, although it appears in 

only the DOHC portion of the decision tree. Due to the changes required to implement 

CVVL on an engine the Volpe model allows it to be applied at redesign model years onl

with time-based learning applied. NHTSA has combined the phase-in caps for DVV

DVVLD, DVVLO and CVVL, as in the MY 2011 final rule, and capped the joint 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

tion of additional technologies such as 2-step variable lift will be highly 

depend

t 

f 

technologies to achieve CAFE regulatory compliance, based on their unique 

circumstances. 

In response to the NPRM, NHTSA received comments from a manufacturer that 

include

ACO)

lf of 

bility – the valves are kept closed, and no fuel is injected – 

as a result, the trapped air within the deactivated cylinders is simply compressed and 

expand

Cylinder deactivation control strategy relies on setting maximum manifold 

ed, 

f 

ge of 

d 

applied to 

Cylinder deactivation has seen a recent resurgence thanks to better valvetrain 

er displacement-to-weight vehicles, operating at lower relative loads 

r normal driving, have the potential to operate in part-cylinder mode more frequently. 

 range depending on the engine valvetrain configuration. For example, for DOHC 

In response to the NPRM, NHTSA received comments from GM that the 

introduc

ent on the cost-effectiveness of the technology from a fuel economy benefit 

standpoint. The Volpe model provides one solution that manufacturers could use to mee

CAFE regulations to demonstrate the feasibility of regulatory standards. It is expected 

that in many cases, manufacturers will identify and implement other combinations o

d confidential business information related to the effectiveness of variable valve 

lift technology. Analysis of the data, that used assumptions similar to those used in the 

NPRM and final rule, showed that effectiveness values are similar to those used in the 

NPRM and final rule. 

(5) Cylinder Deactivation (DEACS, DEACD, DE

In conventional spark-ignited engines throttling the airflow controls engine torque 

output. At partial loads, efficiency can be improved by using cylinder deactivation 

instead of throttling. Cylinder deactivation (DEAC) can improve engine efficiency by 

disabling or deactivating (usually) half of the cylinders when the load is less than ha

the engine’s total torque capa

ed as an air spring, with reduced friction and heat losses. The active cylinders 

combust at almost double the load required if all of the cylinders were operating. 

Pumping losses are significantly reduced as long as the engine is operated in this “partcylinder” mode. 

absolute pressures or predicted torque within which it can deactivate the cylinders. Noise 

and vibration issues reduce the operating range to which cylinder deactivation is allow

although manufacturers are exploring vehicle changes that enable the possibility o

increasing the amount of time that cylinder deactivation might be suitable. Some 

manufacturers may choose to adopt active engine mounts and/or active noise 

cancellations systems to address NVH concerns and to allow a greater operating ran

activation. Manufacturers have stated that use of DEAC on 4 cylinder engines woul

cause unacceptable NVH issues; therefore cylinder deactivation has not been 

4-cylinder engines. 

designs and engine controls. General Motors and Chrysler Group have incorporated 

cylinder deactivation across a substantial portion of their V8-powered lineups. Honda 

(Odyssey, Pilot) offers V6 models with cylinder deactivation. 

Effectiveness improvements scale roughly with engine displacement-to-vehicle 

weight ratio: the high

fo

NHTSA reviewed the MY 2011 CAFE estimates and confirmed their 

appropriateness for this rulemaking. The Volpe model, due to its incremental nature, 

uses a
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

so the 

ent for DEACS. For 

OHV e

at 

d 

n 

ew ICM multipliers for engines that do not have 

lost mo

or 

r 

nd 

ith 

s. 

ld 

purposes of this 

rulema ng, NHTSA revised the costs only by identifying this technology as a low 

complexity technology and applying an indirect cost multiplier of 1.11 resulting in a 

 

engines which are already equipped with DCP and DVVLD, there is little benefit that can 

be achieved from adding cylinder deactivation since the pumping work has already been 

minimized and internal Exhaust Gas Recirculation (EGR) rates are maximized, 

effectiveness range for DEACD is 0.0 to 0.5 percent. For SOHC engines which have 

CCP and DVVLS applied, effectiveness ranged from 2.5 to 3 perc

ngines, without VVT or VVL technologies, the effectiveness for DEACO ranged 

from 3.9 to 5.5 percent. 

NHTSA considered a range of $28 to $190 depending on whether an engine 

already has lost motion devices, oil control valves and camshaft position sensors. This is

a departure from NHTSA’s 2011 final rule, which uses a range of $306 to $400. Th

range was primarily based on 2008 Martec Report and applied a higher RPE value. In 

reviewing these assumptions, NHTSA in consultation with EPA amended the MY 2011 

CAFE estimates and adjusted the estimates to include the new ICM low complexity 

markup of 1.11. The EPA staff report and NHTSA’s MYs 2011-2015 NPRM showe

estimates of a $170 for a 6-cylinder engine and $190 for an 8-cylinder engine whe

adjusted for 2007 dollars and using the n

tion devices. These numbers were within the ranges described by the 2002 NAS 

and NESCCAF reports. For Volpe modeling purposes, these costs are appropriate f

DEACO on OHV engines. If lost motion devices are on the engine, as is the case fo

SOHC and DOHC engines based on the decision tree logic, the cost of DEACS a

DEACD ranges from $0 to $56. This $0 to $56 range154 accounts for the potential 

additional application of active engine mounts on SOHC and DOHC engines and can 

only be applied on 50 percent of the vehicles. 

This technology may be applied only to V-6 and V-8 engines, as discussed above, 

and so does not apply to vehicle classes with I-4 engines. DEAC can be applied during a 

redesign or refresh model year with time-based learning. NHTSA has combined the 

phase-in caps for DEACS, DEACD and DEACO, as it did in MY 2011 final rule, and 

capped the joint penetration allowed at 85 percent for MY 2012 and beyond. 

(6) Conversion to Double Overhead Camshaft Engine w

Dual Cam Phasing (CDOHC)

Double overhead camshaft engines achieve increased airflow at high engine 

speeds, improve volumetric efficiency and reductions of the valvetrain’s moving mas

Such engines typically develop higher power at high engine speeds. Manufacturers may 

choose to replace OHV engines with DOHC engine designs with dual cam phasing 

(DCP). NHTSA continues to use the fuel consumption reduction estimate of 1 to 2.5 

percent, as it did in the MY 2011 final rule. 

 As for costs, NHTSA’s MY 2011 CAFE final rule assumed that CDOHC wou

have an RPE cost of $746 ($497 non-RPE) for a V8 engine, $590 ($393 non-RPE) for a

V6 engine and $373 ($249 non-RPE) for inline 4-cylinder engine. For 

ki

154 The $28 is an adjustment from the $75 estimate used in the MY 2011 final rule to account for the new 

ICM markup factor and the fact that it could only be applied on up to 50 percent of the vehicles. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ompliance cost of $552 for V8 engine, $436 for a V6 and $276 for an inline 4-cylinder 

 technology. The phase-in 

ap for CDOHC has be p p h 16 timeframe. The 

conversion from OHV t ng h th engine redesign 

that can be applied in redes ode s onl time- learning applied. 

(7) Stoichiometric Gasoline Direct Injection (SGDI)

the cyl

ting and 

variable valvetrain designs. 

Several manufacturers ha recently introduced vehicles with SGDI engines, 

includi

c

engine. 

There are no vehicle class-specific applications of this

c en set at 85 

o D C e

ercent 

c

er year for t

ite wi

e 2012-20

OH ine ar cture D a major CP is

ign m l year y with based

Gasoline direct injection (GDI) or Spark Ignition Direct Injection (SIDI) engines 

inject fuel at high pressure directly into the combustion chamber (rather than the intake 

port in port fuel injection). SGDI requires changes to the injector design, an additional 

high pressure fuel pump, new fuel rails to handle the higher fuel pressures and changes to 

inder head and piston crown design. Direct injection of the fuel into the cylinder 

improves cooling of the air/fuel charge within the cylinder, which allows for higher 

compression ratios and increased thermodynamic efficiency without the onset of 

combustion knock. Recent injector design advances, improved electronic engine 

management systems and the introduction of multiple injection events per cylinder firing 

cycle promote better mixing of the air and fuel, enhance combustion rates, increase 

residual exhaust gas tolerance and improve cold start emissions. SGDI engines achieve 

higher power density and match well with other technologies, such as boos

ve

ng VW/Audi, BMW, Toyota (Lexus IS 350) and General Motors (Chevrolet 

Impala and Cadillac CTS 3.6L). BMW, GM, Ford and VW/Audi have announced their

plans to increase dramatically the number of SGDI engines in their portfolios. 

NHTSA’s MY 2011 CAFE final rule estimated the effectiveness of SGDI to be between 

2 and 3 percent. In developing these estimates, NHTSA reviewed estimates from the 

Auto Alliance of American Manufacturers, which projects 3 percent gains in fuel 

efficiency and a 7 percent improvement in torque. The torque increase provides the 

opportunity to mildly downsize the engine allowing an increase in efficiency of up to a 

5.8 percent. NHTSA also reviewed other published literature, reporting 3 percent 

effectiveness for SGDI.155 Another source reports a 5 percent improvement on the 

NEDC drive cycle.156 Confidential manufacturer data reported an efficiency 

effectiveness range of 1 to 2 percent. In response to the NPRM, NHTSA received 

 

155 Paul 

 (last 

156 Stefan Trampert, FEV Motorentechnik GmbH, “Engine and Transmission Development Trends - Rising 

Fuel Cost Pushes Technology,” Symposium on International Automotive Technology, Pune, India, January 

2007. 

Whitaker, Ricardo, Inc., “Gasoline Engine Performance And Emissions – Future Technologies and 

Optimization,” ERC Symposium, Low Emission Combustion Technologies for Future IC Engines,

Madison, WI, June 8-9, 2005. Available at 

http://www.erc.wisc.edu/symposiums/2005_Symposium/June%208%20PM/Whitaker_Ricardo.pdf

accessed Nov. 9, 2008). 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

comme

, NHTSA received comments from MECA stating that 

Gasolin

d 

 downsizing, and cooled EGR along with SGDI, that the 5 

percent

 with EPA revised 

the cos for SGDI to take into account the changes required to the engine 

hardwa e elect c controls, a

(NVH) mitigation systems. Through c

manufa

nts from Porsche stating that Gasoline Direct Injection improves fuel economy up 

to 3%. NHTSA determined that the range of 2 to 3 percent continues to be appropriate. 

However, NHTSA notes that combined with other technologies (i.e., boosting, 

downsizing, and in some cases, cooled EGR), SGDI can achieve greater reductions in

fuel consumption compared to engines of similar power output. 

In response to the NPRM

e Direct Injection offers CO2 emissions reductions ranging from 5% to 20% 

depending on how it is implemented and the base engine to which it is compared. The 

5% to 20% range in MECA’s comments is not specific as to the technology level of the 

base engine for the comparison, nor the accompanying technologies that have been 

incorporated along with GDI. Therefore, there is insufficient information presented in 

MECA’s comments to enable comparison of effectiveness to the effectiveness range for 

SGDI in the NPRM and final rule. However, it should be noted that if MECA’s intende

to include turbocharging,

 to 20 percent effectiveness improvement range would be consistent with 

effectiveness estimates in the final rule. 

In reviewing the MY 2011 estimates, NHTSA in coordination

t estimates 

re, engin roni ncillary and Noise Vibration and Harshness 

ontacts with industry NVH suppliers, and 

cturer press releases, the agency believes that the NVH treatments will be limited 

to the mitigation of fuel system noise, specifically from the injectors and the fuel lines. 

In the final rule, NHTSA, in coordination with EPA, revised the SGDI costs based on the 

FEV work that was not yet available for the NPRM. Focusing on direct manufacturing 

costs, the NPRM estimates, the FEV values, and the final values are shown in 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table V-17. FEV did not directly estimate the SGDI costs shown here. Instead, 

FEV estimated costs associated with downsizing and turbocharging a V8 and V6 engine 

to a V6 and I4 engine, respectively, and simultaneously converting the PFI fuel system to 

a SGDI fuel system. The agencies, working closely with FEV, then “binned” the costs 

into three distinct bins: downsize, turbocharge, and SGDI. As such, the FEV results 

shown in 
199

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

s, 

. 

Table V-17 cannot be found in the FEV reports, but instead are detailed in a 

memo to the docket which also provides details of this binning process.157 Because the

methodology used by FEV presumes high volume production, instead of using the FEV 

results directly the agencies have averaged those results with the NPRM results to 

estimate the final values (this is noted above in section V.C.C.5 and in TSD sections

3.3.2.2, 3.4.2.1.9, and 3.4.2.2.5). Note that the costs for the I4 engine has changed since 

the NPRM but have not been averaged with the NPRM values. The costs changed based 

on a more rigorous binning process than that conducted for the NPRM, but were not 

averaged because they are based on the I4 to I4 teardown conducted by FEV which wa

in fact, used in the NPRM. While the final value of $213 is lower than the NPRM value 

of $226, the $13 difference has simply been shifted from SGDI to the downsizing bin

 

157

 Insert docket info for Mike’s memo to the docket providing details of the FEV binning of costs. 
200

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table V-17. Direct Manufacturing Costs for SGDI (2007$ in 2012) 

Technology NPRM FEV Results Final Rule 

I4 $226 $213 $213 

V6 $293 $321 $307 

V8 $318 $386 $352 

For the final rule marked up costs, the agencies estimate SGDI costs at $236 for 

an inline 4-cylinder and $341 for V6 and $391 for V8 including the low complexity ICM 

158

ed to 

onsumption as the 

engine d 

hat 

 

This includes a battery sensor, incremental wiring and high current switching, an 

markup value of 1.11. As noted above, all of these costs differ slightly from those used 

in the NPRM analysis. These costs were not changed in response to public comments, 

but instead were changed due to updated information from the FEV teardown studies. 

 SGDI systems are regarded as mature technology with minimal technical risk and 

are expected to be increasingly incorporated into manufacturers’ product lineups. Timebased learning has been applied to this technology due to the fact that over 1.5 million 

vehicles containing this technology are now produced annually. Due to the changes to 

the cylinder head and combustion system and the control system development requir

adopt SGDI technology, which are fairly extensive, SGDI can be applied only at redesign 

model years. There are no limitations on applying SGDI to any vehicle class. The phasein cap for SGDI is applied at an 85 percent rate for MY 2012 and beyond. 

(8) Combustion Restart (CBRST)

Combustion restart allows “start-stop” functionality of DI engines through the 

implementation of an upgraded starter with bi-directional rotation to allow precise 

crankshaft positioning prior to subsequent fuel injection and spark ignition, allowing 

engine restart. This method of implementing engine stop/start functionality allows not 

only the fuel savings from not idling the engine, but also reduces fuel c

speeds up to its operational speed. A Direct Injection (DI) fuel system is require

for implementation of this technology. 

NHTSA reviewed the MY 2011 CAFE final rule assumptions and determined t

due to technical risks implementation of combustion restart would likely not be feasible 

prior to MY 2014. Some of the risks are associated with unresolved issues regarding the 

impact of very high or very low ambient air temperatures on the ability to start the engine 

in the described manner. Although the starter motor can provide fail-safe starting 

capability in these temperature limited areas, strategies must be developed to manage the 

transitions. Others relate to production readiness. 

Additional hardware is required to implement combustion restart, beyond SGDI.

incremental crank position sensor, and, in the case of an automatic transmission 

applications, a transmission oil pump to allow for torque converter continuity. 

 

158 Insert docket info for Mike’s memo to the docket providing details of the FEV binning of costs. 
201

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

A 

T to 

m 

t 

t of 

 2012 vehicle and will be reduced in future years with the application of 

time-based learning. 

ble to draw air into the combustion chambers. Turbocharging and 

supercharging (grouped together here as boosting) are two methods to increase the intake 

manifold pressure and cylinder charge-air mass above naturally aspirated levels. 

Boosting increases the airflow into the engine, thus increasing the specific power level, 

and with it the ability to reduce engine displacement while maintaining performance. 

This effectively reduces the pumping losses at lighter loads in comparison to a larger, 

naturally aspirated engine. 

Almost every major manufacturer currently markets a vehicle with some form of 

boosting. While boosting has been a common practice for increasing performance for 

several decades, turbocharging has considerable potential to improve fuel economy when 

the engine displacement is also reduced. Specific power levels for a boosted engine often 

exceed 100 hp/L, compared to average naturally aspirated engine power densities of 

roughly 70 hp/L. As a result, engines can conservatively be downsized roughly 30 

percent to achieve similar peak output levels. In the last decade, improvements to 

turbocharger turbine and compressor design have improved their reliability and 

 

BMW has published a 3.5 percent fuel consumption effectiveness over the NEDC

drive cycle for combustion restart,159 and AVL a 4.8 percent effectiveness.160 However, 

these reported effectiveness levels could potentially be reduced significantly on the EP

combined drive cycle, as combustion restart does not save fuel on the highway drive 

cycle. Therefore, NHTSA estimates the fuel consumption effectiveness for CBRS

range from 2 to 2.5 percent. 

Regarding the cost estimate, NHTSA determined that the estimate of $118 fro

the 2008 Martec Report cost estimates for individual pieces was the best available. The 

total RPE cost (excluding transmission pump) is $141 at high volumes, which includes 

$70 for upgrading the starter, $10 for a battery sensor and wiring, $10 for high curren

switch and $4 for crank sensor a totaling $94 (non-RPE) cost. Applying an indirect cost 

multiplier of 1.25, for a medium complexity technology, results in a compliance cos

$118 for a MY

CBRST is first available in MY 2014 and is applicable to all vehicle classes. 

Confidential product plan data indicates CBRST to be at high volume by 2014 so timebased learning is applied. CBRST can be applied a vehicle refresh. 

(9) Turbocharging and Downsizing (TRBDS)

The specific power of a naturally aspirated engine is primarily limited by the rate 

at which the engine is a

159 Stefan Wolff, Dirk Abendroth, Werner Weigl, Claus-Peter Linner, Rupert Neudecker, Michael 

Schneider, Wolfgang Huber, and Andreas Rau, BMW, “Introducing The Automatic Start-Stop (ASS) 

Function In Series Models,” 7th Stuttgart Automotive Vehicle and Engine Symposium, Organised by 

FKFS, Mar 2007, Vol. 1. 

159 G.K. Fraidl, P.E. Kapus, and H. Friedl, AVL List GmbH, “Future Gasoline Engine Technologies for 130 

 the Working Process of Combustion Engines, TU Graz, 

g/Km 

160 G.K. Fraidl, P.E. Kapus, and H. Friedl, AVL List GmbH, “Future Gasoline Engine Technologies for 130

g/Km CO2,” VKM-THD 11th Symposium on

Sept. 2007. 
DELIB VE DOC E 

202

performance across the entire engine operating range. New variable geometry turbines 

and ball-bearing center cartridges allow faster turbocharger spool-up (virtually 

eliminating the once-common “turbo lag”) while maintaining high flow rates for 

increased boost at high engine speeds. However, even with turbocharger improvements, 

maximum engine torque at very low engine speed conditions, for example launch from 

standstill, is increased less than at mid and high engine speed conditions. The potential to 

downsize engines may be less on vehicles with low displacement to vehicle mass ratios in 

order to provide adequate acceleration from sta , particularly up grades or at high 

altitudes. 

n N om from GM that included a 

ripti h rn tions and risks that need to be 

considered when implementing turbocharging and downsizing technologies on full size 

trucks. T lu in , drivability, control of boost 

pre e, n l ehicles that are designed for 

towing o u a r rs NHTSA judges that the expressed 

technical co s, concerns, limitations a are well recognized within the 

indust a ring the design and 

dev g nsizing technologies. Cost and 

effective s tes u in the final rule are n analysis that assumes each of 

e fa is ressed prior to production im tation of the technologies. In 

me m at potential to address knock limit 

e of higher octane premium fuel 

/or t ddi anol in system. For this rulemaking, 

TSA has ed that either of these ap s is implemented to address knock 

it co assessment of turbocharging 

w ss addition, NHTSA has received 

fide ss information from a manuf that supports that turbocharging 

 downsi asible on a full size truck p uring the rulemaking period. 

 and air-to-air charge air cooling 

n ited combustion and allows the 

 of high n r “Ecob wnsized, turbocharged GDI 

ines intro on MY 2010 vehicles allow ement of V8 engines with V6 

engine o fuel economy improvements of 

up t

 

ERATI UMENT – DO NOT RELEAS

ndstill

ments 

s, limita

e knock

ing for v

hness. 

nd risks

ddress each du

and dow

 based o

plemen

ented th

clude us

jection 

proache

cluded in 

.

161 In 

acturer 

roduct d

engines 

ock lim

oost” do

the replac

n and with

In re

desc

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on of tec

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and

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lim

and

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and

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ctors

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s thro

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add

lated t

ugh v

tion

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ari

of 

ull 

ous

a supplemental eth

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 al

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tern

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ks, 

ve

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s, w

 c

hi

om

cern ch in

 not assum

ncerns, and

nsizing fea

ntial busine

 thes

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ilit

 tec

y, 

hn

cos

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Use of GDI

duces the fue

er compr

 sy

l o

es

ste

cta

sio

ms

ne

 wi

 req

atio

th 

ui

s. Ford’s 

turb

rem

oc

en

ha

ts f

rged

 re or k

duced 

s with impro

2 percent.162

ved in 0-60 mph accelerati

o 1

161 Note t es rging and downsizing conducted by 

FEV I in ed by a 1.6L I4 DOHC SGDI 

turbochar for the study was a premium octane 

fuel engine. For th lemaking, NHTSA intends that a t and downsized engine achieve 

parable perf req ium octane fuel. For the FEV study of 

 tu d ro cification of an engine with a 

lac m tl g htly larger engine would have small 

ct on the ve cost analysis used in this rulemaking teardown studies conducted by 

FEV, both the naturally aspirated engine and the replacem rged and downsized engine were 

specifi use regula ne fuel. 

162 “De ment and e F V6 ombustion System,” Yi,J., 

Woold , S., Coulso oi paioannou, G., Reiche, D. Shelby, M., 

hat for one of

hich a 2.4L 

ged engine, t

is ru

 the

4 D

he p

 tea

OH

arti

rdo

C n

cula

wn 

atu

r 1

ana

rall

.6L

lysi

y as

 tur

s c

pir

boc

ost s

ated

harg

tudi

 eng

ed en

 of turbocha

e was replac

gine chosen

urbocharged

uiring prem

ugh the spe

es that a slig

. For all other 

ent turbocha

EcoBoost C

lanen, P., Pa

, in w

com

the 1

disp

effe

ormanc

rbocharge

ent of sligh

 o rall 

e t

eng

y gr

o a ba

ine, th

eat

s

i

er th

eline e

s co

an 

ngi

uld

1.6

ne

 be a

L. 

 wit

ch

NH

hou

iev

TSA

t 

ed th

 jud

.6L

e

ed to

velop

ridge

r octa

Opt

n, G

imiz

., 

ati

Hild

on of

itc

 th

h, J

ord

r, C

 3.5L

. Iye .O., M
203

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

systems and more 

ggressive engine downsizing targeted towards reduced fuel consumption indicate that 

the

may be rcent relative to port-fuel-injected engines. 

Confidential manufacturer data suggest an incremental range of fuel consumption of 4.8 

to 7 e sources 

suggest 

asp

technic

for dow

using a

NEDC

cylinde

injectio

downsizing to a rbocharged DI engine, again with wall-guided injection.170 These 

ology 

PRM, NHTSA received comments from several sources 

re f t . t 

they u for t h 

o s sho n i to 20 cent y and

a dis nt 30 to 40 perce nomy

 

Recently published data with advanced spray-guided injection 

a

 potential for reducing fuel consumption for turbocharged, downsized GDI engines 

 as much as 15 to 30 pe 163 164 165 166 167

.5 percent for turbocharging and downsizing. Other publicly-availabl

a fuel consumption of 8 to 13 percent compared to current-production naturallyirated engines without friction reduction or other fuel economy technologies: a joint 

al paper by Bosch and Ricardo suggesting fuel economy gain of 8 to 10 percent 

nsizing from a 5.7 liter port injection V8 to a 3.6 liter V6 with direct injection 

 wall-guided direct injection system;168 a Renault report suggesting a 11.9 percent 

 fuel consumption gain for downsizing from a 1.4 liter port injection in-line 4-

r engine to a 1.0 liter in-line 4-cylinder engine, also with wall-guided direct 

n;169 and a Robert Bosch paper suggesting a 13 percent NEDC gain for 

tu

reported fuel economy benefits show a wide range depending on the SGDI techn

employed. 

In response to the N

lated to the effectiveness o

methods to estim

urbocharging and downsizing

ate l econom fits 

Honeywell commented tha

sed four the fue y bene u rging, a

 per

rbocha nd eac

f those method , in 

ddition, engine

wed a mprovement of 15 

 could be reduced 

 in fuel econom

placeme nt. A fuel eco

V B., Weav , Z G., Hinds, B. S . SA cal Paper No -

1

1 s et al., Lot w Cost Solutions for Im Fu my in Gaso

ngines,” Global Powertrain Congress September 27-29, 2005, vol. 33. Available at

http:/

anDerWege, er, C. Xu ., Davis, chamel, A E Techni . 2009-01

494, 2009. 

63 Cairn us, “Lo proved el Econo line 

E

/www.gpc-icpem.org/pages/publications.html (last accessed Nov. 9, 2008). 

im Lake, John Stokes, Richard Murphy, and Richard Osborne of Ricardo and Andreas Schamel of 

rke, “Turbocharging Concepts for Downsized DI Gasoline Engines,” VKA/ika Aachen 

ium 2003. Available at

164 T

Ford-We

Colloqu http://cat.inist.fr/?aModele=afficheN&cpsidt=16973598 (last accessed 

008). 

rim Report: New Powertrain Technologies and Their Projected Costs,” October 2005, EPA42

Nov. 9, 2

165 “Inte 0-R05-0

166 “ t 

Trucks,” PA 

Interim T

167 “Elec

Compan

168 D

App e at 

http:/

169 Yves nault Powertrain 

Division, “The New Renault TCE 1.2L Turbocharged Gasoline Engine,” 28th Vienna Motor Symposium, 

Apr

170 T , CostOptimal Environment 

Conference, September 2005. 

12. 

Cost and Fuel Economy Comparison of Diesel and Gasoline Powertrains in Passenger Cars and Ligh

 submitted by FEV Engine Technology, Inc., April 23, 2003, contained as Appendix I within E

echnical Report EPA420-R-04-002. 

tric Cars: Plugged In, Batteries must be included,” Deutsche Bank Global Markets Research 

y, June 9, 2008. 

avid Woldring and Tilo Landenfeld of Bosch, and Mark J. Christie of Ricardo, “DI Boost: 

lication of a High Performance Gasoline Direct Injection Concept,” SAE 2007-01-1410. Availabl

/www.sae.org/technical/papers/2007-01-1410 (last accessed Nov. 9, 2008) 

 Boccadoro, Loïc Kermanac’h, Laurent Siauve, and Jean-Michel Vincent, Re

il 2007. 

obias Heiter, Matthias Philipp, Robert Bosch, “Gasoline Direct Injection: Is There a Simplified

 System Approach for an Attractive Future of Gasoline Engines?” AVL Engine & 
204

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

imp

improv

econom

uel 

economy improvement when engine performance is maintained”. For analysis of the 

effectiv

d 

ine 

 over a 

comparable performance naturally-aspirated SGDI engine taking into account previously 

applied

ich 

rovement of 15 to 20 percent converts to a fuel consumption effectiveness 

ement of 13 to 17 percent. Porsche commented turbocharging improves fuel 

y up to 1.9%. 

Honeywell also commented “that turbo downsizing enables significant f

eness of technologies, NHTSA uses a constraint to maintaining performance at a 

level that is as similar to baseline as possible, such that vehicle performance attributes are 

affected to the smallest possible extent. Effectiveness estimates in the final rule are base

on use of this constraint. This approach is consistent with the Honeywell comment. 

For the NPRM and final rule, NHTSA estimates a turbocharged and downsized eng

will improve fuel consumption by 0.3 percent to 6.7 percent incrementally

 technologies (e.g., VVT and VVL) as defined on the decision tree. The range of 

incremental fuel consumption improvement for each engine is also based on wh

decision tree path (i.e. SOHC, DOHC or OHV) the engine is following. This is similar to

estimates used in the 2011 final rule. This would equate to a 12 to 14 effectiveness 

improvement over baseline fixed-valve engine, similar to the estimate for Ford’s 

Ecoboost. When accounting for overall effectiveness for combined engine technologies

that may be implemented along with turbocharging and downsizing, as defined in the 

NPRM and final rule decision trees, the NPRM and final rule estimated cumulative fuel 

consumption effectiveness is 11.2 to 17.4 percent which converts to 14 to 21 percent on a

fuel economy improvement basis. This is similar to the 15 to 20 percent range estimated 

by Honeywell. The Porsche estimate for fuel economy improvement is consistent with

the incremental effectiveness values used in the NPRM and final rule. In response to the

NPRM, one manufacturer provided confidential business information related to 

turbocharging and downsizing effectiveness which was similar to NPRM and final rule 

estimates when using similar assumptions for technology application. 

As noted above NHTSA, in coordination with EPA, relied on engine teardown 

analyses conducted by EPA

171

, FEV and Munro to develop costs for turbocharged SGDI 

engines. Teardown studies are the one of the most effective ways to estimate 

technol

y 

PRM 

PRM, 

mpleted and those results are being used in the 

final an

ogy costs. For the proposal, only the 2.4L I4 DOHC to 1.6L I4 DOHC teardown 

study had been completed in time for inclusion in the NPRM, and results from that stud

were used as the cost in the 2012 model year. For other turbo-downsize costs, the N

primarily used values developed for the 2008 EPA staff report. Since issuing the N

two more teardown studies have been co

alysis with some adjustment. NHTSA, in coordination with EPA, has adjusted 

the I4 to I4 turbo-downsize costs slightly to reflect an updated burden rate172 employed 

 

171 U.S. Environmental Protection Agency, “Draft Report – Light-Duty Technology Cost Analysis Pilot 

Study,” Contract No. EP-C-07-069, Work Assignment 1-3, September 3, 2009, Docket EPA-HQ-OAR2009-0472-0149. 

172 Burden costs include the following fixed and variable costs: rented and leased equipment; 

manufacturing equipment depreciation; plant office equipment depreciation; utilities expense; insurance

(fire and general); municipal taxes; plant floor space (equipment and plant offices); maintenance of 

manufacturing equipment - non-labor; maintenance of manufacturing building - general, internal and 
DELIBERATIVE DOCUMENT – DO NOT RELEASE 

205

estimated costs as well. FEV made the assumption that these technologies would be 

mature when produ large volum

that there is potential for near term supplier-leve ng, design, and testing 

(ED&T) costs to be in excess of those considered in the FEV analysis (as existing 

equipm

We 

r the OHV applications, the agencies maintained consistency with the EPA 

008 S

year 

nd 

 

by FEV and an updated binning approach employed by the agencies to distinguish turborelated costs from downsize-related costs.173 NHTSA and EPA modified the other FEV

ced in es (450,000 units or more). The agencies believe 

l engineeri

ent and facilities must be converted to production of new technologies). The 

agencies have therefore decided to average the FEV results with the NPRM values. 

have also used the FEV results, where possible, to estimate costs for turbo-downsize 

scenarios that were not done via actual teardown study (e.g., FEV did not conduct a 

teardown of a V8 DOHC to turbocharged V6 DOHC). We have also used these values to 

estimate costs for other camshaft configuration changes that do not involve engine 

downsizing. 

Fo

2 taff Report and estimated direct manufacturing costs associated with downsizing 

to be $50 per cylinder, $10 per valve, and $100 per cam shaft for the 2015 model 

(2006$). Therefore, these costs have not changed relative to the NPRM. 

 Table V-18 shows how NHTSA developed the direct cost used by the Volpe 

model based on NPRM values and the FEV teardown cost study for turbocharging a

downsizing technology

 

173This “binning” approach simply bins the turbo-downsize-GDI total cost generated by FEV into separate 

 portion, and the GDI portion. 

external, parts, and labor; operating supplies; perishable and supplier-owned tooling; all other plant wages

(excluding direct, indirect and MRO labor); returnable dunnage maintenance; and intra-company shipping 

costs (see EPA-HQ-OAR-2009-0472-0149). 

cost bins for the turbo portion, the downsize
206

Table V-18. Calculation of Direct Manufacturing Cost for Turbocharging and Downsizing in MY 2012 (2007 dollars) DELIBERATIVE DOCUMENT – DO NOT RELEASE 

M d Final NPR FEV Teardown Analysis Base Cost Rule 

a b c d e f g h i 

Turbocharging and Do

(TRBDS) Direct 

Cost 

TRBDS 

wnsizing Direct 

Cost 

Turbocharging 

Dire

Cos

Downs

(w/o S

Downsi

ct 

t 

ize 

GDI 

ze)

Direct 

Cost 

Downsize 

(w/SGDI 

Downsize)

Co

1.2

T

ch

st with 

5 ICM 

urboarging 

Cost 

1.2

ICM

Down

with 

5 

size 

Total 

Cost with 

1.25 ICM 

for 

TRBDS 

Direc

Cos

TRBD

t 

t 

S 

Direc

Cost 

TRBD

V8 SOHC 2v --> V6 DOHC S $878 TRBD $681 ($84) ($149) $851 ($112) $740 $592 $735 V8 DOHC --> V6 DOHC TRBDS $554 $681 ($274) ($339) $851 ($254) $597 $478 $516 V8 OHV --> V6 DOHC TRBDS $990 $681 $315 $250 $851 $313 $1,164 $931 $961 V6 SOHC --> I4 DOHC TRBDS $410 $404 ($382) ($490) $505 ($368) $137 $110 $260 V6 DOHC --> I4 DOHC TRBDS $194 $404 ($547) ($655) $505 ($491) $14 $11 $102 V6 OHV --> I4 DOHC TRBDS $720 $404 $270 $162 $505 $203 $708 $566 $643 I4 SOHC --> I4 DOHC TRBDS $515 $404 ($80) ($80) $505 ($60) $445 $356 $356 I4 DOHC --> I4 DOHC TRBDS $336 $404 ($85) ($85) $505 ($64) $441 $353 $353 I4 OHV --> I4 DOHC TRBDS $515 $404 $65 $65 $505 $81 $586 $469 $469 

* Note that, where downsizing result st savings, the co d th

cost. The absolute value of the di facturing cost is t o thmanufacturing cost of -$149, the com ce cost would be ( 1 d

factor of 1.25 is used for the individu ulations for both t iz

s in co

rect manu

plian

al calc

mpliance cost is calculate

hen subtracted from that t

1.25-1) x │-$149│ - │-$

urbocharging and downs

as the IC markup less 1 

 arrive at the end result. 

49│ = -$112. Note beca

ing. 

which is then multi

 For example, for t

use the Volpe mode

plied by the absolute value of 

he V8 SOHC 2v downsized to

l combines turbocharging and 

e direct man

e V6 DOHC 

ownsizing, th
207

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Detailed descriptions o

Column a. NPRM cost for turbocharging and downsizing used by NHTSA including 

ngine 

al 

 these combinations and downsizing costs are shown in 

f each column in Table V-18 are listed below. 

downsizing of SGDI. 

Column b. FEV teardown study direct cost for turbocharging only. 

Column c. FEV teardown study direct cost for downsizing, but without downsizing of 

SGDI components. FEV conducted major teardown cost analysis on three e

combinations. For three of the other engine downsizing combinations, FEV 

conducted an incremental teardown study to determine costs. For three addition

combinations, cost was determined through calculation using incremental cost 

estimates. A summary of

Table V-19. More detailed explanation is provided in an EPA memo to the 

docket.[1]

Table V-19. Calculated Turbocharging Downsizing Technologies, but Without 

Downsizing of SGDI Components MY 2012 (2007$) 

Technologies Torn-Down 

by FEV Incremental Studied in FEV Calculated Technologies 

Name Value Name Value Name Value

V8 SOHC 3v-> 

V6 DOHC ($155) 

V8 SOHC 2v -> 

V8 SOHC 3v 

V8 SOHC 2v-> 

$72 V6 DOHC ($84) 

V8 SOHC 3v-> 

V6 DOHC ($155) 4) 

V8 SOHC -> V8 

DOHC ($119) 

V8 DOHC -> V6 

DOHC ($27

V6 DOHC -> I4 

DOHC ($547) 

OHC -> V6 

DOHC $165 

V6 SOHC -> I4 

 DOHC ($382) 

V6 S

g with ICM of 

Column d. FEV teardown study direct cost for downsizing including downsizing of 

SGDI components. Cost reduction for SGDI downsizing is based on FEV direct 

manufacturing costs in Table V-17. For V8 to V6 the SGDI cost reduction is 

$386 -$321 = $65, and for V6 to I4 the cost reduction is $321 - $213 = $108. 

Column e. FEV teardown study cost for turbocharging with ICM of 1.25 applied. 

Because the Volpe model combines turbocharging and downsizing, the ICM 

factor of 1.25 is used for the individual calculations for both turbocharging and 

downsizing. 

Column f. FEV teardown study cost for downsizing with ICM of 1.25 applied. 

Column g. FEV teardown study cost for turbocharging and downsizin

1.25 applied. Column g is the sum of column e and column f. 

Column h. FEV teardown study direct cost for turbocharging and downsizing. 

Column h is equal to column g divided by the ICM factor of 1.25. 

 

[1] Insert Mike’s docket number for bucketing memo. 
208

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

, 

V teardown based cost (column h). 

t a 30 

harging. 

e 

ine 

mented that 

onside

y 

e 

t 

 a 

modified from the MY 2011 final rule and are now 

limited nsidered the 

Column i. Final Rule direct cost for turbocharging and downsizing including 

downsizing of SGDI. For V8 to V6 TRBDS and for V6 to I4 TRBDS, column i is

the average of the NPRM direct cost (column a) and the FEV teardown study 

direct cost for turbocharging and downsizing (column h). For I4 to I4 TRBDS

Column i is equal to the updated FE

In response to the NPRM, NHTSA received comments from Honeywell tha

to 40 percent reduction in engine displacement is possible with the use of turboc

Also, if cylinder count is reduced, the cost savings in parts and assembly will offset th

costs of turbocharging. For example, replacing a 6-cylinder dual overhead cam eng

with a 4-cylinder turbocharged engine may be cost neutral. Honeywell com

c ration of the potential to decrease cylinder count and offset costs should be 

included in calculations for fleet fuel economy and implementation costs. 

In the NPRM and final rule, NHTSA uses downsizing ranging from 30 to 40 

percent, which is the same as the Honeywell comment. Also, the cost analysis 

methodology used in the NPRM and final rule account for downsizing and the reduction 

in cylinder count and parts, and in assembly costs. Based on the FEV teardown stud

cost estimates were revised in the final rule. NHTSA estimates the direct cost to replace 

a 6-cylinder dual overhead cam engine with a 4-cylinder turbocharged engine is $102, 

compared to Honeywell’s estimate of no cost difference. NHTSA believes that teardown

studies are the one of the most effective ways to estimate technology costs. In response to

the NPRM, NHTSA received comments from GM related to cost. GM commented that 

for a full-size truck product, the downsized boosted strategy is expected to yield less fuel 

economy benefit at higher cost than a direct injection V8 with aggressive usage of 

cylinder deactivation. NHTSA analysis shows the same relationship in cost, and the

Volpe model applies DEACO prior to TRBDS, recognizing the relationship. The Volp

model used for the NPRM and final rule provides one solution that manufacturers could 

use to meet CAFE regulations to demonstrate the feasibility of regulatory standards. It is 

expected that in many cases, manufacturers will identify and implement other 

combinations of technologies to achieve CAFE regulatory compliance, based on their 

unique circumstances. 

In response to the NPRM, NHTSA received comments from GM that the engine

oil service schedule must be more robust for turbocharged engines to avoid premature 

wear on oiled engine components. For this rulemaking, NHTSA analysis does not 

include maintenance costs. NHTSA intends to investigate maintenance costs and 

consider including them in future rules. 

NHTSA estimates that the MY 2012 incremental compliance cost, including a 

medium complexity ICM mark-up of 1.25, for a turbocharged and downsized engine is 

$445 to downsize from an I-4 SOHC naturally-aspirated engine to a smaller displacemen

I-4 DOHC turbocharged engine, $325 for a downsize from a V-6 SOHC naturallyaspirated engine to an I-4 DOHC turbocharged engine, and $919 for a downsize from

V-8 SOHC naturally-aspirated engine to a V-6 DOHC turbocharged engine. 

Phase-in caps have been 

to 85 percent per year with time-based learning applied. NHTSA co
209

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

comple e 

applied at redesign only. There are no subclass specific limitations on its application. 

(EGRB)

Cooled exhaust gas recirculation (cooled EGR) or EGR Boost is a combustion 

concept tha stion 

mper

f 

ss” 

issues t

mated in 

cost impact of approximately $173 

based o confidential individual component cost data from 2008 Martec describing EGR 

cooler costs of $75, EGR valve costs of $20 and associated piping costs of $20, totaling 

$115 (non-RPE). For purposes of this rulemaking, NHTSA found no information to 

indicate that these estimates were inaccurate. To that end, NHTSA applied an indirect 

cost multiplier of 1.25, for a medium complexity technology, resulting in a compliance 

cost of $144 for MY 2012 vehicles with time-based learning applied. EGRB can be 

 

xity of implementing this technology and determined that this technology can b

(10) Cooled Exhaust Gas Recirculation/EGR Boost 

t involves utilizing EGR as a charge dilutant for controlling combu

te atures and cooling the EGR prior to its introduction to the combustion system. 

Higher exhaust gas residual levels at part load conditions reduce pumping losses for 

increased fuel economy. Cooled EGR reduces knock sensitivity which enables the use o

more optimal spark advance or enables compression ratio to be increased for improved 

thermal efficiency, and increased fuel economy. Currently available turbo, charge air 

cooler, and EGR cooler technologies are sufficient to demonstrate the feasibility of this 

concept. 

 However, this remains a technology with a number of issues that still need to be 

addressed and for which there is no production experience. EGR system fouling 

characteristics could be potentially worse than diesel EGR system fouling, due to the 

higher HC levels found in gasoline exhaust. Turbocharger compressor contamination 

may also be an issue for low pressure EGR systems. Additionally, transient controls of 

boost pressure, EGR rate, cam phasers and intake charge temperature to exploit the 

cooled EGR combustion concept will require development beyond what has already been 

accomplished by the automotive industry. These are all “implementation readine

hat must be resolved prior to putting EGR Boost into high volume production. 

 NHTSA has concluded that these implementation issues could be resolved 

and this technology could be brought to production by MY 2013. Supporting this 

conclusion, MEMA has previously suggested a 5 to 7 percent effectiveness for 

cooled EGR systems, although without boosting.174 Two public sources indicate a 

10 to 20 percent fuel consumption effectiveness for a downsized DI engine with 

cooled EGR compared to a naturally aspirated baseline enginei

 and a 4 percent fuel 

consumption effectiveness for cooled EGR compared to a conventional downsized 

DI turbocharged engine.ii Based on the data from these reports, NHTSA estimates 

the incremental reduction in fuel consumption for EGR Boost to be 4 percent over a 

turbocharged and downsized DI engine. Thus, if TRBDS precedes EGRB, adding 

the 12 percent gain from TRBDS to the 4 percent gain from EGRB results in total 

fuel consumption reduction of 16 percent. This is in agreement with the range 

suggested in the Lotus report.

Regarding costs, the addition of EGR cooler and EGR valve were esti

NHTSA’s MY 2011 rule to have an incremental RPE 

n

174 Docket No. NHTSA-2008-0089-0193.1 
210

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

 learning applied. NHTSA considered the complexity of 

implementing this technolog ined that this techno at 

redesign 

e T logie

D cteristics that give them rior iency 

compared ines. Pum sses uch 

lower du e diesel co on erates 

at a highe lean air/fuel mixture, and turboch d lightduty dies r torque levels at lower ne sp than 

equivalen asoline engines. Additionally sel fuel 

has a hig 5

 

D ssions characteristics that presen lenge eeting 

federal T a significant system ineeri hallenge 

to mainta tage of the diesel engine while meeting U.S. 

emission consumption can be negatively imp y em

reduction gies employed. Emission 

mpliance strategies for diesel vehicles sold in the U.S. are expected to include a 

combin

ent. 

n pressure and 

multiple-injection capability), advanced controls and sensors to optimize combustion and 

emissions performance, higher EGR levels and EGR cooling to reduce NOx, and 

advanced turbocharging systems. 

 On the aftertreatment side, the traditional 3-way catalyst aftertreatment found on 

gasoline-powered vehicles is ineffective due to the lean-burn combustion of a diesel. All 

diesels will require a diesel particulate filter (DPF) or catalyzed diesel particulate filter 

(CDPF), a diesel oxidation catalyst (DOC), and a NOx reduction strategy to comply with 

Tier 2 emissions standards. The most common NOx reduction strategies include the use 

of lean NOx traps (LNT) or selective catalytic reduction (SCR), which are outlined 

below. 

 

applied to all vehicle classes starting in MY 2013. Phase-in caps are limited to 85 

percent per year with time-based

y and determ logy can be applied

only. 

(11) Diesel Engin echno s 

iesel engines have several chara supe

p lo

fuel effic

 to conventional gasoline, spark-ignited eng

rottling. Th

ing are m

e to lack of (or greatly reduced) th

, with a very 

mbusti cycle op

r compression ratio arge

els typically achieve much highe engi eeds 

t-displacement naturally-aspirated g , die

her energy content per gallon.17

iesel engines have emi t chal s to m

ier 2 NOx emissions standards. It is 

sumption advan

s-eng ng c

in the fuel con

s regulations. Fuel acted b issions 

 strategies depending on the combination of strate

co

ation of combustion improvements and aftertreatment. These emission control 

strategies are being introduced on Tier 2 light-duty diesel vehicles today 

To achieve U.S. Tier 2 emissions limits, roughly 45 to 65 percent more NOx

reduction is required compared to the Euro VI standards. Additionally, as discussed 

below, there may be a fuel consumption penalty associated with diesel aftertreatment 

since extra fuel is needed for the aftertreatment, and this extra fuel is not used in the 

combustion process of the engine that provides power to propel the vehicle. 

Light-duty diesel emissions control systems capable of meeting Tier 2 Bin 5 

emission standards are already in production. Several key advances in diesel technology

have made it possible to reduce emissions coming from the engine prior to aftertreatm

These technologies include improved fuel systems (higher injectio

175 Burning one gallon of diesel fuel produces about 15 percent more carbon dioxide than gasoline due to 

the higher density and carbon to hydrogen ratio. 
211

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

A lean N erate in by NO 2 exh

and stor lkali sorben teria en ntrol d ines

mathematical model or a NOx sensor) tha trap is saturated with NO , it switch

ing mo ay me ct the 

m to produce exce o tha a re ag convert the 

 thereby “re ing” NT an nin ore 

stored. L tially sto lfate 

talytic rma The mus ergo dic 

erating at a net-fuel-rich condition at high temperatures in order to 

iciency. 

ded that diese es o ll veh ou LNTe did no de el option for sm hic ause it did 

st effective so on comments received from 

A, an e ar ding el o for small 

l rule, and we the Vo odel oose ther to 

ould b ted th Volpe model an ysis p es one 

s coul to m CAFE lation emonstrate 

andard is exp ted that in many c anu cturers will 

d implement other co atio technologies to a e CA regulat 

eir uniqu rcumstances. 

Diesel En with tive C tic Red n (SC fteren

eatment sy us duc pica mo rived 

that is injected into the ex tr ead o SCR st. s 

he hardware configuration for an 

CR system is more complicated than that of an LNT, due to the onboard urea storage 

ry system (which requires a urea pump and injector to inject urea into the 

 for NOx reduction, 

ma

and

cou

and to Tier 2, Bin 5 emission standards. Based on 

sig

use e 

Cat

ME

tha

Diesel Engine with Lean NOx Trap (LNT) Catalyst After-Treatment

Ox trap op

ing NO2 on a

s, in pr

t ma

ciple, 

l. Wh

oxidizing 

 the co

 to NO

system

in the 

eterm

a

 (via 

es the 

ust 

t the 

 in so

x

engine into a rich operat de or m cases inje fuel directly into 

exhaust strea ss hydr carbons t act as ducing ent to 

stored NOx to N2 and water,

locations for NOx to be 

generat

eferen

 the L

re su

d ope

compou

g up m

NTs pr nds from the 

fuel, which can reduce ca perfo nce. system t und perio

desulfurization by op

retain NOx trapping eff

NHTSA has conclu l engin n sma icles w ld be 

based. In the NPRM, w

not appear to be a co

t inclu

lution. Based 

 a dies all ve les bec

BorgWarner, ICCT, MEM d Mr. Schade w e inclu a dies ption

vehicles in the fina are allowing 

e no

lpe m to ch

al

 whe

apply the technology. It sh rovid

solution that manufacturer

at the 

d use eet regu s to d

feasibility for regulatory st

identify an

s. It

mbin

ec

ns of

ases, m

chiev

fa

FE ory

compliance, based on th e ci

gine Selec ataly uctio R) A

Treatm t 

An SCR aftertr stem es a re tant (ty lly, am nia de from

urea) haust s eam ah f the cataly Ammonia react

with NOx in the SCR catalyst to form N2 and water. T

S

and delive

exhaust stream). While a rich engine-operating mode is not required

the urea is typically injected at a rate of approximately 3 percent of the fuel consumed. 

Manufacturers designing SCR systems intend to align urea tank refills with standard 

intenance practices such as oil changes. As is the case with LNT-based diesels, EPA 

 NHTSA project that SCR-based diesel engines will be available within the next 

ple of years. Mercedes-Benz recently introduced two 2009 model year vehicles R320 

 GL320, both of which are certified

public announcements from several other companies, an increased number of product 

offerings from multiple companies are expected over the next few years. 

In response to the NPRM, NHTSA received comments from MECA that 

nificant criteria emission reductions from diesel vehicles can be achieved through the 

 of several technologies, including: Diesel Particulate Filters (DPFs), and Selectiv

alytic Reduction (SCR) and Lean NOx Adsorber Catalysts for Diesel Engines. 

CA provided a detailed description of these technologies. MECA also commented 

t these emission control technologies allow all high efficiency powertrains to compete 
212

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

in t

pol In nearly all cases, these fuel-efficient powertrain designs, combined 

with appropriate emission controls, can be optimized to either minimize fuel consumption 

ove

and

reg s during the rulemaking period, and therefore enabling diesel engine 

ass

veh around 2.0 liters 

wa

sys

veh n in-line 4-cylinder diesel engine, with displacement varying around 2.8 liters 

mo

per

Tru arge Car vehicle classes for the CAFE model. It was assumed 

res

red

NH er 

data ction of SCR-based diesel system to be between 

rec

effi

con

ME d 

veh n a fuel 

MY

gas

per ental to a turbocharged downsized 

gasoline engine (TRBDS) with EGRB, and a 10.8 to 13.9 percent incremental 

n 

restart (CBRST). 

The

• Fuel systems (higher pressures and more responsive injectors); 

he marketplace by enabling these powertrains to meet current and future criteria 

lutant standards. 

impacts associated with the emission control technology, or, in some cases, improve 

rall fuel consumption of the vehicle. 

As the NPRM and final rule, include descriptions of each of these technologies 

 cite these technologies as enablers for diesel engines to meet criteria emission 

ulation

technology to be included as a viable fuel economy improving technology during the 

rulemaking period, NHTSA views MECA’s comments as supporting NHTSA’s 

essment of the feasibility of diesel engine technology in the final rule. 

In order to maintain equivalent performance to comparable gasoline-engine 

icles, an in-line 4-cylinder diesel engine, with displacement varying

was assumed to replace an I4 gasoline base engine for Subcompact, Compact, and 

Midsize Passenger Car, Performance Subcompact Car and Small Light Truck classes. It 

s assumed that diesel engines for these classes would utilize LNT aftertreatment 

tems. 

In order to maintain equivalent performance to comparable gasoline-engine 

icles, a

was assumed to replace a V6 gasoline base engine for Performance Compact, 

Performance Midsize, Large Passenger Car, Minivan, and Midsize Truck for the CAFE 

del. A V6 diesel engine, with displacement varying around 4.0 liters to meet vehicle

formance requirements, was assumed to replace a V8 gasoline base engine for Large

ck and Performance L

that diesel engines for these classes would utilize SCR aftertreatment systems. 

Confidential manufacturer and non-confidential comment data submitted in 

ponse to NHTSA’s past rulemaking for diesel engines showed a fuel consumption 

uction in the range of 16.7 percent to 26.7 percent over a baseline gasoline engine. 

TSA’s MY 2011 CAFE final rule, which was supported by confidential manufactur

, estimated the fuel consumption redu

20 to 25 percent over a baseline gasoline engine. In response to the NPRM, NHTSA 

eived comments from MECA that light duty diesel powertrains have higher fuel 

ciency compared to gasoline engines on the order of 20 percent to 40 percent. This 

verts to between 16.7 and 28.6 percent on a fuel consumption effectiveness basis. 

MA commented that compared to a traditional gasoline engine, clean diesel-powere

icles average 30 percent better fuel economy. This converts to 23.1 percent o

consumption basis. Based on review of all of this information, NHTSA judged that the 

 2011 estimate of 20 to 25 percent fuel consumption reduction over a baseline 

oline engine remains the best estimate for this final rule. This equates to a 5.3 to 6.9 

cent improvement for DSLT, which is increm

improvement for DSLC, which is incremental to a gasoline engine with combustio

Diesel engines are more costly than port-injected spark-ignition gasoline engines. 

se higher costs result from: 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

• Engine design (higher cylinder pressures require a more robust engine, but 

ent); 

201 final rule analysis, NHTSA in consultation with EPA chose to re-analyze 

and

rep

(LN

NESCCAF facturing costs of $1,500 to $1,950. More recently, 

cyl

SC

sys

tho

tha

e 

wit

show generally lower than the MY 2011 CAFE final rule 

ated. 

EPA and NHTSA engineers decided that an update to the engine-related costs would 

• Controls and sensors to optimize combustion and emissions performance; 

higher torque output means diesel engines can have reduced displacem

• Turbocharger(s); 

• Aftertreatment systems, which tend to be more costly for diesels; 

Due to a significant decrease in platinum group metal prices since NHTSA’s MY 

1 CAFE 

diesel costs. In EPA’s 2008 Staff Report, costs were considered for two types of diesel 

systems: one using a lean-NOx trap (LNT) along with a diesel particulate filter (DPF); 

 one using a selective catalytic reduction (SCR) system along with a DPF. In that 

ort, EPA estimated direct manufacturing costs to range from $1,860 for the small car 

T plus DPF) to $2,710 for the large truck (SCR plus DPF). For comparison, the 

study showed direct manu

NHTSA’s 2011 CAFE final rule showed direct manufacturing costs of $2,670 for a 4-

inder engine using a LNT plus DPF system, $3,735 for a 6-cylinder engine using a 

R plus DPF system, and $4,668 for an 8-cylinder engine using a SCR plus DPF 

tem. NHTSA noted that estimates in the MY 2011 CAFE final rule were higher than

se shown in the proposed rule due largely to the spike in platinum group metal prices 

t had occurred in the months just prior to issuing the 2011 CAFE final rule. 

The following diesel costs were developed by EPA, drawing on their experienc

h diesel engine and aftertreatment systems. A breakdown of the cost estimates is 

n in Table V-. These costs are 

assumptions and were developed by taking a look back at EPA’s 2008 Staff Report, 

which reveals a couple of factors that resulted in somewhat misleading costs. First, the 

engine costs estimated there did not take into account the downsizing that would occur 

when moving from a gasoline engine to a diesel engine (provided equivalent performance

was maintained). Second, the engine costs used in that analysis were actually stated in

terms of 2002 dollars rather than 2006 dollars in which the report was meant to be st

provide a much better cost estimate for converting to diesel. This was done by starting 

with the source for engine costs in the 2008 staff report which was an October 2005 EPA

Interim Reportiii which, in turn, sourced estimates from a 2003 study done by FEV for 

EPA contained within a 2004 EPA Interim Technical Report.iv These direct 

manufacturing costs are reproduced in Table V-20 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table V-20 Diesel Engine Direct Manufacturing Source Costs, Incremental to a Baseline 

Gasoline Engine (2002 dollars)

Component(s) Large SUV Midsize

Gasoline engine (baseline) 5L V8 2.4L I4 

Diesel engine 4L V8 2.2L I4 

Add high-pressure, common rail diesel fuel injection system $980 $630 

Delete gasoline fuel injection system -$245 -$165 

Add variable geometry turbocharger $175 $126 

Delete gasoline ignition system -$120 -$75 

Delete fuel pump and other changes to fuel system -$94 -$75 

Enhance powertrain mounting system $87 $107 

Other engine changes $80 $70 

Add air intercooler, ducts, and sensor $80 $55 

Larger battery and starter, add g s lo g w plu $72 $50 

Delete exhaust gas oxygen sensor* -$60 -$30 

Add supplemental heater $50 $15 

Modify transmission $25 $25 

Enhance sound insulation package $25 $10 

Smaller radiator -$13 -$4 

Total $1,042 $739 

Note: Table reproduced from EPA4 -012, Oc 05 20-R-05 tober 20

 

Building on the direct manufacturing costs shown in Table V-20, the agencies 

 a 4.5L V8 gasoline to a 3L V6 

d from a 3.2L V6 gasoline to a 2.8L I4 diesel; and a large truck converted from a 

5.6L to a 4 el. T s for ase di

n in m T -20 hav

ing the G e defl r of 1 Appe ). Sin

were develo t ysis co s the c

21 as b pplicab e 2012 ear. 

used appropriate scaling to estimate the costs for replacing a baseline gasoline engine 

with a diesel engine for the following five situations: a small car converted from a 2.4L 

I4 gasoline to a 2L I4 Diesel; a large car converted from

diesel; a medium/large MPV converted from a 3.2L V6 to a 2.8L I4 diesel; a small truck

converte

 V8 gasoline

e show

L V6 dies

 Table V-21.

he result

 Values fro

 the five b

able V

 gasoline to

updated to 

esel 

conversions ar

2007 dollars us

e been 

DP pric ator facto .15 (see ndix 3.A ce the 

source costs ped in 2003, his anal nservatively consider osts 

shown in Table V- eing a le to th model y
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Tabl gine Di ufactu ed-C , Inc Basel

Gaso 07 doll

ponent(s) all 

car 

Me

M

Sma

truc

rge 

ck 

e V-21 Diesel En

line Engine (20

rect Man

ars) 

ring Scal osts in 2012 remental to ine 

Com Sm Large 

car 

d/large 

PV 

ll 

k

La

tru

Notes 

(see text 

below)

Gasoline engine (baseline) 2.4L I4 V8 3.2L V6 3.2L V6 5.6L V8 4.5L 

Diesel engine 2.0L I4 3L V6 2.8L I4 2.8L I4 4L V6 

Add high-pressure, common rail 

diesel fuel injection system $517 $1,026 $724 $724 $1,026 1 

Delete gasoline fuel injection 

system -$52 -$89 -$73 -$73 -$89 2 

Add variable geometry 

turbocharger $145 $173 $145 $145 $201 3 

Delete gasoline ignition system -$69 -$138 -$112 -$112 -$138 4 

Delete fuel pump and other 

changes to fuel system -$62 -$108 -$86 -$86 -$108 5

Enhance powertrain mounting 

system $123 $100 $123 $123 $100 6 

Other engine changes $57 $86 $80 $80 $86 7 

Add air intercooler, ducts, and 

sensor $45 $78 $63 $63 $92 8 

L

g

arger battery and starter, add 

low plu $57 $70 $57 $57 $70 9 gs 

Delete exhaust gas oxygen 

sensor* $0 $0 $0 $0 $0 10 

Add supplemental heater $17 $37 $17 $17 $57 11 

Modify transmission $29 $29 $29 $29 $29 12 

Enhance sound insulation package $11 $20 $11 $11 $29 13 

Smaller radiator -$7 -$15 -$10 -$10 -$15 14 

Engine downsize credit $0 -$185 -$390 -$390 -$185 15 

Total $813 $1,085 $580 $580 $1,156 

* Note: Oxygen sensor removals are included in aftertreatment costs. 

NOTES: 

The costs shown in Table V-21 were scaled in the following ways: 

1. Large car and large truck cal d 

25% of midsize car; medium/ e 

V-20’s midsize car; small car calculated using rge MPV value of 

$724 and applying the ratio of diesel engine sizes (2.0/2.8). Values converted to 2007 

dol

tems 

/fuel 

culate as 75% the cost of Table V-20’s large SUV and 

large MPV and small truck calculated as equal to Tabl

 Table V-21’s Med/la

lars using GDP factor of 1.15. 

2. The estimates generated by FEV for eliminating the gasoline fuel injection sys

were considerably larger than EPA & NHTSA believed was appropriate. Therefore, 

for a more accurate estimate, these costs were estimated, in 2007 dollars as follows: 

large car and large truck were calculated using incremental costs of $8/injector, 

$20/fuel rail, and $5 for a pressure damper or $8x8+$20+$5=$89; medium/large 

MPV and small truck were calculated using incremental costs of $8/injector, $20

rail, and $5 for a pressure damper or $8x6+$20+$5=$73; small car calculated using 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

3. Large car calculated as the av f Table V size car; 

medium/large MPV and small truck calculated as equal to Table V-20’s midsize car, 

and

 of 

’s 

f -

arge SUV; small car 

calculated using Table s Med/larg e ratio of 

diesel engine sizes (2.0/2.8). Values conv f 

1.1

r; 

onverted to 2007 dollars using GDP factor of 1.15. 

11. Medium/large MPV and small truck calculated as equal to Table V-20’s midsize car; 

Large car calculated as the average of Table V-20’s large SUV and midsize car; 

Table V-21’s Med/large MPV value of -$73 and applying the ratio of diesel engine 

sizes (2.0/2.8). 

erage o -20’s large SUV and mid

 large truck calculated as equal to Table V-20’s large SUV; small car calculated as 

equal to medium/large MPV. Values converted to 2007 dollars using GDP factor

1.15. 

4. Medium/large MPV and small truck calculated as the average of Table V-20’s large 

SUV and midsize car; Large car and large truck calculated as equal to Table V-20

large SUV; small car calculated as equal to half of Table V-21’s large truck value o

$138. Values converted to 2007 dollars using GDP factor of 1.15. 

5. Medium/large MPV and small truck calculated as equal to Table V-20’s midsize car; 

Lar ar and large truck calculated as equal to Table V-20’s l ge c

V-21’ e MPV value of -$86 and applying th

erted to 2007 dollars using GDP factor o

5. 

6. Medium/large MPV and small truck calculated as equal to Table V-20’s large SUV; 

Large car and large truck calculated as equal to Table V-20’s midsize car; small car 

calculated as equal to medium/large MPV. Values converted to 2007 dollars using 

GDP factor of 1.15. 

7. Medium/large MPV and small truck calculated as equal to Table V-20’s midsize ca

Large car and large truck calculated as the average of Table V-20’s large SUV and 

midsize car; small car calculated using Table V-21’s Med/large MPV value of $80 

and applying the ratio of diesel engine sizes (2.0/2.8). Values converted to 2007 

dollars using GDP factor of 1.15. 

8. Medium/large MPV and small truck calculated as equal to Table V-20’s midsize car; 

Large car calculated as the average of Table V-20’s large SUV and midsize car; 

Large truck calculated as equal to Table V-20’s large SUV; small car calculated using

Table V-21’s Med/large MPV value of $63 and applying the ratio of diesel engine 

sizes (2.0/2.8). Values c

9. Medium/large MPV and small truck calculated as equal to Table V-20’s midsize car; 

Large car and large truck calculated as the average of Table V-20’s large SUV and 

midsize car; small car calculated as equal to medium/large MPV. Values converted 

to 2007 dollars using GDP factor of 1.15. 

10. Oxygen sensor costs are included in the aftertreatment costs discussed below. 

Large truck calculated as equal to Table V-20’s large SUV; small car calculated as 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

equ

14. Medium/large M small tru e 

SUV and midsize arge car a s 

large SUV; small car calculated using Table /large MPV value of -$10 

and

D 

e at 

al to medium/large MPV. Values converted to 2007 dollars using GDP factor of

1.15. 

12. Values from Table V-20 converted to 2007 dollars using GDP factor of 1.15. 

13. Medium/large MPV and small truck calculated as equal to Table V-20’s midsize car; 

Large car calculated as the average of Table V-20’s large SUV and midsize car; 

Large truck calculated as equal to Table V-20’s large SUV; small car calculated as 

equal to medium/large MPV. Values converted to 2007 dollars using GDP factor of 

1.15. 

PV and ck calculated as the average of Table V-20’s larg

 car; L nd large truck calculated as equal to Table V-20’

 V-21’s Med

 applying the ratio of diesel engine sizes (2.0/2.8). Values converted to 2007 

dollars using GDP factor of 1.15. 

15. Based on the approach presented in the turbocharging/downsizing section of the TS

(section 3.5.2.1.11), the savings associated with downsizing the gasoline engine were

calculated by estimating the cost in 2007 dollars of each cylinder at $51, each valv

$10, and each cam at $103.176 Therefore, the large car and large truck, which each 

lose two cylinders (-$102), eight valves (-$82) and no cams realize a $185 savings. 

The medium/large MPV and small truck would each lose two cylinders (-$102) and 

eight valves (-$82) and two cams (-$205) for a savings of $390. The small car 

downsizing credit was left at $0 given the small displacement change and lack of 

cylinder or valve removals. 

For the diesel aftertreatment systems, the approach taken is consistent with the 

approach taken in EPA’s 2007/2010 Highway Diesel rule and EPA’s recent locomotive 

and marine rule.177 For platinum group metal costs, monthly average prices as of March 

2009 as reported by Johnson-Matthey were used.178 Those values were $1,085/troy 

ounce for platinum and $1,169/troy ounce for rhodium. Aftertreatment devices were 

sized according to the diesel engine displacement with a 1:1 ratio for both the SCR 

 

176 These are the correct costs for the 2015MY in 2007$. But, they are used here erroneously as 2012MY 

values. Technically, 3 years of time-based learning should have been backed out to get 2012MY values. 

So, the 2012MY costs are slightly underestimated by roughly $10. This was true in the proposed a

and, because it has no meaningful impact on the analysis (1-2% of the estimated diesel costs), continues to 

be true in the final analysis. 

177 EPA’s 2007/2010 diesel heavy-duty highway final rule at 66 FR 5002; EPA’s Locomotive and Marine 

final rule at 73 FR 37096. 

178

nalysis 

http://www.platinum.matthey.com These are the PGM prices used in the NPRM. As precious metals, 

PGM prices swing widely year-to-year and even month-to-month. Given economic conditions during the 

past year and the tendency of investors during tough economic times to invest in valuable metals such as 

gold and PGMs, PGM prices have increased considerably since the NPRM. Were the January 2010 PG

prices used, the diesel costs presented here would increase on the order of 10-20 percent. That would s

M 

erve 

to make diesels less cost effective options for improving fuel economy or reducing GHGs. Since diesels 

ven 

s for purposes of this rulemaking. 

comprise such a small percentage of each agency’s analysis from a technology penetration standpoint, e

using the lower March 2009 PGM prices, the choice of what PGM prices to use is of little consequence to 

the analytical result
218

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Also 

rge truck 

catalyst and the DPF, and a 0.5:1 ratio for the DOC (i.e., the DOC is half the 

displacement of the engine). The end result for aftertreatment devices, including a urea 

dosing unit, urea tank and necessary brackets and heaters, are shown in Table V-2. 

shown in Table V-2 are the savings associated with removal of the gasoline catalyst. 

Note that the gasoline catalyst was sized according to the gasoline engine that served as 

the baseline engine. 

Table V-22 Diesel Aftertreatment Direct Manufacturing Costs in 2012 (2007 dollars) 

Component(s) Small car Large car Med/large 

MPV Small truck La

Gasoline engine (baseline) 2.4L I4 4.5L V8 3.2L V6 3.2L V6 5.6L V8 

Diesel engine 2.0L I4 3L V6 2.8L I4 2.8L I4 4L V6 

DOC $216 $277 $257 $257 $339 

DPF (in

OBD & $668 cludes a $20 pressure sensor for 

 sensing) $401 $534 $503 $503 

SCR sy

OBD & $996 stem (includes a $50 NOx sensor for 

 sensing) n/a $904 $904 $914 

LNT Sy

OBD a /a s udes $50 NOx sensor for 

nd sensing $442 n/a n/a n/a n tem incl

Removal of gasoline catalysts & sensors -$175 -$401 -$288 -$298 -$483 

Total $883 $1,314 $1,376 $1,376 $1,520 

The incremental costs to convert from a gasoline to a diesel engine—Table V-21 

and Table V-2 combined—are shown in Table V-23. 

Table V-23 Direct Manufacturing Costs to Convert from a Gasoline to Diesel System in 20

dollars) 

Component(s) Small car Large car Med/large 

MPV Small truck Large truc

12 (2007 

k 

Gasoline engine 

(baseline) 2.4L I4 4.5L V8 3.2L V6 3.2L V6 5.6L V8 

Diesel engine 2.0L I4 3L V6 2.8L I4 2.8L I4 4L V6 

Engine-related costs $813 $1,085 $580 $580 $1,156 

Aftertreatment $883 $1,314 $1,376 $1,376 $1,520 

Total $1,697 $2,399 $1,956 $1,956 $2,676 

 

 

This analysis applies time-based learning to diesel systems and a medium 

complexity rating of 1.25. Therefore, the MY 2012 compliance costs are as shown in 

Table V-2. 

Table V-24 Compliance Costs to Convert from a Gasoline to Diesel System in 2012 (2007 dollars) 
219

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Component(s) Small car Large car Med/large 

MPV Small truck Large truck 

Gasoline engine 3.2L V

(baseline) 2.4L I4 4.5L V8 3.2L V6 6 5.6L V8 

Diesel engine 2.0L I4 3L V6 2.8L I4 2.8L I4 4L V6 

Total $2,121 $2,999 $2,445 $2,445 $3,345 

G

g

iven the above analysis, NHTSA estimated that the compliance cost of converting an I4 

asoli

incremental 

de de A 012 $24 s estima verting 

a V6 gasoline eng diesel en s an incremental 

st of $689 o $1,257 f SLT a 1,226 ,6

estimated fo erting aso e eng

This resu s in an incremental c ance c of r 

,945 to $2,667 for DSLC. These compliance costs

M mark 1.25. I onse t e NPR A

n of the I4 gasoline to 

.0L Turbcharged that was a

the cost estimates this final 

 engines 

t 

l 

to 

lock-up o

 Converter Lockup are best 

optimized simultaneously due to the fact that adding both of them primarily requires only 

ne engine to a 2.0L diesel engine was $2,121 for MY 2012. This results in an 

compliance cost of $759 to $907 T and $1,346 to $1,519 for DSLC, 

cision tree path. 

ine to a 2.8L I4

 for DSL

 cost of

gine. This re

pending on MY 2 45 wa

ults in

ted for con

compliance co

2012 cos

 t or D

r conv

nd $

a V8 g

to $1

lin

92 for DSLC. A MY 

t of $3345 was V6 

diesel engine. 

ine to a 4.0L

lt ompli ost $1,097 to $1,478 fo

DSLT and $1

complexity IC

 include the medium 

up of n resp o th M, C RB commented that 

diesel cost estimates in the NPRM were generally consistent with their own. As costs in 

the final rule are unchanged from the NPRM, with the exceptio

2 Diesel dded for the final rule, the CARB comment supports 

used in rule. 

The diesel engine technology can be applied to all vehicle classes. Diesel

can only be applied at redesign with time-based learning. NHTSA assumed a 3 percen

phase-in cap for diesels in MY2012 and increasing 3 percent per year reaching a 

maximum of 15 percent in MY 2016. 

b. Transmission Technologies 

 

NHTSA has reviewed the transmission technology estimates used in the MY 2011 

CAFE final rule and considered or reconsidered all available sources and updated the 

estimates as appropriate. The section below describes each of the transmission 

technologies considered for this rulemaking. 

(12) Improved Automatic Transmission Contro

(IATC) (Aggressive Shift Logic and Early Torque

Converter Lockup) 

Calibrating the transmission shift schedule to upshift earlier and quicker, and 

r partially lock-up the torque converter under a broader range of operating 

conditions can reduce fuel consumption. However, this operation can result in a 

perceptible degradation in noise, vibration, and harshness (NVH). The degree to which 

NVH can be degraded before it becomes noticeable to the driver is strongly influenced by

characteristics of the vehicle, and although it is somewhat subjective, it always places a 

limit on how much fuel consumption can be improved by transmission control changes. 

Given that the Aggressive Shift Logic and Early Torque
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

minor m

f 

er parameters such as 

temperature. Aggressive shift logic (ASL) can be employed in such a way as to 

maxim

the 

, 

el the vehicle, and noise and vibration are not excessive. If the 

torque converter cannot be fully locked up for maximum efficiency, a partial lockup 

strategy

Regarding the effectiveness of Improved Automatic Transmission Control, the 

MY201

 to 

 

 For the purpose of this rule, NHTSA concluded that the 

combin

odifications to the transmission or calibration software, these two technologies 

are combined in the modeling. 

(13) Aggressive Shift Logic

During operation, an automatic transmission’s controller manages the operation o

the transmission by scheduling the upshift or downshift, and locking or allowing the 

torque converter to slip based on a preprogrammed shift schedule. The shift schedule 

contains a number of lookup table functions, which define the shift points and torque

converter lockup based on vehicle speed, throttle position, and oth

ize fuel efficiency by modifying the shift schedule to upshift earlier and inhibit 

downshifts under some conditions, which reduces engine pumping losses and engine 

friction. The application of this technology does require a manufacturer to confirm that 

drivability, durability, and NVH are not significantly degraded. 

 

(14) Early Torque Converter Lockup

A torque converter is a fluid coupling located between the engine and 

transmission in vehicles with automatic transmissions and continuously-variable 

transmissions (CVT). This fluid coupling allows for slip so the engine can run while 

vehicle is idling in gear (as at a stop light), provides for smoothness of the powertrain

and also provides for torque multiplication during acceleration, and especially launch. 

During light acceleration and cruising, the inherent slip in a torque converter causes 

increased fuel consumption, so modern automatic transmissions utilize a clutch in the 

torque converter to lock it and prevent this slippage. Fuel consumption can be further 

reduced by locking up the torque converter at lower vehicle speeds, provided there is 

sufficient power to prop 179

 can be employed to reduce slippage. Early torque converter lockup is applicable

to all vehicle types with automatic transmissions. Some torque converters will require 

upgraded clutch materials to withstand additional loading and the slipping conditions 

during partial lock-up. As with aggressive shift logic, confirmation of acceptable 

drivability, performance, durability and NVH characteristics is required to successfully 

implement this technology. 

1 CAFE final rule, which was supported by the 2002 NAS and NESCCAF reports

as well as confidential manufacturer data, estimated an effectiveness improvement of 1

2 percent for aggressive shift logic and 0.5 percent for early torque converter lockup.

These estimates are in agreement with the values stated in the NESCCAF report and 

confidential manufacturer data. 

ed estimated effectiveness is 1.5 to 2.5% reduction in fuel consumption. 

 

179 Very aggressive early torque converter lock up may require an adjustment to damper stiffness and 

hysteresis inside the torque converter. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

e 

e based 

se 

ic 

ed with 

Ys 2012 

(NAUTO) 

 6-, 7-, 

 of 

 to 

n 

-

UTO) from a 

4- or 5-sp

consu eline 

4 or 5 sp ission without IATC em onsumpti would 

rce TSA wed th fecti

 acc . In re se to the M, P

ese incremental effectiveness values used in the NPRM and final rule.In 

e NPRM, 

For a cost estimate, and for a MY 2012 vehicle, NHTSA updated the MY 2011 

CAFE final rule estimate of $59 with a 1.5 RPE to $60 with a low complexity ICM 

markups value of 1.11. This reflects a revisiting of component costs for the early torqu

converter lock-up technology which potentially involves hardware changes. Tim

learning methods are applied so subsequent MY costs are lower. Given the relative ea

of implementation, from a manufacturing perspective, the Volpe model can apply IATC

at either the refresh or redesign product cycle, and there are no subclass specif

limitations on its application other than that the baseline vehicle must be equipp

an automatic transmission. Phase-in caps in this rule are set at 85 percent for M

to 2014 and 100 percent for the remaining years of the rulemaking. 

(15) Automatic 6-, 7- and 8-Speed Transmissions 

Manufacturers can also choose to replace 4- and 5-speed transmission with

or 8-speed automatic transmissions. Additional ratios allow for further optimization

engine operation over a wider range of conditions, but this is subject to diminishing 

returns as the number of speeds increases. As additional planetary gear sets are added 

(which may be necessary in some cases to achieve the higher number of ratios), 

additional weight and friction are introduced. Also, the additional shifting of such a 

transmission can be perceived as bothersome to some consumers, so manufacturers need 

to develop strategies to minimize the impact of additional shifts. Some manufacturers are 

replacing 4- and 5-speed automatics with 6-speed automatics, and 7- and 8-speed 

automatics have also entered production, albeit in lower-volume applications in luxury

and performance oriented cars. 

As discussed in the MY 2011 CAFE final rule, confidential manufacturer data 

projected that 6-speed transmissions could incrementally reduce fuel consumption by 0

5 percent from a baseline 4-speed automatic transmission, while an 8-speed transmissio

could incrementally reduce fuel consumption by up to 6 percent from a baseline 4-speed

automatic transmission. GM has publicly claimed a fuel economy improvement of up to 

4 percent for its new 6-speed automatic transmissions. The 2008 EPA Staff Technical 

Report found a 4.5 to 6.5 percent fuel consumption improvement for a 6-speed over a 4

speed automatic transmission.180 Based on this information, NHTSA estimated in the 

MY 2011 rule, that the conversion to a 6-,7- and 8-speed transmission (NA

eed automatic transmission with IATC would have an incremental fuel 

mption benefit of 1.4 percent to 3.4 percent, for all vehicle classes. From a bas

eed transm , the incr ental fuel c on benefit 

be approximately 3 to 6 pe nt. NH revie ese ef veness estimates and 

concluded that they remain urate spon NPR orsche provided 

estimate for fuel economy improvement for 6 to7 speed automatic transmission which is 

consistent with th

th NHTSA reviewed the cost estimates from the MY 2011 CAFE final rule 

 

180 Page 17, “EPA Staff Technical Report: Cost and Effectiveness Estimates of Technologies Used to 

Reduce Light-duty Vehicle Carbon Dioxide Emissions” Environmental Protection Agency, EPA420-R-08-

008, March 2008. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Lepelletier gear set) and concluded that some but not all 6-speed 

automatic transmissions would be equipped with Lepelletier gear set. As such, the 

estimates were revise stablish the

divided between applications using Lepelletier, and applications of a standard planetary 

gear se e 

e 

mance 

timates 

n work 

done by F

quire 

analysis performed in this rule 

require

Therefore, the $215 va speed to 6 d 

$91 is subtracted from speed to 5 -

Lepelle

ative 

which used cost estimates from 2008 Martec report and the 2008 EPA Staff Report 

(which assumed use of a 

d to e cost for the 6 speed transmission to be equally 

t 6-speed automatic transmission as estimated in the 2008 Martec Report (and th

MY 2011 CAFE final rule). The 2008 Martec report estimated a cost of $323 with RPE 

adjustment and $215 without RPE adjustment for converting a 4-speed to a 6-speed 

transmission and a cost of $638 with RPE adjustment or $425 without RPE adjustment 

for converting a 4-speed to an 8-speed transmission. As a result, the final incremental 

cost estimate in the NPRM was $170, independent of vehicle type and size and including

a low complexity 1.11 ICM (2007$). In the CAFE model, due to the structure of th

vehicle classes used, an additional $102 (2007$) was included to account for perfor

vehicle classes and for medium and large trucks. This is because for performance 

classes, additional gear ratios, such as 7 and 8 speed transmissions may be utilized, and 

for medium and large trucks heavier duty transmissions are required. These es

represented MY 2012 vehicle costs 

For the final analysis, as noted earlier, NHTSA has considered the teardow

EV. In its teardown work, FEV determined the 6 speed automatic transmission 

to be $106 less costly than a 5 speed automatic transmission (direct manufacturing cost 

without markups). This is counterintuitive but can be attributed to the type of gear set 

employed in the 6 speed automatic transmission studied by FEV. That 6 speed auto 

transmission was equipped with a Lepelletier-like gear set and therefore does not re

a 1-way clutch that is essential to other designs. The cost 

s that the cost difference between both a 4 speed and 5 speed automatic 

transmissions relative to 6 speed automatic transmission be established because there are 

a substantial number of both 4 speed and 5 speed automatic transmissions used in the 

baseline fleet. This was done using the NPRM analysis for a 4 speed to a 5 speed and 

adding the FEV results for the transition from a 5 speed to a 6 speed. The analysis 

resulted in a cost for a 5 speed auto transmission relative to a 4 speed auto of $91 direct 

manufacturing cost (2007$ in 2012). As done in the NPRM, NHTSA averaged the nonLepelletier gear set cost with the Lepelletier gear set cost (FEV tear-down value of -

$106). In the 2011 FRM, NHTSA estimated the cost of a 6 speed auto transmission, 

without a Lepelletier gear set, relative to a 4 speed auto transmission at $215 (2007$). 

lue (4 speed) from NHTSA’s 2011 FRM is used an

that (4 speed) to arrive at a cost of $124 as the non

tier cost for a 6 speed automatic transmission relative to a 5 speed automatic 

transmission. The $124 value is averaged with the FEV value of -$106 (Lepelletier cost) 

to get an end result of $9 (2007$ in 2012). This $9 cost represents the cost for a 6 speed 

auto transmission relative to a 5 speed auto transmission in the final analysis. This $9 

can then be added to the $91 to get a cost of $101 for a 6 speed auto transmission rel

to a 4 speed auto transmission. Error! Not a valid bookmark self-reference. shows the direct 

manufacturing costs used in the proposed and the final analyses. With the low complexity

markup of 1.11, the compliance cost for a 6 speed automatic transmission in relative to a

4 speed automatic transmission in 2012 is $112 (2007$). With time based learning, the 
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compliance costs in 2016 to move from a 4 speed auto to a 5 speed auto and then from a

5 speed auto to a 6 speed auto transmission would be $90 and $9, respectively (2007$). 

Table V-25. Direct Manufacturing Costs for Automatic Transmissions (2007$ in 2012) 

Technology 

Non-Lepelletier 

Cost Used in 2011 

CAFE Analysis 

NPRM 

FEV tear 

down 

(Lepelletier) 

Final 

Rule Comments 

5s auto relative 

to 4s auto $91 n/a $91 Final rule uses NPRM value

6s auto relative 

to 5s auto -$106 $9 $215-$91=$124 

[$124+(-$106)]/2=$9 

6s auto relative 

to 4s auto $215 $153 n/a $101 $91+$9=$101 (values are 

rounded) 

Notes: Blank cells represent values not considered in this analysis; n/a means that FEV did not conduct a 

tear down of the technology; refer to text for more detail on the comments. 

(16) Dual Clutch Transmissions / Automated Manual 

dual-

 transmission with automated 

clutch will 

likely b

DCT uses s

odd-numbe r 

faster and s

shaft with and five has gear three engaged and is transmitting power. 

The sh w

shift is r

engaging th , on the other hand, the 

driver s

change to s

made quickl there is no torque being transferred on it. 

r 

Transmissions (DCTAM) 

An Automated Manual Transmission (AMT) is mechanically similar to a 

conventional manual transmission, but shifting and launch functions are automatically 

controlled by the electronics. There are two basic types of AMTs, single-clutch and 

clutch (DCT). A single-clutch AMT is essentially a manual

and shifting. Because of shift quality issues with single-clutch designs, DCTs

e far more common in the U.S. and are the basis of the estimates that follow. A

eparate clutches (and separate gear shafts) for the even-numbered gears and

red gears. In this way, the next expected gear is pre-selected which allows fo

moother shifting. For example, if the vehicle is accelerating in third gear, the 

gears one, three 

aft ith gears two, four, and six is idle, but has gear four pre-selected. When a 

equired, the controller disengages the odd-gear clutch while simultaneously 

e even-gear clutch, thus making a smooth shift. If

lows down instead of continuing to accelerate, the transmission will have to 

econd gear on the idling shaft to anticipate a downshift. This shift can be 

y on the idling shaft since 

In addition to single-clutch and dual-clutch AMTs, there are also wet clutch and

dry clutch designs which are used for different types of vehicle applications. Wet clutch 

AMTs offer a higher torque capacity that comes from the use of a hydraulic system that 

cools the clutches. Wet clutch systems are less efficient than the dry clutch systems due 

to the losses associated with hydraulic pumping. Additionally, wet AMTs have a highe

cost due to the additional hydraulic hardware required. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ts 

the 

. 

 so 

ch performance. 

ring 

express

e design and development phases of applying DCT 

chnologies. Cost and effectiveness estimates used in the final rule are based on analysis 

that assumes each of t tation of the 

technologies. As it is stated before, NHTSA believes that DCT offers great potential for 

improv

ical sources such as the NESCCAF study and CBI information 

NHTSA

a 

rd 

Subcompact and Compact cars. This results in an incremental effectiveness estimate of 

Overall, DCTs likely offer the greatest potential for effectiveness improvemen

among the various transmission options presented in this report because they offer 

inherently lower losses of a manual transmission with the efficiency and shift quality 

advantages of electronic controls. The lower losses stem from the elimination of the 

conventional torque converter, and a greatly reduced need for high pressure hydraulic

circuits to hold clutches or bands to maintain gear ratios (in automatic transmissions) or 

hold pulleys in position to maintain gear ratio (in Continuously Variable Transmissions)

However, the lack of a torque converter will affect how the vehicle launches from rest,

a DCT will most likely be paired with an engine that offers sufficient torque at low 

engine speeds to allow for adequate laun

In response to NPRM, NHTSA received comments from GM that included a

description of technical considerations, concerns, limitations and risks that need to be 

considered when implementing DCT technologies. These include concerns related to the 

heat stress/durability of the clutch, ability of achieving a smooth control of torque du

launching and shifting, NVH, creep and rollback, packaging in FWD vehicles and the 

application of DCT on full size trucks. GM stated that there might be an additional gear 

needed for DCT on full size trucks because of the lack of a torque converter. GM also

ed concerns about the US customer's acceptance of DCT due to its loss of 

smoothness. NHTSA judges that the expressed technical considerations, concerns, 

limitations and risks are recognized within the industry and it is standard industry

practice to address each during th

te

hese factors is addressed prior to production implemen

ing fuel economy and is a valid choice for the future fuel economy improvement 

according to the techn

 has received. 

GM also expressed concern about the added weight for the electronics for DCT,

NHTSA believe that DCT is a simpler transmission than automatic transmission and it 

does not need a torque converter. The overall weight for DCT should not be more than 

6 speed automatic transmission. For an example, according to public information, Ford’s 

dry-clutch PowerShift is 30 pounds lighter than the existing four speed automatic on Fo

Focus. Therefore, NHTSA judges that overall transmission system mass will not be 

increased with a DCT. 

GM commented that some fuel economy improvement technologies, such as dry 

DCT, are more naturally applicable to smaller footprint vehicles and the smaller sized 

powertrains that accompany them. NHTSA has taken these into consideration when 

developing this rule and applied dry DCT only to the smallest of vehicle subclasses, 

Subcompact and Compact cars 

For the MY 2011 CAFE final rule, NHTSA estimated a 5.5 to 9.7 percent 

improvement in fuel consumption over a baseline 4/5-speed automatic transmission for a

wet clutch DCT, which was assumed for all but the smallest of vehicle subclasses, 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

CT, NHTSA estimated an 8.2 to 12.9 percent fuel consumption improvement over a 

baseline 4/5-speed automatic transmission, which equates to a 5.5 to 7.5 percent 

incremental improvement over the 6-speed t smission. NHTSA has retained these 

estimat el 

economy improvement for t he incremental 

ffectiveness values used in the NPRM and final rule. In reviewing the NPRM 

effectiveness estimates for this final rule NHTSA discovered that the DCTAM 

effectiveness value used in the Volpe model for Subcompact and Compact subclasses 

was incorrect; the (lower) wet clutch effectiveness estimate had been used instead of the 

intended (higher) dry clutch estimate for these vehicle classes. NHTSA has corrected the 

mistake in this final rule. 

In the NPRM analysis, NHTSA estimated costs for 6 speed dual-clutch 

transmissions relative to 6 speed auto transmissions. For the dry clutch DCT, the 

agencies estimated a direct manufacturing cost of $59 (2007$ in 2012). For the wet 

clutch DCT, the estimate was $126 (2007$ in 2012). For the final rule, teardown study 

done by FEV is considered in which FEV found a wet clutch DCT to be $147 less costly 

than a 6 speed auto transmission. This cost savings is not unexpected when one considers 

that the DCT is less complex than an auto transmission. However, such a cost savings 

presumes that capacity exists to produce dual-clutch transmissions at volumes of 450,000 

units, an assumption made by FEV. Since such capacity may not currently exist in the 

US, the FEV value (-$147) is not used directly but instead is averaged with the value 

used in the NPRM analysis ($126). Therefore, in the final rule, the wet clutch DCT is 

estimated to save $11 relative to a 6 speed auto transmission (2007$ in 2012). To 

generate a dry clutch DCT cost for the final analysis, the same cost difference from the 

NPRM for wet clutch versus dry clutch is applied. In other words, the NPRM analysis 

had a c

e 

2.7 to 4.1 percent over a 6-speed automatic transmission with IATC. For Subcompact, 

Compact Cars and Small light truck subclasses, which were assumed to use a dry clutch 

D

ran

es for this rule. In response to the NPRM, Porsche provided an estimate for fu

he DCT which is consistent with t

e

ost difference of $67 which was then subtracted from the final wet-clutch DCT 

cost of -$11 to arrive at a result of -$78 for a dry-clutch DCT relative to a 6 speed auto

transmission (2007$ in 2012). Table shows the direct manufacturing costs used in th

NPRM and final rule for dual clutch transmissions. Applying the medium complexity 

ICM of 1.25 results in costs of -$59 for the wet-clutch DCT and -$8 for the dry clutch 

DCT (2007$ in 2012), both relative to a 6 speed auto transmission. With time based 

learning, these costs become -$68 and -$9, respectively, in 2016 (2007$). 

Table V-26 Direct Manufacturing Costs for Dual-Clutch Transmissions (2007$ in 2012) 

Technology NPRM FEV tear 

down Final Rule Comments 

6s wet DCT relative to 6s auto $126 -$147 -$11 [$126+(-$147)]/2=-$11 

6s dry DCT relative to 6s auto $59 n/a -$78 -$11-($126-$59) = -$78 

Notes: n/a means that FEV did not conduct a tear down of the technology; refer to text for more detail on 

the comments. 

GM commented that "Producing a DCT transmission in North America requires 

significant new investment to build new or retool existing transmission manufacturing 

plants." NHTSA has considered these in NPRM and the final rule by assigning this 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

technol

o Vlic 

e 

s 

or engine optimization. While 

CVTs by definition are fully continuous, some automakers choose to emulate 

conventional steppe

sensation of the engine speed operating independently of vehicle speed. 

-

ss 

to their 

technology

that result 

cycle timin

driver sele

efficient tr

gear losses

actuate the 

transmissio

ratio for fu

manual tra

that optimizes engine operation more often. Typically, this is achieved through adding 

ogy a medium complexity ICM factor of 1.25 to cover the cost. This ICM factor is

carried to this final rule. 

(17) Continuously Variable Transmission (CVT)

A Continuously Variable Transmission (CVT) is unique in that it does not use 

gears to provide ratios for operation. Instead, the most common CVT design uses tw

shaped pulleys connected by a metal belt. Each pulley is split in half and a hydrau

actuator moves the pulley halves together or apart. This causes the belt to ride on either a

larger or smaller diameter section of the pulley which changes the effective ratio of th

input to the output shafts. Advantages of the CVT are that the engine can operate at it

most efficient speed-load point more of the time, since there are no fixed ratios. 

However, CVTs are limited by engine power and cannot be applied to high torque 

applications. Also, CVTs often have a wider range of ratios compared to conventional 

automatic transmissions which can provide more options f

d automatic operation because some drivers are not used to the 

Considering the confidential data together with independent review, NHTSA has

estimated the fuel consumption effectiveness for CVTs at 2.2 to 4.5 percent over a 4/5

speed automatic transmission, which translates into a 0.7 to 2.0 incremental effectivene

improvement over a planetary automatic transmission with the IATC technology. 

NHTSA continues to find these estimates to be accurate. 

NHTSA adjusted the original estimates used in MY 2011 CAFE final rule to 

account for ICM markup of 1.25 for a medium technology. For this rule, this results in an 

incremental compliance cost estimate of $250 for the MY 2012 vehicles. In the Volpe 

model, this technology was only applied to vehicles manufactured with unibody

construction methods, since ladder frame vehicles are typically unsuitable for CVTs due 

size and utility requirements. CVTs are an established and readily available 

 so time based learning is applied, and as with other transmission technologies 

in new installations, CVT are only applied by the Volpe model at redesign 

g. The phase-in caps are now at 85 percent throughout the rulemaking period.

(18) 6-Speed Manual Transmissions (6MAN) 

Manual transmissions are entirely dependent upon driver input to shift gears: the 

cts when to perform the shift and which gear to select. This is the most 

ansfer of energy of all transmission layouts, because it has the lowest internal 

, with a minimal hydraulic system, and the driver provides the energy to 

clutch. From a systems viewpoint, however, vehicles with manual 

ns have the drawback that the driver may not always select the optimum gear

el economy. Nonetheless, increasing the number of available ratios in a 

nsmission can improve fuel economy by allowing the driver to select a ratio 

overdrive ratios to reduce engine speed at cruising velocities (which saves fuel through 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

reduced en s 

the optimu However, if the gear ratio steps are not properly designed, this may 

require

dissatisfac

performan

NH increase of 0.5 

percent for ch was 

derived fro te 

this estima uel consumption for replacing a 

5-speed

2011 final 

an increme

the final ru er costs occurring in later MYs due to the application of time 

based l

in the base

cycle timin

percent for

. H

ary 

ination of the three above mechanisms to 

reduce ption, 

available to plug-in hybrids electric vehicles (PHEV) and battery electric vehicles (EV), 

is by substituting the petroleum fuel energy with energy from another source, such as the 

ric grid. The effectiveness of fuel consumption reduction depends on the utilization 

e and its effect on 

gine pumping losses) and pushing the torque required of the engine toward

m level. 

 the driver to change gears more often in city driving resulting in customer 

tion. Additionally, if gear ratios are selected to achieve improved launch 

ce instead of to improve fuel economy, no fuel saving effectiveness is realized. 

TSA’s MY 2011 CAFE final rule estimated an effectiveness 

replacing a 5-speed manual with a 6-speed manual transmission, whi

m confidential manufacturer data. NHTSA has found no evidence to dispu

te and chosen to use 0.5 percent reduction in f

 manual with a 6-speed manual transmission for this rule. NHTSA updated the

rule costs to reflect the ICM low complexity markup of 1.11 which resulted in 

ntal compliance cost of $250 for MY 2012 vehicles, as compared to $338 in 

le, with low

earning factors. 6MAN is only applied to vehicles that use a manual transmission 

line product, and the Volpe model can only apply the technology at redesign 

g. The phase-in rate has been set to 85 percent for MY 2012 to 2014 and 100

 the remaining years of this rule. 

c ybrid and Electrification/Accessory Technologies 

A Hybrid is a vehicle that combines two or more sources of propulsion energy, 

where one uses a consumable fuel (like gasoline), and one is rechargeable (during 

operation, or by another energy source). Hybrid technology is established in the U.S. 

market and more manufacturers are adding hybrid models to their lineups. Hybrids 

reduce fuel consumption through three major mechanisms: 

• The internal combustion engine can be optimized (through downsizing, 

modifying the operating cycle, or other control techniques) to operate at or 

near its most efficient point more of the time. Power loss from engine 

downsizing can be mitigated by employing power assist from the second

power source. 

• Some of the energy normally lost as heat while braking can be captured and 

stored in the energy storage system for later use. 

• The engine is turned off when it is not needed, such as when the vehicle is 

coasting or when stopped. 

Hybrid vehicles utilize some comb

fuel consumption. A fourth mechanism to reduce petroleum fuel consum

elect

of the above mechanisms and how aggressively they are pursued. One area where this 

variation is particularly prevalent is in the choice of engine siz

balancing fuel economy and performance. Some manufacturers choose not to downsize 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

the eng

ly 

gnificantly diminished 

towing performance with a low battery. 

Although hybrid vehicles using other energy storage concepts (flywheel, 

hydraulic) have been developed, the systems currently in production in the U.S. for 

passenger cars and light trucks use battery storage and electric drive systems. Hybrid 

electric vehicles (HEV) are part of a continuum of vehicles using systems with differing 

levels of electric drive and electric energy storage. This range of vehicles includes 

relatively basic engine start/stop systems, HEV systems with varying degrees of electric 

storage and electric drive system capability, PHEV with differing degrees of all electric 

range and EV that rely entirely on electric drive and battery electric energy storage. 

Different HEV, PHEV and EV concepts utilize these mechanisms differently, so 

they are treated separately for the purposes of this analysis. Below is a discussion of 

battery energy storage and the major hybrid concepts that were determined to be 

available in the near term. 

i. Batteries for HEV, PHEV and EV Applications 

The design of battery secondary cells can vary considerably between HEV, PHEV 

and EV applications. 

MHEV systems will likely continue to use lead-acid batteries due to their lower 

voltage (12-42 VDC) and relatively low power and energy requirements. However, 

technology used is expected to be upgraded over conventional (non-MHEV) lead acid 

batteries to meet the charge cycling demands of MHEV applications, and is likely to 

include extended-cycle-life flooded (ELF) lead-acid batteries or absorptive glass matt, 

valve-regulated lead-acid (AGM/VRLA) batteries. 

HEV applications operate in a narrow, short-cycling, charge-sustaining state of 

charge (SOC). Energy capacity in HEV applications is somewhat limited by the ability 

of the battery and power electronics to accept charge and by space and weight constraints 

within the vehicle design. HEV battery designs tend to be optimized for high power 

density rather than high energy density, with thinner cathode and anode layers and more 

numerous current collectors and separators (Figure V-14). 

EV batteries tend to be optimized for high energy density and are considerably 

larger than HEV batteries. PHEV battery designs are intermediate between poweroptimized HEV and energy-optimized EV battery cell designs. PHEV batteries also must 

provide both charge depleting operation similar to an EV and charge sustaining operation 

similar to an HEV. Unlike HEV applications, charge sustaining operation with PHEVs 

occurs at a relatively low battery state of charge (SOC) which can pose a significant 

ine when applying hybrid technologies. In these cases, performance is vastly 

improved, while fuel efficiency improves significantly less than if the engine was 

downsized to maintain the same performance as the conventional version. While this 

approach has been used in cars such as the Honda Accord Hybrid (now discontinued), it 

is more likely to be used for vehicles like trucks where towing and/or hauling is an 

integral part of their performance requirements. In these cases, the battery can be quick

drained during a long hill climb with a heavy load, leaving only a downsized engine to 

carry the entire load. Because towing capability is currently a heavily-marketed truck 

attribute, manufacturers are hesitant to offer a vehicle with si
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

challen e with respect to attaining acceptable battery cycle life. In the case of the GM 

Volt, this 30%.181 

Figure V-14 Schematic representation of power and energy optimized 

prismatic-layered battery cells 

g

limits charge depleting operation to a minimum SOC of approximately 

Collector (-)

Cathode (-)

Separator

Anode (+)

Collector (+)

EV Energy-optimized Battery Cell

HEV Power-optimized Battery Cell

em) for the GM Volt PHEV and by AESC, GS-Yuasa and 

A123 S

Power-split hybrid vehicles from Toyota, Ford and Nissan, integrated motor assist

hybrid vehicles from Honda and the GM 2-mode hybrid vehicles currently use nickelmetal hydride (NiMH) batteries. Lithium-ion (Li-ion) batteries offer the potential to 

approximately double both the energy and power density relative to current NiMH 

batteries, enabling much more electrical-energy-intensive automotive applications such

as PHEVs and EVs. Li-ion batteries for high-volume automotive applications differ 

substantially from those used in consumer electronics applications with respect to 

cathode chemistry, construction and cell size. Li-ion battery designs currently under 

development by CPI (LG-Ch

ystems (respectively) for the upcoming Nissan, Mitsubishi and Chrysler EVs use 

large-format, layered-prismatic cells assembled into battery modules. The modules are 

then combined into battery packs. 

 

181 “Latest Chevrolet Volt Battery Pack and Generator Details and Clarifications.” Lyle Dennis interview 

of Rob Peterson (GM) regarding the all-electric drive range of the GM Volt, August 29, 2007. Accessed on 

the Internet on June 30, 2009 at: http://gm-volt.com/2007/08/29/latest-Chevrolet-volt-battery-pack-andgenerator-details-and-clarifications/ 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ly 

s). 

ion of 

ciency 

le, is 

ate 

 both the 

hybrid 

em and the complexity for a Crank Integrated 

, 

dai. One estimate from Anderman 

er 

 

Cathodes for large-format, automotive Li-ion batteries are becoming increasing

focused on two chemistries – LiMn2O4-spinel (CPI, GS-Yuasa, AESC) and LiFePO4 

(A123 System

In addition to the purely hybrid technologies, which decrease the proport

propulsion energy coming from the fuel by increasing the proportion of that energy 

coming from electricity, there are other steps that can be taken to improve the effi

of auxiliary functions (e.g., power-assisted steering or air-conditioning) which also 

reduce fuel consumption. These steps, together with the hybrid technologies, are 

collectively referred to as “vehicle electrification” because they generally use electricity 

instead of engine power. In order to achieve consistency between the two modeling 

techniques, and to improve the number and range of technology offerings, the CAFE

model was revised to include one additional mild hybrid technology. The high voltage or 

improved efficiency alternator (HVIA) technology, which was used in the 2011 ru

no longer represented as a separate technology and has instead been incorporated into this

new mild hybrid technology, as discussed further below. 

ii. Hybrid System Sizing and Cost Estimating Methodology 

NHTSA, in coordination with EPA reviewed estimates of cost and effectiveness 

for hybrid and related electrical technologies and adjusted them as appropriate. Both 

agencies found the hybrid technology cost estimating methodology that Ricardo and 

NHTSA developed during the 2011 final rule to be reasonable and used it to estim

hybrid systems costs and account for variation in component sizing across

types and vehicle subclasses. That method utilizes four pieces of data: (1) key 

component sizes for a midsize car by hybrid system type; (2) normalized costs for each 

key component; (3) component scaling factors that are applied to each vehicle 

class/subclass by hybrid system type; and (4) vehicle characteristics for the subclasses 

which are used as the basis for the scaling factors. During development of the 

methodology, NHTSA and Ricardo made several assumptions: 

1) Hybrid controls hardware varies with the level of functionality offered by the 

hybrid technology. Assumed hybrid controls complexity for a 12V micro

hybrid (MHEV) and belt integrated starter generator (BISG) was 25 percent of 

a strong hybrid controls syst

Starter Generator (CISG) was 50 percent. These ratios were estimates based

on the directional need for increased functionality as system complexity 

increases. 

2) Li-Ion batteries for hybrid electric vehicles are currently entering production

including a 2010 MY Mercedes and Hyun

indicates that Li-ion market penetration will achieve 35 percent by 2015.182 

However, as was discussed above, significant development effort is underway 

by a number of battery producers which could impact cost and overcome oth

technical concerns. Therefore it was assumed that mild (MHEV, BISG and 

CISG) and strong hybrids (PSHEV, 2MHEV and PHEV) will use either LiIon or NiMH batteries, depending on cost considerations. However, plug-in

 

182 Anderman, Advanced Automotive Battery Conference, May 2008. Proceedings available for purchase 

at http://www.advancedautobat.com/Proceedings/index.html (last accessed October 17, 2008).
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

hybrids will use Li-ion batteries only. Battery usage is discussed further 

3) The plug-in hybrid battery pack w s sized for a mid-sized car by assuming: 

cle has a 20 mile all nd consum 0 

e battery pack c discharged down to 3 epth of 

he capacity of battery pack is 20 r than 

ge on a new battery pack is 24 miles). 

ncluded a DC conver

e electrical ppropri

cation in the time frame d. 

d with vehicle functio

 of stron id wiring. The s 

need for sed fun

cluded a su ental heater to pro

e is stopped; howe n this rule, it is assumed that only half 

 adapt this technology, as disc

included elect conditioning to enable engine stop/start 

hicle air conditioning w ested b

icardo re ized that some stro ems 

r tional transmission with speci

cost offset (i.e., a cost credit) for the remova f a portion of the clutches and gear sets 

within the transmission. In the MY 2011 rul the transmission cost in Table V-27 below 

express on 

assume the 

below. 

a

the vehi electric range a es an average of 30

W-hr per mile; th an be 0 percent d

discharge; percent greate 183 and t a new

at end of life (i.e., ran

4) All hybrid systems i

ccommodate vehicl

/DC ter which was sized to 

a ate for increased vehicle 

electrifi

loads a

considere

5) High voltage wiring scale hybrid nality and could be

represented as a fraction

based on the directional 

g hybr

 increa

se ratios were estimate

ctionality as system complexity 

increases. 

6) All hybrid systems in pplem vide vehicle heating 

when the engin ver, i

of the vehicles will ussed further below. Only 

the strong hybrids ric air 

when ve as requ y the operator. 

Furthermore, NHTSA and R cogn ng hybrid syst

eplaced a conven a hybrid- fic transmission, resulting in a 

l o

e, 

ed hybrid transmission costs as a percentage of traditional automatic transmissi

cost, as described in the 2008 Martec Report, at $850 direct manufacturing cost (nonRPE/ICM). The method assumed that the mechanical aspect of a power-split 

transmission with a reduced number of gear sets and clutches resulted in a cost savings of 

50 percent ($425) over a conventional transmission with torque converter. For a 2-mode 

hybrid, the mechanical aspects of the transmission are similar in complexity to a 

conventional transmission, so no cost savings was appropriate. The plug-in hybrid 

d a highly simplified transmission for electric motor drive, thus 25 percent of 

base vehicle transmission cost was applied (resulting in a $638 credit). 

The NHTSA MY 2011 CAFE final rule discusses in detail how the hybrid cost 

estimating methodology uses the information provided in the tables below to calculate 

costs for each of the strong hybrid systems used in this rule. It also includes a step-bystep example for the midsize vehicle mild hybrid systems used in the MY 2011 CAFE 

final rule.184 As in that analysis, it is important to understand that the CISG technology 

replaces existing mild hybrid systems.185

NHTSA and EPA in reviewing the above made the following revisions. 

 

183 The GM Volt operates between 30% DOD and 85% DOD. So there is 55% useable DOD, but charge 

sustaining operation starts at 30% and cycles between 30 and 35% DOD. 

184 74 FR 14291 (Mar. 30, 2009) 185 For the incremental CAFE model, before CISG is applied, the costs for MHEV and BISG are subtracted 

if they were previously applied. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

e 

 to 

, 

First, NHTSA and EPA revalidated the component sizes that were estimated for a 

midsize car for each type of hybrid system as shown in Table V-27. However, NHTSA 

and EPA added an additional component-- front engine accessory drive (FEAD), becaus

hybridization often involves revision to the FEAD design such that certain devices (belts, 

pulleys, idlers, etc) as well as other engine components (alternator, A/C compressor, and 

starter) may no longer be needed and can thus be eliminated, or may be de-specified

lower cost alternatives. This is applicable to CISG and the strong hybrid technologies

and is intended to account for cost savings associated with items that changed or are no 

longer required as a result of these technology applications. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table V-27. Component Sizes by Hybrid Type for a Midsize Car 

Pr

Se

Pr

Se

C

Ni

Component MHEV 

BISG CISG PSHEV 2MHEV PHEV

imary Motor power, continuous (kW) 3 11 45 45 45

condary Motor power, continuous (kW) na na 30 45 30

imary Inverter power, continuous (kW) 3 11 45 45 45

condary Inverter power, continuous (kW) na na 30 45 30

ontrols complexity (relative to strong hybrid) 25% 50% 100% 100% 100%

MH Battery Pack capacity (kW-hr)

1 na 1 2 2 na

Li-Ion Battery Pack capacity (kW-hr)

1 na 1 2 2 15

/DC Converter power (kW) 0.7 2 2 2 2

gh Voltage Wiring (relative to strong hybrid) na 50% 100% 100% 100%

DC

Hi

Supplemental heating

2 50% 50% 50% 50% 50%

echanical Transmission (relative to baseline vehicle) 100% 100% 50% 100% 25%

ectric AC No No Yes Yes Yes

Blended Brakes No Yes Yes Yes Yes

FEAD Credit No Yes Yes Yes Yes

harger power, continuous (kW) na na na na 3

 2 - Implemented through a reduction in component cost (50%)

 1 - Assumes the use of either NiMH or Li-Ion, and not both.

M

El

C

 

 

Hybrid Type

Second, the costs estimates of the key components were revised and comment to 

the cost as they apply to NiMH was provided by ICCT. The MY 2011 CAFE final ru

as developed at a time when economic conditions were significantly different than 

those that currently exist, a time when o e 

hybrid systems were more expensive than today. These changes in economic conditions 

were o

 either 

e 

t per kilowatt hour (kW-hr) for Nickel Metal Hydride (NiMH) battery was 

revised 

ated, 

 the marketplace today, as discussed above, and is 

expecte

g 

 in 

r 

-

 study 

le

w

many f the commodity materials used in th

ne of the factors leading to some of the cost revisions EPA and NHTSA jointly 

discussed and made. Differences in estimates provided by confidential sources to

EPA or NHTSA also played a part in the revisions. In addition, the agencies applied the 

new ICM mark-up factors instead of the RPE that was used previously. An appropriat

ICM factor (1.45 for most mild and strong hybrid technologies) replaces the previous 

RPE factor (1.5). Specifically, the primary and secondary inverter cost per kilowatt were

revised downward from $10 to $7, the controls cost was revised upward from $100 to 

$115, the DC/DC converter costs were revised from $100 to $88, the blended brake 

system that was revised from $400 to $310, and finally the fully learned, high volume 

production, cos

from $350 to $320. 

The cost for Lithium Ion (Li-Ion) batteries was also revised. As previously st

Li-Ion batteries are being implemented in series production in model year 2010. Battery 

technology is changing rapidly in

d to continue along this path throughout the rulemaking period. OEMs are now 

forming relationships with battery manufacturers in an effort to research and develop not

only new and improved battery technology, but also more efficient manufacturin

processes capable of supporting high volume production. Accordingly, as shown

Table V-28, the $600 per kW-hr used in the 2011 rule was revised downward to $320 pe

kW-hr, matching that of the NiMH technology. The revision downward from $600/kW

hr in the 2011 CAFE final rule to $320/kW-hr in this analysis was done based on a
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

the 

 will not be 

accomplished during this rulemaking period to achieve this cost. MEMA commented 

that the cost of $320/kW-hr was t ar exceed $500/kW-hr. 

The $500/kW-hr used in this rulemaking is a 2012 figure that was adopted from the 

Electrif

les are based on an 

assessment of several vehicle models and are specific to those models. For this rule, 

NHTSA l 

e 

s 

assumpti

technology

lume 

lt integrated s r genera fixed cost 

that, like the automatic transmission pump described 

later. 

by Deutsche Bank that estimated Li-Ion battery costs at 300-400 €/kW-hr.v

 This was

converted to $500/kW-hr then learned twice using volume-based learning to arrive at 

$320/kW-hr. 

Comments were received from The State of New Jersey Department of 

Environmental Protection, MEMA, and ICCT on the subject of Lithium-ion battery, and 

system costs. The State of New Jersey Department of Environmental Protection 

commented that the battery costs were too low citing an Air Resources Board report 

which projects $260/kW-hr. Necessary volumes and manufacturing maturity

oo low stating that present costs f

ication Roadmap, November 2009 and then learning, described in the previous 

paragraph, was applied. ICCT provided examples of charge capacity and power 

requirements of recently produced vehicle applications. These examp

 believes it is appropriate to use an average cost which is representative of al

vehicle models using this technology during the 2012 to 2016 model year period. Th

examples cited by commenters do, however, further demonstrate the rapid pace of 

development and innovation in the application of these hybrid technologies. Though the 

agency believes the cost assumptions used in the Volpe model to be correct at the point in 

time of their assessment and are accurate for this rulemaking period, the agency agree

that further research will be necessary to progress from our current point in time 

ons on costs and application parameters for future rule makings. 

Li-ion batteries were originally restricted to plug-in hybrids only. Recent vehicle 

introductions confirm either NiMH or Li-ion battery technology can be used in any mild 

or strong HEV application. However, manufacturers are likely to consider cost highly in 

their selection of battery technology. If Li-ion battery prices decrease to levels similar to 

NiMH, Li-ion batteries would be the default battery technology for all hybrid electric 

vehicles. If Li-ion battery prices remain high, NiMH would be the default battery 

technology for all hybrid electric vehicles. For plug-in hybrids Li-ion would continue to 

be required because plug-in hybrids demand higher energy density than NiMH can 

provide. Neither the CAFE nor OMEGA model predicts a high penetration of plug-in 

 in achieving the standards. 

Finally, the agencies assessed the cost savings associated with the FEAD credit 

discussed above. This cost was not previously represented in the hybrid cost model. As

shown in Table V-28 below, a $100 credit is used which offsets directly the costs of the 

other components specified. This is the best approximation of the value of these items, 

based on NHTSA and EPA engineering assessment. 

Estimates of each key component are shown in Table V-28 below along with the 

sources of those estimates. The cost basis estimates assume fully learned, high-vo

(greater than 1.2 million units per annum) production, and the costs shown are direct 

manufacturing costs that are not RPE or ICM adjusted. This table does not show a cost 

applicable to the be tarte tor system (BISG) since it is a

cost, is not scaled by subclass as
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table V-28 Component Cost Basis at High Volumes and Data Sources 

COMPONENT COST BASIS DATA SOURCE 

Primary Motor ($/kW) $15 

Secondary Motor ($/kW) $15 Martec 2008 

Primary Inverter ($/kW) $7 

Secondary Inverter ($/kW) $7 

Contr

ess Information 

ols $115 

Confidential Busin

NiMH Battery Pack ($/kW-hr.) $320 2011 CAFE FRM 

(with revision) 

Li-ion Battery Pack ($/kW-hr.) $320 Deutsche Bank 2008 

DC/DC Converter (Size: 2kW) $88 Confidential Business Information 

High Voltage Wiring $200 

Suppleme Martec 2008 ntal Heating $42 

Mechanical Transmission $850 Martec 2008 (to 4-spd auto) 

Electric Air Conditioning $450 

Blended Brakes $310 

Charger $100 

Confidential Business Information 

Automatic Transmission Pump $75 Martec 2008 

FEAD Credit $(100) Confidential Business Information 

Third, NHTSA and EPA also revised component size/scaling assumptions for 

some vehicles (i.e., large trucks). NHTSA and EPA recognized that some manufacturers 

may choose not to use supplemental cabin heating opting instead to continue engine 

operation in the event heat demand occurs; therefore supplemental heating is specified for 

e 50 percent application rate 

implemented in the hybrid cost estimating methodology reducing the component cost 

from $84 to $42. 

N d E A also re hoice of a erter as a 

compone or a midsi epre 250 amp current 

capability. In retrospect this is a high specification for a midsize vehicle and we revised 

the estimate to a 2 kW DC/DC converter, as shown in Table V-28 above, which would 

represent a more reasonable 150 amp current capacity. 

The scaling factor used for the primary and secondary mo invertors on the 

large truc V vehicles wa s in the MY 2011 CAFE final rule, a linear 

extrapolation was used from the eh ed it out to the largest of 

vehicles, the large truck class. This resulted in projected component sizes th are larger 

than those used on a commerc lly realized truck in this vehicle class, the Chevrolet 

Tahoe two-mode

(and the agenci

approximates t e motor and inverter sizes specified in the Tahoe application. For future 

analysis, the agencies are considering whether it may be more accurate to use one set of 

scaling for passenger cars and another different set for light trucks. 

only half of the vehicles. Table V-28 above indicates th

HTSA an P

nt size input f

viewed the c

ze vehicle, which r

3 kW DC/DC conv

sented a 

tors and

k and SU s revised. A

 midsize v icle and extend

at 

ia

 HEV. Accordingly the scaling factors have been revised for this class 

es have verified scaling factors for the other classes). This more closely 

h
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

p/ 

se 

igher 

29 

Table V-29 Component Scaling Factors applied to Vehicle Class for each Hybrid 

Li

Ch

Another revision involves the addition of a stand-alone higher voltage Start-Sto

BISG mild hybrid system. NHTSA and EPA determined that by applying a cost increa

to the MHEV technology to allow for a voltage increase (lead acid batteries) and 

efficiency improvements to the alternator, the system would then approximate the h

voltage Start-Stop /BISG applied by EPA. Based on confidential sources, the estimates 

provided were first converted to 2007 dollars and then reverse learned through two 

cycles, since volume learning is applicable, to arrive at a non-RPE/ICM incremental 

compliance cost to be $229. This cost is applicable to all classes that use higher voltage 

Start-Stop/BISG and is not scaled by any vehicle attribute. 

Component scaling factors for each type of hybrid system as shown in Table Vbelow

System 

Component MHEV CISG PSHEV 2MHEV PHEV

Primary Motor Engine 

displacement

Curb 

weight Engine power

Secondary Motor na na Curb weight

Primary Inverter

Secondary Inverter na na

Controls

NiMH Battery Pack na

Hybrid Type

Engine 

displacement

Curb weight1

Primary motor power

Secondary motor power

Complexity

2

na

-Io

arger

all 

vehicle classes

 for all vehicle classes

Curb weight n Battery Pack na Curb weight

DC/DC Converter

High Voltage Wiring na

Supplemental heating

Mechanical Transmission

Electric AC na na

Blended Brakes na Same

Curb weight3

Vehicle footprint

Same for all vehicle classes

Vehicle footprint

Vehicle footprint

na na na na

Same for 

(1) For all vehicle classes except for performance classes which use Engine Torque

(2) Curb weight used as surrogate for vehicle road load

(3) Curb weight used as surrogate for vehicle electrical load

Regarding the market data file from the MY 2011 CAFE final rule, NHTSA a

EPA did not make any revisions to the average vehicle characteristics for each vehicle 

subclass as shown in Table V-30, which defines the average vehicle characteristics for 

each vehicle subclass. These characteristics were used as the basis of the scaling facto

in the Volpe model. 

nd 

rs 
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Table V-30 Key Vehicle Characteristics For Each Vehicle Subcl CAFE 

model 

Engine 

Su

Co

M

La

Pe

ass for 

Vehicle Subclass t

(lbs)

Footpr

(ft2)

gine 

Disp. (L) Power

(hp)

Torque

(ft-lb)

bcompac 41 1.9 134 133

mpact C 44 2 166 167

idsize Car 3725 47 9 206

rge Car 4110 50 3.4 258 248

r

318

Curb 

Weigh int En

t Car

ar

2795

3359 2.

2. 205

formance Subcompact Car 3054 40 2.7 260 260

Performance Compact Car 3516 44 3.0 269 260

Performance Midsize Car 3822 47 3.9 337

Performance Large Car 4189 51 4.8 394 388

Minivan 4090 50 3.3 247 242

Small Truck 3413 45 2.6 178 185

Medium Truck 4260 50 3.6 250 256

Large Truck 5366 63 5.0 323 352

(19) Electrical Power Steering (EPS)

 an 

em which may add cost and 

comple ity. 

In the 2011 final rule NHTSA estim ss based on 

the 2002 NAS report, a Sierra Research report, and confidential manufacturer data. 

NHTSA

ty 

Electric power steering (EPS) provides a potential reduction in fuel consumption 

over hydraulic power steering because of reduced overall accessory loads. This 

eliminates the parasitic losses associated with belt-driven power steering pumps which

consistently draw load from the engine to pump hydraulic fluid through the steering

actuation systems even when the wheels are not being turned. Additionally EPS is

enabler for all vehicle hybridization technologies, since it provides power steering when 

the engine is off, and thus NHTSA places the technology at the top of the electrification 

decision tree. While EPS may be implemented on most vehicles with a standard 12V 

system, heavier vehicles may require a higher voltage syst

x

ated a 1 to 2 percent effectivene

 reviewed these effectiveness estimates and found them to be accurate, thus they 

have been retained for this rule. 

For costs, in the MY 2011 CAFE final rule, NHTSA estimated EPS at $105 - 

$120 at a 1.5 RPE markup factor. NHTSA, working in conjunction with EPA, adjusted 

the EPS cost for this rule based on a review of the specification of the system. 

Adjustments were made to the potentially higher voltage or heavier duty system 

operation, such as would be required on some hybrid trucks. Accordingly, higher costs 

were estimated for EPS due to the system’s higher capability. After accounting for the 

differences in system capability and applying the ICM markup of low complexi
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

technol

l 

p 

oil pumps are 

y driven. A reduction in fuel consumption can be realized by 

driving 

ntarily. 

the 

e, reduce warm-up fuel enrichment and reduce 

ed when electrification is combined with 

an improved higher efficiency engine alter . Ve y heavy 

payloads, ed for towing have cooling em and n loads, and 

benefit less r t cooling. Theref intellige oling is n plied to the 

Large LT su cl FE model, IA refers solely to improv ngine cooling. 

NH ed the 1 to 2 percent CC effect eness estima s used in MY 

2011 rule an f to be accurate fo s rule. N SA also confirmed the cost 

assumption ro le and thus o djusted osts to ref e new ICM 

markup for low complex technology of 1.11; this re lts in a cos

rulemakin at MY 2012. Since thes systems are readily available and in 

production ased learning is applied. Th lpe mode pply IACC at 

either refresh or e however app to th arge Tru d SUV 

ubclass is prohibited due to the cooling system requirements of these high utility 

vehicles. The phase-in rate has been defined as 85 percent in MYs 2012 to 2014, and 100 

y 

ogy of 1.11, the estimated costs for this rulemaking are $106 for a MY 2012 

vehicle. As EPS systems are in wide spread usage today, time based learning is also 

deemed applicable, hence costs will be lower for later MY vehicles. The Volpe mode

can apply EPS at refresh or redesign cycles, since it is a reasonably non-intrusive 

technology. Whereas the 2011 final rule did not apply EPS to the Large Truck and SUV 

subclass, primarily due to concerns with the system’s capability, there are no subclass 

specific limitations on its use in this rule for the reasons stated above. The phase-in ca

has been set at 85 percent in MYs 2012 to 2014, and 100 percent thereafter, 

(20) Improved Accessories (IACC)

The accessories on an engine, including the alternator, coolant and 

traditionally mechanicall

them electrically, and only when needed (i.e., “on-demand”). 

As the oil pump provides lubrication to the engine’s sliding surfaces such as 

bearings, pistons, and camshafts, oil flow must be provided whenever the engine is 

rotating. Because mechanical oil pumps do not operate when the engine is not rotating, 

there is no efficiency benefit for the ability of an electric oil pump to be switched off 

when the engine is not rotating. The increased complexity of an electric oil pump system

creates greater reliability risk compared to a conventional mechanical oil pump, and 

increases risk for significant engine damage should the system fail, even mome

Electric water pumps and electric fans can provide better control of engine

cooling. For example, coolant flow from an electric water pump can be reduced and 

radiator fan can be shut off during engine warm-up or cold ambient temperature 

conditions which will reduce warm-up tim

parasitic losses. Further benefit may be obtain

, nator

 h h

hicles that typically carr

or that are us ig syst coo ng fa li

 fo intelligen ore, nt co ot ap

b ass. In the CA CC ed e

TSA review IA iv te

d ound them r thi HT

s f m the final ru

ity 

nly a the c lect th

a su t estimate for this 

g of $128 e

currently time b e Vo l can a

 redesign cycl lication e L ck an

s

percent thereafter. 

(21) 12V Micro Hybrid (MHEV)

The 12V Micro-Hybrid (MHEV) systems are the most basic of hybrid systems 

and offer only the ability to turn the engine off when the vehicle is stopped or potentiall
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

st and adaptability to existing 

powertrains nd latforms can make them ctive f l he 

convention alternator is repla h a be riven, e ower starteralternator an a d front-end acces drive sy . A conv nal 12V gearreduction st ter ensure reliab old-wea starting. lestop, some er steering and automatic transmission hydraulic 

pressure ar ic power steering d an auxiliary transmission pump may be 

needed. A he MHEV system hown in re V-1. 

In th 20 effectiven s estimates for this techn y ranged from 

2.0 to 4.0 p n whether th hicle is equipped with a 4, 6 or 8 cylinder 

engine, with he engine having t west ra nd the 8 c der having the 

highest. Th est the limited ca bility of 1 olt system ich do not 

er mechanical energy through regenerative braking or provide motive force; sources 

citing higher estimates typically involve higher voltage systems that have increased 

capabil

, the use 

s, 

owever 

he 

s. 

Figure V

during deceleration (i.e. idle stop). Their low co

a p attra

ced wit

or so e app m

l d

ications. T

al belt-driven t- nha d p nce

d redesigne sory stem entio

ar is retained to

ch as pow

l c e th r e Also, during id

functions su

e lost; so electr an

sc matic of the is s Figu

e 11 final rule, the es olog

ercent dependent o e e v

 t 4 cylinder he lo nge a ylin

e imates reflect pa 2 v s wh

recov

ity. 

For this rule, the system specifications assumed in the 2011 rule186 were applied 

(i.e., use of a 3 kW motor and a DC/DC converter) and the hybrid technology cost 

method was used to produce system costs, like was done in 2011 rule. However

of revised component costs and new ICM markups resulted in costs ranging from a low 

of $288 for Subcompact subclass to a high of $410 for the Large Performance subclas

both of which are for MY 2012 vehicles. This technology is not applied to the Large 

Truck and SUV subclass due to the higher utility requirements of these vehicles; h

this is the only subclass limitation of the MHEV technology. Time based learning is 

considered applicable, and thus system costs are lower in later MYs. Application by t

Volpe model is limited to the redesign cycle since the front engine accessory drive will 

likely require significant redesign with a phase-in cap of 85 percent for all MY

-15 Schematic of MHEV Type System [Husted, 2003] 

Higher Voltage Stop-Start/Belt Integrated Starter Generator (BISG) 

 

186 74 FR 14293 (Mar. 30, 2009) 

Engine

Motor/ 

Generator

Trans.

Controller 

Inverter

Final Drive

Wheel

+ -

Battery
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

at 

machine and a higher capacity battery, typically 42 volts or 

above, thus enabling a limited level of regenerative braking which is generally not 

availab

e of the 

se 

or 

superca

). 

on a number of vehicle characteristics such as engine displacement and vehicle 

size. Th

e 

l, which is incremental to 

the MHEV technology, adjusts the costs upwards by $286 to reflect the need for 

additional battery capacity, wiring upgr and a electric machine. 

The cos

0 volts) and can 

provide ue for launch as well as generate current to provide significant levels of 

brake e ergy recovery. The motor/generator also acts as the starter for the engine and 

can replace a typical accessory-driven alternator. Current CISG systems typically do 

not full launch the vehicle on electric power alone, although some can cruise on 

electric power; dual-clutch based CISG systems capable of all-electric drive are under 

Belt Mounted Integrated Starter Generator (BISG) systems are higher voltage 

stop-start similar to a micro-hybrid system, offering idle-stop functionality except th

they utilize larger electric 

le to 12 volt based systems. The larger electric machine and battery also enables a 

limited degree of power assist, which MHEV cannot provide. However, becaus

limited torque capacity of the belt driven design, these systems have a smaller electric 

machine, and thus less capability than crank integrated or stronger hybrid systems. The

systems replace the conventional alternator with a belt-driven starter/alternator. The 

limited electrical requirements of these systems allow the use of lead-acid batteries 

pacitors for energy storage. Schematically BISG is similar to the MHEV 

technology. 

NHTSA did not have an equivalent technology to BISG in the 2011 final rule (the

ISG technology used in the 2011 rule was envisioned to be more capable than BISG

Effectiveness estimates for higher voltage stop-start systems found in literature and 

reports typically range from 3.0 to 7.5 percent, relative to a vehicle without stop-start, and

dependent 

e Volpe model, which applies BISG incrementally to the MHEV technology, 

uses incremental estimates of 3 to 6 percent in this rule, which makes the net 

effectiveness comparable to the estimates found in the 2002 NAS and 2004 NESCAFF 

reports for higher voltage stop-start systems. This estimate applies for all vehicle 

subclasses except Large Truck and SUV where, due to their high utility requirements, th

BISG technology is not considered applicable. Comment received from GM support the 

exclusion of this technology from Large Truck applications. 

For this rule, the cost estimate used by the Volpe mode

ades, larger optimized 

t estimates reflects volume based learning factors, since these systems are in 

relatively low usage at this time, and an ICM complexity markup of 1.25 for a medium 

complexity technology. Like MHEV, BISG can only be applied at redesign cycles times, 

and a flat 85 percent phase-in setting exists for all MYs. 

(22) Crank Integrated Starter Generator (CISG)

Integrated motor assist (IMA) is a commercially realized system developed and 

marketed by Honda. This is similar to the CISG technology represented in the Volpe 

model. They utilize a thin axial electric motor bolted to the engine’s crankshaft and 

connected to the transmission through a torque converter or clutch. The axial motor is 

motor/generator that typically operates above 100 volts (but lower than the stronger 

hybrid systems discussed below, which typically operate at about 30

 torq

n

y
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

is shown in Figure V-1. 

gure V-16 Schema usted, 2003] 

l 

not apply. Note that the net effectiveness assumptions used in this rule do not include 

engine 

 the 

applicable to all vehicle subclasses. Since significant vehicle modification is required to 

implem cycle. 

ity to move the vehicle on electric power only. 

It replaces the vehicle’s transmission with a single planetary gear and a motor/generator. 

A seco

he 

development. A schematic of the Honda’s IMA system 

Fi tic of Honda IMA System [H

NHTSA did not have an equivalent technology to CISG in the 2011 final rule (

ISG technology used in the 2011 rule was envisioned to be less capable than the CISG 

technology defined here). For the CISG technology NHTSA estimated a net 

effectiveness range of 16 to 20 percent, relative to the baseline vehicle and across al

vehicle subclasses in this analysis. The Volpe model therefore applies an incremental 

effectiveness of approximately 8.6 to 8.9 percent relative to the BISG technology and 

dependent on vehicle subclass except for large truck and SUV in which case BISG does 

the 

downsizing, or any other effectiveness gains from engine, transmission, or vehicle

technologies added to the vehicle by the modeling process. 

Using the hybrid cost estimating method, as discussed above, NHTSA has 

determined a compliance cost range of $2,791 for a Subcompact vehicle to $5,124 for

Large Truck and SUV vehicles, both in MY 2012. These include a high complexity ICM 

markup factor of 1.45 for this technology. As CISG is still in limited production use, 

volume based learning is applied which results in lower costs as the model applies 

sufficient quantities and applies two cycles of 20 percent cost reduction. CISG is 

ent this technology the Volpe model only applies CISG during a redesign 

NHTSA assumed a 3 percent phase-in cap for CISG in MY2012 and increasing 3 percent 

per year reaching a maximum of 15 percent in MY 2016. 

(23) Power Split Hybrid (PSHEV)

The Power Split hybrid has the abil

nd, more powerful motor/generator is directly connected to the vehicle’s final 

drive. The planetary gear splits engine power between the first motor/generator and the 

final drive. The first motor/generator uses power from the engine to either charge t

battery or supply power to the wheels. The speed of the first motor/generator determines 

the relative speed of the engine to the wheels. In this way, the planetary gear allows the

engine to operate independently of vehicle speed, much like a CVT. The Toyota Prius 

and the Ford Hybrid Escape are two examples of power split hybrid vehicles. 

Final Drive

Engine Motor/ 

Generator 

Trans.

+ - 

Battery

Controller 

Inverter

Wheel
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

d 

. The power split 

system provides good fuel consumption in city driving. During highway cycles, the 

hybrid 

e 

otor to provide improved high 

ue. 

n, replacing a 

with a single planetary lectric components are 

ld hybrid and CISG configura the costs are 

lemaking, in conjunction with EPA, 

anufacturer-supplied information that compared cars and small trucks 

 without a PSHEV hybrid system. ata was taken from EPA’s fuel 

and indicated a combined cycle tailpip CO2 reductions, which are 

ivalent to fuel consumption reductions, for the PSHEV equipped vehicles compared 

to the c 32187. 

tes that 

ve to a 

CVT. 

-26% 

 

 

404 

 HEV 2.4L PS 222 

 Net % difference -36% 

In addition to providing the functions of idle engine stop, subsequent restart an

regenerative braking, this hybrid system allows for pure EV operation

functions of regenerative braking, engine start/stop and optimal engine operation 

cannot be applied as often as in city driving, and so the effectiveness in fuel consumption

is slightly less. Additionally, it is less efficient at highway speeds due to the fact that th

first motor/generator must be spinning at a relatively high speed and therefore incurs 

losses. Newer designs incorporate a gear-reduction m

speed efficiency and improved matching of motor torque to engine torq

The Power Split hybrid also reduces the cost o smissio f the tran

conventional multi-speed unit gear. The e

bigger than those in mi tions so

correspondingly higher. 

During development of the joint ru NHTSA

reviewed m

available with and

conomy test data 

 The 

e

d

e

equ

onventional vehicles that ranged from 19 to 36 percent, see Table V- and VConsidering the Volpe model’s incremental approach to technology application, where 

engine downsizing and other vehicle related effectiveness improvements are accounted

for on other technology decision trees, NHTSA determined that net effectiveness 

estimates of 23 to 33 percent were most appropriate for the PSHEV technology in this 

analysis. These net effectiveness values result in incremental effectiveness estima

range from approximately 6 to 12 percent depending on vehicle subclass and relati

 Table V-31 Large Car Power Split Certification Data 

 Tailpipe CO2

 City Hwy 55/45 comb. 

Nissan Altima 

 3.5L CVT 444 306 386 

 HEV 2.5L PS 317 254 286 

 Net % difference 

Toyota Camry 

 3.0L 5-auto 286 355 

234 228 

 

Lexus GS 

 4.3L 6-auto 493 355 423 

 HEV 3.5L PS 355 317 341 

 Net % difference -19% 

 

187 The manufacturer data shows that, for the most part, the PSHEV equipped vehicles in the comparisons 

utilized engine downsizing, however the data is not intended to identify all other differences that may exist 

between the hybrid and non-hybrid vehicle versions, such as hybrid-specific powertrain calibrations or 

other vehicle modifications (tires, mass reductions, etc). Readers should exercise caution in assuming th

all of the noted fuel consumption gains can be attributed solely to engine downsizing and the use of the 

at 

PSHEV technology as there may be other modifications or systems that also contributed. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

 difference -32% 

tion 

sign 

e strong hybrid technologies, NHTSA used phase-in caps of 3 percent 

per MY, so the maximum application rate occurs in MY 2016 at 15 percent. 

or 

h 

 initial costs were 

very high. In addition, virtually all power-split hybrid vehicles have been equipped with 

NiMH batt

battery tec

justify the l 

continue to

(24) 2-Mode Hybrid

w 

e capacity and the 

Table V-32 Small Truck Power Split Certification Data 

 Tailpipe CO2

 City Hwy 55/45 comb. 

Ford Escape 4X4 

 3.0L 4-auto 467 386 423 

 HEV 2.3L PS 277 306 286 

 Net %

 

Ford Escape 4X2 

 3.0L 4-auto 444 370 404 

 HEV 2.3L PS 247 286 261 

 Net % difference -35% 

 

Toyota Highlander 4X4 

 3.3L 5-auto 493 370 423 

 HEV 3.3L PS 286 329 306 

 Net % difference -28% 

Using the hybrid cost estimating method NHTSA established overall PSHEV

system costs, which include the use of Electric Power Steering (EPS) and Improve 

Accessories (IACC) technologies, ranging from $5,509 for the Subcompact subclass to 

$11,534 for the Performance Large Car subclass for MY 2012 vehicles. In the Volpe

model these net costs result in incremental costs ranging from $1,600 to $6,723 

depending on vehicle subclass. The costs were determined using a 1.45 ICM for the high 

complexity PSHEV technology. Volume based learning is applicable to power split 

technology, so costs reduce significantly as penetration levels increase sufficiently. In 

the Volpe model PSHEV is not applicable to the Large Truck and SUV subclass 

primarily due to the high utility requirements of these vehicles. PSHEV implementa

requires significant vehicle revision, therefore its application is restricted to rede

cycles only. For th

A comment received from ICCT disagreed that volume-based learning is over f

the ‘power-split hybrid electric vehicle’ and only time-based learning curve is to be 

applied. While power-split hybrids have been on the market long enough to achieve hig

production volumes, the production ramp up has been very slow and the

eries. NHTSA expects in the future that there will be a shift toward Li-Ion 

hnology, and that this change in technology will be a sufficiently significant to

continued use of volume based learning. Based on this, the Volpe model wil

 use volume based learning for the final rule. 

The 2-Mode Hybrid (2MHEV) uses an adaptation of a conventional stepped-ratio 

automatic transmission which replaces some of the transmission clutches with two 

electric motor/generators allowing the transmission to act like a CVT. The 

motor/generators control the ratio of engine speed to vehicle speed. The clutches allo

the motors to be bypassed improving the transmission’s torqu
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

efficiency 

needed for

Chevrolet 

In a estart 

and regene

motor/gene

motor/gene

motor/gene it 

system due and secondary motor sizing. 

the CAFE 

engine dow ere 

the 2MHE

situations w

values rang ive 

to a CVT. 

NH aling 

factors in t

incrementa

application

2MHEV te

only applie

the passeng phase-in cap, so the 

maxim 

Plug-In H ybrid Electric 

Vehicle b

means to c

grid). Sec

greater capab at 

allows 

cles 

ntinuum with HE

for improved fuel economy at highway speeds and to meet the requirements 

 towing and high payload capacity. This type of system is used in the 

Tahoe Hybrid. 

ddition to providing the hybrid functions of engine stop and subsequent r

rative braking, the 2MHEV allows for pure EV operation. The two 

rators allow the engine to be run in efficient operating zones. The primary 

rator is comparable in size to that in the PSHEV system, but the secondary 

rator is larger. The 2-mode system cost is greater than that for the power spl

 to the additional transmission complexity

For this rule, and for similar reasons as discussed above in the PSHEV section, 

model considered a net effectiveness range of 23 to 33 percent, assuming no 

nsizing so as to preserve the utility nature of medium and large trucks wh

V technology is applied (e.g., maintaining full towing capability even in 

ith low battery charge). These estimates lead to incremental effectiveness 

ing from approximately 3 to 9.5 percent for the truck subclasses, and relat

TSA estimated MY 2012 costs using the updated component costs and sc

he hybrid cost estimating methodology discussed above and determined 

l cost estimates ranging from $3,521 to $5,779 for the three light duty truck 

s. These estimates include the 1.45 ICM markup value for high complexity 

chnology; volume based learning is applicable. The 2MHEV technology is 

d by the Volpe model at redesign cycle times, and it is not applicable to any of 

er car subclasses. NHTSA used a 3 percent per MY

um application rate occurs in MY 2016 at 15 percent. 

(25) Plug-In Hybrid

ybrid Electric Vehicles (PHEVs) are very similar to H

s, ut with three significant functional differences. The first is the addition of a 

harge the battery pack from an outside source of electricity (e.g. the electric 

ond, a PHEV would have a larger battery pack with more energy storage, and a 

ility to be discharged. Finally, a PHEV would have a control system th

the battery pack to be significantly depleted during normal operation. 

Table V-3 below, illustrates how PHEVs compare functionally to both hybrid 

electric vehicles (HEV) and electric vehicles (EV). These characteristics can change 

significantly within each class/subclass, so this is simply meant as an illustration of the 

general characteristics. In reality, the design options are so varied that all these vehi

exist on a co Vs on one end and EVs on the other. 
245

Table V-33 Conventional, HEVs, PHEVs, and EVs Compared 

 Increasing Electrification

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Attribute Conventional HEV PHEV EV 

Drive Power Engine Blended 

Engine/Electric 

Blended 

Engine/Electric Electric 

Engine Size Full Size Full Size or Smaller Smaller or Much 

Smaller No Engine 

Electric Range None None to Very Short Short to Medium Medium to Long 

Battery Charging None On-Board Grid/On-Board Grid Only 

Deriving some of their propulsion energy from the electric grid provides several 

advantages for PHEVs. PHEVs offer a significant opportunity to replace petrole

for transportation energy with domestically-produced electricity. The reduction in 

petroleum usage does, of course, depend on the amount of electric drive the vehicle is 

capable of under its duty cycle. PHEVs also provide electric utilities the possibility to 

increase electric generation during “off-peak” periods overnight when there is excess 

generation capacity and electricity prices are lower. Utilities like to increase this

load” because it increases overall system efficiency and lowers average costs. Util

are also investigating the use of PHEV and EV batteries as a source of grid storag

capacity to provide ancillary services for grid stabilization purposes. Unlike most other 

alternative fuel technologies, PHEVs can initially use an existing infr

um used 

 “base 

ities 

e 

astructure for 

refueling (charging and l e reduced. 

d some 

ower 

ond 

emissions reductions of PHEVs. This model is based on the PERE (Physical Emission 

 

e 

 but the proportion of electric energy that is used to propel the vehicle is 

g 

iquid refueling) so investments in infrastructure may b

PHEVs will be considerably more costly than conventional vehicles an

other advanced technologies. To take advantage of their capability, consumers would 

have to be willing to charge the vehicles nightly, and would need access to electric p

where they park their vehicles. For many urban dwellers who may park on the street, or 

in private or public lots or garages, charging may not be practical. Charging may be 

possible at an owner’s place of work, but that would increase grid loading during peak 

hours which would eliminate some of the benefits to utilities of off-peak charging vs. 

peak. Oil savings will still be the same in this case assuming the vehicle can be charged 

fully. 

The effectiveness potential of PHEVs depends on many factors, the most 

important being the energy storage capacity designed into the battery pack. To estimate 

the fuel consumption and tailpipe CO2 reduction potential of PHEVs, EPA has develope

an in-house vehicle energy model (PEREGRIN) to estimate the fuel consumption/CO2

Rate Estimator) physics-based model used as a fuel consumption input for EPA’s

MOVES mobile source emissions model. 

PHEVs can have a wide variation in the All Electric Range (AER) that they offer.

Some PHEVs are of the “blended” type where the engine is on during most of the vehicl

operation,

significantly higher than that used in a PSHEV or 2MHEV. In this analysis, each PHEV 

was modeled with enough battery capacity for a 20-mile-equivalent AER and a power 

requirement to provide similar performance to a hybrid vehicle. 20 miles was selected 

because it offers a good compromise for vehicle performance, weight, battery packagin
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

e 

To calculate the total energy use, the PHEV can be thought of as operating in two 

distinct n the 

 and the Utility Factor 

calcula r 

a 

smaller, lighter-weight transmission and drive line components. Likewise the 

and cost. Given expected near-term battery capability, a 20 mile range represents th

likely capability that will be seen in PHEVs in the near-to-mid term. 

 modes, electric (EV) mode, and hybrid (HEV) mode. During EV operatio

fuel consumption is zero. The EV mode fuel economy can then be combined with the 

HEV mode fuel economy using the Utility Factor calculation in SAE J1711 to determine 

a total MPG value for the vehicle. (See TableV-3) 

TableV-34. Sample Calculation of PHEV Gasoline-Equivalent CO2 Reduction 

 Midsize Car 

EV energy comb (0.55 city / 0.45 hwy) 0.252 kwh/mi 

EV range (from PEREGRIN) 20 miles 

SAE J1711 utility factor 0.30 

HEV mode comb FE (0.55 city / 0.45 hwy) 49.1 mpg 

Total UF-adjusted FE (UF*FCEV + (1-UF)*FCHEV) 70.1 mpg 

Baseline FE 29.3 mpg 

Percent FE gain 139% 

Percent CO2 reduction -58% 

Calculating a total reduction based on model outputs

tions results in a 58 percent reduction in fuel consumption for midsize and smalle

passenger cars and small trucks and SUVs. This value is used as the net effectiveness 

estimate for these subclasses in the Volpe model, yielding incremental estimates of 

approximately 46 percent relative to CVT and independent of engine and other vehicle 

related effectiveness improvements. The CAFE model does not apply the PHEV 

technology to Large Cars and the Medium and Large Truck and SUV subclasses.

Using the hybrid cost estimating model and updated component costs, NHTSA 

determined MY 2012 incremental cost estimates for the Volpe model ranging from a low

of approximately $11,500 for a subcompact car to a high of approximately $19,000 for 

midsize performance car. This includes the 1.64 ICM markup value for very high 

complexity technology. Volume based learning lowers the costs in later model years, and 

a phase-in cap of 3 percent per model year is also applied. 

d. Vehicle Technologies 

(26) Mass Reduction

Reducing a vehicle’s mass, or down-weighting a vehicle, decreases fuel 

consumption by reducing the energy demand needed to overcome forces resisting motion,

and rolling resistance. Manufacturers employ a systematic approach to mass reduction

where the net mass reduction is the addition of a direct component or system mass 

reduction plus the additional mass reduction taken from indirect ancillary systems and 

components, as a result of full vehicle optimization, effectively compounding or 

obtaining a secondary mass reduction from a primary mass reduction. For example, use 

of a smaller, lighter engine with lower torque output subsequently allows the use of a 

compounded mass reductions of the body, engine and drivetrain reduce stresses on the 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

rther 

ct 

ple, 

ass 

ary weight reduction is 

whether or not the powertrain components can be included in the mass reduction effort, 

with th

d a 

ents 

es, 

 reductions. Mass 

reductions in

suspension components, steering components, wheels, tires and brakes, allowing fu

reductions in the mass of these subsystems. The reductions in unsprung masses such as

brakes, control arms, wheels and tires further reduce stresses in the suspension mounting

points. This produces a compound effect of mass reductions, which results in the socalled ripple effect. 

Estimates of the synergistic effects of mass reduction and the compounding effe

that occurs along with it can vary significantly from one report to another. For exam

in discussing its estimate, an Auto-Steel Partnership report states “These secondary m

changes can be considerable—estimated at an additional 0.7 to 1.8 times the initial mass 

change.”188 This means for each one pound reduction in a primary component, up to 1.8 

pounds can be reduced from other structures in the vehicle (i.e., a 180% factor). The 

report also discusses that a primary variable in the realized second

e lower end estimates being applicable when powertrain elements are unavailable 

for down-weighting. However another report by the Aluminum Association, which 

primarily focuses on the use of aluminum as an alternative material for steel, estimate

factor of 64 percent for secondary mass reduction even though some powertrain elem

were considered in the analysis.189 That report also notes that typical values for this 

factor vary from 50 to 100 percent. Although there is a wide variation in stated estimat

synergistic mass reductions exist and the effects result in tangible mass

 a single vehicle component, for example a door side impact / intrusion 

system, may actually result in a significantly higher weight savings in the total vehicle, 

depending on how well the manufacturer integrates the modification into the overall 

vehicle design. Accordingly care must be taken when reviewing reports on weight 

reduction methods and practices to ascertain if compounding effects have been 

considered or not. 

Manufacturers consider and utilize various methods and options for achieving 

vehicle mass reductions. Automotive companies have largely used weight savings in 

some vehicle subsystems to offset or mitigate weight gains in other subsystems from 

increase feature content such as sound insulation, entertainment system, etc. The mass 

reduction methods can be grouped in four major categories as follows. 

• Material Substitution: One of the more common methods, and one which 

NHTSA has considered in prior rulemakings, is material substitution, where 

lower density and/or higher strength materials are utilized in a manner that 

preserves or improves the function of a component under consideration for 

 

188 “Preliminary Vehicle Mass Estimation Using Empirical Subsystem Influence Coefficients,” M

D.E., Reddy, K. Auto-Steel Partnership Report, May 2007. Accessed on the Internet on May 30, 200

http://www.a-sp.org/database/custom/Mass%20Compounding%20-%20Final%20Report.pdf 

189 “Benefit Analysis: Use of Aluminum Structures in Conjunction with Alternative Powertrain 

Technologies in Automobiles,” Bull, M. Chavali, R., Mascarin, A., Aluminum Association Research 

Report, May 2008. Accessed on the Internet on April 30, 2009 at: 

alen, 

9 at: 

http://www.autoaluminum.org/downloads/IBIS-Powertrain-Study.pdf
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

usage of plastic composite and its strength in automotive 

industry. NHTSA acknowledge various approaches for material substitution 

and mass reduction. There are increasing numbers of advanced material 

ring. 

These technologies can reduce mass for vehicles components and sub-systems 

significan example 5

d steel 

• : Computer aided en ering (CAE ls are anoth portant 

f improving structural st th and component designs o better 

duce str and bend nts ap to 

r optimiz e dimensional aspects e 

s mass) wh aintaining otentially im ving the 

grate unique s in a mann at reduces by 

functions or eliminating separate faste examp f CAE in 

e a traditiona fram ehicle whic

red uction, where the new design 

c 

size. 

f 

redesign190. Aluminum Association commented on the increasing usage of 

aluminum while American Chemistry Council Plastics Division commented 

on the increasing 

applications in automotive industry, such as high strength steel body structure,

aluminum engine block and transmission case, as well as composite floo

tly or an

e mil

. F , aluminum hoo

counte rt. 

d o offers 40 t 0 percent mass

savings over th rpa

Smart Design gine ) too er im

method o reng so as t

optimize load paths and re esses ing mome plied

them. This allows bette ation of th of th

component (and thus it ile m or p pro

function, or may inte part er th mass 

combining ners. An le o

the extreme would b l “body on e” v h is 

esigned with a lighter “unibody” constr

optimizes exterior body size, passenger compartment space, powertrain layout 

and capacity, and the footprint dimension, while giving careful consideration 

of the utility and market position within the particular segment the vehicle 

competes in. Vehicle crashworthiness and safety performance must also be

considered and at least preserved, if not improved. 

• Content Optimization: Manufacture can achieve mass reduction through 

content optimization. Some manufactures have replaced spare tire and tire 

change hardware with tire inflator kits on some of its models, such as Cadilla

STS, Mazda MX-5 Miata to reduce weight and gain space. 

• Vehicle Downsizing: Another way of mass reduction is reducing vehicle 

This is not common currently in US due to many factors, such as consumer 

choices, attribute-based CAFE standard, gasoline price, etc. 

Regardless of how a vehicle’s mass is actually reduced, and what level if any o

secondary mass reduction is achieved, the fuel consumption reductions that result are 

fairly straightforward. A number of researchers and reports have examined the fuel 

consumption vs. weight reduction question for a variety of vehicle and engine types. For

the most part, one primary variable exists which thereby bounds the two possible 

alternatives191, that being whether or not the mass reductions result in: a) improved 

 

190 This includes substitution of high-strength steels, aluminum, magnesium or composite materials for 

components currently fabricated from mild steel. 

191 A third alternative would be to degrade the vehicle such that mass reduction and engine downsizing 

results in lower performance metrics however a primary objective established by NHTSA is that the 

modeling process does not perceptibly change the use, function, or utility of the vehicle under 

consideration, therefore this is not a viable alternative. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

lished 

, 

e, a 

 weight is generally expected to reduce fuel 

consumption by 3 to 4 percent. When appropriate engine resizing is applied and vehicle 

perform

e also 

he NPRM which, together with response received 

from P che, MEMA and CARB, agrees with these effectiveness values. 

In preparation for this rule, rch st for 

confidential product plan and other CAFE related technical information from 

manufa

iven 

2009. NHTSA reviewed the responses related to the subject of 

mass redu

ew 

tent), in other cases no 

signific or 

vehicle performance, such as 0 to 60 times, towing capacity; or power to weight ratio, or 

alternatively b) performance metrics that remain constant as a result of the weight 

reduction. This second alternative, with constant performance metrics, is accomp

through the application of engine resizing (e.g. engines with smaller displacements which

consume less fuel) that offsets the performance enhancing effects of the weight reduction

which from a fuel consumption perspective is obviously the more preferable approach. 

Thus two fuel consumption effectiveness estimates relating to mass reduction are 

generally stated in reports and literature, one which assumes improved vehicle 

performance (i.e., the engine displacement is unchanged), and one which assumes 

constant performance (i.e., the engine is resized). For the improved performance cas

10 percent reduction in vehicle curb

ance is held constant, a 10 percent curb weight reduction results in a 6 to 7 

percent fuel consumption savings. Both of these estimates are documented in literature 

and reports on the subject of mass reduction, including the 2002 NAS report, and ar

supported by simulation work conducted by Ricardo, Inc.192, an internationally 

recognized consultant who, under contract, has assisted both EPA and NHTSA in 

technical and rulemaking related matters. Aluminum Association also presented 

Ricardo’s study193 in response to t

ors

 in Ma 2009, NHTSA made a reque

cturers that produce light vehicles for sale in the U.S.194 Not every manufacturer 

responded, and those that did in some cases either resubmitted materials previously 

provided to the agency or submitted truncated responses, which is understandable g

the turmoil and uncertainty the industry was experiencing at that time. NHTSA also 

received responses for the latest request for product plans for this final rule which was 

sent out in September 

ction and the vehicle weight trends likely to occur in the MY 2012 – 2016 fleet. 

These responses didn’t show a consistent approach. In some cases manufacturers are 

indicating weight increases (due either to more stringent FMVSS requirements or n

model plans that incorporate heavier platforms or more con

ant change is noted either way, and in some cases the submissions are outdated

incomplete (e.g., impacts of the Fiat and Chrysler relationship and its effects on future 

product offerings). Although several OEMs have recently made public announcements 

 

192 “Benefit Analysis: Use of Aluminum Structures in Conjunction with Alternative Powertrain 

Technologies in Automobiles,” Bull, M. Chavali, R., Mascarin, A., Aluminum Association Research

Report, May 2008. Accessed on the Internet on April 30, 2009 at: 

http://www.autoaluminum.org/downloads/IBIS-Powertrain-Study.pdf

193 “Imp

acturers also made submissions to 

Congress and other governmental agencies where plans regarding future fleet planning, in terms of sales 

volumes and fleet configuration, were also discussed. 

act of Vehicle Weight Reduction on Fuel Economy for Various Vehicle Architectures”, Research 

Report, conducted by Ricardo Inc. for the Aluminum Association, 2008-04, Docket number: NHTSA2009-0059 

194 This was in addition to similar requests made during the MY 2011 final rule and the 2008 NPRM that 

preceded it. The request also preceded the President’s May 19, 2009 announcement regarding fuel 

economy and green house gas standards. NHTSA notes that some manuf
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

indicating their intentions to ease the 

upcoming years, the confidential product plans, to the extent they are a suitable source for 

making

gh 

’s curb 

ses 

and the 

s 

e 

 the specific reductions will be 

achieved (what techniques will be used, etc.), or what effect the changes will have on the 

vehicle

 analysis. 

, 

s of 

establish the future fleet composition, this included the manufacturer’s 

estimate for a future product’s fuel economy rating. Therefore, in these analyses, 

technol

s 

s will not account for their potential effect on fuel 

consumption without some further revision, as discussed below. 

In the MY 2 inal r

technologies that resulted in a maximum 5 hicle curb weight. 

Materia

les with 

heaviest of the vehicles in the U.S. fleet represented the most safety neutral, or potentially 

 decr light vehicle average fleet weights within 

 such a determination, do not appear to support this contention. 

However one manufacturer did submit what appears to the agency to be a 

comprehensive response to the March request which does show significant curb weight 

decreases on the order of 350 to 550 pounds occurring within the timeframe. Althou

the stated reductions are sizeable, representing some 5 to 10 percent of the vehicle

weight, some notes about the information provided are appropriate. First off, in all ca

these larger reductions are being implemented at product redesign cycles only, 

earliest of these occurs in the MY 2014 period.195 Secondly, the affected vehicles are 

from various vehicle segments, including cars and trucks, which represent high sale

volume and a sizeable portion of the manufacturer’s overall production. And lastly th

information provided does not describe, in any detail, how

’s physical dimensions, utility, or performance (safety and otherwise) afterwards. 

So while this information does support the belief that meaningful weight reductions are

possible, and that at least one OEM is intending to implement them, it does not contain

some of the information needed for a more robust

To gain further insight, NHTSA briefly discussed plans for weight decreases on 

future products with a few vehicle manufacturers. Although discussion of the methods 

used to achieve the reductions, and their impacts on dimensions and vehicle performance

were not within the scope of the conversations, the manufacturers did generally indicate 

their plans for decreasing fleet weights throughout the rulemaking period, with range

5 to 10 percent net curb weight decreases considered potentially realizable by MY 2016. 

In past rulemakings, where confidential product plan information was, to the extent 

possible, used to 

ogy changes such as weight reduction would have theoretically been accounted 

for in the Volpe modeling process. In the current rule, where a baseline MY 2008 fleet i

projected forward into a future adjusted fleet, planned technology changes such as 

reductions in vehicle weights, cannot be accounted for in this way, since there was no 

practical way of doing so. So to the extent mass reductions do occur in this rulemakings 

future fleet, the Volpe modeling proces

011 f ule NHTSA utilized three cumulative material substitution

 percent reduction in ve

l substitution was intended to be the primary means by which the weight 

reductions would be achieved. The three technologies were only applied to vehic

curb weights in excess of 5,000 pounds which effectively limited their applicability to

large trucks and SUVs. This was done on the basis that weight reduction from the

 

195 The reductions might be best characterized as an objective for a new model platform that the company

seeks to obtain. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

t 

SA 

ass 

urb 

eduction across all vehicle subclasses. This technology is available to the 

Volpe 

lement methods, 

are envisioned for achieving the weight savings. It is anticipated that this could occur 

during 

aint, which varies the level of reduction by subclass, results in 

lower levels of mass reduction in the smaller (and lighter) vehicles, and larger levels 

convers t 

tral 

rgest 

ntil 

cle, which was what lead NHTSA to set the cycle time for the MS2 technology 

to redesign only, which is the final constraint used in the modeling process. Table V-35 

below summarizes the mas ction , MS2, 

and the combined effects by each vehicle subclass they are applied to. When both MS1 

and MS

safety beneficial method of reducing vehicle weight. Since only large trucks were 

impacted, where towing and hauling capability is required, NHTSA used a 3.5 percen

fuel consumption reduction per 10 percent weight decrease (i.e., no engine resizing was 

assumed). NHTSA has revised its approach for mass reduction in the current analysis, as 

is discussed in the following paragraphs. 

In this rule, and in contrast to the 2011 rule, the Volpe model now applies two 

mass reduction technologies using a tiered approach. Mass reduction is intended to 

encompass a broader spectrum of methods for reducing vehicle mass, such as those 

discussed above, and those beyond material substitution, and is intended to be applicable 

to all vehicle subclasses, regardless of curb weight. Additionally in this analysis NHT

considers that vehicle performance metrics are maintained constant as a result of the m

reductions, so appropriate levels of engine resizing are assumed. 

The first of these technologies is MS1 which represents a 1.5 percent vehicle c

weight mass r

model from the start of the rulemaking period, MY 2012, and may be applied 

during both the refresh and the redesign cycle time. For the level of mass reduction 

required, material substitution techniques, or other relatively easy to imp

the early MYs of the rulemaking period and at the cycle times. 

The second mass reduction technology is MS2, which occurs subsequent to, and 

is cumulative to, the MS1 technology. Since MS2 requires more rigorous mass 

reduction, additional constraints are utilized in its application. MS2 involves mass 

reductions of 3.5 to 8.5 percent of curb weight dependent on which vehicle subclass it is 

applied to. This first constr

ely for the larger (and heavier) vehicles. This is intended to reflect, to the exten

possible, the agency’s past practice of reducing vehicle weights in the most safety neu

manner; smallest reductions in the smallest vehicles, largest reductions in the la

vehicles. Secondly, the MS2 technology is made unavailable to the Volpe model u

MY 2014 and thus constrained on the basis that the larger levels of mass reductions 

required, and the types of methods and techniques needed to achieve them, cannot 

realistically occur without sufficient leadtime for planning and implementation. In all 

likelihood these levels of mass reduction can only be achieved through a major redesign

of the vehi

s redu s, as a percent of curb weight, for the MS1

2 are applied, overall mass reduction of 5 to 10 percent can occur, dependent on

vehicle subclass. MEMA commented that "postponing additional mass reduction 

technologies until MY2014 not only hinders incorporation of already developed 

technologies, but also delays the overarching goal of the revised standard". NHTSA 

encourages any new technology application to comply with the revised standard without 

hindering vehicle safety. It is the manufacturer's choice to apply the most cost benefit 

technologies. Applying a phase-in year of 2014 does not mean manufacturers cannot 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

 to the 

th Technologies 

apply developed technology ahead of that. It just shows that NHTSA thinks that up to 

10% mass reduction needs more research, development and integration work, therefore 

realistically more lead time. 

Table V-35. Vehicle Mass (Weight) Reduction as a Percent of Curb Weight Due

Application of the MS1, MS2, and the Combination of Bo

Vehicle Class 

MS1 (%) 

Refresh/Redesign 

MS2 (%)* 

Redesign only 

Maximum Total 

Reduction (%) 

Subcompact PC 1.5 3.5 5.0 

Compact PC 1.5 3.5 5.0 

Midsize PC 1.5 6.0 7.5 

Large PC 1.5 8.5 10.0 

Subcompact Performance PC 1.5 3.5 5.0 

Compact Performance PC 1.5 3.5 5.0 

Midsize Performance PC 1.5 6.0 7.5 

Large Performance PC 1.5 8.5 10.0 

Small LT 1.5 6.0 7.5 

Midsize LT 1.5 6.0 7.5 

Large LT and Minivan 1.5 8.5 10.0 

 * - MS2 is unavailable until MY2014 

For effectiveness, and as discussed above, NHTSA assumes in this rule that a 10 

percent reduction in mass results in a 6.5 percent reduction in fuel consumption for MS2 

with appropriate engine downsizing (regardless of reduction technique used or the 

compounding factor achieved). This approach is intended to yield equivalent vehicle 

performance (i.e. 0-60 mph time, towing capacity, etc). Based on the Aluminum 

Association’s response to the NRPM, NHTSA modified the effectiveness for MS1. For 

MS1, because the amount of the mass reduction is small, normally no engine downsizing 

is cons is 3.5 

percent reduction in fuel consumption for a 10 percent reduction in mass. In developing 

costs fo

 material substitution by only considering the direct 

idered for this amount of mass reduction and the appropriate effectiveness 

r this rule NHTSA and EPA reviewed three studies of down-weighting/material 

substitution and the associated cost. The first study, the NAS report, estimated that 

vehicle weight could be reduced for approximately $1.50 per pound. (3-4% reductions in 

fuel consumption, without engine downsizing, from a 5% reduction in vehicle weight at a 

cost of $210-$350. This translates into $1.50 per pound, assuming a 3800 pound base

vehicle and using the midpoint cost.) Additionally, Sierra Research estimated a 10% 

reduction, with compounding, could be accomplished for a cost of $1.01 per pound. 

Finally, MIT estimated that the weight of a vehicle could be reduced by 14%, with no 

compounding, for a cost of $1.36 per pound. Our final cost estimate is $1.32 per pound 

and is based on the average of the three referenced studies. Applying an ICM factor of 

1.11 for a low complexity technology results in a compliance cost of $1.48 per pound. 

For the vehicle mass reduction technologies, neither volume-based nor time-based cost

reductions are applied since many of the materials under consideration are commodity 

based and the build of materials is only loosely defined. 

The Aluminum Association commented that NHTSA "significantly 

underestimated the potential of
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

compo ction". MEMA also commented that light materials can provide 

secondary mass saving anufacturers can achieve compounding 

through a systematica sign approach. But as stated before, the magnitude of 

compo of 

r 

e 

 compounding. 

 that the mass reduction technologies in this rule represent a 

realisti

B)

ow drag brakes redu c brake pads on rotors when the 

brakes disc 

 up 

applied, remains so th

nent mass redu

s. It is evident that m

l rede

unding effect varies significantly among different studies. NHTSA uses a total 

up to10 percent mass reduction in the Volpe model which includes mass compounding. 

The effect of mass compounding is also reflected in the cost of mass reduction due to the

cost saving in the downsizing of some of the components. NHTSA’s cost estimate fo

mass reduction also takes mass compounding into consideration by averaging the costs 

from the three studies mentioned above, in some of which mass compounding is 

considered. For future rulemaking, NHTSA intends to conduct further study of th

magnitude of mass

Lastly, the phase-in cap for MS1 in this rule is 85 percent in MYs 2012 to 2015 

and 100 percent in MY 2016, while for MS2 an 85 percent cap exists in MYs 2014 and 

2015 followed by a 100 percent in MY 2016. Although a departure from the 2011 

rulemaking, NHTSA believes

c approach that effectively, and when overall application rates are considered, 

accurately emulates the weight reductions likely to occur in the U.S. light vehicle fleet

within the rulemaking timeframe. 

(27) Low Drag Brakes (LD

L ce the sliding friction of dis

are not engaged because the brake pads are pulled away from the rotating 

either by mechanical or electric methods. While most passenger cars have already 

adopted this technology with the standardization of electronic brake control, there are 

indications that this technology is still available for body-on-frame trucks and for some 

large passenger cars. 

NHTSA’s MY 2011 CAFE final rule estimated the effectiveness of LDB to be

to 1 percent, based on confidential manufacturer data. NHTSA has reviewed this 

estimate and believes it to be applicable for this final rule. 

NHTSA reviewed the cost estimates from the MY 2011 CAFE final rule and 

determined that these estimates remain applicable for this final rule. The agency adjusted 

the costs to apply the ICM indirect cost multiplier of 1.11, for a low complexity 

technology, instead of the 1.5 RPE factor used in the 2011 final rule. The compliance 

cost for LDB is therefore $63 for a MY 2012 vehicle, and since no cost learning is 

roughout the rulemaking timeframe. 

The phase-in cap for LDB in this rule is 85 percent in MYs 2012 to 2014, and 100 

percent through the remainder of the rulemaking period. The Volpe model can apply this 

technology at a vehicle’s refresh or redesign years, and the technology is only applicable 

to the Large Car, Minivan, and Medium and Large Truck and SUVs since, as mentioned 

above, it is already largely utilized in most other subclasses. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

accomp

ehicle. This is based 

on a cost of $1 per tire per vehicle, 

includi

e to 

assess any potential impacts on vehicle dynamics and braking characteristics, 

vehicles du

heel 

ing 

(28) Low Rolling Resistance Tires (ROLL)

Tire rolling resistance is the frictional loss associated mainly with the energy 

dissipated in the deformation of the tires under load and thus influences fuel economy 

and CO2 emissions. Other tire design characteristics (e.g., materials, construction, and 

tread design) influence durability, traction (both wet and dry grip), vehicle handling, and 

ride comfort in addition to rolling resistance. A typical low rolling resistance tire’s 

attributes would include: increased tire inflation pressure, material changes, tire 

construction with less hysteresis, geometry changes (e.g., reduced aspect ratios), and

reduction in sidewall and tread deflection. These changes would generally be 

anied with additional changes to suspension tuning and/or suspension design. For

performance vehicle classifications, due to the increased traction requirements for 

braking and handling which currently cannot be fully met with low rolling resistance 

designs, the Volpe model does not apply this technology. 

NHTSA estimates a 1 to 2 percent increase in effectiveness with a 10 percent 

reduction in rolling resistance, which was based on the 2002 NAS report findings and 

consistent with the MY 2011 final rule estimate. NHTSA still believes that this NAS 

effectiveness estimate is valid for this final rule. 

Based on the MY 2011 CAFE final rule and the 2006 NAS/NRC report, NHTSA 

has estimated the cost r low rolling resistance tires to be $6 per v fo

 as estimated by NAS/NRC 2006 report, which is $5

ng the spare tire. When applying the ICM low complexity markup factor of 1.11, 

this results in a compliance cost of $6 per vehicle for a MY 2012 vehicle.196 Lower 

rolling resistance tires are widely available today however, due to the commodity based 

nature of the materials used in tire manufacturing, cost learning is not considered 

applicable. 

The phase-in cap for the ROLL technology in this final rule is 85 percent in MYs 

2012 to 2014, and 100 percent through the remainder of the rulemaking period. Du

the need to 

the Volpe model can only apply this technology at a vehicle’s refresh or redesign cycle, 

and as noted above, the model does not apply the technology to the performance subclass 

e to suitability concerns. 

(29) Front or Secondary Axle Disconnect for Four-W

Drive Systems (SAX)

Energy is required to continually drive the front, or secondary, axle in a four 

wheel drive system even when the system is not required during most operat

conditions. This energy loss directly results in increased fuel consumption and CO2

emissions. Many part-time four-wheel drive systems use some type of front axle 

 

196 Note that the costs developed for low rolling resistance tires for this analysis do not include the increase 

e 

nd to include the lifetime costs in the final analysis. 

in lifetime costs that would be expected at each tire replacement. Instead, the analysis includes only th

upfront increase in costs. The agencies inte
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

disconn rmally 

o- 

 front 

ot aware of any manufacturer 

offerin

 an 

e MY 

e lower and are estimated to be $84 for a 

MY 2016 vehicle (200

2014, 

 Drag Reduction (AERO)

ct of its frontal area and drag coefficient. Reductions in these quantities can 

therefore reduce drag and lower the vehicle’s fuel consumption and CO2 emissions. 

Although frontal areas tend to be relatively similar within a vehicle class (mostly due to 

market-competitive size requirements), variations in drag coefficient can be observed. 

ect to provide shift-on-the-fly capabilities. The front axle disconnect is no

part of the front differential assembly. As part of a shift-on-the-fly four-wheel drive 

system, the front axle disconnect serves two basic purposes. First, in two-wheel-drive 

mode, it disengages the front axle from the front driveline so the front wheels do not turn 

the front driveline at road speed, saving wear and tear. Second, when shifting from tw

to four-wheel drive "on the fly" (while moving), the front axle disconnect couples the 

front axle to the front differential side gear only when the transfer case's synchronizing

mechanism has spun the front driveshaft up to the same speed as the rear driveshaft. 

Four-wheel drive systems that have a front axle disconnect typically do not have either

manual- or automatic-locking hubs. To isolate the front wheels from the rest of the

driveline, front axle disconnects use a sliding sleeve to connect or disconnect an axle 

shaft from the front differential side gear. NHTSA is n

g this technology in the U.S. today on unibody frame vehicles; however, it is 

possible this technology could be introduced by manufacturers within the rulemaking 

time period. 

Based on confidential manufacturer data, the MY 2011 final rule estimated

effectiveness improvement of 1 to 1.5 percent for the SAX technology and after thorough 

review. NHTSA finds this to be an accurate estimate for this final rule. 

Regarding costs, NHTSA reviewed the incremental compliance cost from th

2011 final rule and concluded it remains accurate. However a new ICM factor of 1.11, 

for a low complexity technology, replaces the 1.5 RPE markup factor used previously. 

Thus, the compliance cost estimate for this rule is $87 for MY 2012 vehicles. As the 

SAX technology is readily available and in use today, time based learning is considered 

applicable, hence the costs for later MYs will b

7$) 

The phase-in cap for SAX in this final rule is 85 percent in MYs 2012 to 

and 100 percent throughout the remainder of the rulemaking period. Due to varying 

vehicle architecture designs, and thus the potential complexity associated with 

implementing these systems, the Volpe model can only apply this technology at a 

vehicle’s refresh or redesign years. SAX is applicable to all vehicle subclasses however 

an engineering constraint programmed within the Volpe model’s programming code 

ensures the SAX technology is only applied to vehicles that have (true) four-wheel drive 

systems in the baseline vehicle (i.e., SAX is not applicable to all-wheel drive equipped 

vehicles). 

(30) Aerodynamic

Many factors affect a vehicle’s aerodynamic drag and the resulting power 

required to move it through the air. While these factors change with air density and the 

square and cube of vehicle speed, respectively, the overall drag effect is determined by 

the produ
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Signific ented 

during a mic 

reductions, with a somewhat lower effective s, may be achieved through the use of 

rev

dev

fascias, modified front air ar deck lips and 

underbody panels, and lower aerodynamic drag ex

at a flee o 0 t to

ith a cav r ve

equates to increm l reductions in fuel consump n of 2 to 3 

s are g by confid al 

fore, N A continues to use 

le. 

so estimated e from $60 to $116 which a 1

5. N A and re ed th 11 

uld o t wer en the 

 cost estimat this making is $48 wi

 ICM mar e fo w complexity lo

 v d wi crease uture

O te logy is conside al

ce subclasse re th lpe m e app is 

e in cap for AERO his rule 

00 pe roug rema t lem 

es of imp ts en ed i AE echn

h or r cycle

d but e e fin e a

ntified hnolo hat w t be lab e 

is rulemak hese technologie ile ider

E and The e: el ic ve s, 

 lean bur line direct injectio BD mog s 

I), and assi cha an ser

s are likely to become available in small 

olo estim by t encies) 

ith the more conve l techn ies lis eref

alysis would preclude election, when e ting cost e 

ines ently lable i rope eve ese 

e t oth eff and the stan s 

lfu in t ls. T er lo

he research phase of de t. A an w ti

dustry and system supplier re se o nd ld 

ailable, consider the e in rul y. 

 

ant changes to a vehicle’s aerodynamic performance may need to be implem

 redesign (e.g. changes in vehicle shape). However, shorter-term aerodyna

nes

ised exterior components (typically at a model refresh in mid-cycle) and add-on 

ices that currently being applied. The latter list would include revised front and rear 

 dams and rear valances, addition of re

terior mirrors. 

The MY 2011 final rule estimated th

uction is attainable (w

t average

eat for “highf 10 to 2rfo

 percen

ma

tal 

aerodynamic drag red pe nce” hicles 

described below) which enta tio

percent for both cars and trucks. These number enerally supported enti

manufacturer data and public technical literature and there HTS

this estimate for this final ru

The 2011 final rule al a rang used .5 

RPE; the non-RPE costs were therefore $40 to $7 HTS EPA view e 20

costs and concluded the estimate sho be closer t he lo d of 2011

rulemaking range. Thus, the e used in rule ($43 thout 

markup), which includes a 1.11 kup valu r a lo techno gy. 

This compliance cost is for a MY 2012 ehicle an ll de in f years due to

the application of time-based learning. The AER chno red to ready 

be in use on most performan s, therefo e Vo odel do s not ly th

technology to performance vehicles. Th phase- in t final is 85

percent in MYs 2012 to 2014, and 1 rcent th h the inder of he ru aking

period. As noted above, the typ rovemen vision n the RO t ology 

are suitable for application at refres edesign . 

e. Technologies considere not includ d in th al rul nalysis

NHTSA and EPA have ide six tec gies t ill no avai le in th

time frame considered under th ing. T s, wh cons ed, 

were not made available in the CAF OMEGA models. y ar ectr hicle

camless valve actuation (CVA), n gaso n (L I), ho eneou

charge compression ignition (HCC

hydrauli

 electric st turbo rging d full ies 

c hybrids (HHV). While electric v

numbers in the near future, the costs for t

ehicle

his techn gy (as ated he ag

are non-competitive w ntiona

 their 

olog ted above. Th ore, 

the Volpe model an s

are curr

stima the s of th

rule. Lean Burn direct injection eng

vehicles cannot be designed at this ti

 avai n Eu , how r, th

m

in the United States with the current su

o be b icient 

he fue

m

he oth

eet NOx

 techno

dard

r levels gies 

listed are still in t velopmen

rog

NHTS d EPA ill con nue to 

monitor the in s for p

 us

ss on the

 re 

 technol

em ng 

gies, a

a it

shou

they become more av m for futu aki ctiv More

details are described below.
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

i. Electric Vehicle

ntense interest in Hyb icles a he dev men ybr

vehicle battery and motor technology has he ed make Electric Vehicle technology more 

viable than it has ever been. Electric Vehicles (EVs) require much larger batteries than 

either HEVs or PHEVs, but the batteries must be of a high-energy and lower-power 

design to deliver an appropriate amount of power over the useful charge of the battery. 

These high-energy batteries are generally less expensive per kilowatt-hour than highpower batteries required for hybrids, but the size of the battery pack still incurs a 

considerable cost. 

Electric motor and power electronics designs are very similar to HEV and PHEV 

designs, but they must be larger, more powerful, and more robust since they provide the 

only motive power for the vehicle. On the other hand, the internal combustion engine, 

fuel system, and possibly the transmission can all be removed for significant weight, 

complexity and cost savings. 

While a few manufactures have released public statements indicating that they are 

planning on producing small volumes of electric vehicles within the rulemaking time 

frame, the agency believes that the application of electric vehicles above and beyond 

these small volumes will not likely be feasible. Thus for purposes of this final rule, 

NHTSA has not included electric vehicles in its analysis. 

ii. Camless Valve Actuation 

Camless valve actuation relies on electromechanical actuators instead of 

camshafts to open and close the cylinder valves. When electromechanical actuators are 

used to replace cams and coupled with sensors and microprocessor controls, valve timing 

and lift can be optimized over all conditions. An engine valvetrain that operates 

independently of any mechanical means provides the increased flexibility for intake and 

exhaust timing and lift optimization. With it comes increased ability to vary valve 

overlap, the rapid response required to change between combustion operating modes 

(such as HCCI and GDI), intake valve throttling, cylinder deactivation, and elimination 

of the camshafts (reduced friction and rotating mass). This level of control can enable 

even further incremental reductions in fuel consumption and. 

 This technology has been under research for many decades and although progress 

is being made, NHTSA has not found evidence to support that the technology can be 

successfully implemented within the 2012 through 2016 timeframe of these regulations. 

Thus, NHTSA has not estimated cost or effectiveness for this technology at this time. 

iii. Lean-Burn Gasoline Direct Injection Technology 

Direct injection, especially with diesel-like “spray-guided” injection systems, 

enables operation with excess air in a stratified or partially-stratified fuel-air mixture, as a 

way of reducing the amount of intake throttling. Also, with higher-pressure fuel injection 

systems, the fuel may be added late enough during the compression stroke so as to delay 

the onset of auto-ignition, even with higher engine compression ratios or with boosted 

s 

The recent i rid veh nd t elop t of H id 

lp
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

engine may achieve high engine thermal effi ncy, which approaches that of a diesel 

eng

lea

Federal Tier 2 em in combustion 

chamber design and repositioning of ors wed f air/fu g 

and combustion efficiency. There is a s wall- jection ay 

guided injection, which improves injec recision targeting ards the sp

ombin ith advanc n NOx afte

DI e ay e tually be ossibility in North Americ 

nt a ent is the avai ltra ess than 

 a nic quireme r lean-bur DI engines eet 

ions standards, Since we do not believe that ULS gasoline will 

od app le to this final rule, the technology w t 

e N , NHTS ed comments from MECA stating t at 

ine Direct Injection of e pote for lean operation. MECA commen so 

 fuel r limits gasoline ppm avera 80 ppm ca re 

Ox a er catalysts to be a v able NOx control strategy fo fuel 

ur th ploy direct fuel injecti chnology

nsistent with NHTSA’s assessment. 

iv. H eou arge C ession I 

Gasoline homogene e c ression ign e

 alt e engin ing mode that does no y on 

m n. Th inciples more close ligned with

ch the compressed charge exceeds a temperature and 

on auto-ignition although it diffe diesel ing 

 tha ing a dif n control ombustion nt. 

is much shorter in d with h er therma

ag its over ficiency f o main reasons: 

he engine is op with gher comp ion ratio, with a short 

esult a h d e

ated ally e a

hav ease in eng e brake ef ncy (typica 25-

greater than 35% a h en the HC erating ra 197 

em s are favorab ring HCC eration. L r 

peratures e to high dilution) k engine-ou ission a 

ally bel er 2 le ithout aftertreatment d particulates are 

us nature of the premixed charge. 

 

intake pressure. Taken together, an optimized “lean-burn” direct injection gasoline 

cie

ine. European gasoline direct-injection engines have implemented stratified-charge

n-burn GDI, although at higher NOx emissions levels than are allowed under U.S. 

issions standards. Fuel system improvements, changes

the inject have allo or better el mixin

currently hift from guided in to spr

tion p and tow ark 

plug, increasing lean combustion stability. C ed w es i rtreatment, lean-burn G ngines m ven a p a. 

NHTSA’s curre ssessm that lability of u -low sulfur (l

15 ppm sulfur) gasoline is

EPA’s Tier 2 N

 key tech al re nt fo n G to m

Ox emiss

be available during the m el years licab as no

applied in the NHTSA analysis. 

In response to th

Gasol

PRM

fers th

A receiv

ntial 

h

ts al

stated the current EPA

too hig

 sulfu

dsorb

for (30

i

ge, p) a

h to allow lean N r 

efficient, gasoline lean-b n engines at em on te . 

MECA’s comments are co

omogen

ous charg

s Ch

omp

ompr

ition (HCCI), a

gnition

lso referr d to as 

controlled auto-ignition (CAI), is an ernat e operat t rel

a spark event to initiate co bustio e pr are ly a a 

diesel combustion cycle, in whi

pressure necessary for sp taneous rs from by hav

a homogenous fuel/air charge rather n be fusio led c eve

The subsequent combustion

efficiency. 

 event uration igh l 

An HCCI engine has inherent advant es in all ef or tw

• T erated a hi ress and er

combustion duration, r ing in igher thermo ynamic effici ncy, and 

• The engine can be oper virtu unthrottled, ven at light lo ds, 

Combined, these effects 

28%) to 

e shown an 

t the hig

incr

d of

in

CI op

ficie

nge.

lly

Criteria pollutant 

peak in-cylinder 

ission

(du

very le du

eep 

I op

t NOx em

owe

tem s to 

minimum – realistic ow Ti vels w – an

low due to the homogeneo

 197 “An HCCI Engine Powe

Technical Paper No. 2004-01

r Pla rid icle,” Sun Thomas a . Gray, Jr., S

-093

nt for a Hyb

3, 2004. 

 Veh , R., R. nd C AE 
DELIBERATIVE DOCUMENT – DO NOT RELEASE 

259

nherent difficulty in maintaining combustion stability without 

knock I is di lt to cont quiring k from

nsors a d eng ontrol lo o optimiz bustion t g, 

ering the t natu f operat onditions in a vehic ue 

er wh asoline I combustion is stable, t

hie a natur lly-aspirated engine is somewhat limi

ely y com application would n a “

between HCCI and spark ignition combustion modes, in which HCCI 

 for best e at ngine and spa tion wou

 loads and at s ty f dual-mode strategy h ready bee

diesel HCCI engin n Europ and A bly the vensis D-Cat 

 light-duty “ mb diese

, gaso CCI te logy was considered t l be in the 

 ufa ers have e public s ents abou

H to lig y pass vehicles, have sign nt 

ration prog imed oducing able produ ithin the n -10 

d n as to fuel consumption and reduction 

 in the li . Ba n confi al manufacturer information, it is 

believed that a gasoline HCCI / GDI dual-mode engine might achieve 10-12% reduction 

in fuel consumption, compared to a comparable SI engine. Despite its promise, 

application of HCCI in light duty vehicles is not yet ready for the market. It is not 

anticipated to be seen in volume for at least e next 5-10 years, which is concurrent with 

many manufacturers’ public estimates. As noted in MY 2011 CAFE final rule that the 

technology will not be available within the time frame considered based on a review of 

confidential product plan information. 

v. Electric Assist Turbocharging 

The Alliance commented in NHTSA’s previous rulemaking that global 

development of electric assist turbocharging has not demonstrated the fuel efficiency 

effectiveness of a 12V EAT up to 2kW power levels since the 2004 NESCCAF study, 

and stated that it saw remote probability of its application over the next decade. While 

hybrid vehicles lower the incremental hardware requirements for higher-voltage, higherpower EAT systems, NHTSA believes that significant developmental work is required to 

demonstrate effective systems and that implementation in significant volumes will not 

occur in the 2012 to 2016 time frame considered in this rulemaking. Thus, this 

technology was not included in the final rule. 

 E. Cost and effectiveness tables

 The tables representing the Volpe model input files for MY 2012 incremental 

technology costs by vehicle subclass are presented below. The tables have been divided 

into passenger cars, performance passenger cars, and light trucks to make them easier to 

read.

Due to the i

encountering engine , HCC fficu rol, re feedbac incylinder pressure se nd rapi ine c gic t e com imin

especially consid ransient re o ing c seen le. D

to the highly dilute conditio

range of e

ns und

vable in 

ich g

a

 HCC he 

ngine loads ac ted. 

Because of this, it is lik

mode” strategy 

that an mercial operate i dualwould be utilized fficiency light e loads rk igni ld be 

used at higher idle. Thi pe o as al n 

employed in 

and the Nissan

es i

MK” co

e

ustion 

sia (nota

ls). 

 Toyota A

Until recently line H chno o stil

research phase. However, most man ctur mad tatem t the 

viability of incorporating CCI in ht-dut enger and ifica

vehicle demonst rams a at pr a vi ct w ext 5

years. There is widesprea opinio the CO2

potential for HCCI terature sed o denti

th
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T

S 

able V-36. Technology Incremental Cost Estimates, Passenger Cars

VEHICLE TECHNOLOGY ICM COSTS PER VEHICLE (2007$) BY VEHICLE

SUBCLASS - PASSENGER CAR

Su act bcomp Compact Midsize Large

 Car Car Car Car

Nominal Baseline Engine (Fo t B r Cos asis) In e 4 lin I 4 Inline V6 n e lin 4

Low Friction Lubricants 3 3 3 3 

Engine Friction Reduction EFR 50 50 50 75 

VVT - Coupled Cam Phasing (CCP) on SOHC CCPS 45 45 45 90 

Discrete Variable Valve Lift (DVVL) on SOHC DV S VL 142 142 142 205 

Cylinder Deactivation on SOHC DEACS n.a. n.a. n.a. 56 0 -

VVT - Intake Cam Phasing (ICP) ICP 45 45 45 90 

VVT - Dual Cam Phasing (DCP) DCP 38 38 38 83 

Discrete Variable Valve Lift (DVVL) DV D on DOHC VL 142 142 205 142

Continuously Variable Valve Lift (CVVL) CVVL 277 277 277 509 

Cylinder Deactivation on DOHC DEACD n.a. n.a. n.a. 0 - 56 

Cylinder Deactivation on OHV DEACO n.a. n.a. n.a. 170 

VVT - Coupled Cam Phasing (CCP) o CC n OHV PO 45 45 45 45 

Discrete Variable Valve Lift (DVVL) D on OHV VVLO 142 142 142 - 56 0

Conversion to DOHC with DCP CDOHC 276 276 276 436 

Stoichiometric Gasoline Direct Injection (GDI) SGDI 236 236 341 236

Combustion Restart CBRST 118 118 118 118 

Turbocharging and Downsizing TRBDS 445 445 445 325 

Exhaust Gas Recirculation (EGR) Bo EG ost RB 144 144 144 144 

Conversion to Diesel following CBRS D 1,527 556 - 

1,612 T SLC 1,527. 1,527 1,

Conversion to Diesel following TRBD D 938 088-

1,143 S SLT 938. 938 1,

6-Speed Manual/Improved Internals 6MAN 250 250 250 250 

Improved Auto. Trans. Controls/Externals IATC 60 60 60 60 

Continuously Variable Transmission CVT 250 250 250 250 

6/7/8-Speed Auto. Trans with Improved NAUTO 112 112 112 112 Internals 

Dual Clutch or Automated Manual Tr ion ansmiss DCTAM (59) (59) (8) (8) 

Electric Power Steering EPS 106 106 106 106 

Improved Accessories IACC 128 128 128 128

12V Micro-Hybrid MH EV 288 311 342 367 

Belt mounted Integrated Starter Generator BISG 286 286 286 286 

Crank mounted Integrated Starter Gen CI erator SG 2,791 3, 47 3,107 319 3,5

Power Split Hybrid PSHEV 1,600 2,133 2,742 3,261 

2-Mode Hybrid 2MHEV n.a. n.a. n.a. n.a.

Plug-in Hybrid PHEV 11,520 16,21 n.a. 14,135 5

Mass Reduction (1.5%) MS1 1.5 1.5 1.5 1.5 

Mass Reduction (3.5 to 8.5%) MS2 1.5 1.5 1.5 1.5 
261

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Low Rolling Resistance Tires ROLL 6 6 6 6 

Low Drag Brakes LDB n.a. n.a. n.a. 63 

Secondary Axle Disconnect SAX 87 87 87 87 

Aero Drag Reduction AERO 48 48 48 48 
262

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T ars 

E 

able V-37. Technology Incremental Cost Estimates, Performance Passenger C

 

VEHICLE TECHNOLOGY ICM COSTS PER VEHICLE (2007$) BY VEHICL

SUBCLASS - PERFORMANCE PASSENGER CARS 

Perform. Perform. Perform. Perform. 

Subcomp. Compact Midsize Large 

 Car Car Car Car 

Nominal Baseline Engine (For Cost Basis) Inline 4 V6 V6 V8 

Low Friction Lubricants LU 3 B 3 3 3 

Engine Friction Reduction EF 50 75 R 75 101 

VVT - Coupled Cam Phasing 

(CCP) on SOHC CC 45 PS 90 90 90

Discrete Variable Valve Lift 

(DVVL) on SOHC DV 142 205 VLS 205 293 

Cylinder Deactivation on SOHC DE n.a. 0 - 56 ACS 0 - 56 0 – 56 

VVT - Intake Cam Phasing 

(ICP) ICP 45 90 90 90

VVT - Dual Cam Phasing 

(DCP) DCP 38 83 83 82

Discrete Variable Valve Lift 

(DVVL) on DOHC DV 142 205 VLD 205 293 

Continuously Variable Valve CV 277 509 5 5 Lift (CVVL) VL 09 55

Cylinder Deactivation on 

DOHC DE n.a. 0 - 5 ACD 6 0 - 56 0 – 56 

Cylinder Deactivation on OHV DE n.a. 170 ACO 170 190 

VVT - Coupled Cam Phasing

(CCP) on OHV CC 45 45 PO 45 45

Discrete Variable Valve Lift DV 142 0 - 5 56 (DVVL) on OHV VLO 6 0 - 56 0 – 

Conversion to DOHC with DCP CD 276 436 OHC 436 552 

Stoichiometric Gasoline Direct

Injection (GDI) SG 236 341 DI 341 552 

Combustion Restart CBRST 118 118 118 118 

Turbocharging and Downsizing TR 44 BDS 5 325 325 919 

Exhaust Gas Recirculation 

(EGR) Boost EG 144 144 RB 144 144 

Conversion to Diesel following 

CBRST DS 1,527 556 – 1,6 1,556 LC 1, 12 – 1,612 2,294 – 2,349 

Conversion to Diesel following DS 938 8 – ,08 1,287 TRBDS LT 1,08 1,143 1 8 – 1,143 1,231 –

6-Speed Manual/Improved

Internals 6M 250 250 AN 250 250 

Improved Auto. Trans. 

Controls/Externals IAT 60 C 60 60 60

Continuously Variable CV 250 250 0 Transmission T 250 25

6/7/8-Speed Auto. Trans with NA 12 – 2 2 – 11 214 Improved Internals UTO 1 14 11 214 2 – 214 112 - 

Dual Clutch or Automated DCTAM (8) (8) (8) (8) 
263

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Manual Transmission 

Electric Power Steering EPS 106 106 106 106 

Improved Accessories IACC 128 128 128 128 

12V Micro-Hybrid MH 314 33 EV 7 372 410 

Belt mounted Integrated Starter BIS 286 286 2 286 Generator G 86 

Crank mounted Integrated CISG 839 3,149 3 ,571 Starter Generator 2, ,335 3

Power Split Hybrid PS 3,661 4,018 5, HEV 287 6,723 

2-Mode Hybrid 2M n.a. n.a. n.a. n.a. HEV 

Plug-in Hybrid PH 14,98 16,79 EV 7 2 19,265 n.a. 

Mass Reduction (1.5%) MS1 1.5 1.5 1.5 1.5 

Mass Reduction (3.5 to 8.5%) MS2 1.5 1.5 1.5 1.5 

Low Rolling Resistance Tires ROLL n.a. n.a. n.a. n.a. 

Low Drag Brakes LDB n.a. n.a. n.a. 63 

Secondary Axle Disconnect SAX 87 87 87 87 

Aero Drag Reduction AERO n.a. n.a. n.a. n.a. 
264

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Table V-38. Technology Incremental Cost Estimates, Light Trucks 

VEHICLE TECHNOLOGY ICM COSTS PER VEHICLE (2007$) BY VEHICLE

SUBCLASS - LIGHT TRUCKS 

Minivan Small Midsize Large

 LT LT LT LT

Nominal Baseline En ne (For Cost Basis) gi V6 line 4 V6 nI V8 

Low Friction Lubricants LUB 3 3 3 3 

Engine Friction Reduction EFR 75 50 75 101

VVT - Coupled Cam Phasing (CCP)

on SOHC CCP 90 5 90 S 4 90 

Discrete Variable Valve Lift (DVVL)

on SOHC DVV 0 4 2 LS 2 5 1 2 05 293 

Cylinder Deactivation on SOHC DEA - 56 n.a - CS 0 . 0 56 0 – 56 

VVT - Intake Cam Phasing (ICP) ICP 90 45 90 90 

VVT - Dual Cam Phasing (DCP) DCP 83 38 83 83 

Discrete Variable Valve Lift (DVVL)

on DOHC DVV 0 4 2 LD 2 5 1 2 05 293 

Continuously Variable Valve Lift C (CVVL) VV 50 7 5 L 9 2 7 09 555 

Cylinder Deactivation on DOHC DEACD 0 - 56 n.a - . 0 56 0 – 56 

Cylinder Deactivation on OHV DEACO 17 .a 1 0 n . 70 190 

VVT - Coupled Cam Phasing (CCP) 

on OHV CCP 5 5 45 O 4 4 45 

Discrete Variable Valve Lift (DVVL) DVV - 5 4 - on OHV LO 0 6 1 2 0 56 0 – 56 

Conversion to DOHC with DCP CDO 43 7 4 HC 6 2 6 36 552 

Stoichiometric Gasoline Direct SGDI 34 3 3 Injection (GDI) 1 2 6 41 391 

Combustion Restart CBR 11 1 1 ST 8 1 8 18 118 

Turbocharging and Downsizing TRBD 325 445 32 S 5 919 

Exhaust Gas Recirculation (EGR) 

Boost EGRB 4 44 14 14 1 4 144 

Conversion to Diesel following 

CBRST DSL 6 -

1,61 C 2,29 1,55

2 1,527 556 - 1, 1,612 4 – 2,349 

Conversion to Diesel following 

TRBDS DSLT 088-1 38 1, ,143 9 1,088 – 1,143 1,23 287 1 – 1,

6-Speed Manual/Improved Internals 6MAN 250 250 250 250 

Improved Auto. Trans. 

Controls/Externals IATC 0 0 60 6 6 60 

Continuously Variable Transmission CVT 25 5 2 0 2 0 50 n.a. 

6/7/8-Speed Au

Improved Intern

to. Trans with NAU 11 1 als TO 2 1 2 112 - 214 112 - 214

Dual Clutch or Automated Manual 

Transmission DCT (8 AM ) (8) (8) (8) 

Electric Power Steering EPS 10 6 106 6 10 106 

Improved Accessories IACC 128 128 128 n.a. 

12V Micro-Hybrid MHEV 367 325 376 n.a. 
DELIBERATIVE DOCUMENT – DO NOT RELEASE 

265

ntegrated Starter BISG 286 286 28 Belt mounted I

Generator 6 n.a.

Crank mounted Integrated Starter CISG 3,547 3,141 3,611 Generator 5,124 

Power Split Hybrid PSH 3,261 2,377 3,46 EV 2 n.a. 

2-Mode Hybrid 2MH n.a. 3,661 EV 4,887 - 4,989 5,90 ,004 2 – 6

Plug-in Hybrid PHE n.a ,7 n V . 14 21 .a. n.a. 

Mass Reduction (1.5%) MS1 1.5 1.5 1.5 1.5 

Mass Reduction (3.5 to 8.5%) MS2 5 1.5 1.5 1.5 1.

Low Rolling Resistance Tires ROLL 6 6 6 6 

Low Drag Brakes LDB 63 n.a. 63 63 

Secondary Axle Disconnect SAX 87 87 87 87 

Aero Drag Reduction AERO 48 48 48 48 

The tables representing the Volpe model input files for incremental technology 

effectiveness values by vehicle subclass are presented below. The tables have been 

divided into passenger cars, performance passenger cars, and light trucks to make them 

easier to read.
266

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T

VEHI 

able V-39. Technology Incremental Effectiveness Estimates, Passenger Cars

CLE TECHNOLOGY INCREMENTAL FUEL CONSUMPTION REDUCTION

(-%) BY VEHICLE SUBCLASS - PASSENGER CAR 

Subcompact Compact Midsize Large

 Car Car Car Car

Nominal Baseline Engine (For Cost Basis) Inline I I e 4 4 n 4 line nlin V6

Low Friction Lubricants LUB 0.5 0.5 0.5 0.5 

Engine Friction Reduction EFR 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 0 1.0 - 2.

VVT - Coupled Cam Phasing (CCP) 

on SOHC CCPS 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0

Discrete Variable Valve Lift (DVVL) 

on SOHC DVVLS 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0

Cylinder Deactivation on SOHC DEAC n S .a. n.a. n.a. 2.5 - 3.0

VVT - Intake Cam Phasing (ICP) ICP 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0

VVT - Dual Cam Phasing (DCP) DCP 2.0 - 3.0 2.0 - 3.0 2.0 - 3.0 0 2.0 - 3.

Discrete Variable Valve Lift (DVVL) 

on DOHC DVVLD 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0

Continuously Variable Valve Lift 

(CVVL) CVVL .5 1. 5 1 - 3.5 5 - 3. 1.5 - 3.5 1.5 - 3.5

Cylinder Deactivation on DOHC DEAC n D .a. n.a. n.a. 0 - 0.5

Cylinder Deactivation on OHV DEAC n O .a. n.a. n.a. 3.9 - 5.5

VVT - Coupled Cam Phasing (CCP) 

on OHV CCPO 1.0 - 1.5 1.0 - 1.5 1.0 - 1.5 1.0 - 1.5

Discrete Variable Valve Lift (DVVL) DVVL .5 on OHV O 0 - 2.5 0.5 - 2.5 0.5 - 2.5 0.5 - 2.5

Conversion to DOHC with DCP CDOH 1.0 C - 2.5 1.0 - 2.5 1.0 - 2.5 1.0 - 2.5

Stoichiometric Gasoline Direct SGDI Injection (GDI) 2.0 - 3.0 2.0 - 3.0 2.0 - 3.0 2.0 - 3.0

Combustion Restart CBRST 2.0 - 2.5 2.0 - 2.5 2.0 - 2.5 2.0 - 2.5

Turbocharging and Downsizing TRBD 4.2 S - 4.8 4 .2 - 4.8 4.2 - 4.8 1.8 - 1.9

Exhaust Gas Recirculation (EGR) 

Boost EGRB 3.5 - 3 .0 .0 4.0 .5 - 4.0 3.5 - 4 3.5 - 4

Conversion to Diesel following 

CBRST DSLC 3.5 – 1  7 1 13.9 3.5 –13.9 

13.5 – 

13.9

10.8 - 

11.

Conversion to Diesel following D TRBDS SLT 5.3 – 6.9 5.3 – 6.9 5.3 – 6.9 9 5.3 - 6.

6-Speed Manual/Improved Internals 6MAN 0.5 0.5 0.5 0.5 

Improved Auto. Trans. IATC 1.5 - 2.5 1.5 - 2.5 1.5 - 2.5 1.5 - 2.5 Controls/Externals 

Continuously Variable Transmission CVT 0.7 - 2.0 0.7 - 2.0 0.7 - 2.0 0 0.7 - 2.

6/7/8-Speed Auto. Trans with NAUT 1.4 4 Improved Internals O - 3.4 1.4 - 3.4 1.4 - 3.4 1.4 - 3.

Dual Clutch or Automated Manual CTA .5 4.1 Transmission D M 5 – 7.5 5.5 – 7.5 2.7 - 4.1 2.7 - 

Electric Power Steering EPS 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 .0 1.0 - 2

Improved Accessories IACC 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 .0 1.0 - 2

12V Micro-Hybrid MHEV - 2 .0 3.5 2.0 3.0 .0 - 3.0 2.0 - 3 2.5 - 

Belt mounted Integrated Starter BISG 4.0 - 4 .0 5 6.0 .0 - 6.0 4.0 - 6 3.5 - 5.
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Generator 

Crank mounted In

Generator 

tegrated Starter CISG 8.6 - 8 .9 8.9 8.9 .6 - 8.9 8.6 - 8 8.7 - 

Power Split Hybrid PSHE 6.3 - 1 6.3 .4 6 .4 - 

4 V 2.4 - 12 .3 - 12 6.312.

2-Mode Hybrid 2MHE n V .a. n.a. n.a. n.a. 

Plug-in Hybrid PHEV 45.2 4 - 47.7 5.2 -

47.7 

45.2 - 

47.7 n.a. 

Mass Reduction (1.5%) MS1 0.5 0.5 0.5 0.5 

Mass Reduction (3.5 to 8.5%) MS2 2.7 2.7 4.4 6.0 

Low Rolling Resistance Tires ROLL 0 - 2.0 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 1.

Low Drag Brakes LDB n.a. n.a. n.a. 0.5 - 1.0 

Secondary Axle Disconnect SAX 1.0 - 1.5 1.0 - 1.5 1.0 - 1.5 1.0 - 1.5 

Aero Drag Reduction AERO 2.0 - 3.0 2.0 - 3.0 2.0 - 3.0 2.0 - 3.0 
268

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VEHICL 

(-%) BY VEHIC R

Table V-40. Technology Incremental Effectiveness Estimates, 

Performance Cars 

E TECHNOLOGY INCREMENTAL FUEL CONSUMPTION REDUCTION

LE SUBCLASS - PERFORMANCE PASSENGER CA

Perform. . P Perform Perform. erform.

Subcomp t . Compac Midsize Large 

 Car Car Car Car 

Nominal Baseline Engine (For Cost Basis) Inline 4 V6 V6 V8 

Low Friction Lubricants LUB 0.5 0.5 0.5 0.5 

Engine Friction Reduction EFR - 2.0 2.0 1 1.0 1.0 1.0 - .0 - 2.0 - 2.0 

VVT 

SOHC CCPS 3.0 1. - Coupled Cam Phasing (CCP) on 1.0 - 1.0 - 3.0 1.0 - 3.0 0 - 3.0 

Discre

SOHC DVVLS - 3.0 .0 1.0 te Variable Valve Lift (DVVL) on 1.0 1.0 - 3 1.0 - 3.0 - 3.0 

Cylinder Deactivation on SOHC DEACS .a. n 2.5 - 3.0 2. .0 5 - 3 2.5 - 3.0 

VVT - Intake Cam Phasing (ICP) ICP - 2.0 1.0 1.0 - 2.0 1 .0 .0 - 2 1.0 - 2.0 

VVT - Dual Cam Phasing (DCP) DCP 2.0 - 3.0 .0 2.0 2.0 - 3 2.0 - 3.0 - 3.0 

Discrete Variable Valve Lift (DVVL) on 

DOHC DVVLD 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0 

Continuously Variable Valve Lift (CVVL) CVVL 1.5 - 3.5 1.5 - 3.5 1.5 - 3.5 1.5 - 3.5 

Cylinder Deactivation on DOHC DEACD n.a. 0.0 - 0.5 0.0 - 0.5 0.0 - 0.5 

Cylinder Deactivation on OHV DEACO n.a. 3.9 - 5.5 3.9 - 5.5 3.9 - 5.5

VVT - Coupled Cam Phasing (CCP) on OHV CCPO 1.0 - 1.5 1.0 - 1.5 1.0 - 1.5 1.0 - 1.5

Discrete

OHV LO 0. Variable Valve Lift (DVVL) on DVV 0.5 - 2.5 0.5 - 2.5 0.5 - 2.5 5 - 2.5 

Conversion to DOHC with DCP CDOHC - 2.5 - 2.5 1 .5 1.0 1.0 1.0 .0 - 2 - 2.5

Stoich

(GDI) SGDI 0 iometric Gasoline Direct Injection 2.0 - 3. 2.0 - 3.0 2.0 - 3.0 2.0 - 3.0 

Combustion Restart CBRST 2.5 .5 5 2 2.0 - 2.0 - 2 2.0 - 2. .0 - 2.5 

Turbocharging and Downsizing TRBDS 4.8 .9 9 1. 4.2 - 1.8 - 1 1.8 - 1. 8 - 1.9 

Exhaust Gas Recirculation (EGR) Boost EGRB 3.5 - 4.0 3.5 - 4.0 3.5 - 4.0 3.5 - 4.0 

Conve BRST DSLC 5 – 

13.9 

 - 

11.7 11.7 11.7 rsion to Diesel following C 13. 10.8 10.8 - 10.8 - 

Conversion to Diesel following TRBDS DSLT .9 .9 9 5. 5.3 – 6 5.3 - 6 5.3 - 6. 3 - 6.9 

6-Speed Manual/Improved Internals 6MAN 5 0. 0.5 0.5 0.5 

Improved Auto. Trans. Controls/Externals IATC - 2.5 .5 5 1. 1.5 1.5 - 2 1.5 - 2. 5 - 2.5 

Continuously Variable Transmission CVT - 2.0 0.7 0.7 - 2.0 0.7 - 2.0 n.a. 

6/7/8-S proved 

Internals NAUTO 1.4 - 3.4 1.4 - 3.4 1.4 - 3.4 1.4 - 3.4 peed Auto. Trans with Im

Dual Clu

Transm

tch or Automated Manual 

ission DCTAM 2.7 - 4.1 2.7 - 4.1 2.7 - 4.1 2.7 - 4.1 

Electric Power Steering EPS 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 

Improved Accessories IACC 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 

12V Micro-Hybrid MHEV 2.0 - 3.0 2.5 - 3.5 2.5 - 3.5 3.0 - 4.0 

Belt mounted Integrated Starter Generator BISG 4.0 - 6.0 3.5 - 5.5 3.5 - 5.5 3.0 - 5.0 

Crank mounted Integrated Starter Generator CISG 8.6 - 8.9 8.7 - 8.9 8.7 - 8.9 8.7 - 8.9 

Power Split Hybrid PSHEV 6.3 - 12.4 6.3 - 

12.4 

6.3 - 

12.4 

6.3 - 

12.4 
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2-Mode Hybrid 2MHEV n.a. n.a. n.a. n.a. 

Plug-in Hybrid PHEV 47.7 47.7 47.7 n.a. 45.2 - 45.2 - 45.2 - 

Mass Reduction (1.5%) MS1 0.5 0.5 0.5 0.5 

Mass Reduction (3.5 to 8.5%) MS2 2.7 2.7 4.4 6.0

Low Rolling Resistance Tires ROLL n.a. n.a. n.a. n.a. 

Low Drag Brakes LDB n.a. 0.5 - 

1.0 n.a. n.a. 

Secondary Axle Disconnect SA .0 - 1. .5 X 1 5 1.0 - 1 1.0 - 1.5 1.0 - 1.5 

Aero Drag Reduction AERO n.a. n.a. n.a. n.a. 
270

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Ta

VEHICL

LE SS R

ble V-41. Technology Incremental Effectiveness Estimates, Light Trucks 

E TECHNOLOGY INCREMENTAL FUEL CONSUMPTION 

REDUCTION (-%) BY VEHIC SUBCLA - LIGHT T UCKS 

Minivan Small Midsize Large

 LT LT LT LT

Nominal Baseline Engine (For Cost Basis) V6 Inline 4 V6 V8

Low Friction Lubricants LUB 0.5 0.5 0.5 0.5

Engine Friction Reduction EFR 1.0 - 2.0 .0 1 0 - 2 1.0 - 2 .0 - 2.0 1. .0 

VVT - Coupled Cam Phasing (CCP) on CCPS SOHC 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0 

Discrete Variable Valve Lift (DVVL) on D SOHC - 3 0 - 3.0 VVLS 1.0 .0 1.0 - 3.0 1.0 - 3.0 1.

Cylinder Deactivation on SOHC DEACS 2.5 - 3.0 n.a. 2.5 - 3.0 2.5 - 3.0 

VVT - Intake Cam Phasing (ICP) ICP 1.0 - 2.0 1.0 - 2.0 1.0 1.0 - 2.0 - 2.0 

VVT - Dual Cam Phasing (DCP) DCP 2.0 - 3.0 2.0 - 3.0 2.0 - 3.0 2.0 - 3.0 

Discrete Variable Valve Lift (DVVL) on 

DOHC DVVLD 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0 1.0 - 3.0 

Continuously Variable Valve Lift (CVVL) CVVL 1.5 - 3.5 1.5 - 3.5 1.5 - 3.5 1.5 - 3.5 

Cylinder Deactivation on DOHC DEACD 0 - 0.5 n.a. 0.0 - 0.5 0.0 - 0.5 

Cylinder Deactivation on OHV DEACO 3.9 - 5.5 n.a. 3.9 - 5.5 3.9 - 5.5 

VVT - Coupled Cam Phasing (CCP) on 

OHV CCPO 1.0 - 1.5 1.0 - 1.5 1.0 - 1.5 1.0 - 1.5 

Discrete Variable Valve Lift (DVVL) on 

OHV DVVLO 0.5 - 2.5 0.5 - 2.5 0.5 - 2.5 0.5 - 2.5 

Conversion to DOHC with DCP CDOHC 1.0 - 2.5 1.0 - 2.5 1.0 - 2.5 1.0 - 2.5 

Stoichiometric Gasoline Direct Injection 

(GDI) SGDI 2.0 - 3.0 2.0 - 3.0 2.0 - 3.0 2.0 - 3.0 

Combustion Restart CBRST 2.0 - 2.5 2.0 - 2.5 2.0 - 2.5 2.0 - 2.5 

Turbocharging and Downsizing TRBDS 1.8 - 1.9 4.2 - 4.8 1.8 - 1.9 1.8 - 1.9 

Exhaust Gas Recirculation (EGR) Boost EGRB 3.5 - 4.0 3.5 - 4.0 3.5 - 4.0 3.5 - 4.0 

Conversion to Diesel following CBRST DSLC 10.8 - 

11.7 

13.5 – 

13.9. 

10.8 - 

11.7 

10.8 - 

11.7 

Conversion to Diesel following TRBDS DSLT 5.3 - 6.9 n.a. 5.3 - 6.9 5.3 - 6.9 

6-Speed Manual/Improved Internals 6MAN 0.5 0.5 0.5 0.5 

Improved Auto. Trans. Controls/Externals IATC 1.5 - 2.5 1.5 - 2.5 1.5 - 2.5 1.5 - 2.5 

Continuously Variable Transmission CVT 0.7 - 2.0 0.7 - 2.0 0.7 - 2.0 n.a. 

6/7/8-Speed Auto. Trans with Improved 

Internals NAUTO 1.4 - 3.4 1.4 - 3.4 1.4 - 3.4 1.4 - 3.4 

Dual Clutch or Automated Manual 

Transmission DCTAM 2.7 - 4.1 2.7 -4.1 2.7 - 4.1 2.7 - 4.1 

Electric Power Steering EPS 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 

Improved Accessories IACC 1.0 - 2.0 1.0 - 2.0 1.0 - 2.0 n.a. 

12V Micro-Hybrid MHEV 2.5 - 3.5 2.0 - 3.0 2.5 - 3.5 n.a. 

Belt mounted Integrated Starter Generator BISG 3.5 - 5.5 4.0 - 6.0 3.5 - 5.5 n.a. 

Crank mounted Integrated Starter Generator CISG 8.7 - 8.9 8.6 - 8.9 8.7 - 8.9 14.1 - 

16.3 

Power Split Hybrid PSHEV 6.3 - 

12.4 

6.3 - 

12.4 

6.3 - 

12.4 n.a. 
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2-Mode Hybrid 2MHEV n.a. 3.0 - 7.3 3.0 - 7.3 4.1 - 9.5 

Plug-in Hybrid PHEV 45

4 n.a. n.a. n .2 - 7.7 .a. 

Mass Reduction (1.5%) MS1 0.5 0.5 0.5 0.5 

Mass Reduction (3.5 to 8.5%) MS2 6.0 4.4 4 6. .4 0 

Low Rolling Resistance Tires ROLL 1. 1.0 1.0 1.0 0 - 2.0 - 2.0 - 2.0 - 2.0 

Low Drag Brakes LDB 0.5 n. 0.5 0.5 - - 1.0 a. - 1.0 1.0 

Secondary Axle Disconnect SAX 1.0 1.0 1.0 1.0 - - 1.5 - 1.5 - 1.5 1.5 

Aero Drag Reduction AERO 2.0 2.0 2.0 2.0 - - 3.0 - 3.0 - 3.0 3.0 

for a ima (ac ated

d be The hav di 

 and light to m them er to . 

oximate Net (Accu ted) nolo sts, 

ger C

HICL BY V LE CL TO K

 nded t est $1

The tables representing the Volpe model inpu

technology costs by vehicle subclass are presente

t files pprox te net cumul ) 

low. tables e been vided into

passenger cars, performance passenger cars, trucks ake easi read

Table V-42. Appr mula Tech gy Co

Passen ars 

APPROXIMATE ICM NET COSTS PER VE

TECHNOLOGIE

E ($) 

(Rou

EHIC

o near

ASS 

00) 

EY 

S 

Final technology (As compared to baseline vehicle prior S

to technology application) 

ubcom

Car 

Com 

C

pact pact M 

ar 

idsize 

Car 

Large 

Car 

Stoichiometric Gasoline Direct Injection 47 4 716 1 (SGDI) 7 77 477 - 77

Turbocharging and Downsizing (TRBDS) 1,03 1,0 1 9 39 ,039 1,158 -

1,213

Diesel Engine (DSLT/DSLC) 2,12 2,1 2 1 21 ,121 2,445

Dual Clutch or Automated Manual 

Transmission (DCTAM) 113 11 3 164 164 

Crankshaft Integrated Starter Generator 

(CISG) 3,59 3, 4 9 939 ,180 4,434 

Power Split Hybrid (PSHEV) 5,509 6,381 7,233 8,005 

2-Mode Hybrid (2MHEV) n.a n . .a. n.a. n.a. 

Plug-in Hybrid (PHEV) 15,429 18,384 20,705 n.a. 

 
272

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e Net (Accu ted) nolo sts, 

e Passe Cars

NET COSTS PER VEH L BY V LE CLAS TO KEY

TECHNOLOGIES (Rounded to nearest $100) 

Table V-43. Approximat mula Tech gy Co

Performanc nger

APPROXIMATE ICM IC

 

E ($) EHIC S 

Final technology (As compared to baseline vehicle prior 

to technology application) 

Subcompact 

Perf Car 

Compact 

Perf Car 

Midsize 

Perf Car 

Large 

Perf Car 

Stoichiometric Gasoline Direct Injection 

(SGDI) 477 716 - 771 716 - 771 878 - 934 

Turbocharging and Downsizing (TRBDS) 1,039 1,158 - 

1,213 

1,158 - 

1,213 

1,914 - 

1,970 

Diesel Engine (DSLT/DSLC) 2,121 2,445 2,445 3,345 

Dual Clutch or Automated Manual 

Transmission (DCTAM) 164 - 266 164 - 266 164 - 266 164 - 266 

Crankshaft Integrated Starter Generator 

(CISG) 3,673 4,007 4,227 4,500 

Power Split Hybrid (PSHEV) 7,645 8,335 9,824 11,534 

2-Mode Hybrid (2MHEV) n.a. n.a. n.a. n.a. 

Plug-in Hybrid (PHEV) 18,970 21,109 23,802 n.a. 

 

Table V-44. Approximate Net (Accumulated) Technology Costs, Light Trucks 

APPROXIMATE ICM NET COSTS PER VEHICLE ($) BY VEHICLE CLASS TO KEY 

TECHNOLOGIES (Rounded to nearest $100) 

Final technology (As compared to baseline vehicle prior 

to technology application) 

Minivan 

LT 

Small 

LT 

Midsize 

LT 

Large 

LT 

Stoichiometric Gasoline Direct Injection 

(SGDI) 716 - 771 477 716 - 771 878 - 934 

Turbocharging and Downsizing (TRBDS) 1,158 - 

1,213 1,039 1,158 - 1,213 

1,914 - 

1,970 

Diesel Engine (DSLT/DSLC) 2,445 2,121 2,445 3,345 

Dual Clutch or Automated Manual 

Transmission (DCTAM) 164 164 164 - 266 164 - 266 

Crankshaft Integrated Starter Generator 

(CISG) 4,434 3,986 4,507 5,230 

Power Split Hybrid (PSHEV) 8,005 6,673 8,279 n.a. 

2-Mode Hybrid (2MHEV) n.a. 7,810 9,660 11,398 

Plug-in Hybrid (PHEV) n.a. 18,878 n.a. n.a. 

 

The tables representing the Volpe model input files for approximate net (accumulated) 

technology effectiveness values by vehicle subclass are presented below. The tables have been 

divided into passenger cars, performance passenger cars, and light trucks to make them easier to 

read. 
273

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 Approximate Net Technology Effectiveness, Passenger Cars 

MATE NET EFFECTIVENESS ESTIMATES DU ) PE ICL BY 

CLASS TO KEYTECHNOLOG ound eare ) 

Table V-45. 

APPROXI (FC RE CTION R VEH E (-%) 

VEHICLE IES (R ed to n st 0.5%

Final technology (As compared to baseline vehicle prior Subcompact

r 

omp

Car 

M rge 

to technology application) Ca Car 

 C act idsize

Car 

La 

Stoichiometric Gasoline Direct Injection 

(SGDI) 5.4 - 11.0 5.4 - 11 5.4 0 - 13.7 .0 - 11. 7.8

Turbocharging and Downsizing (TRBDS) 11.2 - 17.4 1.2 - 1 11. .4 - 17.4 1 7.4 2 - 17 11.2

Diesel Engine (DSLT/DSLC) 20.2 - 24.9 .2 - 2 20 9 - 24. 20 4.9 .2 - 24. 20.2 9 

Dual Clutch or Automated Manual 

Transmission (DCTAM) 8.2 - 12.9 .2 - 1 5 - 9.7 8 2.9 .5 - 9.7 5.5 

Crankshaft Integrated Starter Generator 

(CISG) 16.0 - 20.0 6.0 - 2 16. .0 - 20.0 1 0.0 0 - 20 16.0

Power Split Hybrid (PSHEV) 23.0 - 33.0 3.0 - 3 23. .0 - 33.0 2 3.0 0 - 33 23.0

2-Mode Hybrid (2MHEV) n.a. n.a. n.a. n.a. 

Plug-in Hybrid (PHEV) 55.0 - 60.0 5.0 - 6 55. .0 n.a. 5 0.0 0 - 60

 

et T logy e 

Performance Passe Cars

 ESTIMATES EDUC ) PER ICLE BY 

TECHNOLOG Round neares ) 

Table V-46. Approximate N echno Effectiv ness, 

nger

APPROXIMATE NET EFFECTIVENESS (FC R TION VEH (-%) 

VEHICLE CLASS TO KEY IES ( ed to t 0.5%

Final technology (As compared to baseline vehicle prior 

to technology application) 

Subcompact 

Perf Car 

pa 

 C

M 

Pe r 

arge 

rf Car 

 Com

Perf

ct 

ar 

idsize

rf Ca

L

Pe

 

Stoichiometric Gasoline Direct Injection 

(SGDI) 5.4 - 11.0 .8 - 1 7.8 7 - 13.7 7 3.7 - 13. 7.8

Turbocharging and Downsizing (TRBDS) 11.2 - 17.4 .2 - 1 11 4 - 17. 11 7.4 .2 - 17. 11.2 4 

Diesel Engine (DSLT/DSLC) 20.2 - 24.9 20.2 - 24.9 20.2 - 24.9 20.2 - 24.9 

Dual Clutch or Automated Manual 

Transmission (DCTAM) 5.5 - 9.7 5.5 - 9 5. .7 5 - 9.7 5.5 - 9.7 

Crankshaft Integrated Starter Generator 

(CISG) 16.0 - 20.0 .0 - 2 16 0 - 20. 16 0.0 .0 - 20. 16.0 0 

Power Split Hybrid (PSH VE ) 23.0 - 33.0 .0 - 3 23 0 - 33. 23 3.0 .0 - 33. 23.0 0 

2-Mode Hybrid (2MHEV) n.a. n.a. n.a. n.a. 

Plug-in Hybrid (PHEV) 55.0 - 60.0 5.0 - 6 55. .0 n.a. 5 0.0 0 - 60
274

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et Technolo ffecti c

T EFFECTIVENESS ESTIMATES EDU ) PE ICL BY 

LE CLASS TO KEYTECHNOLOG ound eare ) 

Table V-47. Approximate N gy E veness, Light Tru ks 

APPROXIMATE NE

VEHIC

 (FC R

IES (R

CTION

ed to n

R VEH

st 0.5%

E (-%) 

Final technology (As compared to baseline vehicle prior 

to technology application) 

Minivan 

LT 

Small 

LT 

Midsize 

LT 

Large 

LT 

Stoichiometric Gasoline Direct Injection 

(SGDI) 7.8 - 13.7 5.4 - 11.0 7.8 - 13.7 7.8 - 13.7 

Turbocharging and Downsizing (TRBDS) 11.2 - 17.4 11.2 - 17.4 11.2 - 17.4 11.2 - 17.4 

Diesel Engine (DSLT/DSLC) 20.2 - 24.9 20.2 - 24.9 20.2 - 24.9 20.2 - 24.9 

Dual Clutch or Automated Manual 

Transmission (DCTAM) 5.5 - 9.7 5.5 - 9.7 5.5 - 9.7 5.5 - 9.7 

Crankshaft Integrated Starter Generator 

(CISG) 16.0 - 20.0 16.0 - 20.0 16.0 - 20.0 15.0 - 18.0 

Power Split Hybrid (PSHEV) 23.0 - 33.0 23.0 - 33.0 23.0 - 33.0 n.a. 

2-Mode Hybrid (2MHEV) n.a. 23.0 - 33.0 23.0 - 33.0 23.0 - 33.0 

Plug-in Hybrid (PHEV) n.a. 55.0 - 60.0 n.a. n.a. 

 

C. Penetration of Technologies by Alternative 

Table V-48 shows the penetration of technologies by alternative for passenger cars and Table V-46 

shows the penetration of technologies for light trucks for the alternatives. These tables are for the 

whole fleet combined, not by specific manufacturers. The application rate only includes technologies 

that the model applied. The penetration rate includes technologies that the model applies and 

technologies that were already present in the base fleet/base vehicle. They allow the reader to see the 

progression of technologies used as the alternatives get stricter. Table V-48. Penetration Rate of New 

Technologies to Passenger Cars, by Alternative 
275

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Preferred Alternative

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 76% 78% 78% 78% 77%

Engine Friction Reduction 28% 50% 55% 58% 66%

VVT - Coupled Cam Phasing (CCP) on SOHC 5% 6% 6% 8% 10%

Discrete Variable Valve Lift (DVVL) on SOHC 6% 7% 8% 9% 10%

Cylinder Deactivation on SOHC 1% 1% 1% 0% 1%

VVT - Intake Cam Phasing (ICP) 35% 33% 34% 34% 27%

VVT - Dual Cam Phasing (DCP) 41% 45% 45% 46% 53%

Discrete Variable Valve Lift (DVVL) on DOHC 17% 27% 30% 31% 37%

Continuously Variable Valve Lift (CVVL) 3% 2% 3% 3% 3%

Cylinder Deactivation on DOHC 1% 1% 1% 2% 3%

Cylinder Deactivation on OHV 1% 2% 2% 2% 2%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 5% 5% 5% 5%

Discrete Variable Valve Lift (DVVL) on OHV 0% 1% 1% 3% 3%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 18% 26% 31% 35% 38%

Combustion Restart 0% 0% 2% 5% 11%

Turbocharging and Downsizing 13% 20% 21% 25% 27%

Exhaust Gas Recirculation (EGR) Boost 0% 8% 10% 14% 17%

Conversion to Diesel following TRBDS 2% 2% 2% 2% 2%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 3% 3% 3% 3% 3%

Improved Auto. Trans. Controls/Externals 11% 13% 13% 10% 7%

Continuously Variable Transmission 11% 11% 11% 11% 11%

6/7/8-Speed Auto. Trans with Improved 

Internals 14% 9% 7% 4% 3%

Dual Clutch or Automated Manual 

Transmission 24% 38% 48% 61% 69%

Electric Power Steering 40% 54% 57% 59% 72%

Improved Accessories 36% 43% 46% 50% 61%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 5% 12% 19% 25% 25%

Crank mounted Integrated Starter Generator 4% 3% 3% 3% 3%

Power Split Hybrid 5% 5% 6% 5% 5%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 19% 26% 33% 39% 47%

Mass Reduction (3.5% to 8.5%) 0% 0% 17% 31% 40%

Low Rolling Resistance Tires 50% 60% 66% 75% 78%

Low Drag Brakes 8% 9% 11% 11% 13%
276

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 4% 5% 5% 5% 6%

Aero Drag Reduction 39% 52% 60% 66% 71%
277

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3% Annual Increase 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 65% 68% 66% 74% 74%

Engine Friction Reduction 26% 44% 46% 48% 57%

VVT - Coupled Cam Phasing (CCP) on SOHC 5% 5% 5% 6% 7%

Discrete Variable Valve Lift (DVVL) on SOHC 6% 7% 8% 9% 9%

Cylinder Deactivation on SOHC 1% 1% 1% 1% 1%

VVT - Intake Cam Phasing (ICP) 39% 40% 40% 42% 34%

VVT - Dual Cam Phasing (DCP) 38% 40% 40% 40% 47%

Discrete Variable Valve Lift (DVVL) on DOHC 16% 24% 27% 28% 32%

Continuously Variable Valve Lift (CVVL) 3% 2% 3% 3% 3%

Cylinder Deactivation on DOHC 1% 1% 1% 2% 1%

Cylinder Deactivation on OHV 1% 2% 2% 2% 2%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 4% 4% 4% 4%

Discrete Variable Valve Lift (DVVL) on OHV 0% 0% 0% 0% 0%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 13% 13% 15% 17% 19%

Combustion Restart 0% 0% 2% 5% 7%

Turbocharging and Downsizing 7% 8% 10% 11% 14%

Exhaust Gas Recirculation (EGR) Boost 0% 2% 4% 5% 9%

Conversion to Diesel following TRBDS 1% 1% 1% 1% 1%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 2% 2% 2% 2% 2%

Improved Auto. Trans. Controls/Externals 10% 11% 8% 5% 5%

Continuously Variable Transmission 11% 11% 11% 11% 11%

6/7/8-Speed Auto. Trans with Improved 

Internals 16% 11% 10% 7% 8%

Dual Clutch or Automated Manual 

Transmission 15% 28% 34% 42% 47%

Electric Power Steering 39% 49% 52% 55% 63%

Improved Accessories 30% 30% 31% 35% 39%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 3% 5% 7% 10% 10%

Crank mounted Integrated Starter Generator 1% 1% 1% 1% 1%

Power Split Hybrid 4% 4% 4% 4% 4%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 10% 10% 17% 22% 32%

Mass Reduction (3.5% to 8.5%) 0% 0% 14% 23% 32%

Low Rolling Resistance Tires 47% 55% 57% 59% 73%

Low Drag Brakes 8% 8% 9% 9% 9%
278

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 4% 4% 5% 5% 5%

Aero Drag Reduction 34% 41% 46% 54% 71%
279

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4% Annual Increase 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 65% 67% 74% 73% 74%

Engine Friction Reduction 26% 45% 51% 56% 66%

VVT - Coupled Cam Phasing (CCP) on SOHC 5% 6% 6% 8% 10%

Discrete Variable Valve Lift (DVVL) on SOHC 6% 7% 8% 9% 9%

Cylinder Deactivation on SOHC 1% 1% 1% 0% 0%

VVT - Intake Cam Phasing (ICP) 39% 40% 40% 37% 29%

VVT - Dual Cam Phasing (DCP) 38% 39% 40% 44% 53%

Discrete Variable Valve Lift (DVVL) on DOHC 15% 24% 27% 27% 32%

Continuously Variable Valve Lift (CVVL) 3% 2% 3% 3% 3%

Cylinder Deactivation on DOHC 1% 1% 1% 2% 3%

Cylinder Deactivation on OHV 1% 2% 2% 2% 2%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 4% 4% 4% 4%

Discrete Variable Valve Lift (DVVL) on OHV 0% 0% 1% 2% 2%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 17% 22% 27% 31% 36%

Combustion Restart 0% 0% 3% 6% 15%

Turbocharging and Downsizing 9% 12% 15% 19% 21%

Exhaust Gas Recirculation (EGR) Boost 0% 4% 7% 11% 15%

Conversion to Diesel following TRBDS 1% 1% 1% 1% 1%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 3% 3% 3% 3% 3%

Improved Auto. Trans. Controls/Externals 10% 12% 14% 11% 11%

Continuously Variable Transmission 11% 11% 11% 11% 11%

6/7/8-Speed Auto. Trans with Improved 

Internals 19% 15% 1 1 6% 7% 16%

Dual Clutch or Automated Manual 

Transmission 15% 28% 35% 45% 52%

Electric Power Steering 39% 55% 62% 64% 79%

Improved Accessories 32% 39% 43% 50% 57%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 5% 12% 18% 24% 25%

Crank mounted Integrated Starter Generator 1% 1% 1% 1% 1%

Power Split Hybrid 4% 4% 4% 4% 4%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 18% 17% 25% 34% 40%

Mass Reduction (3.5% to 8.5%) 0% 0% 18% 32% 40%

Low Rolling Resistance Tires 48% 58% 66% 74% 88%

Low Drag Brakes 8% 9% 11% 11% 13%
280

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 4% 5% 5% 5% 7%

Aero Drag Reduction 35% 44% 51% 63% 79%
281

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5% Annual Increase 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 65% 75% 74% 77% 76%

Engine Friction Reduction 26% 47% 58% 64% 68%

VVT - Coupled Cam Phasing (CCP) on SOHC 5% 6% 9% 10% 10%

Discrete Variable Valve Lift (DVVL) on SOHC 6% 7% 9% 10% 10%

Cylinder Deactivation on SOHC 1% 1% 1% 0% 0%

VVT - Intake Cam Phasing (ICP) 39% 36% 31% 27% 24%

VVT - Dual Cam Phasing (DCP) 38% 41% 47% 51% 53%

Discrete Variable Valve Lift (DVVL) on DOHC 18% 30% 34% 35% 38%

Continuously Variable Valve Lift (CVVL) 3% 2% 3% 3% 3%

Cylinder Deactivation on DOHC 1% 1% 1% 2% 1%

Cylinder Deactivation on OHV 1% 2% 2% 2% 2%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 5% 5% 5% 5%

Discrete Variable Valve Lift (DVVL) on OHV 0% 0% 1% 2% 2%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 20% 32% 39% 45% 50%

Combustion Restart 0% 0% 4% 9% 17%

Turbocharging and Downsizing 14% 24% 30% 34% 34%

Exhaust Gas Recirculation (EGR) Boost 0% 12% 18% 22% 28%

Conversion to Diesel following TRBDS 1% 1% 2% 3% 5%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 3% 3% 3% 4% 4%

Improved Auto. Trans. Controls/Externals 10% 13% 14% 9% 2%

Continuously Variable Transmission 11% 11% 11% 11% 11%

6/7/8-Speed Auto. Trans with Improved 

Internals 15% 10% 6% 2% 1%

Dual Clutch or Automated Manual 

Transmission 25% 41% 53% 66% 77%

Electric Power Steering 39% 56% 67% 70% 79%

Improved Accessories 32% 40% 45% 53% 66%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 11% 21% 28% 34% 37%

Crank mounted Integrated Starter Generator 1% 1% 1% 1% 1%

Power Split Hybrid 4% 4% 5% 5% 5%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 18% 25% 34% 45% 61%

Mass Reduction (3.5% to 8.5%) 0% 0% 19% 33% 45%

Low Rolling Resistance Tires 48% 59% 68% 77% 90%

Low Drag Brakes 8% 9% 11% 12% 13%
282

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 4% 5% 5% 5% 7%

Aero Drag Reduction 39% 51% 59% 66% 80%
283

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6% Annual Increase 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 64% 72% 75% 89% 88%

Engine Friction Reduction 25% 48% 60% 69% 83%

VVT - Coupled Cam Phasing (CCP) on SOHC 5% 6% 9% 9% 9%

Discrete Variable Valve Lift (DVVL) on SOHC 6% 7% 9% 9% 9%

Cylinder Deactivation on SOHC 1% 1% 1% 0% 0%

VVT - Intake Cam Phasing (ICP) 37% 33% 25% 18% 6%

VVT - Dual Cam Phasing (DCP) 37% 42% 49% 57% 69%

Discrete Variable Valve Lift (DVVL) on DOHC 26% 39% 48% 54% 64%

Continuously Variable Valve Lift (CVVL) 3% 2% 3% 3% 3%

Cylinder Deactivation on DOHC 1% 1% 1% 1% 1%

Cylinder Deactivation on OHV 1% 2% 1% 0% 0%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 5% 5% 4% 4%

Discrete Variable Valve Lift (DVVL) on OHV 0% 2% 2% 2% 2%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 19% 33% 44% 48% 56%

Combustion Restart 0% 0% 3% 7% 14%

Turbocharging and Downsizing 15% 27% 37% 43% 49%

Exhaust Gas Recirculation (EGR) Boost 0% 14% 25% 31% 41%

Conversion to Diesel following TRBDS 4% 4% 6% 9% 9%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 3% 3% 4% 4% 4%

Improved Auto. Trans. Controls/Externals 11% 14% 14% 9% 0%

Continuously Variable Transmission 11% 11% 10% 10% 11%

6/7/8-Speed Auto. Trans with Improved 

Internals 14% 9% 5% 2% 0%

Dual Clutch or Automated Manual 

Transmission 25% 44% 56% 67% 77%

Electric Power Steering 39% 62% 72% 78% 90%

Improved Accessories 32% 41% 46% 55% 71%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 8% 19% 27% 33% 36%

Crank mounted Integrated Starter Generator 4% 5% 6% 5% 6%

Power Split Hybrid 5% 6% 6% 8% 8%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 18% 27% 36% 47% 61%

Mass Reduction (3.5% to 8.5%) 0% 0% 19% 33% 45%

Low Rolling Resistance Tires 49% 66% 74% 80% 90%

Low Drag Brakes 8% 10% 11% 12% 14%
284

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 4% 5% 5% 6% 7%

Aero Drag Reduction 39% 53% 61% 66% 80%
285

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7% Annual Increase 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 71% 74% 90% 88% 86%

Engine Friction Reduction 27% 52% 66% 73% 83%

VVT - Coupled Cam Phasing (CCP) on SOHC 5% 8% 11% 9% 9%

Discrete Variable Valve Lift (DVVL) on SOHC 6% 7% 9% 9% 9%

Cylinder Deactivation on SOHC 1% 1% 1% 0% 0%

VVT - Intake Cam Phasing (ICP) 37% 31% 21% 12% 2%

VVT - Dual Cam Phasing (DCP) 37% 42% 51% 61% 68%

Discrete Variable Valve Lift (DVVL) on DOHC 26% 38% 49% 56% 62%

Continuously Variable Valve Lift (CVVL) 3% 2% 3% 3% 3%

Cylinder Deactivation on DOHC 1% 1% 1% 2% 1%

Cylinder Deactivation on OHV 1% 2% 1% 0% 0%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 5% 4% 4% 4%

Discrete Variable Valve Lift (DVVL) on OHV 0% 2% 2% 4% 4%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 25% 40% 52% 61% 71%

Combustion Restart 0% 0% 2% 7% 21%

Turbocharging and Downsizing 15% 30% 41% 48% 53%

Exhaust Gas Recirculation (EGR) Boost 0% 17% 29% 36% 45%

Conversion to Diesel following TRBDS 4% 5% 7% 9% 12%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 3% 3% 4% 4% 4%

Improved Auto. Trans. Controls/Externals 11% 14% 14% 9% 0%

Continuously Variable Transmission 11% 10% 9% 9% 9%

6/7/8-Speed Auto. Trans with Improved 

Internals 14% 9% 5% 2% 0%

Dual Clutch or Automated Manual 

Transmission 25% 43% 53% 64% 74%

Electric Power Steering 40% 67% 81% 87% 90%

Improved Accessories 33% 46% 58% 71% 82%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 11% 22% 30% 37% 42%

Crank mounted Integrated Starter Generator 4% 4% 5% 5% 5%

Power Split Hybrid 5% 8% 10% 11% 12%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 18% 27% 36% 48% 85%

Mass Reduction (3.5% to 8.5%) 0% 0% 19% 33% 53%

Low Rolling Resistance Tires 50% 66% 75% 80% 90%

Low Drag Brakes 8% 10% 12% 13% 14%
286

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 4% 5% 6% 6% 7%

Aero Drag Reduction 39% 56% 64% 69% 80%
287

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Max Net Benefit 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 74% 76% 91% 90% 89%

Engine Friction Reduction 27% 55% 70% 75% 85%

VVT - Coupled Cam Phasing (CCP) on SOHC 5% 8% 11% 9% 9%

Discrete Variable Valve Lift (DVVL) on SOHC 6% 7% 9% 9% 9%

Cylinder Deactivation on SOHC 1% 1% 1% 0% 0%

VVT - Intake Cam Phasing (ICP) 37% 28% 19% 14% 10%

VVT - Dual Cam Phasing (DCP) 37% 45% 54% 60% 62%

Discrete Variable Valve Lift (DVVL) on DOHC 24% 36% 47% 51% 56%

Continuously Variable Valve Lift (CVVL) 3% 2% 3% 3% 3%

Cylinder Deactivation on DOHC 1% 1% 1% 2% 0%

Cylinder Deactivation on OHV 1% 2% 1% 1% 1%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 5% 4% 4% 4%

Discrete Variable Valve Lift (DVVL) on OHV 0% 2% 2% 4% 4%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 22% 37% 47% 53% 59%

Combustion Restart 0% 0% 3% 8% 16%

Turbocharging and Downsizing 15% 28% 37% 42% 47%

Exhaust Gas Recirculation (EGR) Boost 0% 15% 25% 31% 39%

Conversion to Diesel following TRBDS 4% 4% 7% 8% 9%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 3% 3% 4% 4% 4%

Improved Auto. Trans. Controls/Externals 11% 14% 14% 9% 2%

Continuously Variable Transmission 1 1 1% 0% 10% 10% 10%

6/7/8-Speed Auto. Trans with Improved 

Internals 14% 9% 5% 2% 1%

Dual Clutch or Automated Manual 

Transmission 25% 43% 54% 65% 72%

Electric Power Steering 40% 66% 80% 83% 84%

Improved Accessories 33% 55% 64% 64% 67%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 11% 22% 32% 37% 41%

Crank mounted Integrated Starter Generator 4% 5% 5% 5% 5%

Power Split Hybrid 5% 8% 9% 10% 10%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 18% 32% 41% 50% 62%

Mass Reduction (3.5% to 8.5%) 0% 0% 18% 32% 47%

Low Rolling Resistance Tires 50% 66% 75% 80% 90%

Low Drag Brakes 8% 12% 14% 14% 14%
288

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 4% 6% 6% 7% 7%

Aero Drag Reduction 39% 56% 64% 69% 80%
289

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Total Cost = Total Benefit 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 75% 78% 90% 89% 87%

Engine Friction Reduction 27% 54% 69% 75% 84%

VVT - Coupled Cam Phasing (CCP) on SOHC 5% 8% 11% 9% 9%

Discrete Variable Valve Lift (DVVL) on SOHC 6% 7% 9% 9% 9%

Cylinder Deactivation on SOHC 1% 1% 1% 0% 0%

VVT - Intake Cam Phasing (ICP) 35% 27% 17% 12% 6%

VVT - Dual Cam Phasing (DCP) 39% 47% 55% 62% 65%

Discrete Variable Valve Lift (DVVL) on DOHC 30% 43% 54% 62% 66%

Continuously Variable Valve Lift (CVVL) 3% 2% 3% 3% 3%

Cylinder Deactivation on DOHC 1% 1% 1% 2% 1%

Cylinder Deactivation on OHV 1% 2% 1% 0% 0%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 5% 4% 4% 4%

Discrete Variable Valve Lift (DVVL) on OHV 0% 2% 2% 4% 4%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 30% 47% 62% 68% 72%

Combustion Restart 0% 0% 5% 9% 17%

Turbocharging and Downsizing 1 3 6% 2% 43% 49% 54%

Exhaust Gas Recirculation (EGR) Boost 0% 19% 31% 37% 46%

Conversion to Diesel following TRBDS 4% 5% 7% 8% 11%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 3% 3% 4% 4% 4%

Improved Auto. Trans. Controls/Externals 11% 14% 14% 9% 2%

Continuously Variable Transmission 1 1 1% 0% 10% 10% 10%

6/7/8-Speed Auto. Trans with Improved 

Internals 14% 9% 5% 2% 0%

Dual Clutch or Automated Manual 

Transmission 25% 43% 54% 65% 72%

Electric Power Steering 40% 66% 81% 84% 84%

Improved Accessories 36% 58% 67% 71% 75%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 1 2 3% 3% 33% 39% 44%

Crank mounted Integrated Starter Generator 4% 4% 5% 4% 5%

Power Split Hybrid 5% 8% 9% 10% 12%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 2 4 1% 0% 51% 58% 66%

Mass Reduction (3.5% to 8.5%) 0% 0% 19% 33% 47%

Low Rolling Resistance Tires 50% 66% 75% 80% 90%

Low Drag Brakes 8% 12% 14% 14% 14%
290

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 4% 6% 6% 7% 7%

Aero Drag Reduction 39% 56% 64% 69% 80%

Table V-49. Penetration Rate of New Technologies to Light Trucks, by Alternative 
291

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Preferred Alternative

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 98% 98% 98% 98% 98%

Engine Friction Reduction 57% 78% 79% 82% 94%

VVT - Coupled Cam Phasing (CCP) on SOHC 12% 12% 12% 12% 12%

Discrete Variable Valve Lift (DVVL) on SOHC 5% 5% 5% 6% 6%

Cylinder Deactivation on SOHC 9% 10% 9% 9% 9%

VVT - Intake Cam Phasing (ICP) 13% 12% 9% 6% 2%

VVT - Dual Cam Phasing (DCP) 38% 41% 49% 49% 53%

Discrete Variable Valve Lift (DVVL) on DOHC 25% 29% 35% 34% 35%

Continuously Variable Valve Lift (CVVL) 4% 4% 4% 4% 4%

Cylinder Deactivation on DOHC 9% 10% 9% 11% 9%

Cylinder Deactivation on OHV 17% 17% 15% 17% 22%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 6% 5% 5% 18%

Discrete Variable Valve Lift (DVVL) on OHV 0% 13% 14% 19% 19%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 22% 27% 34% 35% 42%

Combustion Restart 0% 0% 3% 7% 20%

Turbocharging and Downsizing 9% 12% 16% 17% 20%

Exhaust Gas Recirculation (EGR) Boost 0% 4% 7% 7% 11%

Conversion to Diesel following TRBDS 1% 1% 1% 1% 1%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 1% 1% 1% 1% 1%

Improved Auto. Trans. Controls/Externals 35% 25% 16% 5% 1%

Continuously Variable Transmission 3% 3% 3% 4% 4%

6/7/8-Speed Auto. Trans with Improved 

Internals 11% 6% 2% 1% 2%

Dual Clutch or Automated Manual 

Transmission 32% 54% 72% 84% 90%

Electric Power Steering 72% 76% 75% 84% 91%

Improved Accessories 36% 38% 39% 43% 51%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 7% 11% 21% 22% 22%

Crank mounted Integrated Starter Generator 0% 0% 0% 0% 0%

Power Split Hybrid 3% 2% 2% 3% 3%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 15% 17% 34% 47% 61%

Mass Reduction (3.5% to 8.5%) 0% 0% 20% 34% 55%

Low Rolling Resistance Tires 92% 95% 95% 98% 99%

Low Drag Brakes 33% 52% 50% 51% 60%
292

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 30% 33% 35% 36% 43%

Aero Drag Reduction 87% 92% 96% 97% 100%
293

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3% Annual Increase 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 81% 80% 77% 76% 89%

Engine Friction Reduction 39% 54% 56% 59% 64%

VVT - Coupled Cam Phasing (CCP) on SOHC 11% 10% 10% 10% 10%

Discrete Variable Valve Lift (DVVL) on SOHC 4% 4% 5% 5% 5%

Cylinder Deactivation on SOHC 4% 3% 3% 3% 3%

VVT - Intake Cam Phasing (ICP) 17% 17% 17% 15% 13%

VVT - Dual Cam Phasing (DCP) 33% 35% 41% 43% 44%

Discrete Variable Valve Lift (DVVL) on DOHC 17% 20% 23% 22% 23%

Continuously Variable Valve Lift (CVVL) 4% 4% 4% 4% 4%

Cylinder Deactivation on DOHC 7% 8% 7% 8% 8%

Cylinder Deactivation on OHV 17% 16% 14% 15% 18%

VVT - Coupled Cam Phasing (CCP) on OHV 3% 2% 2% 3% 3%

Discrete Variable Valve Lift (DVVL) on OHV 0% 0% 0% 0% 0%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 11% 13% 14% 14% 15%

Combustion Restart 0% 0% 3% 6% 6%

Turbocharging and Downsizing 5% 8% 9% 9% 11%

Exhaust Gas Recirculation (EGR) Boost 0% 3% 5% 4% 6%

Conversion to Diesel following TRBDS 0% 0% 0% 0% 0%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 1% 1% 1% 1% 1%

Improved Auto. Trans. Controls/Externals 34% 23% 14% 4% 1%

Continuously Variable Transmission 3% 3% 3% 4% 4%

6/7/8-Speed Auto. Trans with Improved 

Internals 14% 11% 13% 15% 17%

Dual Clutch or Automated Manual 

Transmission 31% 50% 60% 70% 72%

Electric Power Steering 59% 60% 61% 66% 74%

Improved Accessories 29% 29% 32% 33% 40%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 7% 9% 12% 12% 12%

Crank mounted Integrated Starter Generator 0% 0% 0% 0% 0%

Power Split Hybrid 1% 1% 1% 2% 2%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 5% 5% 25% 35% 51%

Mass Reduction (3.5% to 8.5%) 0% 0% 20% 32% 48%

Low Rolling Resistance Tires 80% 82% 81% 92% 94%

Low Drag Brakes 19% 20% 22% 26% 45%
294

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 13% 14% 19% 22% 30%

Aero Drag Reduction 74% 79% 88% 97% 100%
295

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4% Annual Increase 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 80% 79% 77% 82% 97%

Engine Friction Reduction 44% 60% 62% 69% 84%

VVT - Coupled Cam Phasing (CCP) on SOHC 12% 12% 12% 11% 11%

Discrete Variable Valve Lift (DVVL) on SOHC 5% 4% 5% 9% 9%

Cylinder Deactivation on SOHC 3% 3% 2% 6% 5%

VVT - Intake Cam Phasing (ICP) 16% 16% 14% 11% 6%

VVT - Dual Cam Phasing (DCP) 34% 35% 44% 46% 51%

Discrete Variable Valve Lift (DVVL) on DOHC 24% 27% 33% 31% 36%

Continuously Variable Valve Lift (CVVL) 4% 4% 4% 4% 4%

Cylinder Deactivation on DOHC 7% 7% 7% 9% 9%

Cylinder Deactivation on OHV 17% 16% 14% 15% 21%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 5% 5% 5% 18%

Discrete Variable Valve Lift (DVVL) on OHV 0% 13% 14% 18% 18%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 23% 27% 33% 33% 37%

Combustion Restart 0% 0% 3% 8% 8%

Turbocharging and Downsizing 12% 14% 17% 17% 19%

Exhaust Gas Recirculation (EGR) Boost 0% 2% 4% 4% 7%

Conversion to Diesel following TRBDS 1% 2% 2% 2% 2%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 1% 1% 1% 1% 1%

Improved Auto. Trans. Controls/Externals 34% 24% 18% 8% 3%

Continuously Variable Transmission 3% 3% 3% 4% 4%

6/7/8-Speed Auto. Trans with Improved 

Internals 13% 7% 5% 6% 7%

Dual Clutch or Automated Manual 

Transmission 32% 54% 66% 78% 83%

Electric Power Steering 66% 70% 73% 81% 87%

Improved Accessories 30% 31% 33% 40% 48%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 10% 15% 24% 27% 28%

Crank mounted Integrated Starter Generator 0% 0% 0% 0% 0%

Power Split Hybrid 1% 1% 1% 2% 2%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 15% 15% 36% 45% 61%

Mass Reduction (3.5% to 8.5%) 0% 0% 21% 32% 50%

Low Rolling Resistance Tires 81% 84% 92% 99% 99%

Low Drag Brakes 20% 21% 22% 26% 48%
296

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 16% 17% 21% 24% 33%

Aero Drag Reduction 74% 79% 89% 98% 100%
297

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5% Annual Increase 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 77% 93% 91% 91% 91%

Engine Friction Reduction 42% 63% 73% 81% 86%

VVT - Coupled Cam Phasing (CCP) on SOHC 12% 12% 12% 11% 11%

Discrete Variable Valve Lift (DVVL) on SOHC 5% 4% 6% 12% 13%

Cylinder Deactivation on SOHC 3% 2% 2% 5% 6%

VVT - Intake Cam Phasing (ICP) 14% 13% 11% 8% 3%

VVT - Dual Cam Phasing (DCP) 34% 36% 40% 41% 45%

Discrete Variable Valve Lift (DVVL) on DOHC 22% 29% 34% 34% 39%

Continuously Variable Valve Lift (CVVL) 4% 4% 4% 4% 4%

Cylinder Deactivation on DOHC 7% 8% 6% 8% 15%

Cylinder Deactivation on OHV 17% 16% 15% 16% 22%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 5% 7% 7% 18%

Discrete Variable Valve Lift (DVVL) on OHV 0% 14% 17% 22% 22%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 20% 37% 43% 52% 59%

Combustion Restart 0% 0% 3% 16% 34%

Turbocharging and Downsizing 11% 15% 22% 22% 24%

Exhaust Gas Recirculation (EGR) Boost 0% 4% 10% 11% 13%

Conversion to Diesel following TRBDS 5% 6% 8% 8% 8%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 1% 1% 1% 1% 1%

Improved Auto. Trans. Controls/Externals 34% 24% 15% 5% 1%

Continuously Variable Transmission 3% 3% 3% 4% 4%

6/7/8-Speed Auto. Trans with Improved 

Internals 12% 6% 2% 1% 1%

Dual Clutch or Automated Manual 

Transmission 32% 53% 71% 84% 90%

Electric Power Steering 69% 77% 83% 88% 90%

Improved Accessories 30% 32% 40% 47% 52%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 8% 12% 22% 25% 27%

Crank mounted Integrated Starter Generator 2% 2% 4% 4% 4%

Power Split Hybrid 3% 4% 4% 4% 4%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 15% 17% 38% 50% 62%

Mass Reduction (3.5% to 8.5%) 0% 0% 21% 36% 55%

Low Rolling Resistance Tires 81% 84% 92% 99% 99%

Low Drag Brakes 25% 32% 38% 42% 65%
298

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 16% 17% 24% 28% 39%

Aero Drag Reduction 81% 86% 90% 95% 97%
299

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6% Annual Increase 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 76% 93% 90% 87% 85%

Engine Friction Reduction 42% 66% 76% 81% 79%

VVT - Coupled Cam Phasing (CCP) on SOHC 12% 12% 12% 12% 12%

Discrete Variable Valve Lift (DVVL) on SOHC 5% 4% 6% 12% 13%

Cylinder Deactivation on SOHC 3% 3% 2% 2% 1%

VVT - Intake Cam Phasing (ICP) 14% 11% 6% 1% 1%

VVT - Dual Cam Phasing (DCP) 33% 38% 46% 47% 46%

Discrete Variable Valve Lift (DVVL) on DOHC 21% 29% 34% 34% 38%

Continuously Variable Valve Lift (CVVL) 4% 4% 4% 4% 4%

Cylinder Deactivation on DOHC 7% 8% 6% 7% 5%

Cylinder Deactivation on OHV 17% 13% 8% 5% 5%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 8% 9% 8% 19%

Discrete Variable Valve Lift (DVVL) on OHV 0% 14% 17% 19% 20%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 22% 43% 54% 63% 74%

Combustion Restart 0% 0% 7% 16% 38%

Turbocharging and Downsizing 15% 29% 40% 47% 57%

Exhaust Gas Recirculation (EGR) Boost 0% 14% 25% 34% 47%

Conversion to Diesel following TRBDS 5% 6% 9% 12% 14%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 1% 1% 1% 1% 1%

Improved Auto. Trans. Controls/Externals 35% 25% 17% 5% 1%

Continuously Variable Transmission 3% 3% 2% 2% 2%

6/7/8-Speed Auto. Trans with Improved 

Internals 11% 6% 2% 1% 0%

Dual Clutch or Automated Manual 

Transmission 30% 51% 68% 82% 89%

Electric Power Steering 71% 79% 87% 89% 91%

Improved Accessories 31% 36% 45% 51% 53%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 12% 16% 28% 32% 38%

Crank mounted Integrated Starter Generator 1% 2% 2% 2% 2%

Power Split Hybrid 5% 6% 8% 8% 8%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 15% 18% 40% 56% 82%

Mass Reduction (3.5% to 8.5%) 0% 0% 21% 36% 55%

Low Rolling Resistance Tires 85% 88% 92% 97% 97%

Low Drag Brakes 25% 50% 53% 65% 77%
300

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 16% 26% 33% 50% 56%

Aero Drag Reduction 87% 92% 96% 97% 100%
301

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7% Annual Increase 

Technology

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

Low Friction Lubricants 87% 91% 87% 85% 83%

Engine Friction Reduction 42% 65% 76% 80% 78%

VVT - Coupled Cam Phasing (CCP) on SOHC 12% 12% 13% 13% 13%

Discrete Variable Valve Lift (DVVL) on SOHC 5% 4% 6% 12% 13%

Cylinder Deactivation on SOHC 3% 3% 2% 2% 1%

VVT - Intake Cam Phasing (ICP) 14% 10% 4% 4% 4%

VVT - Dual Cam Phasing (DCP) 33% 38% 46% 47% 45%

Discrete Variable Valve Lift (DVVL) on DOHC 21% 28% 38% 39% 44%

Continuously Variable Valve Lift (CVVL) 4% 4% 4% 4% 4%

Cylinder Deactivation on DOHC 7% 8% 8% 9% 2%

Cylinder Deactivation on OHV 17% 9% 5% 2% 1%

VVT - Coupled Cam Phasing (CCP) on OHV 5% 19% 17% 17% 18%

Discrete Variable Valve Lift (DVVL) on OHV 0% 13% 14% 18% 19%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 22% 40% 55% 64% 76%

Combustion Restart 0% 0% 10% 22% 39%

Turbocharging and Downsizing 15% 34% 50% 57% 67%

Exhaust Gas Recirculation (EGR) Boost 0% 20% 35% 46% 60%

Conversion to Diesel following TRBDS 6% 9% 12% 15% 17%

Conversion to Diesel following CBRST 0% 0% 0% 0% 0%

6-Speed Manual/Improved Internals 1% 1% 1% 1% 1%

Improved Auto. Trans. Controls/Externals 35% 25% 17% 5% 1%

Continuously Variable Transmission 3% 3% 2% 2% 2%

6/7/8-Speed Auto. Trans with Improved 

Internals 11% 6% 2% 1% 0%

Dual Clutch or Automated Manual 

Transmission 31% 51% 67% 79% 84%

Electric Power Steering 72% 80% 88% 89% 90%

Improved Accessories 33% 38% 47% 52% 53%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 13% 16% 27% 29% 36%

Crank mounted Integrated Starter Generator 3% 4% 7% 9% 7%

Power Split Hybrid 4% 6% 9% 10% 12%

2-Mode Hybrid 0% 0% 0% 1% 1%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 15% 22% 44% 60% 87%

Mass Reduction (3.5% to 8.5%) 0% 0% 21% 36% 57%

Low Rolling Resistance Tires 92% 95% 97% 97% 97%

Low Drag Brakes 29% 56% 60% 69% 77%
302

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 22% 35% 40% 53% 56%

Aero Drag Reduction 87% 92% 96% 97% 100%
303

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MY MY MY MY MY 

Max Net Benefit 

Technology 2012 2013 2014 2015 2016

Low Friction Lubricants 93% 91% 88% 85% 85%

Engine Friction Reduction 54% 77% 76% 77% 79%

VVT - Coupled Cam Phasing (CCP) on SOHC 13% 13% 13% 13% 13%

Discrete Variable Valve Lift (DVVL) on SOHC 5% 5% 6% 12% 13%

Cylinder Deactivation on SOHC 9% 9% 8% 4% 4%

VVT - Intake Cam Phasing (ICP) 10% 6% 3% 3% 2%

VVT - Dual Cam Phasing (DCP) 35% 40% 44% 43% 44%

Discrete Variable Valve Lift (DVVL) on DOHC 21% 28% 33% 33% 33%

Continuously Variable Valve Lift (CVVL) 4% 4% 4% 4% 4%

Cylinder Deactivation on DOHC 7% 8% 8% 9% 6%

Cylinder Deactivation on OHV 18% 12% 9% 6% 5%

VVT - Coupled Cam Phasing (CCP) on OHV 7% 21% 21% 20% 20%

Discrete Variable Valve Lift (DVVL) on OHV 0% 13% 15% 19% 19%

Conversion to DOHC with DCP 0% 0% 0% 0% 0%

Stoichiometric Gasoline Direct Injection (GDI) 21% 40% 50% 60% 63%

Combustion Restart 0% 0% 9% 18% 28%

Turbocharging and Downsizing 16% 34% 44% 51% 54%

Exhaust Gas Recirculation (EGR) Boost 0% 18% 28% 35% 42%

Conversion to Diesel following TRBDS 7% 9% 12% 14% 15%

Conversion to Diesel following CBRST 0% 1% 1% 1% 1%

6-Speed Manual/Improved Internals 1% 1% 1% 1% 1%

Improved Auto. Trans. Controls/Externals 35% 25% 17% 5% 1%

Continuously Variable Transmission 3% 3% 2% 2% 2%

6/7/8-Speed Auto. Trans with Improved 

Internals 11% 6% 2% 1% 0%

Dual Clutch or Automated Manual 

Transmission 30% 50% 67% 80% 88%

Electric Power Steering 73% 80% 84% 89% 91%

Improved Accessories 37% 42% 47% 53% 52%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted Integrated Starter Generator 12% 15% 27% 30% 33%

Crank mounted Integrated Starter Generator 3% 3% 5% 5% 5%

Power Split Hybrid 5% 7% 9% 9% 9%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 29% 51% 64% 71% 81%

Mass Reduction (3.5% to 8.5%) 0% 0% 21% 35% 56%

Low Rolling Resistance Tires 92% 95% 97% 97% 97%

Low Drag Brakes 33% 61% 70% 72% 74%
304

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Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 30% 42% 47% 54% 54%

Aero Drag Reduction 87% 92% 96% 97% 100%
305

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otal Cost = Total Benefit 

Technology 012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

T

MY 

2

Low Friction Lubricants 93% 91% 87% 85% 84%

Engine Friction Reduction 54% 77% 82% 79% 80%

VVT - Coupled Cam Phasing (CCP) on SOHC 13% 13% 13% 13% 13%

Discrete Variable Valve Lift (DVVL) on SOHC 5% 5% 6% 12% 13%

Cylinder Deactivation on SOHC 9% 9% 8% 2% 1%

VVT - Intake Cam Phasing (ICP) 10% 6% 1% 1% 0%

VVT - Dual Cam Phasing (DCP) 35% 40% 46% 45% 45%

Discrete Variable Lift (D n D Valve VVL) o OHC 21% 28% 34% 36% 41%

Continuously Va alve L VL riable V ift (CV ) 4% 4% 5% 5% 5%

Cylinder Deacti DOH vation on C 7% 8% 8% 9% 8%

Cylinder Deacti OHV vation on 18% 10% 6% 2% 1%

VVT - Coupled C ing ( O am Phas CCP) on HV 7% 21% 21% 20% 20%

Discrete Variable Valve Lift (D on O VVL) HV 0% 13% 15% 18% 20%

Conversion to D ith DC OHC w P 0% 0% 0% 0% 0%

Stoichiometric G Direct n asoline Injectio (GDI) 21% 40% 52% 60% 68%

Combustion Restart 0% 0% 12% 25% 30%

Turbocharging a nsizin nd Dow g 16% 36% 49% 55% 62%

Exhaust Gas Recirculation (EG st R) Boo 0% 20% 32% 44% 54%

Conversion to D followin S iesel g TRBD 7% 9% 12% 15% 15%

Conversion to D llowin T iesel fo g CBRS 0% 1% 1% 1% 1%

6-Speed Manual/Improved Internals 1% 1% 1% 1% 1%

Improved Auto. ntro rn Trans. Co ls/Exte als 35% 25% 17% 5% 1%

Continuously V Transm ariable ission 3% 3% 2% 2% 2%

6/7/8-Speed Auto. Trans with ve

Internals 1% 0%

 Impro d 

11% 6% 2%

Dual Clutch or Auto Ma

Transmission 80% 85%

mated nual 

30% 49% 67%

Electric Power Steering 73% 80% 88% 90% 92%

Improved Accessories 37% 42% 52% 57% 57%

12V Micro-Hybrid 0% 0% 0% 0% 0%

Belt mounted In Starte rat tegrated r Gene or 12% 14% 24% 25% 29%

Crank mounted Integrated Sta ner rter Ge ator 3% 4% 6% 9% 7%

Power Split Hybrid 5% 7% 10% 10% 12%

2-Mode Hybrid 0% 0% 0% 0% 0%

Plug-in Hybrid 0% 0% 0% 0% 0%

Mass Reduction (1.5%) 29% 51% 69% 76% 83%

Mass Reduction (3.5% to 8.5%) 0% 0% 21% 36% 56%

Low Rolling Resistance Tires 92% 95% 97% 97% 97%

Low Drag Brakes 33% 61% 70% 72% 77%
306

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Secondary Axle Disconnect - Unibody 0% 0% 0% 0% 0%

Secondary Axle Disconnect - Ladder Frame 30% 42% 49% 55% 57%

Aero Drag Reduction 87% 92% 96% 97% 100%
307

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

VI. MANUFACTURER CAFE CAPABILITIES 

Table VI-1 shows the agencies’ forecast of wh nufacturers’ passenger car mpg would 

be, based on the MY 2008 vehicles exten re. These mpg estimates change for 

some of the model years, but usually to a ased on changes in sales forecasts 

between passenger cars and light trucks.

Table VI-2 show TE SEL p ger t hen we do cost 

and benefit analyses, w e ST S th ut is. The 

adjusted baseline h ma turer 20 et an kes t the MY 2011 fuel 

economy standard by adding te y. ju seli me e analysis that 

each manufacture the M d ap le t an rer, (except BMW, 

Daimler, Porsche d Vo en) ap hno ac e MY 2011 

standard. Our rati is en e b is t co benefits of 

achieving MY 20 evels alre en a ed a imat e previous 

analysis. The cos tec ies ima t th no ered part of this 

rule. We then es e cost ne goi m th ste to the level of 

the alternatives.198

The estimated req ard n in VI pass rs for the 

preferred alternative. Table VI ide tim hi pg for passenger cars 

for each of the alt tives. Ta -5 t h V id ame light trucks as 

Tables VI-1 throu 4 show e rs. 

Note that not all m ers um ttem me l es. We assume 

that BMW, Daimler, Porsche, T d V e d n t th els because, for 

them, the cost of hese is m an t st of e These 

manufacturers hav n, in t , th gn ay ies than spend more 

money to improv econ duc he be it is reasonable to 

assume that they e th ce n th

The agency has p an a s of anu ers resp changes in the 

alternative CAFE levels. The a us hn ppl to systematically 

apply consistent c nd perfor ass ns ent ustr ell as consistent 

assumptions rega onom ion g by manufa . T lting computer 

model (the CAFE iance a ct l, o fer s t lpe model”), 

developed by tec f t T V t ran tion ms Center in 

consultation with NHTSA staff to stim e o co mpact of the 

alternative CAFE lpe m anal how impact of the 

standards in terms of increases in new vehicle pr es on a manufacturer-wide, industry-wide, and 

average per-vehicle basis. Based on these estim es and corresponding estimates of net 

 

ere the ma

ded into the futu

 minimal extent, b

 

s the ADJUS

e use th

D BA INE for 

A

assen cars. No e that w

ADJU

nufac

ED B

’s MY

ELINE

08 fle

rougho

d ma

the analys

takes eac it mee

chnolog

Y 20

 The ad

andar

sted ba

plicab

ne assu

o that 

s for th

r, below 11 st ufactu

lkswag

m

, Tata, an logy to

onale for th

 would ply tec hieve th

adjustm

 have 

t of th

ady be

aseline

nalyz

hat the 

nd est

sts and

11 mpg l ed in th

ts of these

timate th

hnolog

s and 

are est

fits of

ted, bu

ng fro

ey are

e adju

t consid

be d baseline

 

uired stand levels are show Table -3 for enger ca

-4 prov

bles V

s the es

hroug

ated ac

I-8 prov

eved m

e the s

levels 

erna I tables for 

gh VI- for pass nger ca 

anufactur are ass ed to a pt to “ et” the a ternativ

ata, an

 levels

olkswag

ore th

n woul

he co

ot mee

 paying p

ese lev

meeting t nalties. 

e show

e the fuel 

he past

omy of th

e willin

eir pro

ess to p

ts, so 

 penalt

agenc

rather 

t lieves

e future. 

y

would mak at choi again i

erformed nalysi how m factur could ond to

nalysis

manc

es a tec

umptio

ology a

to the

ication alg

ire ind

orithm

ost a e y, as w

rding ec ic decis

 Compl

-makin cturers he resu

nd Effe

he DO

s Mode

olpe Na

ften re

ional T

red to a

sporta

he “Vo

hnical staff o Syste

, is used

he Vo

 help e

odel 

ate th

ysis s

verall e

s the econ

nomic i

 standards. T omic 

ic

at

198 If the manufacturer’s MY 2008 fleet extended mpg level is above the level of the alternative, their mpg is 

assumed to remain at that level. Some manufacturer’s levels go slightly above the required mpg mark for them 

since some technologies are applied to all models of a particular manufacturer so that the exact level for each 

manufacturer may be slightly higher than the level of the standard and costs and benefits are estimated to that level. 
308

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

economic and other benefits, the agency is der alternatives that are economically 

practicable and technologically feasible. 

We note that, as explained above in Chap model has been updated to account for 

manufacturers’ ability to apply “multi-ye rder to minimize compliance burdens 

over multiple model years, and to accoun ers’ use of CAFE credits (when 

specified as a model input). The model h iewed. The model documentation, 

f the input assumptions and process, as well as peer review reports, was 

aking docket for the August 2005 NPRM, and updated 

documentation is also available o TSA bsite.

Our analyses of the potential ef alt e CAFE stan er two major 

elements: (1) pro s of the ical ter nd olu future product 

offerings and (2) of th cab d i a and vings associated 

with different har ange no th ht b ed onse to alternative 

CAFE standards.

 

 

 able to consi

ter V, the Volpe

ar planning” in o

t for manufactur

as been peer rev

including a description o

made available in the rulem

n NH ’s we 199

fects of

 techn

ernativ

chara

dards w

sales v

e founded on 

jection c mes o

ility an

istics a f

estimates fuel sa

dware ch

e appli ncrement l cost 

s—tech logies— at mig e utiliz in resp

 

199 See Docket Nos. NHTSA-2005-22223-3, 4, 5. 
309

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

MY ded 

Estimated mpg 

Pa er C

cturer 

Table VI-1 

2008 Fleet Exten

sseng ars 

Manufa

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

27.2 

 

27.2 

 

27.2 

 

27.2 

 

27.2 

Chrysler 

 

28.4 

 

28.7 

 

28.7 

 

28.7 

 

28.7 

Daimler 

 

25.9 

 

25.9 

 

25.6 

 

25.2 

 

25.2 

Ford 

 

28.3 

 

28.3 

 

28.3 

 

28.1 

 

28.1 

Genera

Motors 

l 

28.5 

 

28.6 

 

28.5 

 

28.4 

 

28.4 

Honda 

 

33.9 

 

34.1 

 

34.1 

 

33.9 

 

34.0 

Hyundai 

 

32.3 

 

31.2 

 

31.1 

 

31.9 

 

32.0 

Kia 

 

31.9 

 

32.2 

 

32.5 

 

32.9 

 

33.0 

Mazda 

 

30.6 

 

30.9 

 

31.0 

 

30.9 

 

30.9 

Mitsubishi 

 

29.5 

 

29.4 

 

29.1 

 

28.9 

 

28.9 

Nissan 

 

32.0 

 

32.1 

 

32.0 

 

32.0 

 

32.0 

Porsche 

 

26.2 

 

26.2 

 

26.2 

 

26.2 

 

26.2 

Subaru 

 

29.4 

 

29.4 

 

29.4 

 

29.4 

 

29.4 

Suzuki 

 

31.2 

 

30.9 

 

30.8 

 

30.8 

 

30.9 

Tata 

 

24.6 

 

24.6 

 

24.6 

 

24.6 

 

24.6 

Toyota 

 

35.4 

 

35.5 

 

35.4 

 

35.3 

 

35.3 

Volkswagen 

 

29.0 

 

29.0 

 

29.0 

 

29.0 

 

29.0 

Total/Average 

 

30.5 

 

30.8 

 

30.8 

 

30.7 

 

30.7 
310

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

A

Passenger Cars 

Table VI-2 

djusted Baseline 

 Estimated mpg 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

29.9 

 

29.9 

 

30.2 

 

30.2 

 

30.2 

Chrysler 

 

29.7 

 

29.9 

 

29.9 

 

29.8 

 

29.9 

Daimler 

 

27.4 

 

27.9 

 

29.1 

 

29.0 

 

29.0 

Ford 

 

30.0 

 

30.0 

 

30.0 

 

30.0 

 

30.0 

General 

Motors 

 

30.4 

 

30.4 

 

30.4 

 

30.4 

 

30.4 

Honda 

 

33.9 

 

34.1 

 

34.1 

 

33.9 

 

34.0 

Hyundai 

 

32.3 

 

31.2 

 

31.1 

 

31.9 

 

32.0 

Kia 

 

31.9 

 

32.2 

 

32.5 

 

32.9 

 

33.0 

Mazda 

 

30.6 

 

30.9 

 

31.0 

 

30.9 

 

30.9 

Mitsubishi 

 

31.1 

 

31.0 

 

31.1 

 

31.0 

 

31.0 

Nissan 

 

32.0 

 

32.1 

 

32.0 

 

32.0 

 

32.0 

Porsche 

 

28.3 

 

29.1 

 

29.1 

 

29.2 

 

29.2 

Subaru 

 

31.0 

 

31.0 

 

31.0 

 

31.1 

 

31.1 

Suzuki 

 

31.4 

 

31.6 

 

31.6 

 

31.6 

 

31.6 

Tata 

 

26.0 

 

27.8 

 

28.1 

 

28.1 

 

28.1 

Toyota 

 

35.4 

 

35.5 

 

35.4 

 

35.3 

 

35.3 

Volkswagen 

 

30.8 

 

30.8 

 

30.8 

 

30.7 

 

30.7 

Total/Average 

 

31.6 

 

31.8 

 

31.8 

 

31.8 

 

31.9 
311

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Required Fuel for Preferred Alternative 

Passenger Cars 

Table VI-3 

Economy Levels 

Estimated mpg 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

33.0 

 

33.7 

 

34.5 

 

35.7 

 

37.3 

Chrysler 

 

32.6 

 

33.3 

 

34.1 

 

35.2 

 

36.7 

Daimler 

 

32.0 

 

32.7 

 

33.3 

 

34.4 

 

35.8 

Ford 

 

32.9 

 

33.7 

 

34.4 

 

35.6 

 

37.1 

General 

Motors 

 

32.7 

 

33.5 

 

34.2 

 

35.4 

 

36.9 

Honda 

 

33.8 

 

34.6 

 

35.4 

 

36.7 

 

38.3 

Hyundai 

 

33.8 

 

34.3 

 

35.1 

 

36.6 

 

38.2 

Kia 

 

33.4 

 

34.2 

 

35.0 

 

36.3 

 

37.9 

Mazda 

 

33.8 

 

34.6 

 

35.5 

 

36.8 

 

38.4 

Mitsubishi 

 

34.2 

 

35.0 

 

35.8 

 

37.1 

 

38.7 

Nissan 

 

33.3 

 

34.1 

 

34.9 

 

36.1 

 

37.7 

Porsche 

 

35.9 

 

36.8 

 

37.8 

 

39.2 

 

41.1 

Subaru 

 

34.6 

 

35.5 

 

36.3 

 

37.7 

 

39.4 

Suzuki 

 

35.8 

 

36.6 

 

37.5 

 

39.0 

 

40.8 

Tata 

 

30.7 

 

31.4 

 

32.1 

 

33.3 

 

34.7 

Toyota 

 

33.9 

 

34.7 

 

35.5 

 

36.8 

 

38.4 

Volkswagen 

 

34.3 

 

35.0 

 

35.9 

 

37.2 

 

38.8 

Total/Average 

 

33.3 

 

34.2 

 

34.9 

 

36.2 

 

37.8 
312

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable evels, by Alternative 

Passenger Cars 

Preferred Alternative 

cturer 

Table VI-4 

 Fuel Economy L

Estimated mpg 

Manufa

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

29.9 

 

29.9 

 

30.3 

 

31.0 

 

32.4 

Chrysler 

 

31.5 

 

34.4 

 

35.1 

 

36.1 

 

36.7 

Daimler 

 

27.4 

 

27.9 

 

30.5 

 

31.8 

 

33.2 

Ford 

 

32.5 

 

34.6 

 

34.7 

 

35.9 

 

37.1 

Genera

Motors 

l 

30.8 

 

33.5 

 

35.0 

 

36.2 

 

36.9 

Honda 

 

34.0 

 

34.9 

 

36.0 

 

36.7 

 

38.3 

Hyundai 

 

34.8 

 

34.3 

 

36.1 

 

37.6 

 

38.5 

Kia 

 

33.4 

 

34.3 

 

35.1 

 

36.6 

 

37.9 

Mazda 

 

32.4 

 

35.1 

 

36.3 

 

36.8 

 

38.4 

Mitsubishi 

 

32.2 

 

32.1 

 

37.0 

 

38.7 

 

38.7 

Nissan 

 

33.3 

 

34.7 

 

36.6 

 

36.7 

 

37.7 

Porsche 

 

28.5 

 

29.2 

 

29.2 

 

29.2 

 

29.2 

Subaru 

 

32.4 

 

32.8 

 

37.1 

 

39.4 

 

39.4 

Suzuki 

 

31.4 

 

37.0 

 

39.1 

 

39.5 

 

40.9 

Tata 

 

26.3 

 

28.1 

 

28.7 

 

29.2 

 

30.8 

Toyota 

 

36.6 

 

36.8 

 

37.0 

 

38.1 

 

38.4 

Volkswagen 

 

31.6 

 

33.6 

 

33.9 

 

34.0 

 

35.5 

Total/Average 

 

32.8 

 

34.4 

 

35.3 

 

36.3 

 

37.2 
313

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable Fuel Economy Levels, by Alternative 

Estimated mpg 

Passenger Cars 

3% Annual Increase 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

29.9 

 

29.9 

 

30.3 

 

31.0 

 

32.4 

Chrysler 

 

31.1 

 

32.6 

 

32.9 

 

33.6 

 

34.5 

Daimler 

 

27.4 

 

27.9 

 

30.5 

 

31.8 

 

33.2 

Ford 

 

31.3 

 

33.0 

 

33.1 

 

33.9 

 

34.8 

General 

Motors 

 

30.8 

 

32.2 

 

33.1 

 

33.9 

 

34.7 

Honda 

 

33.9 

 

34.1 

 

34.2 

 

34.8 

 

35.9 

Hyundai 

 

33.5 

 

32.8 

 

33.9 

 

34.9 

 

35.8 

Kia 

 

31.9 

 

32.6 

 

33.6 

 

34.5 

 

35.5 

Mazda 

 

32.1 

 

33.4 

 

34.5 

 

34.9 

 

36.4 

Mitsubishi 

 

32.2 

 

32.1 

 

35.3 

 

36.2 

 

36.3 

Nissan 

 

32.3 

 

32.9 

 

33.8 

 

34.3 

 

35.3 

Porsche 

 

28.5 

 

29.2 

 

29.2 

 

29.2 

 

29.2 

Subaru 

 

32.4 

 

32.8 

 

36.2 

 

36.9 

 

36.8 

Suzuki 

 

31.4 

 

35.6 

 

37.0 

 

37.3 

 

38.5 

Tata 

 

26.3 

 

28.1 

 

28.7 

 

29.2 

 

30.8 

Toyota 

 

35.4 

 

35.5 

 

35.4 

 

35.3 

 

36.0 

Volkswagen 

 

31.6 

 

33.6 

 

33.9 

 

34.0 

 

35.5 

Total/Average 

 

32.2 

 

33.2 

 

33.7 

 

34.3 

 

35.2 
314

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable Fuel Economy Levels, by Alternative 

4% Annual Increase 

rer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

Estimated mpg 

Passenger Cars 

Manufactu

BMW 

 

2

 

2

 

3

 

3

 

3

 

9.9 

 

9.9 

 

0.3 

 

1.0 

 

2.4 

Chrysler 

 

31.4 

 

34.1 

 

34.8 

 

35.7 

 

36.1 

Daimler 

 

27.4 

 

27.9 

 

30.5 

 

31.8 

 

33.2 

Ford 

 

31.6 

 

33.8 

 

34.0 

 

35.2 

 

36.5 

General 

Motors 

 

30.8 

 

32.8 

 

34.2 

 

35.5 

 

36.4 

Honda 

 

34.0 

 

34.2 

 

35.3 

 

36.2 

 

37.7 

Hyundai 

 

34.1 

 

33.4 

 

35.2 

 

36.7 

 

37.7 

Kia 

 

32.1 

 

33.6 

 

34.8 

 

36.5 

 

37.3 

Mazda 

 

32.4 

 

34.4 

 

36.0 

 

36.4 

 

37.8 

Mitsubishi 

 

32.2 

 

32.1 

 

36.7 

 

38.1 

 

38.2 

Nissan 

 

32.3 

 

33.2 

 

35.3 

 

36.2 

 

37.1 

Porsche

 

28.5 

 

29.2 

 

29.2 

 

29.2 

 

29.2 

Subaru 

 

32.4 

 

32.8 

 

36.5 

 

38.7 

 

38.7 

Suzuki 

 

31.4 

 

36.2 

 

38.2 

 

38.6 

 

40.1 

Tata 

 

26.3 

 

28.1 

 

28.7 

 

29.2 

 

30.8 

Toyota 

 

35.5 

 

35.7 

 

35.6 

 

36.3 

 

37.8 

Volkswagen 

 

31.6 

 

33.6 

 

33.9 

 

34.0 

 

35.5 

Total/Average 

 

32.3 

 

33.6 

 

34.6 

 

35.5 

 

36.7 
315

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable Fuel Economy Levels, by Alternative 

Estimated mpg 

Passenger Cars 

5% Annual Increase 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

29.9 

 

29.9 

 

30.3 

 

31.0 

 

32.4 

Chrysler 

 

31.5 

 

35.0 

 

36.0 

 

37.3 

 

37.8 

Daimler 

 

27.4 

 

27.9 

 

30.5 

 

31.8 

 

33.2 

Ford 

 

31.9 

 

34.8 

 

35.0 

 

36.5 

 

38.3 

General 

Motors 

 

30.8 

 

33.2 

 

35.3 

 

36.8 

 

38.1 

Honda 

 

34.3 

 

35.2 

 

36.9 

 

37.8 

 

40.1 

Hyundai 

 

34.5 

 

34.0 

 

36.5 

 

38.5 

 

39.5 

Kia 

 

32.4 

 

34.2 

 

35.9 

 

37.3 

 

39.2 

Mazda 

 

32.4 

 

34.9 

 

37.0 

 

38.0 

 

39.7 

Mitsubishi 

 

32.2 

 

32.1 

 

38.3 

 

40.5 

 

40.6 

Nissan 

 

33.3 

 

35.0 

 

37.6 

 

38.3 

 

38.9 

Porsche 

 

28.5 

 

29.2 

 

29.2 

 

29.2 

 

29.2 

Subaru 

 

32.4 

 

32.8 

 

38.4 

 

40.7 

 

40.7 

Suzuki 

 

31.4 

 

38.2 

 

41.4 

 

42.1 

 

43.8 

Tata 

 

26.3 

 

28.1 

 

28.7 

 

29.2 

 

30.8 

Toyota 

 

36.6 

 

36.8 

 

37.1 

 

38.3 

 

39.7 

Volkswagen 

 

31.6 

 

33.6 

 

33.9 

 

34.0 

 

35.5 

Total/Average 

 

32.6 

 

34.4 

 

35.8 

 

36.9 

 

38.3 
316

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable F Levels, by Alternative 

6% Annual Increase 

uel Economy

Estimated mpg 

Passenger Cars 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

29.9 

 

29.9 

 

30.3 

 

31.0 

 

32.4 

Chrysler 

 

31.5 

 

36.3 

 

38.0 

 

39.5 

 

39.8 

Daimler 

 

27.4 

 

27.9 

 

30.5 

 

31.8 

 

33.2 

Ford 

 

32.4 

 

35.5 

 

35.8 

 

37.4 

 

39.1 

General 

Motors 

 

30.8 

 

33.8 

 

36.0 

 

38.4 

 

39.9 

Honda 

 

34.3 

 

36.3 

 

38.3 

 

39.1 

 

41.8 

Hyundai 

 

34.8 

 

34.4 

 

38.4 

 

39.8 

 

41.4 

Kia 

 

32.8 

 

34.9 

 

36.8 

 

38.8 

 

41.1 

Mazda 

 

32.4 

 

35.4 

 

38.0 

 

39.2 

 

41.6 

Mitsubishi 

 

32.2 

 

32.1 

 

39.1 

 

40.8 

 

40.8 

Nissan 

 

33.6 

 

35.4 

 

39.2 

 

40.0 

 

40.8 

Porsche 

 

28.5 

 

29.2 

 

29.2 

 

29.2 

 

29.2 

Subaru 

 

32.4 

 

32.8 

 

39.9 

 

42.8 

 

42.8 

Suzuki 

 

31.4 

 

38.5 

 

42.1 

 

42.8 

 

44.5 

Tata 

 

26.3 

 

28.1 

 

28.7 

 

29.2 

 

30.8 

Toyota 

 

36.9 

 

37.1 

 

37.5 

 

39.3 

 

41.7 

Volkswagen 

 

31.6 

 

33.6 

 

33.9 

 

34.0 

 

35.5 

Total/Average 

 

32.8 

 

34.9 

 

36.6 

 

38.0 

 

39.7 
317

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable F Levels, by Alternative 

7% Annual Increase 

uel Economy

Estimated mpg 

Passenger Cars 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

29.9 

 

29.9 

 

30.3 

 

31.0 

 

32.4 

Chrysler 

 

31.5 

 

37.0 

 

38.7 

 

40.3 

 

40.4 

Daimler 

 

27.4 

 

27.9 

 

30.5 

 

31.8 

 

33.2 

Ford 

 

32.5 

 

35.7 

 

36.1 

 

37.7 

 

39.4 

General 

Motors 

 

30.8 

 

33.9 

 

36.5 

 

38.9 

 

40.8 

Honda 

 

34.3 

 

37.6 

 

40.2 

 

40.9 

 

43.6 

Hyundai 

 

35.1 

 

34.8 

 

39.3 

 

41.4 

 

43.7 

Kia 

 

33.0 

 

35.6 

 

37.8 

 

40.4 

 

43.1 

Mazda 

 

32.4 

 

36.0 

 

38.9 

 

39.7 

 

43.7 

Mitsubishi 

 

32.2 

 

32.1 

 

38.7 

 

40.6 

 

40.5 

Nissan 

 

34.1 

 

35.9 

 

40.2 

 

40.8 

 

41.3 

Porsche 

 

28.5 

 

29.2 

 

29.2 

 

29.2 

 

29.2 

Subaru 

 

32.4 

 

32.8 

 

39.4 

 

42.6 

 

42.6 

Suzuki 

 

31.4 

 

40.3 

 

45.1 

 

46.4 

 

47.4 

Tata 

 

26.3 

 

28.1 

 

28.7 

 

29.2 

 

30.8 

Toyota 

 

37.7 

 

38.1 

 

39.1 

 

41.2 

 

43.7 

Volkswagen 

 

31.6 

 

33.6 

 

33.9 

 

34.0 

 

35.5 

Total/Average 

 

33.0 

 

35.4 

 

37.4 

 

38.9 

 

40.7 
318

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

P

Max Net Benefits 

cturer 

Estimated Achievable Fuel Economy Levels, by Alternative 

Estimated mpg 

assenger Cars

Manufa

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

29.9 

 

29.9 

 

30.3 

 

31.0 

 

32.4 

Chrysler 

 

31.5 

 

37.1 

 

38.5 

 

39.9 

 

40.0 

Daimler 

 

27.4 

 

27.9 

 

30.5 

 

31.8 

 

33.2 

Ford 

 

32.5 

 

36.1 

 

36.4 

 

38.0 

 

39.6 

Genera

Motors 

l 

30.8 

 

33.9 

 

36.5 

 

38.5 

 

39.9 

Honda 

 

34.3 

 

37.3 

 

39.4 

 

40.0 

 

41.6 

Hyundai 

 

35.0 

 

34.7 

 

38.6 

 

39.9 

 

41.5 

Kia 

 

33.1 

 

36.4 

 

38.3 

 

39.6 

 

41.1 

Mazda 

 

32.4 

 

36.2 

 

38.5 

 

39.6 

 

41.8 

Mitsubishi 

 

32.2 

 

32.1 

 

38.7 

 

40.6 

 

40.5 

Nissan 

 

34.2 

 

36.1 

 

40.0 

 

40.2 

 

40.8 

Porsche 

 

28.5 

 

29.2 

 

29.2 

 

29.2 

 

29.2 

Subaru 

 

32.4 

 

32.8 

 

39.7 

 

42.2 

 

42.2 

Suzuki 

 

31.4 

 

38.9 

 

42.5 

 

43.3 

 

44.5 

Tata 

 

26.3 

 

28.1 

 

28.7 

 

29.2 

 

30.8 

Toyota 

 

37.6 

 

38.0 

 

38.9 

 

40.3 

 

41.7 

Volkswagen 

 

31.6 

 

33.6 

 

33.9 

 

34.0 

 

35.5 

Total/Average 

 

33.0 

 

35.5 

 

37.3 

 

38.4 

 

39.8 
319

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable F Levels, by Alternative 

Total Cost=Total Benefit 

rer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

uel Economy

Estimated mpg 

Passenger Cars 

Manufactu

BMW 

 

2

 

2

 

3

 

3

 

3

 

9.9 

 

9.9 

 

0.3 

 

1.0 

 

2.4 

Chrysler 

 

31.5 

 

37.1 

 

38.7 

 

39.7 

 

39.8 

Daimler 

 

27.4 

 

27.9 

 

30.5 

 

31.8 

 

33.2 

Ford 

 

32.5 

 

36.2 

 

36.6 

 

38.1 

 

39.6 

General 

Motors 

 

30.8 

 

33.9 

 

36.5 

 

38.9 

 

40.8 

Honda 

 

34.3 

 

38.3 

 

40.8 

 

41.5 

 

43.2 

Hyundai 

 

35.0 

 

34.7 

 

39.4 

 

41.3 

 

43.0 

Kia 

 

33.5 

 

36.9 

 

39.2 

 

40.9 

 

42.5 

Mazda 

 

32.4 

 

36.2 

 

38.5 

 

39.6 

 

43.1 

Mitsubishi 

 

32.2 

 

32.1 

 

38.7 

 

40.6 

 

40.5 

Nissan 

 

34.4 

 

36.4 

 

40.4 

 

40.6 

 

41.3 

Porsche

 

28.5 

 

29.2 

 

29.2 

 

29.2 

 

29.2 

Subaru 

 

32.4 

 

32.8 

 

39.7 

 

42.4 

 

42.4 

Suzuki 

 

31.4 

 

40.2 

 

43.9 

 

44.6 

 

45.3 

Tata 

 

26.3 

 

28.1 

 

28.7 

 

29.2 

 

30.8 

Toyota 

 

38.3 

 

38.7 

 

39.9 

 

41.5 

 

43.1 

Volkswagen 

 

31.6 

 

33.6 

 

33.9 

 

34.0 

 

35.5 

Total/Average 

 

33.1 

 

35.7 

 

37.7 

 

39.0 

 

40.5 

 
320

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

MY ded 

E

Light Trucks 

Table VI-5 

2008 Fleet Exten

stimated mpg

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

23.0 

 

23.1 

 

23.1 

 

23.0 

 

23.0 

Chrysler 

 

21.9 

 

22.1 

 

22.2 

 

22.2 

 

22.2 

Daimler 

 

21.1 

 

21.1 

 

21.0 

 

21.1 

 

21.1 

Ford 

 

21.1 

 

21.2 

 

21.3 

 

21.3 

 

21.3 

General 

Motors 

 

21.3 

 

21.4 

 

21.5 

 

21.4 

 

21.4 

Honda 

 

25.1 

 

25.1 

 

25.1 

 

25.0 

 

25.0 

Hyundai 

 

24.3 

 

24.3 

 

24.3 

 

24.3 

 

24.3 

Kia 

 

23.7 

 

23.7 

 

23.8 

 

23.8 

 

23.8 

Mazda 

 

26.2 

 

26.6 

 

26.4 

 

26.4 

 

26.4 

Mitsubishi 

 

23.7 

 

23.7 

 

23.7 

 

23.6 

 

23.6 

Nissan 

 

21.9 

 

22.0 

 

22.1 

 

22.1 

 

22.1 

Porsche 

 

20.0 

 

20.0 

 

20.0 

 

20.0 

 

20.0 

Subaru 

 

26.2 

 

26.4 

 

26.5 

 

26.8 

 

26.9 

Suzuki 

 

23.3 

 

23.3 

 

23.3 

 

23.3 

 

23.3 

Tata 

 

19.7 

 

19.8 

 

19.8 

 

19.7 

 

19.7 

Toyota 

 

23.9 

 

24.0 

 

24.2 

 

24.2 

 

24.2 

Volkswagen 

 

20.2 

 

20.2 

 

20.2 

 

20.2 

 

20.2 

Total/Average 

 

22.3 

 

22.5 

 

22.6 

 

22.6 

 

22.6 
321

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

A

Light Trucks 

Table VI-6 

djusted Baseline 

Estimated mpg

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

25.7 

 

25.8 

 

25.8 

 

25.7 

 

25.7 

Chrysler 

 

24.5 

 

24.7 

 

24.8 

 

24.8 

 

24.8 

Daimler 

 

24.6 

 

24.7 

 

24.6 

 

25.2 

 

25.2 

Ford 

 

23.8 

 

23.8 

 

23.9 

 

24.0 

 

24.0 

General 

Motors 

 

23.3 

 

23.4 

 

23.5 

 

23.5 

 

23.5 

Honda 

 

25.8 

 

25.9 

 

25.9 

 

25.8 

 

25.8 

Hyundai 

 

25.9 

 

25.9 

 

25.9 

 

25.9 

 

25.9 

Kia 

 

25.3 

 

25.3 

 

25.3 

 

25.3 

 

25.3 

Mazda 

 

26.4 

 

26.7 

 

26.6 

 

26.6 

 

26.6 

Mitsubishi 

 

27.1 

 

27.1 

 

27.1 

 

27.1 

 

27.1 

Nissan 

 

24.5 

 

24.5 

 

24.6 

 

24.7 

 

24.7 

Porsche 

 

24.4 

 

24.4 

 

24.4 

 

25.6 

 

25.6 

Subaru 

 

26.7 

 

26.8 

 

27.0 

 

27.2 

 

27.3 

Suzuki 

 

24.7 

 

26.4 

 

26.4 

 

26.4 

 

26.4 

Tata 

 

23.8 

 

23.9 

 

24.1 

 

24.3 

 

26.3 

Toyota 

 

24.8 

 

25.0 

 

25.2 

 

25.2 

 

25.2 

Volkswagen 

 

21.1 

 

23.8 

 

25.0 

 

25.1 

 

25.1 

Total/Average 

 

24.3 

 

24.5 

 

24.7 

 

24.7 

 

24.7 
322

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Required Fuel for Preferred Alternative 

E

Light Trucks 

Table VI-7 

Economy Levels 

stimated mpg

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

26.6 

 

27.3 

 

27.9 

 

28.9 

 

30.2 

Chrysler 

 

25.7 

 

26.2 

 

26.8 

 

27.8 

 

29.0 

Daimler 

 

25.6 

 

26.3 

 

26.9 

 

27.8 

 

29.1 

Ford 

 

24.8 

 

25.4 

 

26.0 

 

27.0 

 

28.1 

General 

Motors 

 

24.2 

 

24.8 

 

25.2 

 

26.1 

 

27.2 

Honda 

 

26.9 

 

27.5 

 

28.0 

 

29.1 

 

30.4 

Hyundai 

 

27.0 

 

27.6 

 

28.2 

 

29.3 

 

30.7 

Kia 

 

26.2 

 

26.7 

 

27.3 

 

28.3 

 

29.5 

Mazda 

 

27.6 

 

28.4 

 

28.9 

 

30.1 

 

31.5 

Mitsubishi 

 

27.8 

 

28.5 

 

29.1 

 

30.2 

 

31.7 

Nissan 

 

25.6 

 

26.2 

 

26.8 

 

27.8 

 

29.1 

Porsche 

 

26.3 

 

26.9 

 

27.5 

 

28.5 

 

29.8 

Subaru 

 

27.9 

 

28.6 

 

29.2 

 

30.4 

 

31.9 

Suzuki 

 

27.5 

 

28.2 

 

28.8 

 

29.9 

 

31.4 

Tata 

 

27.4 

 

28.2 

 

28.8 

 

29.9 

 

31.3 

Toyota 

 

25.7 

 

26.2 

 

26.8 

 

27.8 

 

29.1 

Volkswagen 

 

25.8 

 

26.4 

 

27.0 

 

28.0 

 

29.2 

Total/Average 

 

25.4 

 

26.0 

 

26.6 

 

27.5 

 

28.8 
323

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable evels, by Alternative 

E

Light Trucks 

Preferred Alternative 

cturer 

Table VI-8 

 Fuel Economy L

stimated mpg

Manufa

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

26.6 

 

26.7 

 

26.8 

 

26.7 

 

27.9 

Chrysler 

 

24.8 

 

26.2 

 

27.6 

 

27.9 

 

29.0 

Daimler 

 

24.7 

 

24.8 

 

24.7 

 

25.3 

 

25.3 

Ford 

 

25.1 

 

25.7 

 

26.0 

 

27.7 

 

28.1 

Genera

Motors 

l 

23.4 

 

25.0 

 

25.9 

 

26.2 

 

27.2 

Honda 

 

27.7 

 

27.7 

 

28.5 

 

29.1 

 

30.5 

Hyundai 

 

28.1 

 

28.0 

 

30.6 

 

30.7 

 

30.7 

Kia 

 

26.1 

 

26.7 

 

27.5 

 

28.4 

 

29.7 

Mazda 

 

27.8 

 

29.5 

 

29.5 

 

30.1 

 

31.5 

Mitsubishi 

 

27.1 

 

27.1 

 

29.7 

 

30.4 

 

33.0 

Nissan 

 

25.8 

 

26.2 

 

27.5 

 

27.8 

 

29.1 

Porsche 

 

24.4 

 

24.4 

 

24.4 

 

26.7 

 

26.7 

Subaru 

 

30.3 

 

30.7 

 

31.1 

 

31.8 

 

31.9 

Suzuki 

 

24.7 

 

31.1 

 

31.1 

 

31.1 

 

31.6 

Tata 

 

23.8 

 

23.9 

 

24.1 

 

24.3 

 

27.9 

Toyota 

 

25.7 

 

26.3 

 

27.6 

 

28.3 

 

29.2 

Volkswagen 

 

21.1 

 

23.8 

 

26.3 

 

26.2 

 

26.2 

Total/Average 

 

25.1 

 

26.0 

 

27.0 

 

27.6 

 

28.5 
324

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable Fuel Economy Levels, by Alternative 

Estimated mpg 

Light Trucks

3% Annual Increase 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

25.6 

 

25.7 

 

25.8 

 

27.2 

 

28.4 

Chrysler 

 

24.5 

 

25.1 

 

26.1 

 

26.4 

 

27.2 

Daimler 

 

24.7 

 

24.8 

 

24.7 

 

25.3 

 

25.3 

Ford 

 

24.0 

 

24.5 

 

25.0 

 

26.6 

 

26.6 

General 

Motors 

 

23.0 

 

24.1 

 

24.7 

 

25.0 

 

25.6 

Honda 

 

26.6 

 

26.7 

 

27.1 

 

27.8 

 

28.4 

Hyundai 

 

26.6 

 

26.6 

 

28.4 

 

28.6 

 

28.6 

Kia 

 

25.3 

 

25.5 

 

26.1 

 

26.8 

 

28.0 

Mazda 

 

27.0 

 

28.3 

 

28.3 

 

28.5 

 

29.4 

Mitsubishi 

 

27.1 

 

27.1 

 

28.3 

 

28.6 

 

29.5 

Nissan 

 

24.9 

 

25.2 

 

26.0 

 

26.5 

 

27.2 

Porsche 

 

24.4 

 

24.4 

 

24.4 

 

26.7 

 

26.7 

Subaru 

 

28.5 

 

28.7 

 

29.4 

 

29.9 

 

30.1 

Suzuki 

 

24.7 

 

29.1 

 

29.1 

 

29.1 

 

29.3 

Tata 

 

23.8 

 

23.9 

 

24.1 

 

24.3 

 

27.9 

Toyota 

 

24.9 

 

25.1 

 

26.0 

 

26.5 

 

27.2 

Volkswagen 

 

21.1 

 

23.8 

 

26.3 

 

26.2 

 

26.2 

Total/Average 

 

24.4 

 

25.0 

 

25.8 

 

26.4 

 

26.9 
325

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

se 

Estimated Achievable Fuel Economy Levels, by Alternative 

Estimated mpg 

Light Trucks

4% Annual Increa

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

25.8 

 

25.8 

 

26.0 

 

27.2 

 

28.4 

Chrysler 

 

24.7 

 

25.8 

 

27.2 

 

27.5 

 

28.5 

Daimler 

 

24.7 

 

24.8 

 

24.7 

 

25.3 

 

25.3 

Ford 

 

24.6 

 

25.2 

 

25.7 

 

27.6 

 

27.7 

General 

Motors 

 

23.3 

 

24.7 

 

25.5 

 

25.8 

 

26.8 

Honda 

 

26.8 

 

26.9 

 

28.1 

 

28.9 

 

29.9 

Hyundai 

 

27.2 

 

27.2 

 

29.9 

 

30.2 

 

30.2 

Kia 

 

25.3 

 

26.0 

 

27.0 

 

27.9 

 

29.1 

Mazda 

 

27.1 

 

29.0 

 

29.0 

 

30.0 

 

31.0 

Mitsubishi 

 

27.1 

 

27.1 

 

29.4 

 

29.8 

 

32.4 

Nissan 

 

25.5 

 

25.9 

 

27.0 

 

27.5 

 

28.6 

Porsche 

 

24.4 

 

24.4 

 

24.4 

 

26.7 

 

26.7 

Subaru 

 

29.4 

 

29.8 

 

30.8 

 

31.6 

 

31.7 

Suzuki 

 

24.7 

 

29.6 

 

29.6 

 

29.6 

 

30.8 

Tata 

 

23.8 

 

23.9 

 

24.1 

 

24.3 

 

27.9 

Toyota 

 

24.9 

 

25.5 

 

26.8 

 

27.5 

 

28.6 

Volkswagen 

 

21.1 

 

23.8 

 

26.3 

 

26.2 

 

26.2 

Total/Average 

 

24.7 

 

25.5 

 

26.5 

 

27.2 

 

28.1 
326

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable Fuel Economy Levels, by Alternative 

Estimated mpg 

Light Trucks

5% Annual Increase 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

26.1 

 

26.2 

 

26.3 

 

27.2 

 

28.4 

Chrysler 

 

24.8 

 

26.1 

 

28.0 

 

28.5 

 

30.0 

Daimler 

 

24.7 

 

24.8 

 

24.7 

 

25.3 

 

25.3 

Ford 

 

25.0 

 

25.8 

 

26.4 

 

28.7 

 

29.0 

General 

Motors 

 

23.4 

 

25.2 

 

26.2 

 

26.8 

 

28.0 

Honda 

 

27.1 

 

27.2 

 

28.9 

 

30.2 

 

31.5 

Hyundai 

 

27.5 

 

27.5 

 

31.5 

 

31.8 

 

31.8 

Kia 

 

25.4 

 

26.6 

 

27.9 

 

29.0 

 

30.5 

Mazda 

 

27.8 

 

30.1 

 

30.1 

 

30.9 

 

32.6 

Mitsubishi 

 

27.1 

 

27.1 

 

30.6 

 

31.3 

 

32.8 

Nissan 

 

25.9 

 

26.4 

 

28.2 

 

28.7 

 

30.0 

Porsche 

 

24.4 

 

24.4 

 

24.4 

 

26.7 

 

26.7 

Subaru 

 

30.1 

 

30.4 

 

31.8 

 

32.4 

 

32.6 

Suzuki 

 

24.7 

 

31.5 

 

31.5 

 

31.5 

 

32.8 

Tata 

 

23.8 

 

23.9 

 

24.1 

 

24.3 

 

27.9 

Toyota 

 

25.1 

 

26.2 

 

28.2 

 

28.9 

 

30.0 

Volkswagen 

 

21.1 

 

23.8 

 

26.3 

 

26.2 

 

26.2 

Total/Average 

 

24.9 

 

26.0 

 

27.4 

 

28.3 

 

29.3 
327

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

chievable Fuel Economy Levels, by Alternative 

Estimated mpg 

Estimated A

Light Trucks

6% Annual Increase 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

26.4 

 

26.4 

 

26.6 

 

27.2 

 

28.4 

Chrysler 

 

24.8 

 

26.6 

 

28.8 

 

29.6 

 

31.4 

Daimler 24.7 24.8 24.7 25.3 25.3 

 

Ford 

 

25.0 

 

25.8 

 

26.2 

 

29.9 

 

30.4 

General 

Motors 

 

23.4 

 

26.2 

 

27.5 

 

28.4 

 

29.3 

Honda 

 

28.0 

 

28.0 

 

30.5 

 

31.6 

 

33.3 

Hyundai 

 

28.2 

 

28.2 

 

32.0 

 

32.7 

 

32.7 

Kia 

 

25.7 

 

27.1 

 

28.6 

 

30.2 

 

32.5 

Mazda 28.2 31.5 31.6 32.5 34.4 

 

Mitsubishi 

 

27.1 

 

27.1 

 

31.7 

 

32.5 

 

35.3 

Nissan 

 

26.1 

 

26.6 

 

28.6 

 

29.0 

 

31.5 

Porsche 

 

24.4 

 

24.4 

 

24.4 

 

26.7 

 

26.7 

Subaru 

 

30.3 

 

30.8 

 

32.7 

 

33.3 

 

33.5 

Suzuki 

 

24.7 

 

32.4 

 

32.4 

 

32.4 

 

33.5 

Tata 

 

23.8 

 

23.9 

 

24.1 

 

24.3 

 

27.9 

Toyota 

 

25.3 

 

26.8 

 

29.1 

 

29.9 

 

31.5 

Volkswagen 

 

21.1 

 

23.8 

 

26.3 

 

26.2 

 

26.2 

Total/Average 

 

25.0 

 

26.5 

 

28.1 

 

29.4 

 

30.6 
328

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable F Levels, by Alternative 

7% Annual Increase 

cturer 

uel Economy 

Estimated mpg 

Light Trucks

Manufa

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

26.6 

 

26.6 

 

26.8 

 

27.2 

 

28.4 

Chrysler 

 

24.8 

 

27.1 

 

29.5 

 

30.2 

 

32.4 

Daimler 

 

24.7 

 

24.8 

 

24.7 

 

25.3 

 

25.3 

Ford 

 

25.2 

 

26.0 

 

26.4 

 

30.2 

 

30.8 

General

Motors 

 

23.4 

 

26.6 

 

28.4 

 

29.6 

 

30.2 

Honda 

 

28.4 

 

28.4 

 

31.1 

 

31.7 

 

33.5 

Hyundai 

 

28.5 

 

28.5 

 

32.7 

 

33.4 

 

33.4 

Kia 

 

25.9 

 

27.1 

 

28.8 

 

31.3 

 

34.5 

Mazda 

 

28.9 

 

34.0 

 

34.0 

 

34.9 

 

36.5 

Mitsubishi 

 

27.1 

 

27.1 

 

31.7 

 

32.4 

 

35.3 

Nissan 

 

26.2 

 

26.6 

 

28.6 

 

29.0 

 

31.6 

Porsche 

 

24.4 

 

24.4 

 

24.4 

 

26.7 

 

26.7 

Subaru 

 

30.3 

 

30.8 

 

33.1 

 

33.8 

 

33.9 

Suzuki 

 

24.7 

 

32.4 

 

32.4 

 

32.4 

 

33.5 

Tata 

 

23.8 

 

23.9 

 

24.1 

 

24.3 

 

27.9 

Toyota 

 

25.6 

 

27.4 

 

30.5 

 

31.3 

 

33.0 

Volkswagen 

 

21.1 

 

23.8 

 

26.3 

 

26.2 

 

26.2 

Total/Average 

 

25.2 

 

26.9 

 

28.8 

 

30.1 

 

31.4 

 
329

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable Levels, by Alternative 

ax Net Benefits 

cturer 

Fuel Economy 

Estimated mpg 

Light Trucks

M

Manufa

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

26.6 

 

26.7 

 

26.8 

 

26.7 

 

27.9 

Chrysler 

 

24.8 

 

27.1 

 

29.6 

 

30.3 

 

31.4 

Daimler 

 

24.7 

 

24.8 

 

24.7 

 

25.3 

 

25.3 

Ford 

 

25.9 

 

26.7 

 

27.0 

 

30.0 

 

30.5 

General

Motors 

 

23.4 

 

26.6 

 

28.0 

 

28.8 

 

29.3 

Honda 

 

29.0 

 

28.9 

 

31.6 

 

32.1 

 

33.1 

Hyundai 

 

29.5 

 

29.5 

 

33.3 

 

33.5 

 

33.5 

Kia 

 

26.1 

 

27.0 

 

28.8 

 

31.2 

 

33.0 

Mazda 

 

29.4 

 

33.2 

 

33.0 

 

33.3 

 

34.4 

Mitsubishi 

 

27.1 

 

27.1 

 

31.7 

 

32.4 

 

35.3 

Nissan 

 

26.6 

 

27.1 

 

29.1 

 

29.2 

 

31.4 

Porsche 

 

24.4 

 

24.4 

 

24.4 

 

26.7 

 

26.7 

Subaru 

 

30.9 

 

31.4 

 

33.0 

 

33.7 

 

33.9 

Suzuki 

 

24.7 

 

33.3 

 

33.3 

 

33.3 

 

34.2 

Tata 

 

23.8 

 

23.9 

 

24.1 

 

24.3 

 

27.9 

Toyota 

 

26.3 

 

28.2 

 

30.3 

 

31.0 

 

31.5 

Volkswagen 

 

21.1 

 

23.8 

 

26.3 

 

26.2 

 

26.2 

Total/Average 

 

25.5 

 

27.3 

 

28.8 

 

29.9 

 

30.6 

 
330

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Achievable Fuel Economy Levels, by Alternative 

E

Total Cost=Total Benefit 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

stimated mpg

Light Trucks

Manufacturer 

BMW 

 

2

 

2

 

26

 

26

 

6.6 6.7 .8 .7 27.9 

Chrysler 

 

24.8 

 

27.1 

 

29.6 

 

30.3 

 

32.1 

Daimler 

 

24.7 

 

24.8 

 

24.7 

 

25.3 

 

25.3 

Ford 

 

25.9 

 

26.7 

 

27.0 

 

30.4 

 

31.0 

General 

Motors 

 

23.4 

 

26.9 

 

28.5 

 

29.6 

 

29.9 

Honda 

 

29.1 

 

29.1 

 

31.9 

 

32.4 

 

34.1 

Hyundai 

 

29.7 

 

29.7 

 

33.6 

 

33.8 

 

33.8 

Kia 

 

26.1 

 

27.0 

 

28.8 

 

31.2 

 

33.0 

Mazda 

 

29.7 

 

34.2 

 

34.0 

 

34.4 

 

35.4 

Mitsubishi 

 

27.1 

 

27.1 

 

31.7 

 

32.4 

 

35.3 

Nissan 

 

26.6 

 

27.0 

 

29.0 

 

29.2 

 

31.4 

Porsche 

 

24.4 

 

24.4 

 

24.4 

 

26.7 

 

26.7 

Subaru 

 

30.9 

 

31.4 

 

33.2 

 

33.9 

 

34.0 

Suzuki 

 

24.7 

 

34.2 

 

34.2 

 

34.2 

 

35.1 

Tata 

 

23.8 

 

23.9 

 

24.1 

 

24.3 

 

27.9 

Toyota 

 

26.3 

 

28.2 

 

30.8 

 

31.4 

 

32.2 

Volkswagen 

 

21.1 

 

23.8 

 

26.3 

 

26.2 

 

26.2 

Total/Average 

 

25.5 

 

27.4 

 

29.1 

 

30.2 

 

31.1 
331

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

VII. COST IMPACTS 

ion algorithm implemented with the Volpe model was used as the basis 

 fleet. The agency did estimate the costs or fines to bring passenger 

ar manufacturers up to the MY 2011 standards from their MY 2008 levels, as shown in Table 

VII-1a and VII-1b for passenger c nd li ks se co ve b stimated, but they 

are not considere f o g ir sts, and 

commensurate be e con pa e c d b of ing with 

previously issued The est s cha om o ye co anges in the 

manufacturers’ fl on c in t. is st 2012 

would be consistent from MY 2 16

Tables VII-2a to w the es o eh i ta sts in millions 

for the various alt for p r ab 3a imated cost per 

vehicle and incre otal co ill th s ht trucks. The 

costs for several manufacturers fin e nuf rs w ave to pay in 

addition to the te impr ents ve hicl s. W ume that the costs 

of fines will be p co s. em tota the estimated 

total manufacturer cos illi doll ate n when we are 

considering total al costs nefi es ar incl inc are transfer 

payments and not technology c

In a confidential N 0 9-0 r rese higher cost 

estimate than show le V ]. 

The technology applicat

for estimating costs for the

c

ars a

e costs

ght truc

 meetin

. The

he requ

sts ha

ments. Th

een e

d to be part o th ese co

sidered

f

rt of th

 t

osts an

e

enefits

ac

nefits, ar

 rules. 

comply

imate r ch

hanges

nge fr

footprin

year t

 Otherw

ar to 

e the co

unt fo

eet based shown in MY 

012-20 . 

2o sho timated c st per v

 T

icle and

IIncremeno sho

l total co

ernatives e est

mental t

assenge

sts in m

cars.

ions for 

les V

e variou

 to 3

 alternativ

w th

es for lig

are the

ovem

es that th

on an a

se ma

rage ve

acture

e basi

ould h

chnology e ass

assed on to

ts and fin

nsumer The incr ental l cost tabl

e a

es show

es in m ,

and be

ons of 

ts, fin

ars. L

e not 

r in th

uded, s

alysis

societ e fines

osts. 

submission (

n in Tab

HTSA-2 09-005 099), Ch ysler p nted a

II-2a [ 
332

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table a 

Estimated Incremental Co er Manufacturer’s Plans 

acturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

 VII-1

sts or Fines ov

To get to Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Passenger Cars 

Manuf

BMW 

 

456 

 

445 

 

489 

 

476 

 

464 

Chrysler 

 

8

 

7

 

74

 

72

 

69

 

3 

 

6 

 

 

 

 

 

 

Daimler 

 

362 

 

413 

 

570 

 

570 

 

555 

Ford 

 

92 

 

91 

 

88 

 

102 

 

97 

General 

Motors 

 

176 

 

173 

 

170 

 

173 

 

168 

Honda 

 

- 

 

- 

 

- 

 

- 

 

- 

Hyundai 

 

- 

 

- 

 

- 

 

- 

 

- 

Kia 

 

- 

 

- 

 

- 

 

- 

 

- 

Mazda 

 

- 

 

- 

 

- 

 

- 

 

- 

Mitsubishi 

 

197 

 

191 

 

177 

 

168 

 

166 

Nissan 

 

- 

 

- 

 

- 

 

- 

 

- 

Porsche 

 

661 

 

861 

 

849 

 

834 

 

818 

Subaru 

 

215 

 

205 

 

203 

 

198 

 

191 

Suzuki 

 

12 

 

46 

 

45 

 

43 

 

42 

Tata 

 

361 

 

748 

 

751 

 

731 

 

710 

Toyota 

 

- 

 

- 

 

- 

 

- 

 

- 

Volkswagen 

 

171 

 

166 

 

161 

 

157 

 

152 

Total/Average 

 

91 

 

88 

 

92 

 

95 

 

92 
333

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-1b 

Estimated Incremental C er Manufacturer’s Plans 

er 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

osts or Fines ov

To get to Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Light Trucks 

Manufactur

BMW 

 

2

 

2

 

26

 

25

 

73 72 5 3 249 

Chrysler 

 

490 

 

470 

 

463 

 

453 

 

442 

Daimler 

 

729 

 

714 

 

708 

 

805 

 

785 

Ford 

 

495 

 

460 

 

455 

 

449 

 

439 

General 

Motors 

 

498 

 

487 

 

497 

 

472 

 

459 

Honda 

 

108 

 

124 

 

119 

 

112 

 

110 

Hyundai

 

100 

 

96 

 

93 

 

90 

 

87 

Kia 

 

144 

 

136 

 

133 

 

129 

 

126 

Mazda 

 

12 

 

10 

 

10 

 

10 

 

9 

Mitsubishi 

 

489 

 

469 

 

463 

 

464 

 

451 

Nissan 

 

492 

 

461 

 

458 

 

453 

 

442 

Porsche 

 

1,059 

 

1,033 

 

1,009 

 

1,146 

 

1,115 

Subaru 

 

63 

 

57 

 

51 

 

42 

 

40 

Suzuki 

 

621 

 

717 

 

700 

 

684 

 

668 

Tata 

 

903 

 

890 

 

923 

 

949 

 

1,709 

Toyota 

 

91 

 

97 

 

91 

 

85 

 

82 

Volkswagen 

 

395 

 

1,084 

 

1,387 

 

1,364 

 

1,333 

Total/Average 

 

367 

 

367 

 

367 

 

356 

 

353 
334

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Incremental er Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Passenger Cars 

verage Cost per Vehicle 

Manufacturer 

Table VII-2a 

 Costs or Fines ov

Preferred Alternative 

A

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

157 

 

196 

 

255 

 

443 

 

855 

Chrysler 

 

794 

 

1,043 

 

1,129 

 

1,270 

 

1,358 

Daimler 

 

160 

 

198 

 

564 

 

944 

 

1,252 

Ford 

 

1,641 

 

1,537 

 

1,533 

 

1,713 

 

1,884 

General 

Motors

 

552 

 

896 

 

1,127 

 

1,302 

 

1,323 

Honda 

 

33 

 

98 

 

205 

 

273 

 

456 

Hyundai 

 

559 

 

591 

 

768 

 

744 

 

838 

Kia 

 

110 

 

144 

 

177 

 

235 

 

277 

Mazda 

 

632 

 

656 

 

799 

 

854 

 

923 

Mitsubishi 

 

644 

 

620 

 

1,588 

 

1,875 

 

1,831 

Nissan 

 

119 

 

323 

 

707 

 

723 

 

832 

Porsche 

 

316 

 

251 

 

307 

 

390 

 

496 

Subaru 

 

413 

 

472 

 

988 

 

1,385 

 

1,361 

Suzuki 

 

242 

 

625 

 

779 

 

794 

 

1,005 

Tata 

 

243 

 

258 

 

370 

 

532 

 

924 

Toyota 

 

31 

 

29 

 

41 

 

121 

 

126 

Volkswagen 

 

293 

 

505 

 

587 

 

668 

 

964 

Total/Average 

 

505 

 

573 

 

690 

 

799 

 

907 

 
335

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-2b 

 Estimated Incremental over Adjusted Baseline 

Preferred Alternative 

otal Incremental Costs 

rer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

Costs or Fines 

Total Incremental Costs in Millions (2007$) 

Passenger Cars 

T

Manufactu

BMW 

 

4

 

5

 

9

 

1

 

3

 

5.5 

 

7.7 

 

4.4 

 

82.2 

 

61.4 

Chrysler 

 

325.3 

 

444.7 

 

464.5 

 

498.2 

 

542.8 

Daimler 

 

33.8 

 

40.1 

 

137.8 

 

249.0 

 

339.3 

Ford 

 

2,408.9 

 

2,283.1

 

2,403.0

 

2,642.2

 

2,937.0

General 

Motors 

 

875.6 

 

1,383.9 

 

1,637.5 

 

1,936.6 

 

2,003.9 

Honda 

 

30.3 

 

104.1 

 

223.1 

 

249.5 

 

424.1 

 

Hyundai 

 

210.4 

 

233.7 

 

303.7 

 

380.1 

 

434.3 

Kia 

 

33.0 

 

47.0 

 

75.8 

 

126.8 

 

151.9 

Mazda 

 

178.8 

 

216.3 

 

302.2 

 

352.8 

 

388.0 

Mitsubishi 

 

71.0 

 

64.8 

 

140.0 

 

154.3 

 

151.4 

Nissan 

 

97.9 

 

268.7 

 

603.7 

 

669.2 

 

787.1 

Porsche

 

13.0 

 

10.8 

 

10.4 

 

12.7 

 

16.5 

Subaru 

 

75.7 

 

82.8 

 

182.3 

 

283.5 

 

281.5 

Suzuki 

 

17.5 

 

51.1 

 

70.6 

 

79.9 

 

103.6 

Tata 

 

8.8 

 

13.0 

 

18.2 

 

33.9 

 

60.5 

Toyota 

 

50.0 

 

56.6 

 

85.4 

 

263.4 

 

279.5 

Volkswagen 

 

127.3 

 

251.6 

 

304.2 

 

379.2 

 

562.2 

Total/Average 

 

4,602.7 

 

5,610.1 

 

7,056.8

 

8,493.8

 

9,825.0
336

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Inc ted Baseline 

Average (2007$) 

Passenger Cars 

% Annual Increase 

Average Cost per Vehicle 

cturer 3 4 5 6 

 

Table VII-2c 

remental Costs or Fines over Adjus

Cost per Vehicle

3

Manufa

 MY 

2012 

 MY 

201

 MY 

201

 MY 

201

 MY 

201

BMW 

 

69 

 

114 

 

178 

 

349 

 

728 

Chrysler 

 

335 

 

445 

 

481 

 

571 

 

695 

Daimler 

 

77 

 

121 

 

492 

 

851 

 

1,137 

Ford 

 

292 

 

461 

 

467 

 

621 

 

754 

General

Motors 

 

470 

 

555 

 

667 

 

781 

 

857 

Honda 

 

- 

 

- 

 

31 

 

90 

 

131 

Hyundai 

 

211 

 

261 

 

412 

 

372 

 

467 

Kia 

 

4 

 

26 

 

102 

 

152 

 

205 

Mazda 

 

273 

 

308 

 

462 

 

516 

 

538 

Mitsubishi 

 

550 

 

582 

 

1,106 

 

1,241 

 

1,218 

Nissan 

 

6 

 

53 

 

229 

 

263 

 

361 

Porsche 

 

217 

 

178 

 

213 

 

275 

 

342 

Subaru 

 

319 

 

379 

 

767 

 

842 

 

824 

Suzuki 

 

143 

 

267 

 

334 

 

342 

 

521 

Tata 

 

161 

 

188 

 

298 

 

438 

 

809 

Toyota 

 

- 

 

- 

 

- 

 

- 

 

24 

Volkswagen 

 

200 

 

429 

 

505 

 

563 

 

832 

Total/Average 

 

191 

 

248 

 

317 

 

394 

 

493 
337

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-2d 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Total Incremental Costs in Millions (2007$) 

Passenger Cars 

3% Annual Increase 

Total Incremental Costs 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

20.0 

 

33.5 

 

65.9 

 

143.7 

 

307.9 

Chrysler 

 

137.2 

 

189.7 

 

197.7 

 

224.2 

 

278.0 

Daimler 

 

16.3 

 

24.5 

 

120.3 

 

224.4 

 

308.0 

Ford 

 

429.2 

 

685.6 

 

732.5 

 

957.4 

 

1,175.1 

General 

Motors 

 

744.8 

 

856.7 

 

969.3 

 

1,161.4 

 

1,297.1 

Honda 

 

- 

 

- 

 

33.5 

 

82.1 

 

122.3 

Hyundai 

 

79.4 

 

103.4 

 

162.9 

 

190.2 

 

242.3 

Kia 

 

1.2 

 

8.5 

 

43.5 

 

82.1 

 

112.1 

Mazda 

 

77.3 

 

101.8 

 

174.7 

 

213.1 

 

226.4 

Mitsubishi 

 

60.7 

 

60.9 

 

97.5 

 

102.1 

 

100.7 

Nissan 

 

4.6 

 

44.0 

 

195.6 

 

243.6 

 

341.7 

Porsche 

 

8.9 

 

7.7 

 

7.2 

 

8.9 

 

11.4 

Subaru 

 

58.6 

 

66.4 

 

141.4 

 

172.5 

 

170.5 

Suzuki 

 

10.3 

 

21.9 

 

30.2 

 

34.5 

 

53.6 

Tata 

 

5.8 

 

9.5 

 

14.7 

 

27.9 

 

53.0 

Toyota 

 

- 

 

- 

 

- 

 

- 

 

53.0 

Volkswagen 

 

86.7 

 

213.9 

 

261.4 

 

319.8 

 

485.3 

Total/Average 

 

1,741.1 

 

2,427.9 

 

3,248.3 

 

4,188.0 

 

5,338.3 
338

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-2e 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Passenger Cars 

4% Annual Increase 

Average Cost per Vehicle 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

86 

 

147 

 

228 

 

421 

 

822 

Chrysler 

 

499 

 

860 

 

952 

 

1,082 

 

1,137 

Daimler 

 

94 

 

149 

 

542 

 

922 

 

1,219 

Ford 

 

425 

 

686 

 

710 

 

955 

 

1,138 

General 

Motors 

 

486 

 

712 

 

932 

 

1,141 

 

1,239 

Honda 

 

33 

 

27 

 

134 

 

220 

 

343 

Hyundai 

 

506 

 

521 

 

751 

 

734 

 

838 

Kia 

 

8 

 

71 

 

169 

 

209 

 

210 

Mazda 

 

560 

 

637 

 

860 

 

915 

 

922 

Mitsubishi 

 

567 

 

612 

 

1,511 

 

1,706 

 

1,670 

Nissan 

 

16 

 

122 

 

554 

 

653 

 

739 

Porsche 

 

233 

 

196 

 

274 

 

363 

 

457 

Subaru 

 

336 

 

417 

 

827 

 

1,206 

 

1,184 

Suzuki 

 

160 

 

412 

 

559 

 

582 

 

798 

Tata 

 

177 

 

214 

 

348 

 

510 

 

897 

 

Toyota 

 

21 

 

20 

 

34 

 

122 

 

205 

Volkswagen 

 

216 

 

455 

 

560 

 

641 

 

931 

 

Total/Average 

 

254 

 

366 

 

500 

 

640 

 

764 
339

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimate aseline 

Total Increme lions (2007$) 

Passenger Cars 

Table VII-2f 

d Incremental Costs or Fines over Adjusted B

ntal Costs in Mil

4% Annual Increase 

Total Incremental Costs 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

24.8 

 

43.1 

 

84.3 

 

173.2 

 

347.4 

Chrysler 

 

204.5 

 

366.8 

 

391.7 

 

424.8 

 

454.3 

Daimler 

 

19.8 

 

30.1 

 

132.5 

 

243.2 

 

330.4 

Ford 

 

623.3 

 

1,018.5 

 

1,113.0 

 

1,472.5 

 

1,773.7 

General 

Motors 

 

771.0 

 

1,099.3 

 

1,354.0 

 

1,696.7 

 

1,875.6 

Honda 

 

30.3 

 

29.3 

 

146.2 

 

200.5 

 

319.5 

Hyundai 

 

190.4 

 

206.2 

 

296.9 

 

375.4 

 

434.5 

Kia 

 

2.5 

 

23.3 

 

72.2 

 

112.8 

 

115.2 

Mazda 

 

158.6 

 

210.1 

 

325.4 

 

378.3 

 

387.5 

Mitsubishi 

 

62.5 

 

63.9 

 

133.2 

 

140.4 

 

138.1 

Nissan 

 

13.0 

 

101.8 

 

473.1 

 

604.5 

 

699.5 

Porsche 

 

9.6 

 

8.5 

 

9.3 

 

11.8 

 

15.2 

Subaru 

 

61.6 

 

73.1 

 

152.5 

 

246.8 

 

244.9 

Suzuki 

 

11.5 

 

33.7 

 

50.6 

 

58.6 

 

82.2 

Tata 

 

6.4 

 

10.8 

 

17.1 

 

32.5 

 

58.7 

Toyota 

 

34.2 

 

39.3 

 

71.2 

 

265.1 

 

456.8 

Volkswagen 

 

93.9 

 

227.0 

 

290.0 

 

363.6 

 

543.0 

Total/Average 

 

2,317.8 

 

3,584.8 

 

5,113.1 

 

6,800.8 

 

8,276.5 
340

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-2g 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Passenger Cars 

5% Annual Increase 

Average Cost per Vehicle 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

102 

 

180 

 

283 

 

498 

 

915 

 

Chrysler 

 

745 

 

1,303 

 

1,462 

 

1,653 

 

1,727 

Daimler 

 

110 

 

182 

 

591 

 

988 

 

1,313 

Ford 

 

743 

 

1,245 

 

1,261 

 

1,583 

 

1,923 

General 

Motors 

 

503 

 

823 

 

1,187 

 

1,425 

 

1,594 

Honda 

 

50 

 

109 

 

271 

 

375 

 

606 

 

Hyundai 

 

747 

 

882 

 

1,057 

 

1,052 

 

1,124 

Kia 

 

49 

 

128 

 

197 

 

261 

 

369 

Mazda 

 

577 

 

718 

 

1,166 

 

1,407 

 

1,427 

Mitsubishi 

 

583 

 

650 

 

2,534 

 

3,213 

 

3,141 

Nissan 

 

294 

 

491 

 

965 

 

1,064 

 

1,125 

Porsche 

 

255 

 

234 

 

340 

 

456 

 

578 

Subaru 

 

358 

 

456 

 

1,372 

 

1,723 

 

1,679 

Suzuki 

 

182 

 

959 

 

1,267 

 

1,316 

 

1,540 

Tata 

 

194 

 

247 

 

403 

 

581 

 

990 

 

Toyota 

 

31 

 

29 

 

52 

 

129 

 

212 

Volkswagen 

 

233 

 

494 

 

620 

 

723 

 

1,041 

Total/Average 

 

362 

 

558 

 

749 

 

918 

 

1,088 
341

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-2h 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Total Incremental Costs in Millions (2007$) 

Passenger Cars 

5% Annual Increase 

Total Incremental Costs 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

29.6 

 

52.8 

 

104.6 

 

204.9 

 

387.0 

Chrysler 

 

305.0 

 

555.4 

 

601.5 

 

648.8 

 

690.2 

Daimler 

 

23.3 

 

36.8 

 

144.6 

 

260.7 

 

355.7 

Ford 

 

1,091.0 

 

1,849.2 

 

1,977.1 

 

2,441.5 

 

2,998.2 

General 

Motors 

 

797.1 

 

1,271.7 

 

1,723.6 

 

2,119.1 

 

2,413.3 

Honda 

 

45.1 

 

115.9 

 

294.3 

 

342.1 

 

563.9 

 

Hyundai 

 

281.1 

 

349.0 

 

418.1 

 

538.0 

 

582.7 

Kia 

 

14.7 

 

42.0 

 

84.0 

 

140.5 

 

202.1 

Mazda 

 

163.2 

 

236.8 

 

441.1 

 

581.5 

 

599.9 

 

Mitsubishi 

 

64.3 

 

68.0 

 

223.4 

 

264.4 

 

259.7 

Nissan 

 

242.2 

 

408.5 

 

823.8 

 

984.9 

 

1,065.0 

Porsche 

 

10.5 

 

10.1 

 

11.6 

 

14.8 

 

19.3 

Subaru 

 

65.6 

 

79.9 

 

253.1 

 

352.8 

 

347.4 

Suzuki 

 

13.1 

 

78.4 

 

114.8 

 

132.3 

 

158.6 

Tata 

 

7.0 

 

12.5 

 

19.9 

 

37.1 

 

64.8 

Toyota 

 

50.0 

 

56.6 

 

107.7 

 

279.8 

 

472.8 

Volkswagen 

 

101.1 

 

246.2 

 

321.3 

 

410.4 

 

607.1 

Total/Average 

 

3,303.9 

 

5,469.6 

 

7,664.3 

 

9,753.6 

 

11,787.6 
342

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Inc ted Baseline 

Average (2007$) 

Passenger Cars 

verage Cost per Vehicle 

Manufacturer 

Table VII-2i 

remental Costs or Fines over Adjus

Cost per Vehicle

6% Annual Increase 

A

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

119 

 

218 

 

338 

 

575 

 

1,020 

Chrysler 

 

761 

 

1,964 

 

2,470 

 

2,800 

 

2,795 

Daimler 

 

127 

 

215 

 

646 

 

1,060 

 

1,406 

Ford 

 

1,435 

 

1,749 

 

1,886 

 

2,344 

 

2,707 

General 

Motors

 

519 

 

1,026 

 

1,457 

 

1,965 

 

2,182 

Honda 

 

50 

 

191 

 

386 

 

470 

 

845 

Hyundai 

 

731 

 

845 

 

1,277 

 

1,175 

 

1,315 

Kia 

 

39 

 

140 

 

268 

 

386 

 

597 

Mazda 

 

593 

 

756 

 

1,534 

 

2,110 

 

2,279 

Mitsubishi 

 

605 

 

642 

 

2,688 

 

2,934 

 

2,933 

Nissan 

 

679 

 

899 

 

1,755 

 

1,851 

 

1,997 

Porsche 

 

277 

 

278 

 

406 

 

550 

 

699 

Subaru 

 

374 

 

494 

 

2,093 

 

2,736 

 

2,692 

Suzuki 

 

198 

 

1,186 

 

1,589 

 

1,629 

 

1,816 

Tata 

 

210 

 

280 

 

452 

 

653 

 

1,084 

Toyota 

 

97 

 

93 

 

119 

 

266 

 

404 

Volkswagen 

 

249 

 

527 

 

675 

 

806 

 

1,151 

Total/Average 

 

526 

 

758 1,064 1,321 1,546 

 
343

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-2j 

Estimated Incremental C ver Adjusted Baseline 

se 

osts or Fines o

Total Incremental Costs in Millions (2007$) 

Passenger Cars 

6% Annual Increa

Total Incremental Costs 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

34.4 

 

64.2 

 

125.0 

 

236.6 

 

431.1 

Chrysler 

 

311.7 

 

837.5 

 

1,015.9 

 

1,098.8 

 

1,117.1 

Daimler 

 

26.8 

 

43.4 

 

158.0 

 

279.5 

 

381.0 

Ford 

 

2,106.8 

 

2,598.6 

 

2,956.3 

 

3,615.3 

 

4,220.7 

General 

Motors 

 

823.3 

 

1,585.1 

 

2,115.6 

 

2,922.7 

 

3,304.9 

Honda 

 

45.5 

 

203.8 

 

419.4 

 

428.7 

 

786.5 

Hyundai 

 

275.2 

 

334.3 

 

505.1 

 

600.6 

 

681.5 

Kia 

 

11.8 

 

45.8 

 

114.7 

 

208.1 

 

326.9 

Mazda 

 

167.9 

 

249.3 

 

580.3 

 

872.2 

 

958.1 

 

Mitsubishi 

 

66.8 

 

67.1 

 

236.9 

 

241.5 

 

242.5 

Nissan 

 

559.3 

 

747.9 

 

1,498.5 

 

1,712.6 

 

1,890.5 

Porsche 

 

11.4 

 

12.0 

 

13.8 

 

17.8 

 

23.3 

Subaru 

 

68.7 

 

86.6 

 

386.2 

 

560.2 

 

556.9 

Suzuki 

 

14.3 

 

97.0 

 

144.0 

 

163.9 

 

187.0 

Tata 

 

7.6 

 

14.1 

 

22.3 

 

41.6 

 

71.0 

Toyota 

 

155.1 

 

181.4 

 

247.5 

 

579.6 

 

899.2 

 

Volkswagen 

 

108.2 

 

262.6 

 

349.8 

 

457.3 

 

671.3 

Total/Average 

 

4,794.8 

 

7,430.9 

 

10,889.2 

 

14,037.0 

 

16,749.7 
344

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-2k 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Passenger Cars 

7% Annual Increase 

Average Cost per Vehicle 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

135 

 

251 

 

393 

 

652 

 

1,124 

Chrysler 

 

778 

 

2,195 

 

2,696 

 

3,064 

 

3,096 

Daimler 

 

138 

 

248 

 

696 

 

1,131 

 

1,500 

Ford 

 

1,619 

 

1,902 

 

2,079 

 

2,559 

 

2,990 

General 

Motors 

 

536 

 

1,248 

 

1,912 

 

2,417 

 

2,904 

Honda 

 

50 

 

454 

 

737 

 

804 

 

1,181 

Hyundai 

 

770 

 

911 

 

1,493 

 

1,464 

 

1,750 

Kia 

 

55 

 

251 

 

489 

 

698 

 

963 

Mazda 

 

610 

 

1,013 

 

2,097 

 

2,299 

 

2,704 

Mitsubishi 

 

622 

 

675 

 

2,758 

 

3,098 

 

3,182 

Nissan 

 

867 

 

1,280 

 

2,356 

 

2,482 

 

2,574 

Porsche 

 

294 

 

317 

 

472 

 

643 

 

831 

Subaru 

 

391 

 

533 

 

1,844 

 

2,629 

 

2,711 

Suzuki 

 

220 

 

2,182 

 

3,127 

 

3,294 

 

3,331 

Tata 

 

221 

 

313 

 

507 

 

724 

 

1,183 

Toyota 

 

295 

 

276 

 

371 

 

574 

 

774 

Volkswagen 

 

271 

 

565 

 

736 

 

894 

 

1,267 

Total/Average 

 

616 

 

952 

 

1,361 

 

1,634 

 

1,941 
345

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-2l 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Total Incremental Costs in Millions (2007$) 

Passenger Cars 

7% Annual Increase 

Total Incremental Costs 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

39.1 

 

73.8 

 

145.3 

 

268.3 

 

475.3 

Chrysler 

 

318.5 

 

935.8 

 

1,109.0 

 

1,202.4 

 

1,237.7 

Daimler 

 

29.1 

 

50.1 

 

170.1 

 

298.4 

 

406.4 

Ford 

 

2,376.6 

 

2,825.5 

 

3,259.6 

 

3,946.3 

 

4,662.1 

General 

Motors 

 

849.5 

 

1,927.5 

 

2,777.0 

 

3,594.5 

 

4,398.3 

Honda 

 

45.5 

 

483.5 

 

801.3 

 

733.5 

 

1,099.0 

Hyundai 

 

289.8 

 

360.4 

 

590.4 

 

748.4 

 

907.0 

Kia 

 

16.5 

 

81.8 

 

208.8 

 

375.9 

 

527.5 

Mazda 

 

172.6 

 

334.0 

 

793.1 

 

950.0 

 

1,136.8 

Mitsubishi 

 

68.6 

 

70.5 

 

243.1 

 

255.0 

 

263.1 

Nissan 

 

714.6 

 

1,064.1 

 

2,012.0 

 

2,296.6 

 

2,435.8 

Porsche 

 

12.1 

 

13.7 

 

16.0 

 

20.9 

 

27.7 

Subaru 

 

71.7 

 

93.4 

 

340.2 

 

538.3 

 

561.0 

Suzuki 

 

15.9 

 

178.5 

 

283.3 

 

331.4 

 

343.1 

Tata 

 

8.0 

 

15.8 

 

25.0 

 

46.2 

 

77.5 

Toyota 

 

470.0 

 

536.5 

 

770.8 

 

1,249.3 

 

1,722.8 

Volkswagen 

 

117.8 

 

281.8 

 

381.1 

 

507.2 

 

738.6 

Total/Average 

 

5,615.8 

 

9,326.9 

 

13,926.3 

 

17,362.4 

 

21,019.7 
346

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-2m 

Estimated Incremental C ver Adjusted Baseline 

Max Net Benefits 

cle 

Manufacturer 

 MY MY MY MY MY 

osts or Fines o

Average Cost per Vehicle (2007$) 

Passenger Cars 

Average Cost per Vehi

2012 2013 2014 2015 2016 

BMW 

 

141 

 

301 

 

426 

 

619 

 

1,020 

Chrysler 

 

778 

 

2,159 

 

2,452 

 

2,660 

 

2,608 

Daimler 

 

143 

 

292 

 

723 

 

1,104 

 

1,406 

Ford 

 

1,624 

 

1,962 

 

2,149 

 

2,545 

 

2,891 

General 

Motors 

 

536 

 

1,292 

 

1,939 

 

2,235 

 

2,400 

Honda 

 

49 

 

365 

 

562 

 

609 

 

891 

Hyundai 

 

757 

 

945 

 

1,304 

 

1,196 

 

1,321 

Kia 

 

48 

 

264 

 

422 

 

503 

 

602 

Mazda 

 

615 

 

1,219 

 

1,654 

 

2,171 

 

2,437 

Mitsubishi 

 

622 

 

730 

 

2,787 

 

3,077 

 

3,072 

Nissan 

 

882 

 

1,229 

 

2,080 

 

2,086 

 

2,104 

Porsche 

 

299 

 

372 

 

510 

 

605 

 

699 

Subaru 

 

396 

 

582 

 

1,961 

 

2,589 

 

2,580 

Suzuki 

 

226 

 

1,248 

 

1,649 

 

1,721 

 

1,876 

Tata 

 

227 

 

357 

 

535 

 

697 

 

1,084 

Toyota 

 

264 

 

242 

 

327 

 

414 

 

464 

Volkswagen 

 

271 

 

620 

 

769 

 

855 

 

1,151 

Total/Average 

 

612 

 

954 

 

1,282 

 

1,460 

 

1,628 
347

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimate aseline 

Total Incremen llions (2007$) 

Passenger Cars 

otal Incremental Costs 

rer 

Table VII-2n 

d Incremental Costs or Fines over Adjusted B

tal Costs in Mi

Max Net Benefits 

T

Manufactu

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

40.7 

 

88.4 

 

157.5 

 

254.7 

 

431.1 

Chrysler 

 

318.5 

 

920.5 

 

1,008.7 

 

1,044.1

 

1,042.3

Daimler 

 

30.3 

 

59.0 

 

176.8 

 

291.1 

 

381.0 

Ford 

 

2,384.6 

 

2,914.3 

 

3,368.6 

 

3,924.9 

 

4,507.0 

General 

Motors

 

849.5 

 

1,995.5 

 

2,816.9 

 

3,323.3 

 

3,633.9 

Honda 

 

44.1 

 

389.1 

 

610.9 

 

555.4 

 

828.4 

Hyundai 

 

284.7 

 

373.8 

 

515.6 

 

611.7 

 

684.6 

Kia 

 

14.3 

 

86.2 

 

180.5 

 

271.2 

 

330.0 

Mazda 

 

174.1 

 

402.0 

 

625.5 

 

897.2 

 

1,024.7 

Mitsubishi 

 

68.6 

 

76.3 

 

245.7 

 

253.2 

 

254.0 

Nissan 

 

727.1 

 

1,021.8 

 

1,776.2 

 

1,930.7 

 

1,991.5 

Porsche 

 

12.3 

 

16.1 

 

17.4 

 

19.6 

 

23.3 

Subaru 

 

72.7 

 

102.0 

 

361.9 

 

530.0 

 

533.7 

Suzuki 

 

16.3 

 

102.0 

 

149.4 

 

173.1 

 

193.2 

Tata 

 

8.2 

 

18.0 

 

26.4 

 

44.4 

 

71.0 

Toyota 

 

420.2 

 

470.7 

 

679.9 

 

901.0 

 

1,033.5 

Volkswagen 

 

117.8 

 

309.2 

 

398.2 

 

485.4 

 

671.3 

Total/Average 5,584.0 9,345.0 13,115.9 15,511.1 17,634.6 

 
348

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-2o 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Average C e (2007$) 

Passen

Total Cost = Total Benefit 

Average Cost per Vehicle 

acturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

ost per Vehicl

ger Cars 

Manuf

BMW 

 

163 

 

334 

 

481 

 

685 

 

1,091 

Chrysler 

 

8

 

2,

 

2,

 

2,6

 

2,

 

00 

 

057 

 

483 

 

34 

 

639 

Daimler 

 

165 

 

325 

 

773 

 

1,164 

 

1,472 

 

Ford 

 

1,646 

 

1,966 

 

2,198 

 

2,612 

 

2,947 

General 

Motors 

 

558 

 

1,325 

 

1,994 

 

2,455 

 

2,871 

Honda 

 

50 

 

630 

 

873 

 

917 

 

1,192 

Hyundai

 

757 

 

984 

 

1,494 

 

1,415 

 

1,569 

Kia 

 

131 

 

354 

 

604 

 

750 

 

847 

Mazda 

 

637 

 

1,257 

 

1,709 

 

2,248 

 

2,489 

Mitsubishi 

 

649 

 

768 

 

2,847 

 

3,143 

 

3,154 

Nissan

 

958 

 

1,451 

 

2,278 

 

2,288 

 

2,549 

Porsche 

 

327 

 

416 

 

576 

 

687 

 

793 

Subaru 

 

424 

 

626 

 

2,022 

 

2,726 

 

2,777 

Suzuki 

 

253 

 

2,043 

 

2,420 

 

2,496 

 

2,550 

Tata 

 

249 

 

390 

 

584 

 

763 

 

1,155 

Toyota

 

496 

 

465 

 

622 

 

727 

 

772 

Volkswagen 

 

299 

 

659 

 

829 

 

932 

 

1,228 

Total/Average 

 

675 

 

1,065 

 

1,440 

 

1,653 

 

1,878 
349

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimate aseline 

Total Incremen llions (2007$) 

Passenger Cars 

efit 

Table VII-2p 

d Incremental Costs or Fines over Adjusted B

tal Costs in Mi

Total Cost = Total Ben

Total Incremental Costs 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

47.1 

 

98.1 

 

177.9 

 

281.8 

 

461.4 

Chrysler 

 

327.5 

 

877.2 

 

1,021.3 

 

1,033.6 

 

1,055.0 

Daimler 

 

34.9 

 

65.7 

 

188.9 

 

307.1 

 

398.9 

Ford 

 

2,416.9 

 

2,920.9 

 

3,445.3 

 

4,029.2 

 

4,595.3 

General 

Motors 

 

884.4 

 

2,046.5 

 

2,896.8 

 

3,651.8 

 

4,348.3 

Honda 

 

45.5 

 

670.5 

 

949.5 

 

837.0 

 

1,108.5 

Hyundai 

 

284.7 

 

389.1 

 

590.8 

 

723.1 

 

813.5 

Kia 

 

39.1 

 

115.7

 

257.9 

 

404.2 

 

464.1 

Mazda 

 

180.3 

 

414.7

 

646.3

 

929.0

 

1,046.7 

Mitsubishi 

 

71.6 

 

80.3 

 

251.0 

 

258.7 

 

260.8 

Nissan 

 

789.1 

 

1,206.2 

 

1,945.5 

 

2,117.4 

 

2,412.6 

Porsche 

 

13.4 

 

18.0 

 

19.6 

 

22.3 

 

26.4 

Subaru 

 

77.7 

 

109.7 

 

373.0 

 

558.2 

 

574.6 

Suzuki 

 

18.3 

 

167.0 

 

219.2 

 

251.1 

 

262.6 

Tata 

 

9.0 

 

19.7 

 

28.8 

 

48.6 

 

75.6 

Toyota 

 

788.5 

 

903.3 

 

1,292.2 

 

1,581.4 

 

1,718.4 

Volkswagen 

 

129.7 

 

328.4

 

429.6 

 

529.1 

 

716.2 

Total/Average 

 

6,157.9 1 

 

10,431.

 

14,733.6 

 

17,563.5 

 

20,339.0 
350

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Inc ted Baseline 

Average C e (2007$) 

Light Trucks 

verage Cost per Vehicle 

Manufacturer 

Table VII-3a 

remental Costs or Fines over Adjus

ost per Vehicl

Preferred Alternative 

A

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

252 

 

272 

 

338 

 

402 

 

827 

Chrysler 

 

409 

 

527 

 

876 

 

931 

 

1,170 

Daimler 

 

98 

 

123 

 

155 

 

189 

 

260 

Ford 

 

465 

 

633 

 

673 

 

1,074 

 

1,174 

General

Motors

 

336 

 

513 

 

749 

 

807 

 

986 

Honda 

 

233 

 

217 

 

370 

 

457 

 

806 

Hyundai 

 

693 

 

630 

 

1,148 

 

1,136 

 

1,113 

Kia 

 

406 

 

467 

 

582 

 

780 

 

1,137 

Mazda 

 

144 

 

241 

 

250 

 

354 

 

480 

Mitsubishi 

 

39 

 

77 

 

553 

 

686 

 

1,371 

Nissan 

 

398 

 

489 

 

970 

 

1,026 

 

1,362 

Porsche 

 

44 

 

76 

 

109 

 

568 

 

640 

Subaru

 

1,036 

 

995 

 

1,016 

 

1,060 

 

1,049 

Suzuki 

 

66 

 

1,797 

 

1,744 

 

1,689 

 

1,732 

Tata 

 

66 

 

110 

 

137 

 

198 

 

690 

Toyota 

 

130 

 

150 

 

384 

 

499 

 

713 

Volkswagen 

 

44 

 

77 

 

552 

 

557 

 

606 

Total/Average 

 

322 

 

416 

 

621 

 

752 

 

961 

 
351

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

referred Alternative 

Manufacturer 

 MY MY MY MY MY 

Table VII-3b 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Total Incremental Costs in Millions (2007$) 

Light Trucks 

P

Total Incremental Costs 

2012 2013 2014 2015 2016 

BMW 

 

51.4 

 

49.9 

 

64.5 

 

70.5 

 

141.2 

Chrysler 

 

283.4 

 

313.0 

 

451.2 

 

442.5 

 

540.6 

Daimler 

 

10.6 

 

14.0 

 

21.2 

 

24.6 

 

32.8 

Ford 

 

396.3 

 

595.1 

 

649.5 

 

1,006.4 1 

 

1,069.

General 

Motors 

 

506.9 

 

787.9 

 

1,001.2 

 

1,113.6 

 

1,322.7 

Honda 

 

148.0 

 

146.7 

 

235.0 

 

256.3 

 

439.2 

Hyundai 

 

40.3 

 

63.9 

 

119.2 

 

107.4 

 

102.4 

Kia 

 

35.6 

 

48.0 

 

66.6 

 

92.4 

 

130.9 

Mazda 

 

8.8 

 

15.6 

 

17.0 

 

26.3 

 

34.7 

Mitsubishi 

 

1.9 

 

3.6 

 

29.2 

 

39.0 

 

75.8 

Nissan 

 

161.2 

 

191.4 

 

393.9 

 

401.8 

 

518.8 

Porsche 

 

0.6 

 

1.1 

 

1.8 

 

9.7 

 

10.7 

Subaru 

 

101.5 

 

89.5 

 

100.8 

 

123.0 

 

123.0 

Suzuki 

 

0.3 

 

29.8 

 

35.0 

 

34.7 

 

34.6 

Tata 

 

2.0 

 

3.7 

 

5.5 

 

8.7 

 

29.3 

Toyota 

 

115.6 

 

148.6 

 

420.4 

 

552.2 

 

767.5 

Volkswagen 

 

4.6 

 

10.9 

 

83.9 

 

71.2 

 

75.4 

Total/Average 8 .7 .8 .4 .7 

 

1,868.

 

2,512

 

3,695

 

4,380

 

5,448
352

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Light Trucks 

3% Annual Incr

Average Cost pe cle 

Manu 

Table VII-3c 

 

ease 

r Vehi

facturer 

 MY 

2012 

 MY 

2013 

 MY

2014 

 MY

2015 

 MY

2016

BMW 

 

96 

 

106 

 

179 

 

463 

 

867 

Chrysler 

 

- 

 

29 

 

242 

 

315 

 

477 

Daimler 

 

49 

 

66 

 

89 

 

112 

 

155 

Ford 

 

146 

 

295 

 

364 

 

725 

 

720 

General 

Motors 

 

(213) 

 

(52) 

 

94 

 

165 

 

292 

Honda 

 

135 

 

121 

 

204 

 

263 

 

452 

Hy undai

 

216 

 

227 

 

607 

 

620 

 

611 

Ki

 

a 

 

- 

 

19 

 

195 

 

323 

 

675 

Mazda 

 

47 

 

62 

 

71 

 

85 

 

215 

Mitsubishi 

 

- 

 

- 

 

154 

 

215 

 

478 

Ni

 

ssan 

 

67 

 

111 

 

356 

 

423 

 

632 

Porsche 

 

(28) 

 

11 

 

43 

 

486 

 

535 

Su u bar

 

385 

 

396 

 

377 

 

396 

 

397 

Suzuki 

 

(11) 

 

782 

 

735 

 

708 

 

709 

Tata 

 

(11) 

 

33 

 

66 

 

110 

 

575 

Toyota 15

 

 

 

21 

 

214 

 

281 

 

454 

Volkswagen 

 

(28) 

 

11 

 

514 

 

480 

 

507 

Total/Average 

 

1 

 

78 

 

234 

 

348 

 

484 
353

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-3d 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Total Incremental Costs in Millions (2007$) 

Light Trucks 

3% Annual Increase 

Total Incremental Costs 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

19.7 

 

19.5 

 

34.3 

 

81.4 

 

148.1 

Chrysler 

 

- 

 

17.4 

 

124.7 

 

149.5 

 

220.6 

Daimler 

 

5.3 

 

7.6 

 

12.2 

 

14.6 

 

19.6 

Ford 

 

124.5 

 

277.2 

 

351.1 

 

679.0 

 

655.9 

General 

Motors 

 

(321.9) 

 

(79.3) 

 

125.5 

 

227.3 

 

391.4 

Honda 

 

85.4 

 

82.0 

 

129.7 

 

147.5 

 

246.5 

Hyundai 

 

12.5 

 

23.1 

 

63.0 

 

58.6 

 

56.2 

Kia 

 

- 

 

1.9 

 

22.3 

 

38.2 

 

77.7 

Mazda 

 

2.9 

 

4.0 

 

4.8 

 

6.3 

 

15.5 

Mitsubishi 

 

- 

 

- 

 

8.1 

 

12.3 

 

26.4 

Nissan 

 

27.2 

 

43.4 

 

144.7 

 

165.8 

 

240.6 

Porsche 

 

(0.4) 

 

0.2 

 

0.7 

 

8.3 

 

8.9 

Subaru 

 

37.7 

 

35.6 

 

37.5 

 

45.9 

 

46.5 

Suzuki 

 

(0.1) 

 

12.9 

 

14.7 

 

14.5 

 

14.2 

Tata 

 

(0.3) 

 

1.1 

 

2.7 

 

4.8 

 

24.4 

Toyota 

 

13.7 

 

20.9 

 

234.8 

 

311.6 

 

488.8 

Volkswagen 

 

(2.9) 

 

1.6 

 

78.1 

 

61.4 

 

63.1 

Total/Average 

 

3.4 

 

469.1 

 

1,388.8 

 

2,027.0 

 

2,744.3 
354

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-3e 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Light Trucks 

4% Annual Increase 

Average Cost per Vehicle 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

103 

 

140 

 

218 

 

524 

 

939 

 

Chrysler 

 

130 

 

287 

 

610 

 

678 

 

867 

Daimler 

 

49 

 

94 

 

133 

 

173 

 

232 

Ford 

 

512 

 

796 

 

850 

 

1,262 

 

1,266 

General 

Motors 

 

- 

 

196 

 

373 

 

432 

 

609 

Honda 

 

226 

 

207 

 

407 

 

468 

 

695 

Hyundai 

 

554 

 

561 

 

1,201 

 

1,208 

 

1,182 

Kia 

 

- 

 

136 

 

331 

 

447 

 

798 

Mazda 

 

82 

 

179 

 

177 

 

305 

 

383 

 

Mitsubishi 

 

- 

 

33 

 

471 

 

532 

 

1,238 

Nissan 

 

315 

 

381 

 

741 

 

839 

 

1,153 

Porsche 

 

(17) 

 

39 

 

87 

 

546 

 

612 

Subaru 

 

946 

 

967 

 

981 

 

1,028 

 

1,017 

Suzuki 

 

- 

 

812 

 

764 

 

736 

 

993 

Tata 

 

- 

 

60 

 

116 

 

176 

 

663 

Toyota 

 

15 

 

30 

 

329 

 

465 

 

729 

Volkswagen 

 

(11) 

 

39 

 

530 

 

535 

 

579 

Total/Average 

 

166 

 

293 

 

506 

 

646 

 

830 
355

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-3f 

Estimated Incremental C ver Adjusted Baseline 

% Annual Increase 

Manufacturer 

 MY MY MY MY MY 

osts or Fines o

Total Incremental Costs in Millions (2007$) 

Light Trucks 

4

Total Incremental Costs 

2012 2013 2014 2015 2016 

BMW 

 

21.1 

 

25.7 

 

41.6 

 

92.0 

 

160.3 

Chrysler 

 

90.1 

 

170.8 

 

313.9 

 

322.4 

 

400.8 

Daimler 

 

5.3 

 

10.7 

 

18.2 

 

22.4 

 

29.3 

Ford 

 

436.1 

 

748.4 .0 .2 

 

820.6

 

1,182

 

1,153

General 

Motors 3 2 4 6 

 

- 

 

301.

 

498.

 

596.

 

816.

Honda 

 

143.3 

 

140.2 

 

258.2 

 

262.5 

 

378.7 

Hyundai 

 

32.2 

 

57.0 

 

124.7 

 

114.3 

 

108.7 

Kia 

 

- 

 

14.0 

 

37.9 

 

52.9 

 

91.8 

Mazda 

 

5.0 

 

11.6 

 

12.0 

 

22.6 

 

27.6 

Mitsubishi 

 

- 

 

1.5 

 

24.9 

 

30.2 

 

68.5 

Nissan 

 

127.6 

 

149.2 

 

301.0 

 

328.6 

 

439.0 

Porsche 

 

(0.2) 

 

0.6 

 

1.4 

 

9.4 

 

10.2 

Subaru 

 

92.7 

 

87.0 

 

97.4 

 

119.2 

 

119.2 

Suzuki 

 

- 

 

13.4 

 

15.3 

 

15.1 

 

19.8 

Tata 

 

- 

 

2.0 

 

4.7 

 

7.7 

 

28.2 

Toyota 8 4 

 

13.3 

 

29.5 

 

360.4 

 

514.

 

784.

Volkswagen 

 

(1.2) 

 

5.4 

 

80.6 

 

68.4 

 

72.0 

Total/Average 8.4 1.0 1.0 

 

965.2 

 

1,76

 

3,01

 

3,76

 

4,708.3 
356

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

% Annual Increase 

cle 

Manufacturer 

 MY MY MY MY MY 

Table VII-3g 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Light Trucks 

5

Average Cost per Vehi

2012 2013 2014 2015 2016 

BMW 

 

169 

 

209 

 

316 

 

591 

 

1,028 

Chrysler 

 

365 

 

559 

 

1,120 

 

1,216 

 

1,432 

Daimler 

 

60 

 

116 

 

177 

 

233 

 

309 

Ford 

 

1,207 

 

1,663 

 

1,882 

 

2,258 

 

2,225 

General 

Motors 

 

297 

 

628 

 

866 

 

968 

 

1,136 

Honda 

 

258 

 

234 

 

611 

 

750 

 

1,047 

Hyundai 

 

711 

 

685 

 

1,923 

 

1,909 

 

1,862 

Kia 

 

47 

 

293 

 

556 

 

782 

 

1,157 

Mazda 

 

248 

 

408 

 

419 

 

519 

 

768 

Mitsubishi 

 

- 

 

66 

 

1,037 

 

1,189 

 

1,556 

Nissan 

 

613 

 

723 

 

2,142 

 

2,148 

 

2,315 

Porsche 

 

- 

 

66 

 

131 

 

612 

 

695 

Subaru 

 

1,225 

 

1,220 

 

1,365 

 

1,374 

 

1,357 

Suzuki 

 

16 

 

1,998 

 

1,895 

 

1,837 

 

2,096 

Tata 

 

17 

 

94 

 

165 

 

242 

 

751 

Toyota 

 

63 

 

187 

 

594 

 

734 

 

991 

Volkswagen 

 

- 

 

66 

 

574 

 

596 

 

661 

Total/Average 

 

417 

 

633 

 

1,036 

 

1,186 

 

1,361 
357

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-3h 

Estimated Incremental C ver Adjusted Baseline 

% Annual Increase 

Manufacturer 

 MY MY MY MY MY 

osts or Fines o

Total Incremental Costs in Millions (2007$) 

Light Trucks 

5

Total Incremental Costs 

2012 2013 2014 2015 2016 

BMW 

 

34.5 

 

38.4 

 

60.4 

 

103.7 

 

175.4 

Chrysler 

 

252.9 

 

332.0 

 

576.5 

 

577.9 

 

662.0 

Daimler 

 

6.5 

 

13.3 

 

24.2 

 

30.3 

 

39.0 

Ford 

 

1,028.4 .5 .0 .4 .6 

 

1,563

 

1,817

 

2,115

 

2,026

General 

Motors 5 8.1 6.1 3.8 

 

448.7 

 

964.

 

1,15

 

1,33

 

1,52

Honda 

 

163.6 

 

158.3 

 

387.9 

 

420.4 

 

570.6 

Hyundai 

 

41.4 

 

69.5 

 

199.7 

 

180.6 

 

171.3 

Kia 

 

4.1 

 

30.1 

 

63.6 

 

92.5 

 

133.2 

Mazda 

 

15.1 

 

26.5 

 

28.4 

 

38.5 

 

55.4 

Mitsubishi 

 

- 

 

3.0 

 

54.8 

 

67.6 

 

86.1 

Nissan 

 

248.4 

 

283.0 

 

869.7 

 

841.4 

 

881.9 

Porsche 

 

- 

 

1.0 

 

2.1 

 

10.5 

 

11.6 

Subaru 

 

120.0 

 

109.8 

 

135.5 

 

159.4 

 

159.2 

Suzuki 

 

0.1 

 

33.1 

 

38.0 

 

37.7 

 

41.9 

Tata 

 

0.5 

 

3.2 

 

6.6 

 

10.6 

 

31.9 

Toyota 8 7 6.6 

 

55.8 

 

185.1 

 

650.

 

812.

 

1,06

Volkswagen 

 

- 

 

9.3 

 

87.3 

 

76.2 

 

82.2 

Total/Average 0.0 3.5 60.6 11.7 18.6 

 

2,42

 

3,82

 

6,1

 

6,9

 

7,7
358

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-3i 

Estimated Incremental ver Adjusted Baseline 

6% Annual Increase 

ehicle 

Manufacturer 

 MY MY MY MY MY 

Costs or Fines o

Average Cost per Vehicle (2007$) 

Light Trucks 

Average Cost per V

2012 2013 2014 2015 2016 

BMW 

 

242 

 

301 

 

411 

 

657 

 

1,115 

Chrysler 

 

382 

 

672 

 

1,412 

 

1,665 

 

2,062 

Daimler 

 

71 

 

139 

 

221 

 

294 

 

392 

Ford 

 

1,149 

 

1,662 

 

1,684 

 

2,596 

 

2,723 

General 

Motors 

 

308 

 

1,268 

 

1,655 

 

1,976 

 

2,163 

Honda 

 

786 

 

675 

 

1,368 

 

1,531 

 

2,032 

Hyundai 

 

1,517 

 

1,430 

 

2,398 

 

2,442 

 

2,434 

Kia 

 

123 

 

979 

 

1,179 

 

1,654 

 

1,990 

Mazda 

 

302 

 

622 

 

637 

 

785 

 

1,031 

Mitsubishi 

 

- 

 

99 

 

2,082 

 

2,130 

 

2,747 

Nissan 

 

989 

 

1,136 

 

2,525 

 

2,481 

 

3,194 

Porsche 

 

11 

 

93 

 

181 

 

678 

 

777 

Subaru 

 

1,254 

 

1,225 

 

1,466 

 

1,507 

 

1,562 

Suzuki 

 

33 

 

3,317 

 

2,987 

 

2,928 

 

3,152 

Tata 

 

33 

 

127 

 

215 

 

314 

 

844 

Toyota 

 

98 

 

338 

 

797 

 

952 

 

1,315 

Volkswagen 

 

17 

 

99 

 

618 

 

662 

 

744 

Total/Average 

 

516 

 

943 

 

1,394 

 

1,706 

 

2,007 
359

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

se 

Table VII-3j 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Total Incremental Costs in Millions (2007$) 

Light Trucks 

6% Annual Increa

Total Incremental Costs 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

49.4 

 

55.2 

 

78.6 

 

115.3 

 

190.4 

Chrysler 

 

264.3 

 

399.2 

 

726.9 

 

791.5 

 

952.8 

Daimler 

 

7.7 

 

15.9 

 

30.2 

 

38.1 

 

49.4 

Ford 

 

978.7 

 

1,562.8 

 

1,626.1 

 

2,431.8 

 

2,480.1 

General 

Motors 

 

465.3 

 

1,948.3 

 

2,212.4 

 

2,726.4 

 

2,901.6 

Honda 

 

498.7 

 

456.5 

 

867.9 

 

858.4 

 

1,107.9 

Hyundai 

 

88.2 

 

145.1 

 

249.0 

 

231.1 

 

223.8 

Kia 

 

10.8 

 

100.6 

 

134.9 

 

195.8 

 

229.1 

Mazda 

 

18.4 

 

40.3 

 

43.1 

 

58.3 

 

74.4 

Mitsubishi 

 

- 

 

4.6 

 

110.0 

 

121.2 

 

151.9 

Nissan 

 

400.6 

 

444.8 

 

1,025.0 

 

972.0 

 

1,216.4 

Porsche 

 

0.1 

 

1.4 

 

2.9 

 

11.6 

 

13.0 

Subaru 

 

122.8 

 

110.1 

 

145.5 

 

174.9 

 

183.2 

Suzuki 

 

0.2 

 

54.9 

 

59.9 

 

60.2 

 

63.0 

Tata 

 

1.0 

 

4.3 

 

8.6 

 

13.7 

 

35.9 

Toyota 

 

86.8 

 

335.0 

 

873.3 

 

1,054.0 

 

1,415.6 

Volkswagen 

 

1.7 

 

14.0 

 

94.0 

 

84.6 

 

92.5 

Total/Average 

 

2,994.7 

 

5,693.1 

 

8,288.4 

 

9,938.9 

 

11,381.2 
360

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

verage Cost per Vehicle 

Manufacturer 

Table VII-3k 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Light Trucks 

7% Annual Increase 

A

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

303 

 

376 

 

509 

 

728 

 

1,203 

Chrysler 

 

393 

 

1,603 

 

2,145 

 

2,379 

 

3,014 

Daimler 

 

87 

 

167 

 

265 

 

354 

 

474 

Ford 

 

1,250 

 

1,694 

 

1,657 

 

2,911 

 

3,263 

General 

Motors

 

319 

 

1,682 

 

2,247 

 

2,868 

 

3,030 

Honda 

 

940 

 

819 

 

1,774 

 

1,943 

 

2,479 

Hyundai 

 

1,601 

 

1,515 

 

2,433 

 

2,514 

 

2,558 

Kia 

 

151 

 

1,007 

 

1,289 

 

2,449 

 

3,050 

Mazda 

 

985 

 

1,984 

 

1,940 

 

2,027 

 

2,382 

Mitsubishi 

 

17 

 

132 

 

2,078 

 

2,262 

 

3,101 

Nissan 

 

1,003 

 

1,172 

 

2,297 

 

2,415 

 

3,195 

Porsche 

 

27 

 

126 

 

225 

 

744 

 

871 

Subaru 

 

1,260 

 

1,230 

 

1,579 

 

1,624 

 

1,740 

Suzuki 

 

49 

 

3,442 

 

2,889 

 

2,882 

 

3,146 

Tata 

 

50 

 

160 

 

264 

 

391 

 

943 

Toyota 

 

164 

 

572 

 

1,221 

 

1,359 

 

1,703 

Volkswagen 

 

28 

 

127 

 

662 

 

722 

 

826 

Total/Average 

 

575 1,222 1,716 2,181 2,549 

 
361

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimate aseline 

Total Incremen llions (2007$) 

Light Trucks 

otal Incremental Costs 

rer 

Table VII-3l 

d Incremental Costs or Fines over Adjusted B

tal Costs in Mi

7% Annual Increase 

T

Manufactu

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

61.8 

 

69.1 

 

97.2 

 

127.9 

 

205.5 

Chrysler 

 

271.9 

 

952.1 

 

1,104.1

 

1,130.6

 

1,392.6

Daimler 

 

9.4 

 

19.1 

 

36.2 

 

46.0 

 

59.9 

Ford 

 

1,064.4 

 

1,592.7 

 

1,599.7 

 

2,726.6 

 

2,972.3 

General 

Motors

 

482.0 

 

2,583.3 

 

3,003.5 

 

3,957.2 

 

4,064.4 

Honda 9 4 8 

 

596.9 

 

554.1 

 

1,125.

 

1,089.

 

1,351.

Hyundai 

 

93.1 

 

153.8 

 

252.7 

 

237.9 

 

235.3 

Kia 

 

13.2 

 

103.4 

 

147.4 

 

290.0 

 

351.1 

Mazda 

 

59.9 

 

128.5 

 

131.5 

 

150.4 

 

171.9 

Mitsubishi 

 

0.8 

 

6.1 

 

109.8 

 

128.7 

 

171.6 

Nissan 

 

406.4 

 

459.0 

 

932.5 

 

946.1 

 

1,217.0 

Porsche 

 

0.4 

 

1.8 

 

3.6 

 

12.8 

 

14.5 

Subaru 

 

123.4 

 

110.7 

 

156.7 

 

188.5 

 

204.1 

Suzuki 

 

0.2 

 

57.0 

 

58.0 

 

59.2 

 

62.8 

Tata 

 

1.5 

 

5.4 

 

10.6 

 

17.1 

 

40.1 

Toyota 

 

145.5 

 

566.3 

 

1,338.3 

 

1,504.4 

 

1,833.8

Volkswagen 

 

 .7 3 .7 

 

2.9 

 

17.9

 

100

 

92.

 

102

Total/Average 3,333.6 7,380.3 10,208.4 12,705.0 14,451.3 

 
362

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

 MY MY MY MY 

2015 

 MY 

2016 

Table VII-3m 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Light Trucks 

Max Net Benefits 

Average Cost per Vehicle 

Manufacturer 2012 2013 2014 

BMW 

 

314 

 

383 

 

491 

 

567 

 

976 

Chrysler 

 

459 

 

1,482 

 

2,154 

 

2,371 

 

2,512 

Daimler 

 

153 

 

216 

 

293 

 

343 

 

392 

Ford 

 

1,386 

 

1,794 

 

1,738 

 

2,500 

 

2,566 

General 

Motors 

 

380 

 

1,356 

 

1,703 

 

2,021 

 

2,095 

Honda 1,043 908 1,883 2,013 2,159 

 

Hyundai 

 

1,183 

 

1,118 

 

2,177 

 

2,183 

 

2,131 

Kia 

 

461 

 

964 

 

1,309 

 

2,437 

 

2,692 

Mazda 

 

855 

 

1,399 

 

1,321 

 

1,407 

 

1,505 

Mitsubishi 

 

94 

 

187 

 

2,100 

 

2,251 

 

2,802 

Nissan 

 

1,117 

 

1,229 

 

2,391 

 

2,443 

 

2,925 

Porsche 

 

94 175 252 728 783 

Subaru 1,366 1,311 1,556 1,594 1,621 

 

Suzuki 

 

127 

 

2,328 

 

2,212 

 

2,151 

 

2,265 

Tata 121 214 297 374 850 

 

Toyota 936 1,208 

 

1,498 

 

1,613 

 

1,711 

Volkswagen 94 176 

 

690 

 

711 

 

744 

 

Total/Average 

 

761 

 

1,249 

 

1,665 

 

1,948 

 

2,082 
363

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

emental Costs in Millions (2007$) 

Light Trucks 

Table VII-3n 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Total Incr

Max Net Benefits 

Total Incremental Costs 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

64.2 

 

70.3 

 

93.8 

 

99.5 

 

166.6 

Chrysler 317.6 880.7 1,109.0 1,126.8 

 

1,160.9 

 

Daimler 

 

16.6 

 

24.7 

 

40.0 

 

44.6 

 

49.4 

Ford 

 

1,180.8 

 

1,686.7 

 

1,678.3 

 

2,341.5 

 

2,336.6 

General 

Motors 

 

573.4 

 

2,082.6 

 

2,276.5 

 

2,789.0 

 

2,810.9 

Honda 662.1 614.2 1,194.7 1,128.8 1,177.0 

 

Hyundai 

 

68.8 

 

113.5 

 

226.1 

 

206.5 

 

196.0 

Kia 40.4 99.0 149.7 288.5 

 

309.8 

 

Mazda 

 

51.9 

 

90.6 

 

89.5 

 

104.4 

 

108.6 

Mitsubishi 

 

4.5 

 

8.6 

 

111.0 

 

128.1 

 

155.0 

Nissan 

 

452.4 

 

481.1 

 

970.6 

 

957.1 

 

1,114.0 

Porsche 

 

1.2 

 

2.6 

 

4.0 

 

12.5 

 

13.0 

Subaru 

 

133.8 

 

117.9 

 

154.5 

 

185.0 

 

190.2 

Suzuki 

 

0.6 

 

38.5 

 

44.4 

 

44.2 

 

45.2 

Tata 

 

3.6 

 

7.2 

 

12.0 

 

16.3 

 

36.1 

Toyota 

 

829.9 

 

1,196.7 

 

1,641.8 

 

1,785.8 

 

1,842.4 

Volkswagen 

 

9.8 

 

24.9 

 

104.8 

 

90.9 

 

92.5 

Total/Average 4,411.6 7,539.9 9,900.7 11,349.5 11,804.4 

 
364

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

 MY MY MY MY MY 

Table VII-3o 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Average Cost per Vehicle (2007$) 

Light Trucks 

Total Cost = Total Benefit 

Average Cost per Vehicle 

Manufacturer 2012 2013 2014 2015 2016 

BMW 

 

320 

 

399 

 

530 

 

600 

 

1,020 

Chrysler 

 

464 

 

1,504 

 

2,184 

 

2,405 

 

2,713 

Daimler 

 

153 

 

233 

 

326 

 

371 

 

430 

Ford 

 

1,386 

 

1,811 

 

1,766 

 

2,645 

 

2,942 

General 

Motors 

 

380 

 

1,583

 

 2,035 2,558 2,597 

Honda 1,052 927 1,939 2,073 2,390 

 

Hyundai 

 

1,825 

 

1,620 

 

2,670 

 

2,682 

 

2,649 

Kia 

 

466 

 

980 

 

1,342 

 

2,464 

 

2,692 

Mazda 

 

2,121 

 

3,292 

 

2,849 

 

2,964 

 

3,035 

Mitsubishi 

 

99 

 

209 2,139 2,279 3,052 

Nissan 1,062 1,197 2,389 2,436 2,929 

 

Porsche 

 

99 

 

197 

 

291 

 

755 

 

821 

Subaru 1,366 1,311 1,638 

 

1,697 

 

1,741 

 

Suzuki 127 3,242 2,947 

 

2,885 

 

2,995 

Tata 127 237 336 407 894 

 

Toyota 

 

942 

 

1,208 

 

1,605 

 

1,689 

 

1,855 

Volkswagen 

 

99 

 

193 

 

723 

 

739 

 

782 

Total/Average 780 1,344 1,806 2,157 2,366 

 
365

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-3p 

Estimated Incremental Costs or Fines over Adjusted Baseline 

Total Incremental Costs in Millions (2007$) 

Light Trucks 

Total Cost = Total Benefit 

Total Incremental Costs 

Manufacturer 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

BMW 

 

65.3 

 

73.3 

 

101.1 

 

105.3 

 

174.1 

Chrysler 321.4 893.7 1,124.2 1,143.2 1,253.5 

 

Daimler 

 

16.6 

 

26.6 

 

44.5 

 

48.1 

 

54.3 

Ford 

 

1,180.8 

 

1,702.2 

 

1,704.8 

 

2,478.0 

 

2,679.8 

General 

Motors 

 

573.4 

 

2,431.0 

 

2,720.6 

 

3,528.8 

 

3,484.3 

Honda 

 

667.7 

 

627.1 

 

1,230.7 

 

1,162.4 

 

1,303.1 

Hyundai 

 

106.1 

 

164.5 

 

277.3 

 

253.7 

 

243.7 

Kia 

 

40.9 

 

100.7 

 

153.5 

 

291.7 

 

309.8 

Mazda 128.9 213.2 193.1 220.0 219.0 

 

Mitsubishi 

 

4.8 

 

9.7 

 

113.0 

 

129.6 

 

168.8 

Nissan 

 

430.2 

 

468.8 

 

970.2 

 

954.2 

 

1,115.4 

Porsche 

 

1.3 

 

2.9 

 

4.7 

 

12.9 

 

13.7 

Subaru 133.8 117.9 162.6 197.0 204.2 

 

Suzuki 

 

0.6 

 

53.7 

 

59.1 

 

59.3 

 

59.8 

Tata 

 

3.8 

 

8.0 

 

13.5 

 

17.8 

 

38.0 

Toyota 

 

834.7 

 

1,196.7 

 

1,759.3 

 

1,869.6 

 

1,996.7 

Volkswagen 

 

10.4 

 

27.2 

 

109.9 

 

94.5 

 

97.3 

Total/Average 

 

4,520.5 

 

8,117.4 

 

10,742.1 

 

12,566.3 

 

13,415.5 
366

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

direct costs for producing or acquiring each technology to improve fuel 

onomy, depending on the complexity of the technology and the time frame over which costs 

cern is whether achieving the fuel economy improvements required by 

lternative CAFE standards would require manufacturers to compromise the performance, 

e 

compliance with stricter 

AFE standards. While exact dollar values of these attributes to buyers are extremely difficult 

n 

e 

 for 

 technology costs that include costs for 

the accompanying changes in vehicle design that are necessary to maintain performance, 

Financial Impacts of Raising CAFE Standards 

the 

m of 

HTSA believes 

s the 

 

Technology Costs 

Table V-5 above provides the technology cost estimates used in this analysis. The technology 

cost estimates are intended to represent manufacturers’ direct costs for high-volume production

of vehicles with these technologies and sufficient experience with their application so that all 

cost reductions due to “learning curve” effects have been fully realized. Costs are then modified 

by applying indirect cost multipliers ranging from 1.11 to 1.64 to the estimates of vehicle 

manufacturers’ 

ec

are estimated. Chapter V also discusses technology cost issues in much more detail. 

Potential opportunity costs of improved fuel economy 

An important con

a

carrying capacity, safety, or comfort of their vehicles. If it did so, the resulting sacrifice in the

value of these attributes to vehicle buyers would represent an additional cost of achieving th

required improvements in fuel economy, and thus of manufacturers’ 

C

to infer from vehicle purchase prices, it is nevertheless clear that changes in these attributes ca

affect the utility that vehicles provide to their owners, and thus their value to potential buyers. 

The agency has approached this potential problem by developing cost estimates for fuel 

economy-improving technologies that include any additional manufacturing costs that would be 

necessary to maintain the performance, comfort, capacity, or safety of any vehicle to which those 

technologies are applied. Theoretically, opportunity costs could also include any foregone 

opportunities to enhance these products for consumers. However, estimating values for foregon

opportunities is an even tougher task. So, the agency followed the precedent established by the 

National Academy of Sciences (NAS) in its 2002 analysis of the costs and benefits of improving 

fuel economy by raising CAFE standards.200 The NAS study estimated “constant performance 

and utility” costs for fuel economy technologies, and the agency has used these as the basis

developing the technology costs it employed in analyzing manufacturer’s costs for complying 

with alternative standards. 

NHTSA fully acknowledges the difficulty of estimating

capacity, and utility. A fuller discussion of this issue is presented in Chapter VIII. 

The automobile industry is currently experiencing substantial economic hardship, even in 

absence of new fuel economy standards. Many major firms have announced a steady strea

plant closings, layoffs, and employment of new employees at reduced wages. N

these hardships have much to do with the condition of the national economy and perhap

price of gasoline, and little, if anything, to do with the stringency of CAFE standards for the 

 

200 National Academy of Sciences, Costs and Effectiveness of Increasing Corporate Average Fuel Economy 

Standards, 2002. 
367

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

y 

ial 

exibility mechanisms in setting fuel economy standards. 

 policy 

f the 

ered 

n the other hand, the agency is mindful that CAFE standards do affect the relative 

t 

ubstantial financial assistance provided to the automobile 

industry by the U.S. Government. In addition to the large sums provided to Chrysler and GM, 

 the 

ehicle 

current or recent model years. We believe that given the scale of the recent decline in industr

sales, and the restrictiveness of private credit markets, that near-term developments will be 

compelled by the industry’s immediate financial situation, rather than by the long-term financ

consequences of this rulemaking. 

Market forces are already requiring manufacturers to improve the fuel economy of their vehicles, 

as shown both by changes in product plans reported to NHTSA, and by automaker public 

announcements. The improvements in fleet fuel economy required by this rule are consistent 

with the pressure induced by changing consumer preferences. 

The various compliance flexibility mechanisms permitted by EISA, including flexible and 

alternative fuel vehicles, banking, averaging, and trading of fuel economy credits will also 

reduce compliance costs to some degree. By statute, NHTSA is not permitted to consider the 

benefits of fl

On May 19, 2009, President Obama announced a National Fuel Efficiency Policy.201 This

reflected a consensus among stakeholders (including 14 automobile companies) on desirable and 

achievable fuel economy standards. We believe that this consensus reflects the view o

industry that given current economic conditions, and in the light of Federal assistance proff

via various means, that the standards finalized here are economically practicable. 

 O

competitiveness of different vehicle manufacturers, and recognizes that standards more stringen

than those promulgated here could have a more detrimental effect. 

 NHTSA’s central problem is to determine what new standards might be economically 

practicable within the MY 2012-2016 time frame, given the state of both the domestic and the 

international auto industries. The complexity of an economic practicability determination has 

been materially increased by the s

Congress has appropriated $7.5 billion (to support a maximum of $25 billion in loans under 

Section 136 of EISA to support the development of advanced technology vehicles and 

components in the United States.202 On June 23, 2009, the Department of Energy announced

first three loans under this program: $5.9 billion for Ford for advanced vehicle manufacturing, 

$1.3 billion for Nissan for vehicle and battery manufacturing, and $0.5 billion for electric v

start-up Tesla Motors.203 

 

201 The White House, “President Obama Announces National Fuel Efficiency Policy,” May 19, 2009. Available at

http://www.whitehouse.gov/the_press_office/President-Obama-Announces-National-Fuel-Efficiency-Policy/. (last 

s in Section 136 of EISA. This language is amended and funds 

0-343). See also the 

dvanced Technologies 

09).

accessed March 4, 2010). 

202202 The authorizing language for this provision i

are appropriated in the Emergency Economic Stabilization Act of 2008 (H.R. 1424, Pub.L. 11

DOE Advanced Technology Vehicle Manufacturing Loan Program website: http://www.atvmloan.energy.gov/ (last

accessed February 6, 2009). 

203 US Department of Energy, “Obama Administration Awards First Three Auto Loans for A

to Ford Motor Company, Nissan Motors and Tesla Motors,” June 23, 2009. Available at: 

http://www.atvmloan.energy.gov/ (last accessed July 21, 20
368

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

“within the financial capability 

f the industry, but not so stringent as to threaten substantial economic hardship for the 

rimary ways in which the agency seeks to ensure that its standards are within the 

nancial capability of the industry is to attempt to ensure that manufacturers have sufficient lead 

s 

 each manufacturer based on a 3 percent 

iscount rate for future fuel savings. 

ile 

l 

igher fuel economy standards are expected to increase the price of passenger cars and light 

s not 

here is a broad consensus in the economic literature that the price elasticity for demand for 

Given the foregoing, therefore, the agency has decided that in this exceptional situation, 

economic practicability must be determined based on whether the expenditures needed to 

achieve compliance with the final MY 2012-2016 standards are 

o

industry,” no matter who contributes the funds. We have set the MY 2012-2016 CAFE 

standards so that they are both technologically and economically feasible. In principle, most 

vehicles meeting the standard will provide social benefits to the public at large and private 

benefits to automobile owners greater than their extra cost. 

One of the p

fi

time to modify their manufacturing plans to comply with the final standards in the model years 

covered by them. Employing appropriate assumptions about lead time in our analysis helps to 

avoid applying technologies before they are ready to be applied, or when their benefits are 

insufficient to justify their costs. It also helps avoid basing standards on the assumption that 

technologies could be applied more rapidly than practically achievable by manufacturers. 

NHTSA considers these matters in its analysis of issues including refresh and redesign 

schedules, phase-in caps, and learning rates. 

NHTSA further considers the sales and employment impacts of the final standards on individual 

manufacturers as part of its efforts to determine whether the standards are economically 

practicable. The sales analysis looks at a purchasing decision from the eyes of a knowledgeable

and rational consumer, comparing the estimated cost increase versus the payback in fuel saving

over 5 years (the average new vehicle loan) for each manufacturer. This relationship depends on

the cost-effectiveness of technologies available to

d

The agency does not have the capability to predict the capital investment needs of the automob

industry to install fuel economy technologies, nor the capability to determine the level of capita

investments available to specific manufacturers in the future. 

The Impact of Higher Prices on Sales and Employment 

H

trucks. The potential impact of higher vehicle prices on sales was examined on an industry wide 

basis for passenger cars and light trucks separately. The analysis conducted for this rule doe

have the precision to examine effects on individual manufacturers or different vehicle classes. 

T

automobiles is approximately –1.0.204,205,206 Thus, every one percent increase in the price of the 

 

204 Kleit, A.N. (1990). “The Effect of Annual Changes in Automobile Fuel Economy Standards,” Journal of Regulat

Economics, vol. 2, pp 151-172. 205 Bordley, R. (1994). “An Overlapping Choice Set Model of Automotive Price Elasticities,” Transportation Research B, vol 

28B, no 6, pp 401-408. 

206 McCarthy , P.S. (1996). “Market Price and Income Elasticities of New Vehicle Demands,” The Review of 

ory 

Economics and Statistics, vol. LXXVII, no. 3, pp. 543-547. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

costs 

ail price increase 

eeded to cover the fuel economy technology investments will manufacturers be able to pass on 

nd upon how consumers value the fuel 

conomy improvements. Consumer valuation of fuel economy improvements often depends 

on the price of gasoline, which has recently been very volatile. To the extent that we have 

ccurately predicted the price of gasoline and consumers reactions, and manufacturers can pass 

n all of the costs to consumers, then the sales and employment impact analyses are reasonable. 

 manufacturers only increase retail prices to the extent that consumers value these fuel 

conomy improvements, then there would be no impact on sales. 

ales losses are predicted to occur only if consumers fail to value fuel economy improvements at 

ast as much as they pay in higher prices. If manufacturers are unable to raise prices beyond the 

level of consumer's valuation of fuel savings, then manufacturer's profit levels would fall but 

there would be no impact on sales. Likewise, if fuel prices rise beyond levels used in this 

analysis, consumer's valuation of improved fuel economy could increase to match or exceed their 

initial investment, resulting in no impact or even an increase in sales levels. 

 

To estimate the average value consumers place on fuel savings at the time of purchase, we 

assume as a starting point that the average purchaser considers the fuel savings they would 

receive over a 5 year timeframe. We chose 5 years because this is the average length of time of a 

financing agreement.208 The present values of these savings were calculated using a 3 percent 

discount rate. We used a fuel price forecast (see Table VIII-3) that included taxes, because this 

is what consumers must pay. Fuel savings were calculated over the first 5 years and discounted 

back to a present value. The National Automobile Dealers Association (NADA) agreed with 

several of the agency’s assumptions, saying the National Program proposal reasonably assumes 

 

vehicle would reduce sales by one percent. Elasticity estimates assume no perceived change in 

the quality of the product. However, in this case, vehicle price increases result from adding 

technologies that improve fuel economy. If consumers do not value improved fuel economy at 

all, and consider nothing but the increase in price in their purchase decisions, then the estimated

impact on sales from price elasticity could be applied directly. However, we believe that 

consumers do value improved fuel economy, because they reduce the operating cost of the 

vehicles. How much consumers value fuel economy is an ongoing debate. We know that 

different consumers value different aspects of their vehicle purchase, and we are trying to get an

estimate of how average consumers value fuel economy, but we do not have a reliable consumer

survey on this issue. We also believe that consumers consider other factors that affect their 

and have included these in the analysis. Thus, this analysis makes one set of assumption, but 

many different assumptions and estimates of the sales impact could be made. 

One issue that significantly affects this sales analysis is: How much of the ret

n

to consumers? The estimates reported below assume that manufacturers will be able to pass all 

of their costs to improve fuel economy on to consumers. However, the ability of manufacturers 

to pass the compliance costs on to consumers will depe

207 e

up

a

o

If

e

S

le

207 Gron, Ann and Swenson, Deborah, 2000, “Cost Pass-Through in the U.S. Automobile Market”, The Review of 

Economics and Statistics, 82: 316-324. 

208 National average financing terms for automobile loans are available from the Board of Governors of the Federal 

Reserve System G.19 “Consumer Finance” release. See http://www.federalreserve.gov/releases/g19/ (last accessed 

March 4, 2010). 
370

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

uyers will value any fuel savings associated with the purchase of a new motor vehicle over a 5-

yr period, rather than over a vehicle's full en at high fuel prices, consumers who 

view fuel economy as an important essed to make the case for 

buying a more fuel efficient new vehicle pital costs associated with doing so 

cannot be recouped in short order. Of course, for purposes of calculation payback, real-world 

purchaser finance costs, opport costs add ma nce all should be 

accounted for. 

 

The agency believes that su ay er o r e 5 year horizon 

when contemplating the h l ge e ctors into the 

calculation to represent a e o ff mers’ buying 

considerations. 

First, consumers m e to pay at e time purchasing the 

vehicle. We took s axes i y sta d w d t p n by state to 

determine a nationa hted-average sales tax of 5.5 percent. 

Second, we considered insurance costs over the year period. More expensive vehicles will 

require more expensive collision and comprehensive (e.g., theft) car insurance. The increase in 

insurance costs is estimated from the average va e of collision plus comprehensive insurance as 

a proportion of average new vehicle price. comprehensive insurance is the portion 

of insurance costs that depend on vehicle urance Information Institute209 provides 

the average value of collision plus c 06 as $448. The average value 

of a new passenger car in 2006, according partment of Energy, was $22,651.210 

Using sales volumes from Ward motiv earbo 0 20 sales and the MY 

2008 base vehicle a erage pric et d a ge ger d an average light 

truck price. The av se r n u m as $26,201 and for 

all light trucks was $2 l h e s xact price, the 

ratio of light truck price s ca w e r trations for 

passenger cars and light s f 6 w pli t l ht vehicle price.211 

The result is an average f $ 21 6 ge prices and 

estimated sales volumes e ca e e y m ow a percent 

increase in price affects e re al

Dividing the insura st by ag of ve e rtion of 

comprehensive plus ion insurance as 1.86% of the price of a vehicle. If we assume that this 

premium is proport l to the icl i en 1 ent of the new 

 

b

useful life. Ev

purchase criteria will be hard-pr

 if the up-front ca

unity , and itional intena costs 

 con mers m consid several ther facto s over th

 purc ase of a new vehic e. The a ncy add d these fa

how n increas in techn logy costs might a ect consu

ight co

ales t

nsid r the sales taxes they have th of 

n 2007 b te an eighte hem by opulatio

l weig

5 

lu

 Collision plus 

value. The Ins

omprehensive insurance in 20

 to the U.S. De

’s Auto

es, we d

e Y

ermine

ok 20

n avera

8 for MY

passen

07

v car an

erage ba

$29,678 (

 price fo

007 do

 all passe

lars). W

ger cars

ile this m

sing this

thod doe

ethod w

not give an e

s to pa senger r prices as appli d and on- oad regis

 truck or 200 ere ap ed to ge an overa l new lig

price or light vehicles of 24,033 2

 for 200 . Avera

are n eded be use pric lasticit is an esti ate of h

the p rcent dec ase in s es. 

nce co the aver e price a new hicle giv s the propo

 collis

iona new veh e price, t repres ts about .86 perc

209 Insurance Information Institute, 2008, “Average Expen ures for Auto Insurance By State, 2005-2006,” 

available at http://www.iii.org/media/facts/statsbyissue/au / (last accessed March 4, 2010). 

 U.S. Department of Energy, 2008, “Average Price of a New Car, 1970-2006,” available at 

ttp://www1.eere.energy.gov/vehiclesandfuels/facts/2008_fotw520.html (last accessed March 4, 2010). 

211 The base price does not include the more expensive lines of a model or purchased optional equipment; nor does 

it count discounts given. Thus, it is not an average light truck purchase transaction price, but a price that we can 

track. 

212 $29,678/$26,201 = 1.1327 * $22,651 = $25,657 average price for light trucks. In 2006, passenger cars were 54% 

of the on road fleet and light trucks were 46% of the on road fleet, resulting in an average light vehicle price for 

2006 of $24,033. 

dit

to 210

h
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ehicle price and insurance is paid each year for the five year period we are considering for 

payback. Discounting that stream of insurance costs back to present value indicates that the 

present value of the component of insurance cost at vary with vehicle price is equal to 8.5 

percent of the vehicle’s price at a 3 percen . 

Third, we considered that oans to finance their 

purchase. The average new vehi oan is 5 years at a 6 pe t rat 213 t these terms the 

average person taking a loan wi 16 t m r the icle he 5 years than a 

consumer paying cash fo e v t o ase. sc the additional 3.2 

percent (16 percent o g e ear discount 

rate215 results in a disco pr al . n o king a loan. 

Multiplying that by the 7 r t n th e sumer would pay 

10.2 percent more than t t fo n percent discount 

rate. 

Fourth, we considered th e le c years and 

expressed this as a tage of the ew vehicle price. In other words, if the price of the vehicle 

increases due to fue nomy gi res e e go up 

proportionately. Th age resale ice of a vehicle after 5 years is about 35%216 of the 

original purchase p Disc e l v c u percent discount 

rate (35 percent * .8755) gives an effective resid alue at new of 30.6 percent. 

We add these four factors together. At a 3 percent discount rate, the consumer considers she 

ould get 30.6 percent back upon resale in 5 years, but will pay 5.5 percent more for taxes, 8.5 

ercent more in insurance, and 10.2 percent more for loans, results in a 6.48 percent return on the 

 technology (30.6 percent – 5.5 percent - 8.5 percent – 10.2 

ice per vehicle is multiplied by 0.9352 (1 – 0.0648) before 

nt 

et 

ring that to the $22,651 

,202 

v

s th

t discount rate

70 percent of new vehicle purchasers take out l

cle l

ll pay

ehicle

for 

percen

he tim

rcen

ir veh

214 Di

e. A

over t

unting

ore fo

r th purch

 / 5 years)

 a

per year 

t e 

ver the 5

f

years usin

o 

 a 3 perc nt mid-y

unted esent v ue of 14 87 perce t higher f r those ta

0 pe cent that ake a loa , means at the av rage con

he re ail price r loans the consumer discou ted at a 3 

e residual valu (or resa value) of the vehi le after 5

percen

l eco

 n

 technolo es, the ale valu of the v hicle will 

e aver

rice. 

 pr

ounting th residua alue ba k 5 years sing a 3

ual v

c

p

increase in price for fuel economy

percent). Thus, the increase in pr

subtracting the fuel savings to determine the overall net consumer valuation of the increase of 

costs on his purchase decision. 

A sample calculation for passenger cars under the Preferred Alternative at a 3 percent discou

rate in MY 2012 is an estimated retail price increase of $505 which is multiplied by 0.9352 to g

a residual price increase of $472. The estimated fuel savings over the 5 years of $310 at a 3 

percent discount rate results in a net cost to consumers of $162. Compa

average price of a passenger car is a 0.71 percent price increase. Passenger car sales were 

estimated to be about 9,123,000 passenger cars for MY 2012. With a price elasticity of –1.0, a 

0.71 percent increase in net cost to consumers could result in an estimated loss in sales of 65

passenger cars. 

 

213 New car loan rates in 2007 average about 7.8 percent at commercial banks and 4.5 percent at auto finan

companies, so their average is close to 7 percent. 

214 Based on www.bankrate.com auto loan calculator for a 5 year loan at 6 percent. 215 For a 3 percent discount rate, the summation of 3.2 percent x 0.9853 in year one, 3.2 x 0.9566 in year two, 3.2 x 

0.9288 in year three, 3.2 x 0.9017 in year 4, and 3.2 x 0.8755 in year five. 

216 216 Consumer Reports, August 2008,“What That Car Really Costs to Own,” available at

http://www.consumerreports.org/cro/cars/pricing/what-that-car-really-costs-to-own-4-08/overview/what-that-ca

ce 

rreally-costs-to-own-ov.htm (last accessed March 4, 2010). 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

nd 

les 

which the sales volumes of different 

vehicle models might change in response to fuel economy increases, financial outlays for 

dditional technology, and increases in civil penalties that could all result from increased CAFE 

standards. 

There are studies that as a result of an 

increase in price, eve at consumers will 

purcha e of their improved fuel economy. In general, changes in prices 

or othe ew vehicles market will also have consequences for the used 

ehicle et. Specif t r ew ve nd to 

crease prices of used c ting them in 

service for slightly lon r, the age savings over the 

lifetimes of the new vehicles will exceed the i e , prompting an increase in 

f new vehicles d odel year le affects. A onsequence, prices for 

ehicles are also l e, leadin creases in th ate at which used 

es are retired fro crapped”) d with new ls. In turn, this will 

ate the effects o s on fuel co n and GHG ; at the same 

otal criteria poll ns from th icle fleet m decrease, as newer, 

ehicle ed vehicles. 

General Motors (OAR-472-6953.1) commented that the NHTSA usually does a manufacturer by 

acturer analysis so far agen only done an y-wide analysis. 

GM stated that the agencies must complete their analysis of sales and employment impacts of 

ividua rs before standards. In response, NHTSA does 

not believe that estimating sales impacts by manufacturer is required, even if the agency may 

ve done it in the past. With all the uncertainty regarding consumer valuation of fuel economy 

rovements and consumer surplus, estimating sales impacts is an inexact science, and the 

gency has even less confidence at this time in estimating sales by manufacturer. 

R-472-3651.1) commented on the results of two reports that estimated an 

increase in sales. The first, ”CAFE and the U.S. Auto Industry Revisited,” Citi Investment 

Research and Planning, analyzed two regulatory scenarios, specifically, “CAFE 2020,” 

equivalent to reaching a combined 35 mpg in 2020, and National Pavley, equivalent to reaching 

on sales, costs, and profits 

Tables VII-4 a, b, and c show the estimated impact on sales for passenger cars, light trucks, and 

combined, respectively. The Preferred Alternative has the highest combined passenger car a

light truck sales increases predicted using this methodology. 

Note that there is no feedback loop between this sales analysis and the Volpe model. These sa

estimates are not used to determine additional or less mileage traveled or fuel consumed. The

Volpe model does not attempt to estimate the extent to 

a

 estimate that people may hold onto their vehicles longer 

rything else being held equal. This analysis estimates th

se more vehicles becaus

r characteristics of the n

v mark

in

ically, any action tha

vehicles, and in turn

ger. Howeve

aises prices for n

ause owners of exis

ncy estimates that the v

ncrease in their pric s

hicles will also te

 vehicles to keep

alue of fuel 

sales o

used v

uring most m

ikely to declin

s that the ru

g to slight in

s a c

e r

vehicl

accentu

m service (“s

f the standard

and replace

nsumptio

 mode

emissions

time, t

lower-polluting v

utant emissio

s replace us

e entire veh ay also

manuf of sales, but cies have industr

standards on ind l manufacture setting final 

ha

imp

a

Two commenters agreed with the agency analysis that sales would go up. The Investor Network

on Climate Risk (OAR-0472-7243.1) and the New Jersey Department (NHTSA-2009-0059-

0073) agreed with the findings that project a positive impact on vehicle sales due to reduced fuel 

costs outweighing the costs of meeting the new emissions and fuel economy standards. 

Walter McManus (OA

a combined 35 mpg in 2015. The analysis estimated the impacts 

relative to a baseline forecast, and concluded that the National Program will help “Detroit 3” 
373

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

el 

anufacturing plants’ worth of jobs, and that consumers will 

save money too despite pump prices of $2.50/gallon, because fuel savings will more than offset 

vehicle price increases. The second report, ”Fixing Detroit: How Far, How Fast, How Fuel 

Efficient” was described as analyzing three different fuel economy increases--30% (to 35 mpg), 

40% (to 37.7 mpg), and 50% (to 40.4 mpg). The model used in the report estimated the impact 

of improving fuel economy on vehicle costs, vehicle prices, and consumer demand. McManus 

stated that the report found that the Detroit 3 would always be better off increasing fuel 

economy, and that the more they improved, the better off they would be, because consumers 

value fuel economy more than it costs manufacturers to add technology. McManus stated that a 

30% increase in fuel economy, as with the National Program, is estimated to increase vehicle 

costs by $1,715, while the fuel savings value to consumers will be $2,578. 

In response, the agency notes that these analyses appear to come to similar conclusions as 

NHTSA’s, that fuel savings should be valued by consumers at levels higher than price increases, 

and that if that occurs, vehicle sales would increase. 

 

 

profits, which will go up by $3 billion per year based on the relative value consumers put on fu

costs compared to vehicle price, the future price of fuel, and the combined direct and indirect 

costs incurred to improve fuel economy. McManus further stated that the report also found that 

the new standards will save two m
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-4a 

Potent Sales 

 MY MY MY MY MY 

016 

ial Impact on 

Passenger Cars 

2012 2013 2014 2015 2

Preferred -65,202 46,801 103,422 168,334 227,039

3% -9,302 54,3 ,838 131,092 196,193 69 91

4% -18,694 54,899 105,781 162,650 239,959

5% -23,655 57,280 123,764 181,100 253,045

6% -66,461 28,276 69,191 1 1 09,779 77,630

7% -82 - ,835 2,203 19,695 53,158 90,246

Max 

Net -81,930 946 42,573 89,321 147,282

TC =

TB - -1 93,933 6,361 16,698 57,137 100,283

T IPotential Impact on Sales 

Light rucks 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

able VI 4b 

T

Preferred 48,561 106,658 139,893 171,920 213,868

3% 11,021 44,784 72,918 111,536 137,306

4% 7,287 52,946 93,466 136,400 175,282

5% -21,608 28,302 62,836 121,314 169,990

6% -27,282 16,460 55,058 102,421 139,073

7% -27,556 -7,222 40,806 59,225 81,159

Max 

Net -36,600 18,512 57,310 90,736 124,057

TC = 

TB -38,972 7,428 48,414 74,060 102,287
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-4c 

Potential Impact on Sales 

Passenger Cars and Light Trucks Combined 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

Preferred -16,641 153,459 243,315 340,255 440,907

3% 1,719 99,153 164,757 242,628 333,499

4% -11,407 107,845 199,247 299,050 415,241

5% -45,262 85,582 186,601 302,414 423,036

6% -93,743 44,735 124,249 212,200 316,703

7% 

-

110,391 -9,425 60,501 112,383 171,405

Max 

Net 

-

118,530 19,458 99,883 180,056 271,339

TC = 

TB 

-

132,905 -8,933 65,112 131,196 202,570

Potential Impact on Employment 

There are three potential areas of employment that fuel economy standards could impact. The 

first is the hiring of additional engineers by automobile companies and their suppliers to do 

research and development and testing on new technologies to determine their capabilities, 

durability, platform introduction, etc. The agency does not anticipate a huge number of 

incremental jobs in the engineering field. Often people would be diverted from one area to 

another and the incremental number of jobs might be a few thousand. 

The second area is the impact that new technologies would have on the production line. Again, 

we do not anticipate a large number of incremental workers, as for the most part you are 

replacing one engine with another or one transmission with another. In some instances the 

technology is more complex, requiring more parts and there would be a small increase in the 

number of production employees, but we do not anticipate a large change. 

The third area is the potential impact that sales gains or losses could have on production 

employment. This area is potentially much more sensitive to change than the first two areas 

discussed above. In order to get an estimate of potential job losses per sales loss, we examined 

recent U.S. employment (original equipment manufacturers and suppliers) and U.S. production. 

Total employment in 2000 reached a peak in the Motor Vehicle and Parts Manufacturing sector 

of the economy averaging 1,313,600 workers. Since then there has been a steady decline to 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ployment in 2008 was 

about two-thirds of the 2000 level and in the first six months of 2009 employment has been 

w 

ion 

1,096,900 in 2006 and more rapid decreases in 2007, 2008, and 2009. Em

around 680,000, averaging about one-half of the peak in the year 2000. Table VII-5 shows ho

many vehicles are produced by the average worker in the industry. Averaging the informat

shown for 2000-2008, the average U.S. domestic employee produces 11.3 vehicles (the same 

number as in 2008). Thus, one could assume that projected sales loss divided by 11.3 would 

give an estimate of the potential employment loss. 

Table VII-5 

U.S. Light Duty Vehicle Production and Employment 

 

 U.S. Light Vehicle 

Production 

Motor Vehicle 

Vehicle and Parts 

U.S. Employment217

Production per 

Employee 

2000 12,773,714 1,313,600 9.7 

2002 13,568,385 1,151,300 11.8 

2004 13,527,309 1,112,700 12.2 

2006 12,855,845 1,096,900 11.7 

2008 9,870,473 876,300 11.3 

Total/Average 62,595,726 5,550,800 

 

Combining MY 2012-2016, we estimate that the Preferred Alternative will result in a small net 

increase in sales (65,480), and thus in employment (5,795). At this time, the agency considers 

these effects to occur in the short to medium term (meaning up to 5 years). Over the next few 

years, consumers can elect to defer vehicle purchases by continuing to operate existing vehicles. 

Eventually, however, the rising maintenance costs for aging vehicles may make replacements 

look more attractive. 

 

217 U.S. employment data is from the Bureau of Labor Statistics, available at

http://data.bls.gov/PDQ/servlet/SurveyOutputServlet?series_id=CES3133600101&data_tool=XGtable (last accessed 

March 4, 2010). 
377

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

g existing vehicles in service for somewhat longer. In this 

ase, the possibility exists that there may be permanent sales losses, compared with a situation in 

However, vehicle owners may also react to persistently higher vehicle costs by permanently 

owning fewer vehicles, and keepin

c

which vehicle prices are lower. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VII-6 

Impact on Auto Industry Employment by Alternative 

Passenger Cars and Light Trucks Combined 

(Jobs) 

 MY 

2012 

 MY 

2013 

 MY 

2014 

 MY 

2015 

 MY 

2016 

Preferred -1,473 13,580 21,532 30,111 39,018

3% 152 8,775 14,580 21,471 29,513

4% -1,009 9,544 17,632 26,465 36,747

5% -4,006 7,574 16,513 26,762 37,437

6% -8,296 3,959 10,996 18,779 28,027

7% -9,769 -834 5,354 9,945 15,169

Max 

Net -10,489 1,722 8,839 15,934 24,012

TC = 

TB -11,762 -791 5,762 11,610 17,927

Scrappage Rates 

The effect of this rule on the use and scrappage of older vehicles will be related to its effects on 

new vehicle prices, the fuel efficiency of new vehicle models, and the total sales of new 

vehicles. If the value of fuel savings resulting from improved fuel efficiency to the typical 

replacement by new models – to accelerate slightly, thus accentuating the anticipated effect of 

th rule on fleet-wide fuel consumption and CO emissions. However, if potential buyers value 

he 

hich 

potential buyer of a new vehicle outweighs the average increase in new models’ prices, sales of 

new vehicles will rise, while scrappage rates of used vehicles will increase slightly. This will 

cause the “turnover” of the vehicle fleet – that is, the retirement of used vehicles and their 

e 2

future fuel savings resulting from the increased fuel efficiency of new models at less than t

increase in their average selling price, sales of new vehicles will decline, as will the rate at w

used vehicles are retired from service. This effect will slow the replacement of used vehicles by

new models, and thus partly offset the anticipated effects of the final rules on fuel use and 

emissions. 

Because the agencies are uncertain about how the value of projected fuel savings from the final 

rules to potential buyers will compare to their estimates of increases in new vehicle prices, we 
DELIBERATIVE DOCUMENT – DO NOT RELEASE 

379

have not attempted to estimate explicitly the effects of the rule on scrappage of older vehicles 

and the turnover of the vehicle fleet. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

III. BENEFITS FROM IMPROVED FUEL ECONOMY 

Improving new vehicles’ fuel efficiency enefits to their buyers and users by 

reducing fuel consumption an lifetimes, stimulating 

increased vehicle use through the fuel ect, and increasing vehicles’ driving 

range so that they require less frequent refueling. At the same time, the reduction in fuel use 

s from highe y ces fits . 

onomy by lowe e cost of e ic extern hat resu U.S. p m 

umption and cludi cing the f petroleum, lowering ential co

 disruption in ow of oil s, and po reducing l outlay ure 

orted oil supplies d cushion econo st their po interrup n. 

el co ion also e econ of en ental e es 

m fu ction an cluding g the impacts on hum h from

issions of crite ollutants educing onomi from tial 

ges in the glo imate caus eenhou emission

ese benefits are offset by crease in e that res om add icle use 

el econom ound effec ell as by costs from increase gestion, 

es, and noise d by incre ehicle us ould partial et by an

es in the utility new vehicles provide to th yers (and quent ow

nufacturers cha ther vehicl ibutes as p their strat to comp er 

economy req e ss, the tot omic be rom req higher 

nomy are likel e substanti d the agen s attempte antify f these 

components caref

’s analys ternative i e standard ld apply to MY 20

6 passenger c light tru ates th be m ado re 

stringent CAFE standards separately for each mo year over its lifespan in the U.S. vehicle 

fleet, extending from the initial year when a model year is offered for sale through the year when 

nearly all vehicles from that model year have been retired from service. Each category of 

benefits resulting from increased fuel economy is measured by comparing the future values of 

fuel consumption and its associated economic impacts under alternative increases in CAFE 

standards – and the corresponding improvements in fuel economy – to their value under the 

baseline alternative, which would extend current CAFE standards to apply to future model years, 

thus resulting in only minimal improvement in fuel economy. 

Because these benefits occur throughout the lifetimes of vehicles whose fuel economy increases 

in response to higher CAFE standards, their projected values during each future year of their 

respective lifetimes must be discounted to their present values as of the time each model year is 

produced and sold in order to facilitate comparison to the costs incurred by vehicle 

manufacturers for improving fuel economy.218 Thus the selection of an appropriate discount rate 

 

V

provides direct b

d fuel costs throughout those vehicles’

economy rebound eff

that result requiring r fuel econom also produ wider bene to the U.S

ec ring th conom alities t lt from etroleu

cons imports, in ng redu price o the pot sts 

from the fl import ssibly federa s to sec

imp an

nsumpt

 the U.S. 

lowers th

my again

omic costs 

tential 

vironm

tio

Reducing fu xternaliti

resulting fro el produ d use, in reducin an healt

em ria air p , and r future ec c damages poten

chan bal cl ed by gr se gas s. 

Th partly the in fuel us ults fr ed veh due 

to the fu y reb t, as w added the d con

crash cause ased v e. They w also be

 subse

ly offs y 

loss that 

nge o

eir bu

art of

ners) if 

ma ly with high

fuel 

e attr egies

uirements. Nev rthele al econ nefits f uiring fuel 

eco y to b al, an cy ha d to qu each o

ully. 

NHTSA is of al ncreases in th CAFE s that wou 12-

201 ars and cks estim e economic nefits fro pting mo

del

218 Discounting to the year when each model year was produced allows future economic benefits from improving 

each model year’s fuel economy to be compared to added production costs for making those vehicles more fuelefficient, which are assumed to be incurred at the time those vehicles are manufactured. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

is also an important issue in the agency’s fits from requiring cars and light trucks 

to achieve higher fuel economy

This chapter first discusses the forecasts, assump ons, and parameter values that NHTSA uses to 

analyze m l t g the 

magnit hese benefits tio inclu detai scussi the fu onomy 

reboun d the agen ssumption about its magnitu Next, hapter sses the 

method cy employs stima direc fits to cle bu resulti om 

higher my, as we e nat f potential welfar es to rs from nges in 

other v tics ight pan ovem el economy apter 

then de es e use tima der s to ec – and 

in the c ductions in g house missi he glo conom at re om 

lower f tion and co mption also de es how increa exter osts 

resultin m added vehicle are cal ted. 

Finally presents irical e ates of value o of t benefit at the 

agency ould resu m est ing a e C stand or MY 16 

passen d light truc hese e s a esented ica its, as t 

undisco nomic valu f future efits, a iscoun o their ent val sing 

alterna unt rates. 

A. Inputs for Analysis of Economic I cts

 analysis of bene

. 

ti

 benefits from i proved fue economy. Because i plays a critical role in determinin

ude of t , this sec n also des a led di on of el ec

d effect an cy’s a de. the c discu

s the agen

ono

 to e te the t bene vehi yers ng fr

fuel ec

ehicle 

ll as th

 that 

ure o

 acco

e loss

ents 

buye cha

characteris The

tails the procedur

m

 that ar

m

d to es

y r

te broa

 imp in fu

benefit

. ch

the U.S. onomy

ase of re reen gas e ons, t bal e y – th sult fr

uel produc nsu . It scrib the ses in nal c

g fro use cula

, the chapter

s w

 emp stim the f each hese s th

 estimate lt fro ablish lternativ AFE

phys

ards f 2012-20

ger cars an

unted eco

ks. T

es o

stimate

 ben

re pr

nd d

 in 

ted t

l un

 pres

otal

ues u

tive disco

 Basic mpa

The ma conom alues o se ben and co om in ed fue nomy 

are infl by a number cast les, ter and ptio se 

include vel of vehicle s during o affe high rds, the 

relationship between increases in these vehicles’ easured fuel efficiency and their actual 

on-road fuel efficiency, assumptions about the lifetimes and usage of future model-year vehicles, 

the magnitude of the fuel economy rebound effect, future fuel prices and taxes, the values of 

economic externalities resulting from petroleum consumption and imports, the economic values 

of environmental externalities resulting from fuel production, distribution, and use, the value of 

increased refueling range, and the discount rate applied to future benefits and costs. The 

following sections discuss the specific forecasts, parameter values, and assumptions NHTSA has 

employed to estimate benefits and costs from alternative CAFE standards that would require 

increases in the fuel economy of passenger cars and light trucks produced during model years 

2012 through 2016. 

Projected Sales of MY 2012-2016 Passenger Cars and Light Trucks 

A critical variable affecting the total economic benefits from requiring improvements in 

passenger car and light truck fuel economy is the number of vehicles likely to be produced under 

stricter CAFE standards. Projections of total passenger car and light truck sales for future years 

(see Table VIII-1a and VIII-1b) were obtained from the Energy Information Administration’s 

(EIA) Annual Energy Outlook 2010 Early Release (AEO 2010), a standard government 

reference for projections of energy production and consumption in different sectors of the U.S. 

gnitudes and e ic v f the efits sts fr creas l eco

uenced

the le

 of fore

ales 

 variab

each m

 parame

el year 

values,

cted by

 assum

er CAFE 

ns. The

d standa

EPA-m
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

economy.219 In using these forecasts, NHTSA made the simplifying assumption that projected 

 from 2012 through 2016 represented the 

. 

 light truck sales for the 

 passenger car and light 

sts 

 in 

PCA) 

ctured primarily for use in the transportation 

f not more than 10 individuals.” Thus there are two general groups of automobiles that qualify 

rily” 

y 

n-passenger automobiles in subsections (a) and (b), respectively, of 

9 CFR Part 523.5. 

n 

sales of cars and light trucks during each calendar year

likely production volumes for the corresponding model year. The agency did not attempt to 

establish the exact correspondence between projected sales during individual calendar years and 

production volumes for specific model years. 

NHTSA estimated production volumes of passenger cars and light trucks for individual 

manufacturers by first calculating their respective shares of total production for each model year

These shares were calculated by dividing each manufacturer’s planned car or light truck 

production volumes by the sum of planned production volumes reported by all manufacturers.220 

Next, the resulting estimates of individual manufacturer’s shares of total car and light truck 

production during a model year were applied to forecast total car and

corresponding calendar year from AEO 2010. This produces estimates of

truck production by each manufacturer during each model year from 2012 through 2016. 

NHTSA employs this process in order to develop production forecasts that are consistent with 

both the production plans that individual manufacturers reported to the agency, and the foreca

of total sales of new cars and light trucks reported by the Energy Information Administration

AEO 2010.

221 

Changes in Vehicle Classification 

Passenger automobiles were defined in the Energy Policy and Conservation Act of 2007 (E

as “any automobile (other than an automobile capable of off-highway operation) which the 

Secretary [i.e., NHTSA] decides by rule is manufa

o

under EPCA as non-passenger automobiles or light trucks: (1) those defined by NHTSA in its 

regulations as other than passenger automobiles because they were not manufactured “prima

for transporting up to ten individuals; and (2) those expressly excluded from the passenger 

category by statute due to their capability for off-highway operation, regardless of whether the

were manufactured primarily for passenger transportation. NHTSA’s classification rule directly

tracks those two groups of no

4

In the final rule for model year 2011, NHTSA tightened the coverage of its regulatory definitio

of “light truck” to ensure that 2 wheel drive (2WD) versions of an SUV are not classified as light 

trucks under Part 523.5(b) simply because that same SUV model is also available in a 4WD 

 

219 U.S. Department of Energy, Energy Information Administration, Annual Energy Outlook 2009, Updated 

Reference Case (April 2009), Supplemental Table 57, 

http://www.eia.doe.gov/oiaf/aeo/supplement/stimulus/arra/excel/suptab_57.xls (last accessed July 24, 2 009). 0 These product plans are submitted to NHTSA in response to the agency’s request for information from vehicle 

manufacturers, and include responses to very detailed questions about vehicle model characteristics that influence 

NHTSA’s CAFE compliance 

22

fuel economy. The baseline market forecast mix of products (make/model, engines, transmissions, etc.) that 

NHTSA has used in its analysis is based on the confidential product plan information manufacturers submit to the

agency. 

221 For manufacturers that did not submit plans, planned production volumes for model years 2012-2016 were 

assumed to be the same as their model year 2008 production volumes as recorded in 

database. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

s 

djusted Sales Forecasts 

 

 reflect the reasonable assumption that while sales of cars or light trucks produced 

uring a model year will be distributed over more than one calendar year, production and sales 

 

version.222 In addition, 2WD SUVs may not be properly classified as light trucks simply 

because a manufacturer asserts that their base form has no back seat and thus would “provide 

greater cargo-carrying than passenger-carrying volume” according to Part 523.5(a)(4). No 

change in the regulatory definition of a light truck is necessary to implement this clarification. It 

results in the re-classification of an average of 1,400,000 2WD SUVs from light trucks to 

passenger cars in each of the five model years that would be covered by the alternative standard

considered in this rulemaking. 

A

Tables VIII-1a and VIII-1b report forecast production volumes of passenger cars and light trucks 

for each manufacturer during model years 2012 through 2016. The figures reported in these 

tables reflect the AEO 2009 Reference Case forecasts of passenger car and light truck sales for 

2012-2016, the planned production volumes for model years 2012-2106 reported to NHTSA by 

individual manufacturers, and the reclassification of certain light truck models as passenger cars.

The tables also

d

for each model year will ultimately be equal. 

222 In order to be properly classifiable as a light truck under Part 523, a 2WD SUV must either be over 6,000 lbs 

GVWR and meet 4 out of 5 ground clearance characteristics to make it off-highway capable under Part 523.5(b), or 

meet one of the functional characteristics under Part 523.5(a) (e.g., greater cargo carrying capacity than passenger 

carrying capacity). In other words, a 2WD vehicle of 6,000 lbs GVWR or less, even if it has a sufficient number of 

clearance characteristics, cannot be considered off-highway capable. 
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Sales Projections – Passenger Cars 

cle

Manufacturer MY 12 Y 20 2 20 MY 2016 

Table VIII-1a 

(1,000s of vehi s) 

MY 2011 20 M 13 MY 014 MY 15 

BMW 231.0 2 293.9 70 89.6 3 .0 411.6 422.8 

Chrysler 326.3 4 426.4 11 09.4 4 .3 392.5 399.7 

Daimler 213.8 2 202.5 44 11.6 2 .5 263.7 270.9 

Ford 1,344.4 1,4 .1 ,485. 68 1 7 1,567.7 1,542. 1,559.2 4 

General Motors 1,248.9 1, 0 ,544. 586. 1 9 1,452.5 1,487. 1,514.4 2 

Honda 850.8 9 ,064.8 08 06.0 1 1, 7.0 912.4 930.3 

Hyundai 382.2 376.3 395.5 395.5 511.2 518.4 

Kia 305.7 299.6 326.6 427.2 538.7 548.0 

Mazda 292.6 283.1 329.9 378.3 413.3 420.5 

Mitsubishi 104.2 110.3 104.5 88.1 82.3 82.7

Nissan 611.6 824.0 831.6 854.1 925.4 946.5

Porsche 25.1 41.1 43.3 34.0 32.4 33.3

Subaru 169.7 183.5 175.2 184.5 204.7 206.9 

Suzuki 49.5 72.3 81.8 90.6 100.6 103.0 

Tata 23.2 36.4 50.5 49.3 63.7 65.5 

Toyota 1,355.6 1,591.0 1,941.4 2,078.9 2,176.5 2,226.4 

Volkswagen 388.1 434.4 498.6 517.9 567.7 583.2 

Total 7,922.7 9,122.7 9,797.1 10,231.3 10,626.4 10,831.7 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VIII-1b 

Sales Projections – Light Trucks 

(1,000s of vehicles) 

Manufacturer MY 2011 MY 2012 MY 2013 MY 2014 MY 2015 MY 2016

BMW 203 204 184 191 176 171 

Chrysler 737 692 594 515 475 462 

Daimler 97 108 115 136 130 126 

Ford 792 852 940 966 937 911 

General Motors 1,347 1,511 1,536 1,337 1,380 1,342 

Honda 585 635 677 635 561 545 

Hyundai 46 58 102 104 95 92 

Kia 88 88 103 114 118 115 

Mazda 58 61 65 68 74 72 

Mitsubishi 45 48 46 53 57 55 

Nissan 331 405 392 406 392 381 

Porsche 13 13 15 16 17 17 

Subaru 105 98 90 99 116 117 

Suzuki 7 5 17 20 21 20 

Tata 31 30 34 40 44 42 

Toyota 888 887 990 1,096 1,107 1,077 

Volkswagen 83 105 141 152 128 124 

Total 5,458 5,798 6,038 5,947 5,826 5,669 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Accounting for the Fuel Ec

The fuel economy rebound e of fuel savings expected to result from an 

increase in vehicle fuel econ e required by the adoption of higher 

CAFE standards – that is off . The increase in vehicle use occurs 

because higher fuel econom iving, typically the largest single 

ent of t tary c and vehicle owners respond to this 

 in op ts y lowe e ma o h

f onomy e number of miles vehicles are driven each 

d over t imes el economy, this additional driving 

s some e fuel gs th w w

rd ma to improve fuel economy. 

und ef ina ect – es t ti e

cte sult fr fuel economy that is offset by additional 

vehicle use. This measure a y which annual vehicle use increases 

e fuel c riving onse el economy. 

ers typ su la l cl

to l ec mile xpr s a e 

percentage (rather than a dec the usual convention for expressing elasticity). 

e the fuel cost of driv el price per gallon divided by fuel 

 in miles per gallon y this measure declines and vehicle use 

 res incr

de oun rminant of the act

 result from ado rds, and thus an important parameter 

ng NHTSA’s evaluati for future model years. Research on the 

magnitude of the rebound ef se dates to the early 1980s, and almost 

ously concludes that bound effect occurs when vehicle fuel 

 improves.223 

omm ch has b aly e r

icle con ices, and other determinants of household travel 

 the respon fuel economy. Several other studies have 

on econometric analy .S. data on vehicle use, fuel economy, fuel prices, and 

ariables to identify th cle use to changes in fleet-wide average 

omy. Two recent s ation in vehicle ownership and use, fuel 

 fuel economy am an ex e period in order to 

e res o r f

 

onomy Rebound Effect 

ffect refers to the fraction

omy – particularly an increas

set by additional vehicle use

y reduces the fuel cost of dr

compon

reduction

use, improved 

he mone

erating cos

uel ec

ost of operating a vehicle,

by driving slightly more. B

 leads to an increase in th

ring th rginal c st of ve icle 

year an

consume

CAFE standa

heir lifet

 fuel, so th

s require

. Even with their higher fu

rebound effect reduces the net 

nufacturers

 savin at result hen ne

The rebo

savings expe

fect – orig

d to re

lly termed the “take back” eff

om an increase in vehicle

 express he frac on of fu l 

lso equals the percentage b

 each mile declines in resp

re the rebound effect by the e

onomy itself or fuel cost per 

imal number,

when th

Research

with respect 

ost of d

ically mea

either fue

to higher fu

sticity of tota

 driven, e

 or averag

essed a

e vehi

positiv

e use 

Becaus

economy

increases in

The magnitu

are likely to

affecti

ing each mile is equal to fu

, it is easy to understand wh

eased fuel economy. 

d effect is an important dete

pting stricter CAFE standa

on of alternative standards

ponse to

 of the reb ual fuel savings that 

fect in light-duty vehicle u

 a statistically significant re

 to estimating its magnitude 

sumption, fuel pr

se of vehicle use to higher

sis of annual U

unanim

efficiency

The most c

data on veh

demand to isolate

relied 

on approa

 use, fuel

een to an ze hous hold su vey 

other v

fuel econ

prices, and

measure th

 

e response of average vehi

tudies analyzed yearly vari

ong individual states over

icle use to changing fuel econ

 

tended tim

ponse of veh my and othe actors.224 

 long-run reb 223 Some studies estimate that the ound effect is significantly larger than the immediate response to 

 fuel effi lthou ent period required for the rebound effect to reach 

 magni is l te fo fu s sio

sultin er to future m

these t U plying appropriate estimation procedures to data 

consisting of each year’s average values of these variables for the separate states. 

increased

its long-run

reductions re

224 In effect, 

ciency. A

tude vary, th

g from strict

studies trea

gh their estimates of the adjustm

ong-run effect is most appropria

standards that would apply 

.S. states as a data “panel” by ap

r evaluating the

odel years. 

el saving and emis ns 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

t distinction am fect is whether they assume that the 

stant, or is likely e in response to the absolute levels of fuel costs, 

al income, or househo st studies using aggregate annual data for 

e U.S. assume a constant r ect, although some of these studies test whether the effect 

using 

ning 

t 

tes 

h 

is 

ks, 

 

An importan

effect is con

person

ong studies of the rebound ef

 to vary over tim

ld vehicle ownership. Mo

th ebound eff

varies in response to changes in retail fuel prices or average fuel economy. Many studies 

household survey data estimate significantly diff rent rebound effects for households ow e

varying numbers of vehicles and thus imply that its average value will change over time as 

vehicle ownership patterns evolve. 

However, these studies arrive at differing conclusions about whether the rebound effect is larger 

among households that own more vehicles, and thus provide conflicting estimates of changes in

its magnitude as the distribution of households by vehicle ownership levels changes. One recent 

study using state-level data concludes that the rebound effect varies directly in response to 

changes in personal income and the degree of urbanization of U.S. cities, as well as in response

to fuel costs. 

In order to arrive at an estimate of the rebound effect for use in assessing the fuel savings, 

emissions reductions, and other impacts of alternative standards, NHTSA reviewed 22 studies of

the rebound effect conducted from 1983 through 2005. The agency then conducted a detailed 

analysis of the 66 separate estimates of the long-run rebound effect reported in these studies, 

which is summarized in Table VIII-2 below.225 As the table indicates, these 66 estimates of the 

long-run rebound effect range from as low as 7 percent to as high as 75 percent, with a mean 

value of 23 percent. Estimates of the rebound effect reported in the 17 published studies show 

the same range, but a slightly higher mean value (24 percent). Although this result is not shown 

in the table, approximately two-thirds of all the estimates reviewed and of all published estimates 

fall in the range of 10-30 percent. 

We are aware of two potential issues involved in these estimates. One, the estimates of total 

annual car and truck VMT are developed by the states and submitted to FHWA. Each state uses 

its own definition of a car and a truck. For example, some states classify minivans as cars and 

some as trucks. Thus, there are known inconsistencies with these estimates when evaluated 

separately for cars and trucks. Also, total gasoline consumption can be reasonably estimated 

from excise tax receipts, but separate estimates for cars and trucks are not available. We are no

aware of the precise methodology used to develop the distinct on-road fuel economy estima

for cars and trucks developed by FHWA. We do not believe that they are based on direct 

measurements from substantial numbers of vehicles, as no such test programs were found by

EPA during its fuel economy labeling rule in 2006. Also, the year-to-year consistency for bot

car and truck fuel economy implies some methodology other than direct measurement. For th

reason, NHTSA and EPA are not using distinct on-road fuel economy gaps for cars and truc

but one common value of 20 percent for both vehicle classes for purposes of estimating the fuel 

savings of the standards. 

225 In some cases, NHTSA derived estimates of the overall rebound effect from more detailed results reported in the 

ers 

computed a weighted average of the reported values using the 

studies. For example, where studies estimated different rebound effects for households owning different numb

of vehicles but did not report an overall value, we 

reported distribution of households among vehicle ownership categories. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Range Distribution 

Table VIII-2 

Summary of Previous Rebound Effect Estimates 

Category of Estimates Number of 

Studies 

Number of 

Estimates Low High Median Mean Std. Dev.

All Estimates 22 66 7% 75% 22% 23% 14% 

Published Estimates 17 50 7% 75% 22% 24% 14% 

U.S. Time-Series Data 7 34 7% 45% 14% 18% 9% 

Household Survey Data 13 23 9% 75% 31% 31% 16% 

Pooled U.S. State Data 2 9 8% 58% 22% 25% 14% 

Constant Rebound Effect (1) 15 37 7% 75% 20% 23% 16% 

Variable Rebound Effect (1) 10 29 10% 45% 23% 23% 10% 

(1) Three studies estimated both constant and variable rebound effects. 

As Table VIII-2 illustrates, the type of data used and authors’ assumption about wheth th er e 

e last five years of that period (1997-2001).226 These authors 

estimating and testing several econometric models of the relationship between vehicle milesrebound effect varies over time have important effects on its estimated magnitude. The 34 

estimates derived from analysis of U.S. annual time-series data have a mean of 18 percent, while 

the mean of 23 estimates based on household survey data is 31 percent, and the mean of 9 

estimates based on pooled state data (25 percent) is slightly above that of the entire sample. The 

average mean is 23 percent for both the 37 estimates that assume a constant rebound effect and 

the 29 estimates reported in studies that allow the rebound effect to vary in response to fuel 

prices, vehicle ownership, or household income. 

Recent studies provide some evidence that the rebound effect has been declining over time, and 

it may decline further over the immediate future if income rises faster than gasoline prices. This 

result seems plausible, because the responsiveness of vehicle use to variation in fuel costs would 

be expected to decline as they account for a smaller proportion of the total monetary cost of 

driving, which has been the case until very recently. At the same time, rising personal incomes 

would be expected to reduce the sensitivity of vehicle use to fuel costs as the time component of 

driving costs – which is likely to be related to income levels – accounts for a larger fraction of

the total cost of automobile travel. The widely-cited study by Small and Van Dender estimated

that the long-run rebound effect averaged 22 percent over the period from 1966-2001, but 

declined to 11 percent over th

subsequently reported that the long-run rebound effect appears to have dropped further to 6 

percent over the period from 2000-2004.227 

To provide additional insight into the rebound effect for the purposes of this rulemaking, 

NHTSA developed several new estimates of its magnitude. These estimates were developed by

 

226 Small, K. and K. Van Dender, 2007a. “Fuel Efficiency and Motor Vehicle Travel: The Declining Rebound 

Effect”, The Energy Journal, vol. 28, no. 1, pp. 25-51. 7 mall, K. and K. Van Dender, 2007b. "Long Run Trends in Transport Demand, Fuel Price Elasticities and 22 S

Implications of the Oil Outlook for Transport Policy," OECD/ITF Joint Transport Research Centre Discussion 

Papers 2007/16, OECD, International Transport Forum. 
389

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

he 

 latter’s effect on fuel cost per mile. 

HTSA’s analysis used national aggregate data on light-duty vehicle travel covering the period 

om 1950 through 2006. Several different approaches were used to estimate the effect of fuel 

efficiency on car and light truck use, and etric procedures were employed to 

ac

estimated value of the rebound effe A’s analysis are presented in 

able VIII-3. For each model that was estimated, the table reports the average value of the 

rebound effect over the period from 1950-2006, as well as its value during the final year of that 

period. In addition, the table reports the average projected values of rebound effect between 

2010 and 2030, which were developed using forecasts of personal income, fuel prices, and fuel 

efficiency from EIA’s Annual Energy Outlook 2009 Reference Case. 

The results of NHTSA’s analysis are broadly consistent with the findings from previous research 

summarized above. The historical average long-run rebound effect is estimated to range from 

16-30%, and comparing these estimates to its calculated values for 2006 (which range from 8-

14%) supports the finding from recent research that it is declining in magnitude. The forecast 

values of the rebound effect shown in the table, which range from 4-16%, also suggest that this 

decline is likely to continue through 2030. 

Table VIII-3 

ound Effect 

traveled and factors that influence it, including household income, fuel prices, vehicle fuel 

efficiency, road supply, the number of vehicles in use, vehicle prices, and other factors. As t

studies by Small and Van Dender emphasize, it is important to account for the effect of fuel 

prices on vehicle buyers’ demand for fuel efficiency when attempting to estimate the rebound

effect. Failing to incorporate the response of fuel efficiency to fuel prices is likely to cause the 

rebound effect to be overestimated, because the changes in fuel economy resulting from variation

in fuel prices partly offset the

N

fr

various econom

count for its relationship to fuel prices and control for the effect of this relationship on the 

ct. The results from NHTS

T

Summary of NHTSA Estimates of the Long-Run Reb

Using U.S. Annual Data for 1950-2006 

Rebound Effects: 

Model VMT 

Measure 

Variables Included in VMT 

Equation 

Estimation 

Technique 1950-

2006 2006 2010-2030* 

Small-Van 

Dender single 

VMT 

equation 

annual 

VMT per 

adult 

fuel cost per mile, per Capita 

income, vehicle stock, road 

miles per adult, fraction of 

population that is adult, 

fraction of population living in 

urban areas, fraction of 

population living in urban 

areas with heavy rail,

OLS 33.0% 15.8% 8.0%

 dummy 

variables for fuel rationing, 

time trend 

Small-Van 

Dender threeequation 

annual 

VMT per 

adult 

fuel cost per mile, per Capita 

income, vehicle stock, road 

miles per adult, fraction of 

3SLS 21.6% 5.8% 3.4% 
390

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

system population that is adult, 

fraction of population living in 

urban areas, fraction of 

population living in urban 

areas with heavy rail, dummy 

variables for fuel rationing, 

time trend 

Singlequation annual 

e

VMT model 

VMT per 

adult 

personal income, road miles 

per Capita, time trend OLS 18.4% 11.7% 9.2% 

Singleequation 

VMT model 

VMT per 

vehicle 

income, road miles per Capita, 

time trend 

OLS 17.6% 15.2% 15.7

annual fuel cost per mile, personal 

% 

Singleequation 

VMT model 

annual 

VMT per 

adult 

fuel cost per mile, personal 

income, road miles per Capita, 

dummy variables for fuel 

rationing, time trend 

OLS 34.0% 20.8% 13.6% 

Singleequation 

VMT model 

annual 

VMT per 

vehicle 

fuel cost per mile, personal 

income, vehicles per road 

mile, % of fleet manufactured 

under CAFE standards, new 

IV (for fuel 

cost per 

mile) 

16.3% 9.2% 7.0%

vehicle prices 

Threeequation 

system for 

VMT, fuel 

efficiency, 

and vehicle 

stock 

annual 

VMT per 

vehicle 

fuel cost per mile, personal 

income, vehicles per capita, 

vehicles per road mile, 

fraction of adult population 

licensed to drive, new vehicle 

prices, % of fleet 

manufactured under CAFE 

standards 

2SLS 29.5% 13.4% 15.9%

Threeiency, vehicle licensed to drive, new vehicle 

equation 

system for 

VMT, fuel 

annual 

VMT per 

income, vehicles per capita, 

vehicles per road mile, 

fraction of adult population 3SLS 29.8% 13.7% 16.2%

effic

and vehicle 

stock 

prices, % of fleet 

manufactured under CAFE 

standards 

fuel cost per mile, personal 

Threeequation 

system for 

VMT, fuel 

efficiency, 

and vehicle 

stock 

annual 

VMT per 

vehicle 

income, vehicles per capita, 

vehicles per road mile, 

fraction of adult population 

licensed to drive, new vehicle 

prices, % of fleet 

manufactured under CAFE 

standards 

Vector autoregression 19.9% 10.8% 

fuel cost per mile, personal 

-- 

Threeequation 

system for 

VMT, fuel 

annual 

VMT per 

vehicle 

fuel cost per mile, personal 

income, vehicles per capita, 

vehicles per road mile, 

fraction of adult population 

Vector errorcorrection 20.7% 11.2% -- 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

efficiency, 

and vehicle 

stock 

licensed to drive, new vehicle 

prices, % of fleet 

manufactured under CAFE 

standards 

*Using AEO2009 Reference Case forecasts of fuel prices, fuel economy, and personal income. 

In light of these results, NHTSA has elected to use a 10 percent rebound effect in its analysis of 

fuel savings and other benefits from higher CAFE standards for MY 2012-2016 vehicles. The 

agency’s judgment is that the apparent decline over time in the magnitude of the rebound effect 

justifies using a value for future analysis that is lower than historical estimates, which average 

approximately 25 percent. Because the lifetimes of vehicles affected by the alternative CAFE 

standards considered in this rulemaking will extend from 2012 until approximately 2050, a value 

that is significantly lower than historical estimates appears to be appropriate. Recognizing the 

uncertainty surrounding its 10 percent estimate, the agency has analyzed the sensitivity of its 

benefits estimates to a range of values for the rebound effect from 5 percent to 15 percent. 

One possible alternative to attempting to estimate the rebound effect per se would be to use the 

price elasticity of demand for gasoline, which measures the sensitivity of gasoline consumption 

to a change in its price, in order to establish a lower bound on its magnitude. The elasticity of 

gasoline demand with respect to its price per gallon is likely to provide a reasonable proxy for 

the rebound effect, since a decline in the price of gasoline has exactly the same effect on the permile cost of driving as an equivalent increase in fuel economy. In the very short run, the only 

way that people can respond to changes in the price of gasoline is to alter the number of miles 

they drive.228 Over the relatively short time span of several months, most estimates indicate that 

the price elasticity of demand for gasoline is approximately -0.1, which corresponds to the shortrun rebound effect of 10 percent used in this FRIA. Over the period of a year, however, the price 

elasticity of demand is likely to increase somewhat in magnitude, up to a range of -0.3 to -0.4.229 

It seems reasonable to assume that the majority of the change in gasoline consumption over such 

a period results from changes in vehicle use, as distinguished from changes in the fuel economy 

of new vehicles, since only about 5-10 percent of the fleet would be replaced within one year. 

Additionally, NHTSA recognizes that as the world price of oil falls in response to lower U.S. 

demand for oil, there is the potential for an increase in oil use and, in turn, greenhouse gas 

emissions outside the U.S. This so called international oil “take back” effect is difficult to 

estimate. Given that oil consumption patterns vary across countries, there will be different 

demand responses to a change in the world price of crude oil. In addition, many countries 

around the world subsidize their oil consumption. It is not clear how oil consumption would 

change due to changes in the market price of oil given the current pattern of demand and 

subsidies. Further, many countries, especially in the developed countries/regions (i.e., the 

European Union), already have or anticipate implementing policies to limit GHG emissions. 

Further out in the future, it is anticipated that developing countries would take actions to reduce 

their GHG emissions as well. Any increases in petroleum consumption and GHG emissions in 

 

228 Over the long run, consumers can alter their choice of vehicle (and thus the fuel economy they achieve), in 

addition to altering their number of miles driven. 

229 The long-run price elasticity of demand for gasoline is in the 0.6 to 0.8 range. 
392

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ther nations that occur in response to a decline in world petroleum prices would be attributed to 

those nations, and recorded in their respe sions inventories. Thus, including the 

same increase U.S. would 

risk double-counting of global em

 

On-Road Fuel Economy Adjustment 

Actual fu onomy levels a by vehicles in o g fall sig short of 

their leve easured under t ory-like test c s used by EPA lish its 

published el economy ratin fferent models. ing the fuel rom 

alternativ assenger car and ck CAFE stand ency adjust al fuel 

economy rformance of eac ger car and ligh odel downwa its rated 

value to r ect the expected is on-road fuel y “gap.” In D 006, EPA 

adopted c nges to its regula el economy l ich were in bring 

vehicles’ d fuel economy oser to their ac oad fuel econo ls.230 

Supplem l analysis report A as part of its le indicates th on-road fuel 

economy ight-duty vehic ges 20 percent an published fu omy 

levels.231 r example, if the EPA fuel econ g of a light tru mpg, the onroad fue nomy actually a y a typical dri at vehicle is ex to be 16 mpg 

(20*.80) e agency has em revised e of this on-road onomy gap in 

its analy f the fuel saving g from alternat E standards fo 011-2016 

passenge rs and light truck

An analy onducted by NH nfirmed that EP of a 20 p ap between 

test and ad fuel econom -founded. The used data on th er of 

passenge rs and light truck model year th service (regi or use) during 

each cale r year from 2000 006, average nomy for passe light 

trucks pr d during each ar, and estimate erage miles driv year by cars 

and light ks of different a g each calenda ver that period. data were 

combine develop estimat ge-weighted e fuel economy e U.S. 

passenge r and light truck ave achie ing each year from 2000 through 

2006 und est conditions. 

Table VII 4 compares the agency’s estimates of fleet-w e average fuel econo y under test 

conditions for 2000 throu tration’ published 

stimates of the estimates of actual on-road fuel economy achieved by passenger cars and light 

ucks during each of those years. As it shows, FHWA’s estimates of actual fuel economy for 

 

o

ctive GHG emis

in emissions as part of the impact of adopting CAFE standards in the 

issions totals. 

el ec chieved n-road drivin nificantly

ls m he laborat ondition to estab

 fu gs for di In analyz savings f

e p light tru ards, the ag s the actu

pe h passen t truck m rd from 

efl size of th econom ecember 2

ha tions on fu abeling, wh tended to

 rate levels cl tual on-r my leve

enta ed by EP Final Ru at actual

 for l les avera lower th el econ

 Fo overall omy ratin ck is 20

l eco chieved b ver of th pected 

. Th ployed EPA’s stimate fuel ec

sis o s resultin ive CAF r MY 2

r ca s. 

sis c TSA co A’s estimate ercent g

on-ro y is well agency e numb

r ca s of each at were in st f ered

nda through 2 fuel eco nger cars and

oduce model ye s of av en per

 truc

d to 

ges durin

es of the usa

r year o

 averag

 These

that th

r ca fleets would h ved dur

er t

I- id m

gh 2006 to the Federal Highway Adminis s (FHWA)

e

tr

230 EPA, Fuel Economy Labeling of Motor Vehicles: Revisions To Improve Calculation of Fuel Economy Estimates; Final Rule, 40 CFR Parts 

86 and 600, Federal Register, December 27, 2006, pp. 77872-77969, http://www.epa.gov/fedrgstr/EPA-AIR/2006/December/Day27/a9749.pdf. 

231 EPA, Final Technical Support Document: Fuel Economy Labeling of Motor Vehicle Revisions to Improve 

Calculation of Fuel Economy Estimates, Office of Transportation and Air Quality EPA420-R-06-017 December 

2006, Chapter II, http://www.epa.gov/fueleconomy/420r06017.pdf. 
393

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

passenger cars ranged from 21 percent to r than NHTSA’s estimates of its fleetwide avera

actual fuel economy for light trucks percent lower than NHTSA’s 

estimates of average light truck fuel economy un er test conditions. These results appear to 

confirm that the 20% o is n te for 

use he f su 2012-

2016 vehicles. 

Table VIII

Estima -Wide Fu my of Passeng ared to 

eported Fuel E

NHTSA 

stimated Test 

MPG

F

Re

Actu

Percent 

Difference Est st 

FHWA 

Reported 

Actual MPG

ent 

rence

Passen

Calendar

Year

ght-Dutry Tru

 23 percent lowe

ge value under test conditions over this period. Similarly, FHWA’s estimates of 

 ranged from 16 percent to 18

d

n-road fuel economy d

uel savings likely to re

count or gap represe

lt from alternative CA

ts a reasonable estima

in evaluating t FE standards for MY 

-4 

ted Fleet el Econo er Cars and Light Trucks Comp

R conomy

E

HWA 

ported 

al MPG

NHTSA 

imated Te

MPG

Perc

Diffe

2000 28.2 -22.2% 17.4 3%

2001 28.2 -21.7% 17.6 5%

2002 28.3 -22.3% 17.5 2%

2003 28.4 -21.9% 17.2 0%

2004 28.5 -21.1% 17.2 3%

2005 28.6 -22.8% 17.7 3%

2006 28.8 -21.8% 17.8 2%

Average,

2000-2006 28.4 -22.0% 17.5 7%

21.9 20.8 -16.

22.1 20.8 -15.

22.0 20.9 -16.

22.2 21.0 -18.

22.5

22.1

21.0

21.1

-18.

-16.

22.5 21.2 -16.

22.2 21.0 -16.

ger Cars Li cks

B. Benefits to Vehicle B om Improving conomy uyers fr Fuel E 

The mai ce of economic from raising CAFE standards is the v the resulting 

fuel savi over the lifetime cles that are req achieve higher f onomy. The 

annual fu avings under eac tive CAFE stan measured by th erence 

between l annual fuel con n by passenger c ght trucks with el economy 

they are cted to achieve driving under ernative standard, and their annual 

fuel cons with the fu els – agai ed for difference n test and 

actual on riving condit ey would achiev the baseline alt ve. The sum 

of these al fuel savings o calendar year t or light trucks p d during a 

model ye re expected to re service represen cumulative lifeti el savings 

with that rnative CAFE st effect. 

Vehicle ival Rates 

These an fuel sav gs de the number of v that remain in us ing each year 

of a mode ear’s lifetimes. rucks m ed during a 

model year that remains in se year is by 

n sour benefits alue of 

ngs s of vehi uired to uel ec

el s h alterna dard are e diff

 tota sumptio ars or li the fu

expe in on-road that alt

umption el economy lev n adjust s betwee

-road d ions – th e under ernati

annu ver each hat cars roduce

ar a main in ts their me fu

 alte andard in

Surv

nual in pend on ehicles e dur

l y The number of passenger cars or light t

rvice during each subsequent calendar 

anufactur

estimated
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

er expected to be produced during that model year by the 

ort NHTSA’s updated estimates of average car and light truck use. The total number of 

iles driven by passenger cars or light trucks produced during a model year are driven during 

. 

6-

m 

es VIII-5a and VIII-5b, 

 is important to understand that vehicles are considered to be of age 1 during the calendar year 

multiplying the original numb

proportion of vehicles expected to remain in service to the age they will have reached during that 

year. The proportions of passenger cars and light trucks expected to remain in service at each 

age up to their maximum lifetimes (26 and 36 years, respectively) are shown in Tables VIII-5a 

and VIII-5b.232 These “survival rates,” which are estimated from experience with recent modelyear vehicles, are slightly different than the survival rates used in past NHTSA analyses, since 

they reflect recent increases in durability and usage of more recent passenger car and light truck 

models.233 

Vehicle Use 

Annual fuel savings during each year of a model year’s lifetime also depend on the number of 

miles that the remaining vehicles in use are driven. Updated estimates of average annual miles 

driven by age were developed by NHTSA for MY 2011 rulemaking from the Federal Highway 

Administration’s 2001 National Household Transportation Survey, and these also differ from the 

estimates of annual mileage employed in past NHTSA analyses.234 Table VIII-5a and VIII-5b 

also rep

m

each year of its lifetime is estimated by multiplying these age-specific estimates of average car 

and light truck use by the number of vehicles projected to remain in service during that year

As Tables VIII-5a and VIII-5b also show, the resulting survival-weighted mileage over the 2

year maximum lifetime of passenger cars is 161,847 miles, while that over the 36-year maximu

lifetime of light trucks is 190, 066 miles. Fuel savings and other benefits resulting from higher 

CAFE standards for passenger cars and light trucks are calculated over their respective lifetimes 

and total expected mileage. It should be noted, however, that survival-weighted mileage is 

extremely low (less than 1,000 miles per year) after age 20 for cars and after age 25 for light 

trucks, and thus has little impact on lifetime fuel savings or other benefits from higher fuel 

economy, particularly after discounting those benefits to their present values. 

In interpreting the survival and annual mileage estimates reported in Tabl

it

 

232 The maximum age of cars and light trucks was defined as the age when the number remaining in service has 

declined to approximately two percent of those originally produced. Based on an examination of recent registration 

data for previous model years, typical maximum ages appear to be 26 years for passenger cars and 36 years for lig

trucks. 

233 The survival rates were calculated from R.L. Polk, National Vehicle Population Profile (NVPP), 1977-2003; see

NHTSA, “Vehicle Survival and Travel Mileage Schedules,” Office of Regulatory Analysis and Evaluation, NCSA

January 2006, pp. 9-11, Docket No. 22223-2218. Polk’s NVPP is an annual census of passenger cars and light 

trucks registered for on-road operation in the United States as of Jul 1 each year. NVPP registration data from 

ht 

, 

vehicle model years 1977 to 2003 were used to develop the survival rates reported in Tables VIII-5a and VIII-5b. 

d regression 

ght 

 the 

inistration, Bureau of Transportation Statistics, and National Highway Traffic Safety 

Survival rates were averaged for the five most recent model years for vehicles up to 20 years old, an

models were fitted to these data to develop smooth relationships between age and the proportion of cars or li

trucks surviving to that age. 

234 See also NHTSA, “Vehicle Survival and Travel Mileage Schedules,” Office of Regulatory Analysis and 

Evaluation, January 2006, pp. 15-17. The original source of information on annual use of passenger cars and light 

trucks by age used in this analysis is the 2001 National Household Travel Survey (NHTS), jointly sponsored by

Federal Highway Adm

Administration. 
395

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

nt 

ffered for sale in June 

rough September of the preceding calendar year, depending on manufacturer). Thus virtually 

5

 

 

that coincides with their model year Thus for example, model year 2012 vehicles will be 

considered to be of age 1 during calendar year 2012. This convention is used in order to accou

for the fact that vehicles produced during a model year typical are first o

th

all of the vehicles produced during a model year will be in use for some or all of the calendar 

year coinciding with their model year, and they are considered to be of age 1 during that year.23

235 As an illustration, virtually the entire production of model year 2012 cars and light trucks will have been sold by 

the end of calendar year 2012, so those vehicles are defined to be of age 1 during calendar year 2012. Model year 

2012 vehicles are subsequently defined to be of age 2 during calendar year 2013, age 3 during calendar year 2014, 

and so on. One complication arises because registration data are typically collected for July 1 of each calendar year, 

so not all vehicles produced during a model year will appear in registration data until the calendar year when they 

have reached age 2 (and sometimes age 3) under this convention. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VIII-5a 

Survival Rates and Unadjusted Annual Miles Traveled (VMT) 

by Age for Passenger Cars 

Vehicle Age Estimated Survival 

Fraction

Estimated Annual 

VMT 

Survival-Weighted 

Annual VMT 

1 0.9950 14,231 14,160 

2 0.9900 13,961 13,821 

3 0.9831 13,669 13,438 

4 0.9731 13,357 12,998 

5 0.9593 13,028 12,497 

6 0.9413 12,683 11,938 

7 0.9188 12,325 11,324 

8 0.8918 11,956 10,662 

9 0.8604 11,578 9,961 

10 0.8252 11,193 9,237 

11 0.7866 10,804 8,499 

12 0.7170 10,413 7,466 

13 0.6125 10,022 6,138 

14 0.5094 9,633 4,907 

15 0.4142 9,249 3,831 

16 0.3308 8,871 2,934 

17 0.2604 8,502 2,214 

18 0.2028 8,144 1,652 

19 0.1565 7,799 1,220 

20 0.1200 7,469 896 

21 0.0916 7,157 656 

22 0.0696 6,866 478 

23 0.0527 6,596 348 

24 0.0399 6,350 253 

25 0.0301 6,131 185 

26 0.0227 5,940 135 

 

Estimated Passenger Car Lifetime VMT 161,847 
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Table VIII-5b 

Survival Rates and Unadjusted Annual Vehicle-Miles Traveled (VMT) 

by Age for Light Trucks 

Vehicle Age Estimated Survival 

Fraction

Estimated Annual 

VMT 

Survival-Weighted 

Annual VMT 

1 0.9950 16,085 16,004 

2 0.9741 15,782 15,374 

3 0.9603 15,442 14,829 

4 0.9420 15,069 14,195 

5 0.9190 14,667 13,479 

6 0.8913 14,239 12,691 

7 0.8590 13,790 11,845 

8 0.8226 13,323 10,960 

9 0.7827 12,844 10,053 

10 0.7401 12,356 9,145 

11 0.6956 11,863 8,252 

12 0.6501 11,369 7,391 

13 0.6042 10,879 6,573 

14 0.5517 10,396 5,735 

15 0.5009 9,924 4,971 

16 0.4522 9,468 4,281 

17 0.4062 9,032 3,669 

18 0.3633 8,619 3,131 

19 0.3236 8,234 2,665 

20 0.2873 7,881 2,264 

21 0.2542 7,565 1,923 

22 0.2244 7,288 1,635 

23 0.1975 7,055 1,393 

24 0.1735 6,871 1,192 

25 0.1522 6,739 1,026 

26 0.1332 6,663 887 

27 0.1165 6,648 774 

28 0.1017 6,648 676 

29 0.0887 6,648 590 

30 0.0773 6,648 514 

31 0.0673 6,648 447 

32 0.0586 6,648 390 

33 0.0509 6,648 338 

34 0.0443 6,648 294 

35 0.0385 6,648 256 

36 0.0334 6,648 222 

Estimated Lifetime Light Truck VMT 190,066 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

s 

use 

 Release 

n of 

and 

e percent 

hose prevailing in 2001 to adjust the estimates 

f vehicle use derived from the NHTS to reflect the effect of higher future fuel prices. This procedure 

ual 

ht 

rtance of 

rowth in average vehicle use, the total number of miles driven by passenger cars increased 35 

nd annual growth rate of 1.5 percent.236 

biles are 

rage 

HTSA calculated the rate of growth in the mileage schedules shown in Tables VIII-5a and 

st 

ced 

Adjusting Vehicle Use 

The estimates of average annual miles driven by passenger cars and light trucks reported in Table

VIII-5a and VIII-5b reflect the historically low gasoline prices that prevailed at the time the 2001

National Household Travel Survey (NHTS) was conducted. To account for the effect on vehicle 

of subsequent increases in fuel prices, the estimates of annual vehicle use derived from the NHTS

were adjusted to reflect the forecasts of future gasoline prices reported in the AEO 2010 Early

Reference Case. This adjustment accounts for the difference between the average price per gallo

fuel forecast for each year over the expected lifetimes of model year 2012-2016 passenger cars 

light trucks, and the average price that prevailed when the NHTS was conducted in 2001. The 

elasticity of annual vehicle use with respect to fuel cost per mile corresponding to the 10% fuel 

economy rebound effect used in this analysis (i.e., an elasticity of -0.10) was applied to th

difference between each future year’s fuel prices and t

o

was applied to the mileage figures reported previously in Tables VIII-5a and VIII-5b to adjust ann

mileage by age during each calendar year of the expected lifetimes of MY 2012-2016 cars and lig

trucks. 

The estimates of annual miles driven by passenger cars and light trucks at each age were also 

adjusted to reflect projected future growth in average vehicle use. Increases in the average 

number of miles cars and trucks are driven each year have been an important source of historical 

growth in total car and light truck use, and are expected to represent an important source of 

future growth in total light-duty vehicle travel as well. As an illustration of the impo

g

percent from 1985 through 2005, equivalent to a compou

During that time, however, the total number of passenger cars registered for in the U.S. grew by

only about 0.3 percent annually.237 Thus growth in the average number of miles automo

driven each year accounted for the remaining 1.2 percent (= 1.5 percent - 0.3 percent) annual 

growth in total automobile use.238 Further, the AEO 2010 Reference Case forecasts of total car 

and light truck use and of the number of cars and light trucks in use suggest that their ave

annual use will continue to increase gradually from 2010 through 2030. 

In order to develop reasonable estimates of future growth in average car and light truck use, 

N

VIII-5b that would be necessary for total car and light truck travel to increase at the rate foreca

in the AEO 2010 Reference Case. This rate was calculated in a manner that is also consistent 

with future changes in the overall size and age distributions of the U.S. passenger car and light 

truck fleets that are implied by the agency’s adjusted forecasts of total car and light truck sales 

reported previously in Tables VIII-1a and VIII-1b, together with the survival rates reported in 

Tables VIII-5a and VIII-5b. The growth rate in average annual car and light truck use produ

 

236 Calculated from data reported in FHWA, Highway Statistics, Summary to 1995, Table vm201at 

http://www.fhwa.dot.gov/ohim/summary95/vm201a.xlw , and annual editions 1996-2005, Table VM-1 at 

http://www.fhwa.dot.gov/policy/ohpi/hss/hsspubs.htm (last accessed April 20, 2008). 237

 A slight increase in the fraction of new passenger cars remaining in service beyond age 10 has accounted for a 

small share of growth in the U.S. automobile fleet. The fraction of new automobiles remaining in service to various 

See supra note [2 above here] 

ages was computed from R.L. Polk vehicle registration data for 1977 through 2005 by the agency’s Center for 

Statistical Analysis. 

238
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

e 

ht 

0. Because the effects of both 

el prices and cumulative growth in average vehicle use vary by year, these adjustments result 

es 

 

ect of these two adjustments is to increase 

xpected lifetime mileage significantly. As an illustration, expected lifetime mileage for 

 

uel 

o 

by this calculation is approximately 1.15% per year.239 This rate was applied to the mileag

figures reported in Tables VIII-5a and VIII-5b to estimate annual mileage by age during each 

year of the expected lifetimes of MY 2012-2016 cars and light trucks. 

Tables VIII-5c and VIII-5d report the results of applying the adjustments for both future fuel 

prices and annual growth in car and light truck use to the figures reported previously in Tables 

VIII-5a and VIII-5b. Separate adjustments for projected fuel prices and growth in car and lig

truck use were made for each calendar year from 2012 through 203

fu

in differing VMT schedules for each future year. The adjusted annual VMT estimates reported

in Tables VIII-5c and VIII-5d, as well as their lifetime totals, represent averages of the adjusted

values of annual car and light truck use by age for calendar years 2012-2030. However, the 

estimates of fuel savings and other impacts of improved fuel efficiency for individual calendar 

years over the lifetimes of model year 2012-16 cars and light trucks employ the adjusted valu

of car and light truck use by age during those specific calendar years. 

While the adjustment for future fuel prices reduces average mileage at each age from the values 

shown previously, the adjustment for expected future growth in average vehicle use increases it.

Comparing the mileage estimates in Tables VIII-5c and VIII-5d to those shown previously in 

Tables VIII-5a and VIII-5b shows that the net eff

e

passenger cars rises to 195,264 miles in Table VIII-5c from the 161,847 miles reported 

previously in Table VIII-5a (or by 21%), while Table VIII-5d shows that expected lifetime 

mileage for light trucks increases from the 190,066 miles reported previously in Table VIII-5b to 

225,865 miles (or by 19%). As previously, however, the estimates of survival-weighted mileage 

decline to less than 1,000 miles per year after age 20 for cars and after age 27 for light trucks.

Thus they have relatively little impact on lifetime fuel savings or other benefits from higher f

economy, particularly after discounting the benefits that occur in those distant future years t

their present values. 

 

239 It was not possible to estimate separate growth rates in average annual use for cars and light trucks, because of 

the significant reclassification of light truck models as passenger cars discussed previously. 
400

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VIII-5c 

Survival Rates and Adjusted Annual Vehicle-Miles Traveled (VMT) 

by Age for Passenger Cars 

Vehicle Age Estimated Survival 

Fraction

Estimated Annual 

VMT 

Survival-Weighted 

Annual VMT 

1 0.9950 17,270 17,183 

2 0.9900 16,943 16,774 

3 0.9831 16,599 16,319 

4 0.9731 16,163 15,728 

5 0.9593 15,761 15,119 

6 0.9413 15,337 14,437 

7 0.9188 14,881 13,672 

8 0.8918 14,429 12,868 

9 0.8604 13,940 11,994 

10 0.8252 13,495 11,136 

11 0.7866 12,964 10,198 

12 0.7170 12,510 8,970 

13 0.6125 11,990 7,344 

14 0.5094 11,470 5,843 

15 0.4142 10,997 4,555 

16 0.3308 10,543 3,488 

17 0.2604 10,125 2,637 

18 0.2028 9,714 1,970 

19 0.1565 9,307 1,456 

20 0.1200 8,891 1,067 

21 0.0916 8,546 783 

22 0.0696 8,285 577 

23 0.0527 8,136 429 

24 0.0399 7,896 315 

25 0.0301 7,699 232 

26 0.0227 7,530 171 

Adjusted Lifetime Passenger Car VMT 195,264 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Survival R ed (VMT) 

by Age for Light Trucks 

Table VIII-5d 

ates and Adjusted Annual Vehicle-Miles Travel

Vehicle Age Estimated Survival 

Fraction

Estimated Annual 

VMT

Survival-Weighted 

Annual VMT 

1 0.9950 19,219 19,123 

2 0.9741 18,782 18,296 

3 0.9603 18,419 17,688 

4 0.9420 17,946 16,905 

5 0.9190 17,502 16,085 

6 0.8913 16,952 15,109 

7 0.8590 16,439 14,121 

8 0.8226 15,829 13,021 

9 0.7827 15,218 11,911 

10 0.7401 14,648 10,841 

11 0.6956 13,992 9,733 

12 0.6501 13,450 8,744 

13 0.6042 12,832 7,753 

14 0.5517 12,212 6,737 

15 0.5009 11,600 5,811 

16 0.4522 11,069 5,005 

17 0.4062 10,617 4,313 

18 0.3633 10,125 3,679 

19 0.3236 9,650 3,123 

20 0.2873 9,238 2,654 

21 0.2542 8,882 2,258 

22 0.2244 8,667 1,945 

23 0.1975 8,400 1,659 

24 0.1735 8,395 1,456 

25 0.1522 8,197 1,248 

26 0.1332 8,188 1,091 

27 0.1165 8,218 957 

28 0.1017 8,216 836 

29 0.0887 8,213 728 

30 0.0773 8,211 635 

31 0.0673 8,210 553 

32 0.0586 8,208 481 

33 0.0509 8,203 418 

34 0.0443 8,196 363 

35 0.0385 8,182 315 

36 0.0334 8,167 273 

Adjusted Lifetim ck V 225, e Light Tru MT 865 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Estimati nual Fuel Con ion 

NHTSA estimated annual fuel mption dur r of pected life

year 201 cars and light with altern AFE sta in effect b ng the 

total num miles that a m ar’s surviv hicles are by the fu omy that 

they are ed to achieve u ch alterna ndard.240 me fuel co tion by 

each mo cars and lig ks is the su e annual the vehicl ed 

during th el year that are ted to rem ervice du ch year o xpected 

lifetimes rn, the savings ime fuel co by MY 2012-2016 ca light 

trucks th ld result from a e increas AFE stan is the diffe between 

their lifet el use at the fu omy level e project ttain unde djusted 

Baseline ative, and their e fuel use igher fue my level e 

rojected to achieve under each alternative standard. 

 benefits to vehicle owners and to the U.S. economy that 

 of 

nsumption 

ed 

. 

ded from the social value of fuel savings because 

e 

nt 

s 

t 

ng An sumpt

consu ing each yea the ex times of model 

2-2016 trucks ative C ndards y dividi

ber of odel ye ing ve driven el econ

expect nder ea tive sta Lifeti nsump

del year’s 

at mod

ht truc

 projec

m of th

ain in s

 use by

ring ea

es produc

f their e

. In tu in lifet nsumption rs and 

at wou lternativ es in C dards rence 

ime fu el econ they ar ed to a r the A

altern lifetim at the h l econo they ar

p

NHTSA’s analysis values the economic

result from future fuel savings over the full expected lifetimes of MY 2012-2016 passenger cars 

and light trucks. This reflects the agency’s assumption that while the purchasers of new vehicles

might not realize the full lifetime benefits of improved fuel economy, subsequent owners of 

those vehicles will continue to experience the resulting fuel savings until they are retired from 

service. Of course, not all vehicles produced during a model year remain in service for the 

complete lifetimes (26 years for passenger cars or 36 years for light trucks) of each model year. 

Due to the pattern of vehicle retirements with increasing age, the expected or average lifetimes

typical representative cars and light trucks are approximately half of these figures. 

Economic Benefits from Reduced Fuel Co

The economic value of fuel savings resulting from alternative CAFE standards is estimated by 

applying the Reference Case forecast of future fuel prices from the Energy Information 

Administration’s Annual Energy Outlook 2010 Early Release to each future year’s estimat

fuel savings. The AEO 2010 Reference Case forecast of future fuel prices, which is reported in 

Table VIII-6, represents retail prices per gallon of fuel, including federal, state, and any 

applicable local taxes. While the retail price of fuel is the proper measure for valuing fuel 

savings from the perspective of vehicle owners, two adjustments to the retail prices are necessary 

in order to accurately reflect the economic value of fuel savings to the U.S. economy

First, federal, state, and local taxes are exclu

these do not reflect costs of resources used in fuel production, and thus do not reflect resourc

savings that would result from reducing fuel consumption. Instead, fuel taxes simply represe

resources that are transferred from purchasers of fuel to road and highway users, since fuel taxe

primarily fund construction and maintenance of those facilities. Any reduction in State and 

Federal fuel tax payments by fuel purchasers will reduce government revenues by the same 

amount, thus ultimately reducing the value of government-financed services by approximately 

that same amount. The benefit derived from lower taxes to individuals is thus likely to be offse

exactly by a reduction in the value of services funded using those tax revenues. 

 

240

 The total number of miles that vehicles are driven each year is slightly different under each alternative as a result 

of the fuel economy “rebound effect,” which is discussed in detail elsewhere in this chapter. 
403

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

nd through 2035, the agency’s 

nalysis of the value of fuel savings over the lifetimes of MY 2012-2016 cars and light trucks 

ue 

st 

st 

l gasoline taxes are currently $0.178 while 

tate and local gasoline taxes together average $0.231 per gallon, for a total tax burden of $0.401 

s 

eep pace with inflation in nominal terms, and thus to remain constant when 

express

r 

fuel), and typically require legislation to change. 

bal 

Second, the economic cost of externalities generated by U.S. consumption and imports of 

petroleum products will be reduced in proportion to fuel savings resulting from higher CAFE 

standards. The estimated economic value of these externalities, which is discussed in detail in 

the subsequent section of this Chapter, is converted into its per-gallon equivalent and added to 

the pre-tax price of gasoline in order to measure this additional benefit to society for each gallon

of fuel saved. This also allows the magnitude of these externalities to be easily compared to the 

value of the resources saved by reducing fuel production and use, which represents the most 

important component of the social benefits from saving gasoline. 

Table VIII-6 illustrates the adjustment of forecast retail fuel prices to remove the value of fuel 

taxes and add the value of economic externalities from petroleum imports and use. While the 

Reference Case fuel price forecasts reported in AEO 2010 exte

a

requires forecasts extending through calendar year 2050, approximately the last year during 

which a significant number of MY 2016 vehicles will remain in service.241 To obtain fuel price 

forecasts for the years 2036 through 2050,the agency assumes that retail fuel prices will contin

to increase after 2035 at the average rates reported in the AEO 2010 Reference Case foreca

over the period from 2025 through 2035 (in constant-dollar terms).242 As Table VIII-6 shows, 

the projected retail price of gasoline expressed in 2007 dollars rises steadily over the foreca

period, from $2.47 in 2011 to $4.49 in 2050. 

The agency has updated its estimates of gasoline taxes, using updated state tax rates reported for 

January 1, 2006243 Expressed in 2007 dollars, federa

s

per gallon. Following the assumptions used by EIA in AEO 2010, state and local gasoline taxe

are assumed to k

ed in constant 2007dollars. In contrast, EIA assumes that federal gasoline taxes will 

remain unchanged in nominal terms, and thus decline throughout the forecast period when

expressed in constant 2007 dollars. These differing assumptions about the likely future behavio

of federal and state/local fuel taxes are consistent with recent historical experience, which 

reflects the fact that federal motor fuel taxes as well as most state fuel taxes are specified on a 

cents-per-gallon basis (some State taxes are levied as a percentage of the wholesale price of 

EIA’s AEO 2010 Early Release Reference Case reflects the effects of the American 

Reinvestment and Recovery Act of 2009, as well as of recent revisions to the U.S. and glo

 

241 The agency defines the maximum lifetime of vehicles as the highest age at which more than 2 percent of those 

originally produced during a model year remain in service. In the case of light-duty trucks, for example, this age has 

typically been 36 years for recent model years. 

242 This projection uses the rate of increase in fuel prices for 2020-2030 rather than that over the complete forecast 

period (2009-2030) because there is extreme volatility in the forecasts for the years 2009 through approximately 

2020. Using the average rate of change over the complete 2009-2030 forecast period would result in projections of 

declining fuel prices after 2030. 

243 FHWA, Highway Statistics 2006, Section I: Motor Fuel -- Rates and Revenues, Table MF-121T, available at 

http://www.fhwa.dot.gov/policy/ohim/hs06/pdf/mf121t.pdf. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

t that the combined mpg level of U.S. cars 

and lig be 

 in 

 initial release of 

AEO 2 n 

economic outlook. In addition, it also reflects the provisions of the Energy Independence and 

Security Act of 2007 (EISA), including the requiremen

ht trucks reach 35 miles per gallon by model year 2020. Because this provision would

expected to reduce future U.S. demand for gasoline, and thus lead to a decline in its future price, 

there is some concern about whether the AEO 2010 forecast of fuel prices partly reflects the 

increases in CAFE standards considered in this rule, and whether it is thus suitable for valuing

the projected reductions in fuel use. 

In response to this concern, the agencies note that EIA issued a revised version of AEO 2008

June 2008, which modified its previous December 2007 Early Release of AEO 2008 to reflect 

the effects of then recently-passed EISA legislation.244 The fuel price forecasts reported in 

EIA’s Revised Release of AEO 2008 differed by less than one cent per gallon throughout the 

entire forecast period (2008-230) from those previously issued as part of its

008. Thus, the agencies are reasonably confident that the fuel price forecasts presented i

AEO 2010 and used to analyze the value of fuel savings projected to result from this rule are not 

unduly affected by the CAFE provisions of EISA. 

 

 

244 Energy Information Administration, Annual Energy Outlook 2008, Revised Early Release (June 2008), Table 12. 

 Available at http://www.eia.doe.gov/oiaf/archive/aeo08/excel/aeotab_12.xls (last accessed September 12, 2009). 
405

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VIII-6 

Adjustment of Forecast Retail Gasoline Prices 

to Reflect the Economic Value of Fuel Savings 

AE0 2010 

Forecast of Retail 

Gasoline Price 

Estimated 

Federal and 

State Taxes 

Forecast 

Gasoline Price 

Excluding 

Taxes 

Forecast 

Gasoline Price 

Including 

Energy 

Security 

Externalities 

Year 

(2007 $/gallon) (2007 

$/gallon) 

(2007 

$/gallon) 

(2007 

$/gallon) 

2011 $2.47 $0.40 $2.08 $2.24 

2012 $2.61 $0.40 $2.21 $2.38 

2013 $2.84 $0.40 $2.45 $2.62 

2014 $2.95 $0.39 $2.56 $2.73 

2015 $3.00 $0.39 $2.61 $2.78 

2016 $3.07 $0.39 $2.68 $2.85 

2017 $3.13 $0.39 $2.75 $2.92 

2018 $3.19 $0.39 $2.80 $2.97 

2019 $3.22 $0.38 $2.84 $3.01 

2020 $3.27 $0.38 $2.89 $3.06 

2021 $3.29 $0.38 $2.92 $3.09 

2022 $3.34 $0.37 $2.96 $3.13 

2023 $3.37 $0.37 $2.99 $3.16 

2024 $3.38 $0.37 $3.01 $3.18 

2025 $3.42 $0.37 $3.05 $3.22 

2026 $3.46 $0.36 $3.09 $3.26 

2027 $3.49 $0.36 $3.13 $3.30 

2028 $3.54 $0.36 $3.18 $3.35 

2029 $3.59 $0.36 $3.23 $3.40 

2030 $3.60 $0.35 $3.25 $3.42 

2031 $3.64 $0.35 $3.29 $3.46 

2032 $3.69 $0.35 $3.34 $3.51 

2033 $3.72 $0.35 $3.37 $3.54 

2034 $3.77 $0.35 $3.42 $3.59 

2035 $3.83 $0.34 $3.48 $3.65 

2036 $3.87 $0.34 $3.53 $3.69 

2037 $3.91 $0.34 $3.57 $3.74 

2038 $3.95 $0.34 $3.61 $3.78 

2039 $3.99 $0.34 $3.66 $3.82 

2040 $4.04 $0.33 $3.70 $3.87 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

2041 $4.08 $0.33 $3.75 $3.91 

2042 $4.12 $0.33 $3.79 $3.96 

2043 $4.17 $0.33 $3.84 $4.01 

2044 $4.21 $0.33 $3.89 $4.05 

2045 $ 26 4. $0.32 $3.93 $4.10 

2046 $4.30 $0.32 $3.98 $4.15 

2047 $4.35 $0.32 $4.03 $4.19 

2048 $4.39 $0.32 $4.08 $4.24 

2049 $4.44 $0.31 $4.12 $4.29 

2050 $4.49 $0.31 $4.17 $4.34 

Benefits from Additional Driving 

The increase in travel associated with the rebound effect produces additional benefits to vehicle 

owners, which reflect the value to drivers and other vehicle occupants of the added (or more 

desirable) social and economic opportunities that become accessible with additional travel. As 

evidenced by the fact that they ele ct to make more frequent or longer trips when the cost of 

erating costs per vehicle-mile and the resulting increase in the annual 

e 

driving range before they require refueling. By reducing the frequency with which drivers 

ically refuel their vehicles and extending the upper limit of the range they can travel before 

e 

ill presumably be 

flected in lower vehicle sales prices. If manufacturers respond by doing so, this presumably 

ase 

driving declines, the benefits from this added travel exceed drivers’ added outlays for the fuel it 

consumes (measured at the improved level of fuel economy resulting from stricter CAFE 

standards).245 The amount by which the benefits from this increased driving travel exceed its 

increased fuel costs measures the net benefits they receive from the additional travel, usually are 

referred to as increased consumer surplus. 

NHTSA’s analysis estimates the economic value of the increased consumer surplus provided by 

added driving using the conventional approximation, which is one half of the product of the

decline in vehicle op

number of miles driven. Because it depends on the extent of improvement in fuel economy, the

value of benefits from increased vehicle use changes by model year and varies among alternativ

CAFE standards. Under even those alternatives that would impose the highest standards, 

however, the magnitude of benefits from additional vehicle use represents a small fraction of the 

total benefits from requiring cars and light trucks to achieve higher fuel economy. 

The Value of Increased Driving Range 

Improving the fuel economy of passenger cars and light-duty trucks may also increase their 

typ

requiring refueling, improving fuel economy thus provides some additional benefits to their 

owners. Alternatively, if manufacturers respond to improved fuel economy by reducing the siz

of fuel tanks to maintain a constant driving range, the resulting cost saving w

re

reflects their judgment that the value to economic benefits to vehicle buyers from lower purch

prices exceeds that from extended refueling range. 

 

245 These benefits are included in the value of fuel savings reported in Tables VIII-5 through VIII-9. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

umber of required refueling cycles that results 

om improved fuel economy, and applies DOT-recommended values of travel time savings to 

he 

y, 

y for all driving trips (1.6 persons), the DOT-recommended value of travel time 

er vehicle-hour is $24.00 (in 2006 dollars).249 Assuming that locating a station and filling up 

re 

he agencies’ estimate of benefits from less frequent refueling is subject to several sources of 

No direct estimates of the value of extended vehicle range are readily available, so the agencies’ 

analyses calculate the reduction in the annual n

fr

convert the resulting time savings to their economic value.246 As a coarse illustration of how t

value of extended refueling range is estimated, a typical small light truck model has an average 

fuel tank size of approximately 20 gallons.247 Based on a California Air Resources Board Stud

the average fuel purchase is approximately 55% of tank volume.248 Therefore, increasing this 

model’s actual on-road fuel economy from 24 to 25 mpg would extend its driving range from

216 miles (= 9 gallons x 24 mpg) to 225 miles (= 9 gallons x 25 mpg). Assuming that this 

vehicle is driven 12,000 miles/year, this reduces the number of times it needs to be refueled each

year from 55.5 (= 12,000 miles per year / 216 miles per refueling) to 53.3 (= 12,000 miles per 

year / 225 miles per refueling), or by 2.2 refuelings per year. 

Weighted by the nationwide mix of urban (about 2/3) and rural (about 1/3) driving and average 

vehicle occupanc

p

requires five minutes, the annual value of time saved as a result of less frequent refueling 

amounts to $4.40 (calculated as 5/60 x 2.2 x $24.00). This calculation is repeated for each futu

calendar year that light trucks of each model year affected by the alternative fuel economy 

standards considered in this rule would remain in service. Like fuel savings and other benefits, 

however, the value of this benefit declines over a model year’s lifetime, because a smaller 

number of vehicles originally produced during that model year remain in service each year, and 

those remaining in service are driven fewer miles. 

T

uncertainty. 

 First, it assumes that manufacturers will not adjust fuel tank capacities downward (from 

the current average of 19.3 gallons) when they improve the fuel economy of their vehicle 

models, so that the entire increase in fuel economy will be reflected in increased driving range. 

Should manufacturers choose to downsize fuel tanks, and all other factors have been estimated 

with no error, the current estimates of refueling benefits would be overstated. On the other hand, 

vehicle space, utility and value could increase and vehicle weight will decrease, improving fuel 

 

246

 Department of Transportation, Guidance Memorandum, “The Value of Saving Travel Time: Departmental 

Guidance for Conducting Economic Evaluations,” Apr. 9, 1997. 

http://ostpxweb.dot.gov/policy/Data/VOT97guid.pdf (last accessed October 20, 2007); update available at

http://ostpxweb.dot.gov/policy/Data/VOTrevision1_2-11-03.pdf (last accessed October 20, 2007).

247 Based on the Volpe Model Market Data file for Model Year 2011, average tank volumes for cars and trucks are 

16.6 gallons and 23.0 gallons, respectively. This produces a production weighted average of 19.3 gallons. 248 California Environmental Protection Agency, Air Resources Board. Draft Assessment of the Real-World Impact

of Commingling California Phase 3 Reformulated Gasoline. August 2003 

249 The hourly wage rate during 2006 is estimated t

s 

o be $24.00. Personal travel (94.4% of urban travel) is valued at 

0 percent of the hourly wage rate. Business travel (5.6% or urban travel) is valued at 100 percent of the hourly 

wage rate. For intercity travel, personal travel (87%) is valued at 70 percent of the wage rate, while business travel 

(13%) is valued at 100 percent of the wage rate. The resulting values of travel time are $12.67 for urban travel and 

5

$17.66 for intercity travel, and must be multiplied by vehicle occupancy (1.6) to obtain the estimated value of time 

per vehicle hour. 
408

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

economy and CO2 emissions (all other things being equal). In the context of the rule, this will 

decrease the cost of compliance with the standards. 

Second, the agencies’ analysis assumes that fuel purchases average 55% of fuel tank 

capacity. However, as shown in the California Air Resource Board (CARB) report, refueling 

patterns vary. Moreover, the 55% estimate implies that drivers, on average, are either refuel

when nearly a half tank of gas remains in their vehicles, or that they are habitually not filling 

their tanks. Since many drivers only refuel when their tanks are very low, and since many 

drivers habitually fill up their tan

ing 

ks, this in turn implies that many drivers in the CARB study are 

fueling when their tanks are still well above 50% full. Certainly instances of this type of 

e 

olve 

. 

avel 

urposes, and drivers are likely to assign different values to their time when traveling for these 

t 

he 

s 

re

behavior occur, but the CARB study implies that it is the norm. Behavior that maximizes the 

number of fill-ups implies a very low value of time, but it is also possible that the results of th

CARB study are not representative of typical behavior across the country. While based on field

data, this estimate may thus overestimate the impact of refueling benefits. 

Third, the agencies’ estimate of refueling benefits assumes that refueling stops inv

the same number of vehicle occupants as the overall average for all vehicle trips (1.6 persons)

To the extent that drivers refuel while doing other errands or in advance of picking up 

passengers, this figure may overestimate the typical vehicle occupancy during refueling, and thus

the total savings in refueling time. Similarly, the hourly value used to estimate the economic

value of savings in refueling time reflects the typical mix of personal and business tr

p

different purposes. To the extent that drivers seek to refuel when traveling for purposes tha

typically use less valuable time, the hourly value used in the agencies’ analysis may overstate t

benefits from saving refueling time. 

Finally, the agencies assume that both finding and using a refueling station takes, on 

average, five minutes. There are few, if any, data sources on average refueling time, and thi

estimate is subject to significant uncertainty. 

NHTSA is planning a nationwide survey of refueling patterns at service stations to obtain 

information to help answer these questions for future rulemakings. 

C. Other Economic Benefits from Reducing U.S. Petroleum Use

Reducing fuel use by requiring cars and light trucks to attain higher fuel economy also produces 

ider benefits to the U.S. economy by lowering the cost of economic externalities that result 

s on human health impacts 

om emissions of criteria air pollutants, and reducing future economic damages from potential 

w

from U.S. petroleum consumption and imports, including reducing the price of petroleum, 

lowering the potential costs from disruption in the flow of oil imports, and possibly reducing 

outlays to support U.S. military activities to secure the flow of oil imports and to cushion the 

economy against their possible interruption by maintaining the Strategic Petroleum Reserve. 

Reducing fuel consumption also lowers the economic costs of environmental externalities 

resulting from fuel production and use, including reducing the impact

fr

changes in the global climate caused by greenhouse gas emissions. 

Economic Externalities from U.S. Petroleum Imports 

U.S. consumption and imports of petroleum products imposes costs on the domestic economy 

that are not reflected in the market price for crude petroleum, or in the prices paid by consumers
409

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

m 

rice; (2) the risk of 

isruptions to the U.S. economy caused by sudden reductions in the supply of imported oil to the 

s 

ing 

esents an additional economic benefit of raising CAFE standards, over and above 

e economic value of saving fuel itself. 

m 

, 

cts 

r 

ate benefits to other oil purchasers by reducing these 

monopsony costs.” 

lex 

of petroleum products such as gasoline. These costs include (1) higher prices for petroleu

products resulting from the effect of U.S. oil import demand on the world oil p

d

U.S.; and (3) expenses for maintaining a U.S. military presence to secure imported oil supplie

from unstable regions, and for maintaining the strategic petroleum reserve (SPR) to cushion 

against resulting price increases.250 

Higher U.S. consumption and imports of crude oil or refined petroleum products can raise the 

magnitude of these external economic costs, thus increasing the true economic cost of supply

transportation fuels above the resource costs of producing them. Conversely, reducing fuel 

consumption by requiring motor vehicles to achieve higher fuel economy will lower U.S. 

consumption and imports of crude petroleum and refined fuels, thus lowering the values of these 

external costs. Any reduction in their value that results from requiring improved vehicle fuel 

economy repr

th

Increased U.S. petroleum consumption can impose higher costs on all purchasers of petroleu

products, because the U.S. is a sufficiently large purchaser of foreign oil supplies that changes in

U.S. demand can affect the world petroleum price. The effect of U.S. petroleum demand on 

world oil prices is determined by the degree of OPEC monopoly power over global oil supplies

and the degree of monopsony power over world oil demand that the U.S. exercises. The 

importance of these two factors means that increases in domestic demand for petroleum produ

that are met through higher oil imports can cause the price of oil in the world market to rise, 

which imposes economic costs on all other purchasers in the global petroleum market in excess 

of the higher prices paid by U.S. consumers.251 Conversely, reducing U.S. oil imports can lowe

the world petroleum price, and thus gener

“

Although the degree of current OPEC monopoly power is subject to considerable debate, the 

consensus appears to be that OPEC remains able to exercise some degree of control over the 

response of world oil supplies to variation in world oil prices, so that the world oil market does 

not behave competitively.252 The extent of U.S. monopsony power is determined by a comp

 

250 See, e.g., Bohi, Douglas R. and W. David Montgomery (1982). Oil Prices, Energy Security, and Import Policy 

Washington, DC: Resources for the Future, Johns Hopkins University Press; Bohi, D. R., and M. A. Toman (1993)

"Energy and Security: Externalities and Policies," Energy Policy 21:1093-1109; and Toman, M. A. (1993). "The 

Economics of Energy Security: Theory, Evidence, Policy," in A. V. Kneese and J. L. Sweeney, eds. (1993). 

Handbook of Natural Resource and Energy Economics, Vol. III. Amsterdam: North-Holland, pp. 1167-1218. 

251 For example, if the U.S. imports 10 million barrels of petroleum per day at a world oil price of $80 per barrel, its 

total daily import bill is $800 million. If increasing imports to 11 million barrels per day causes the world oil price 

to rise to $81 per barrel, the daily U.S

. 

. import bill rises to $891 million. The resulting increase of $91 million per 

ay ($891 million minus $800 million) is attributable to increasing daily imports by only 1 million barrels. This 

1, or $10 more than the newly-increased 

d

means that the incremental cost of importing each additional barrel is $9

world price of $81 per barrel. This additional $10 per barrel represents a cost imposed on all other purchasers in the 

global petroleum market by U.S. buyers, in excess of the price they pay to obtain those additional imports. 

252 For a summary see Leiby, Paul N., Donald W. Jones, T. Randall Curlee, and Russell Lee, Oil Imports: An 

Assessment of Benefits and Costs, ORNL-6851, Oak Ridge National Laboratory, November 1, 1997, at 17. 

Available at http://dmses.dot.gov/docimages/pdf93/343894_web.pdf (last accessed Dec. 2, 2007). 
410

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

FE standards for model 

ears 2005-07 and 2008-11, NHTSA relied on a 1997 study by Oak Ridge National Laboratories 

ternalities from petroleum consumption 

and im rts. More recently, ORNL updated its estimates of the value of these externalities, 

cent 

 oil 

 Fuel 

lue 

f 

U.S. 

st 

imports to $4.52 to 22.65 per barrel, with a most likely estimate of $12.50 per barrel of 

h gallon 

set of factors including the relative importance of U.S. imports in the world oil market, and the 

sensitivity of petroleum supply and demand to its world price among other participants in the 

international oil market. Most evidence appears to suggest that variation in U.S. demand for 

imported petroleum continues to exert some influence on world oil prices, although this 

influence appears to be limited.253 

In analyzing benefits from its recent actions to increase light truck CA

y

(ORNL) to estimate the value of reduced economic ex

254 po

using the analytic framework developed in its original 1997 study in conjunction with re

estimates of the variables and parameters that determine their value. 255 These include world

prices, current and anticipated future levels of OPEC petroleum production, U.S. oil import 

levels, the estimated responsiveness of regional oil supplies and demands to prices in different 

regions of the world, and the likelihood of oil supply disruptions. ORNL’s prepared its updated 

estimates of oil import externalities were for use by EPA in evaluating the benefits of reductions 

in U.S. oil consumption and imports expected to result from its recently-issued Renewable

Standard Rule of 2007 (RFS)256. 

The updated ORNL study was subjected to a detailed peer review, and its estimates of the va

of oil import externalities were subsequently revised to reflect their comments and 

recommendations. 257 Specifically, reviewers recommended that ORNL increase its estimates o

the sensitivity of oil supply by non-OPEC producers and oil demand by nations other than the 

U.S. to changes in the world oil price, as well as reduce its estimate of the sensitivity of U.S. 

gross domestic product (GDP) to potential sudden increases in world oil prices. These revisions 

significantly changed ORNL’s estimates of some components of the external costs of 

petroleum imports. 

At the request of EPA, ORNL further revised its 2008 estimates of external costs from U.S. oil 

imports to reflect recent changes in the outlook for world petroleum prices and continuing 

changes in the structure and characteristics of global petroleum supply and demand. These mo

recent revisions increase ORNL’s estimates of the monopsony cost associated with U.S. oil 

petroleum imported into the U.S. (expressed in 2007$). These estimates imply that eac

of fuel saved as a result of adopting higher CAFE standards that is reflected in lower U.S. 

imports of crude petroleum (or, presumably, refined products) will reduce the monopsony costs 

 

253 Id., at 18-19. 254 Leiby, Paul N., Donald W. Jones, T. Randall Curlee, and Russell Lee, Oil Imports: An Assessment of Benefits 

and Costs, ORNL-6851, Oak Ridge National Laboratory, November 1, 1997. Available at

http://dmses.dot.gov/docimages/pdf93/343894_web.pdf (last accessed Dec. 2, 2007). 

l 

, 

255 Leiby, Paul N. "Estimating the Energy Security Benefits of Reduced U.S. Oil Imports," Oak Ridge National 

Laboratory, ORNL/TM-2007/028, Revised July 23, 2007. Available at http://pzl1.ed.ornl.gov/energysecurity.htm

(click on link below “Oil Imports Costs and Benefits”) (last accessed Sept. 10, 2007). 

256 Federal Register Vol.72, #83, May 1, 2007 pp.23,900-24,014 257 Peer Review Report Summary: Estimating the Energy Security Benefits of Reduced U.S. Oil Imports

ICF, Inc., September 2007. 
411

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ures represent the reduced value of payments from U.S. oil purchasers to foreign oil 

suppliers that results when lower U.S. oil demand reduces the world price of petroleum, beyond 

The second component of external economic costs imposed by U.S. petroleum imports arises 

ported oil 

ly 

nd to occur suddenly rather than 

gradua they can also impose costs on businesses and households for adjusting their use of 

e product of the probability that an oil 

import disruption will occur and the costs of reduced economic output and abrupt adjustment to 

sharply higher petroleum prices – is the appropriate measure of their magnitude. Any reduction 

in the expected value of these costs resulting from a measure that lowers U.S. oil imports 

represents an additional benefit to the U.S. economy beyond the direct value of savings from 

reduced purchases of petroleum products. 

 

imposed by U.S. oil imports by $0.108 to $0.539 per gallon, with the actual value most likely to 

be $0.298 per gallon saved (again in 2007$). 

These fig

the savings from reduced purchases of petroleum itself.258 Consistency with NHTSA’s use of

estimates of the global benefits from reducing emissions of CO2 and other greenhouse gases in 

this analysis, however, requires the use of a global perspective for assessing their net value. 

From this perspective, reducing these payments simply results in a transfer of resources from 

foreign oil suppliers to U.S. purchasers (or more properly, in a savings in the value of resources 

previously transferred from U.S. purchasers to foreign producers), and provides no real savings 

in resources to the global economy. Thus NHTSA’s analysis of the benefits from adopting 

higher CAFE standards for MY 2012-2016 cars and light trucks excludes the reduced value of 

monopsony payments by U.S. oil consumers that might result from lower fuel consumption by 

these vehicles. 

partly because an increase in oil prices triggered by a disruption in the supply of im

reduces the level of output that the U.S. economy can produce. The reduction in potential U.S. 

economic output depends on the extent and duration of the increases in petroleum product prices

that result from a disruption in the supply of imported oil, as well as on whether and how rapid

these prices return to pre-disruption levels. Even if prices for imported oil return completely to

their original levels, however, economic output will be at least temporarily reduced from the 

level that would have been possible without a disruption in oil supplies. 

Because supply disruptions and resulting price increases te

lly, 

petroleum products more rapidly than if the same price increase had occurred gradually over 

time. These adjustments impose costs because they temporarily reduce economic output even 

below the level that would ultimately be reached once the U.S. economy completely adapted to 

higher petroleum prices. The additional costs to businesses and households reflect their inability

to adjust prices, output levels, and their use of energy and other resources quickly and smoothly

in response to rapid changes in prices for petroleum products. 

Since future disruptions in foreign oil supplies are an uncertain prospect, each of these disruption

costs must be adjusted by the probability that the supply of imported oil to the U.S. will actually 

be disrupted. The “expected value” of these costs – th

258 The reduction in payments from U.S. oil purchasers to domestic petroleum producers is not included as a benefit, 

since it represents a transfer that occurs entirely within the U.S. economy. 
412

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

While e vulnerability of the U.S. economy to oil price shocks is widely believed to depend on 

total petroleum consumption rather than o il imports, variation in imports is still 

likely to have some disruption of 

import supply. I gin quan f pet importe the U.S. may also 

affect the probability a . th ely price 

increase or the proba e il imports, the 

expected value of the mic cos ulting pote pply d also 

depend on the level o rts. 

Businesses and house se a va a ech s, includ l futures markets, 

energy conservation m es, and ologi t per id fuel switching to “insure” 

against higher petrole ces and e the ts fo g to price increases. 

While the availability se mark chan as p educed the potential costs of 

disruptions to the sup importe ver onsu of petr roducts are 

unlikely to take accou osts the ose ers, s e costs bably not fully 

reflected in the price orted oi s ch in oi rt leve bly continue to 

ffect the expected co e U.S. ec fr tial ly ns, although this 

each ga on of fuel saved that results in a reduction in U.S. petroleum imports (either crude 

in its e luation of the economic benefits from adopting higher CAFE standards for MY 2012-

ply of imported oil. 

 future 

CAFE standards for light-duty vehicles. U.S. military activities in regions that represent vital 

sources of oil imports also serve a broader range of security and foreign policy objectives than 

th

n the level of o

 effect on the magnitude of price increases resulting from a 

n addition, chan g the tity o roleum d into 

 that such 

bility that U

disruption 

.S. oil supp

will occur

lies will b

 If either 

 disrupted 

e size of the lik

is affected by o

econo ts res from ntial su isruptions will 

f impo

holds u riety of m rket m anism ing oi

easur techn es tha mit rap

um pri

 of the

 reduc

et me

ir cos

isms h

r adjustin

robably r

sudden 

ply of d oil o time, c mers oleum p

nt of c y imp on oth o thes are pro

of imp

st to th

l. Thu

onomy 

anges 

om poten

l impo

oil supp

ls proba

a disruptio

component of oil import costs is likely to be significantly smaller than estimated by studies 

conducted in the wake of the oil supply disruptions that occurred during the 1970s. 

ORNL’s most recently updated and revised estimates of the increase in the expected costs 

associated with oil supply disruptions to the U.S. and the resulting rapid increase in prices for 

petroleum products amount to $3.30 to $11.31 per barrel of imported oil, with a most likely 

estimate of $7.10 per barrel of imports(all figures are in 2007$). According to these estimates, 

ll

petroleum or refined fuel) will reduce the expected costs of oil supply disruptions to the U.S. 

economy by $0.078 to $0.269, with the actual value most likely to be $0.169 per gallon (again in 

2007$). Unlike the reduction in monopsony payments that results from lower U.S. petroleum 

imports, however, the reduction in these expected disruption costs represents a real savings in 

resources, and thus contributes economic benefits in addition to the savings in resource costs for

fuel production that would result from increasing fuel economy. NHTSA employs these values 

va

2016 cars and light trucks. 

The third component of the external economic costs of importing oil into the U.S. includes 

government outlays for maintaining a military presence to secure the supply of oil imports from

potentially unstable regions of the world and protect against their interruption. Some analysts 

also include outlays for maintaining the U.S. Strategic Petroleum Reserve (SPR) as an additional 

cost of U.S. dependence on oil imports, since the SPR is intended to cushion the U.S. economy 

against the consequences of disruption in the sup

NHTSA currently believes that while costs for U.S. military security may vary over time in 

response to long-term changes in the actual level of oil imports into the U.S., these costs are 

unlikely to decline in response to any reduction in U.S. oil imports resulting from raising
413

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

dards. 

either the Congress nor the Executive Branch has ever attempted to calibrate U.S. military 

ble, or to some calculation of 

ed 

an 

ports in order to investigate its impacts on the standards and fuel savings. Assuming that the 

07 

mploys 

 supply disruption may be related to the level of U.S. oil consumption 

imports. 

osts in 

 not 

’s 

st 

This view 

 which 

ernment outlays for these purposes are unlikely to result from 

lting 

orts 

of refined petroleum products among the Reference Case, High Economic Growth, and Low 

s presented in the Energy Information Administration’s Annual 

simply protecting oil supplies, and as a consequence are unlikely to vary significantly in 

response to changes in the level of oil imports prompted by higher stan

N

expenditures, force levels, or deployments to any oil market varia

the projected economic consequences of hostilities in the Persian Gulf. Instead, changes in U.S. 

force levels, deployments, and thus military spending in that region have been largely govern

by political events, emerging threats, and other military and political considerations, rather th

by shifts in U.S. oil consumption or imports. NHTSA thus concludes that the levels of U.S. 

military activity and expenditures are likely to remain unaffected by even relatively large 

changes in light duty vehicle fuel consumption. As a consequence, the agency’s analysis of 

alternative CAFE standards for MY 2012-2016 does not include savings in budgetary outlays to 

support U.S. military activities among the benefits of higher fuel economy and the resulting fuel 

savings. 

Nevertheless, the agency conducted a sensitivity analysis of the potential effect of assuming that 

some reduction in military spending would result from fuel savings and reduced petroleum 

im

preceding estimate of total U.S. military costs for securing Persian Gulf oil supplies is correct, 

and that approximately half of these expenses could be reduced in proportion to a reduction in 

U.S. oil imports from the region, the estimated savings would range from $0.02 to $0.08 (in 20

dollars) for each gallon of fuel savings that was reflected in lower U.S. imports of petroleum 

from the Persian Gulf. If the Persian Gulf region is assumed to be the marginal source of supply 

for U.S. imports of crude petroleum and refined products, then each gallon of fuel saved might 

reduce U.S. military outlays by $0.05 per gallon, the midpoint of this range. NHTSA e

this estimate in its sensitivity analysis. 

Similarly, while the optimal size of the SPR from the standpoint of its potential influence on 

domestic oil prices during a

and imports, its actual size has not appeared to vary in response to recent changes in oil 

Thus while the budgetary costs for maintaining the Reserve are similar to other external c

that they are not likely to be reflected in the market price for imported oil, these costs do

appear to have varied in response to changes in oil import levels. As a result, the agency

analysis of benefits from alternative CAFE standards for MY 2012-2016 does not include co

savings from maintaining a smaller SPR among the external benefits of reducing gasoline 

consumption and petroleum imports by means of tightening future CAFE standards. 

concurs with that of the recent ORNL study of economic costs from U.S. oil imports,

concludes that savings in gov

reductions in consumption of petroleum products and oil imports on the scale of those resu

from higher CAFE standards. 

The Impact of Fuel Savings on U.S. Petroleum Imports 

Based on a detailed analysis of differences in fuel consumption, petroleum imports, and imp

Economic Growth Scenario

Energy Outlook 2009, NHTSA estimates that approximately 50 percent of the reduction in fuel 
414

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

 reduced 

ected in 

 U.S. 

k, while the remaining 10 percent is 

xpected to reduce U.S. domestic production of crude petroleum.260 Thus on balance, each 

tal 

consumption resulting from adopting higher CAFE standards is likely to be reflected in

U.S. imports of refined fuel, while the remaining 50 percent would be expected to be refl

reduced domestic fuel refining.259 Of this latter figure, 90 percent is anticipated to reduce

imports of crude petroleum for use as a refinery feedstoc

e

gallon of fuel saved as a consequence of higher CAFE standards is anticipated to reduce to

U.S. imports of crude petroleum or refined fuel by 0.95 gallons.261 

The Economic Value of Reducing CO2 Emissions

NHTSA has taken the economic benefits of reducing CO2 emission into account in this 

lemaking, both in developing alternative CAFE standards and in assessing the economic 

 benefits 

terature on 

age” of 

enefits 

ental 

es in 

h, 

ue of 

 usually expressed in dollars per additional metric ton of CO2

missions occurring during a specified year, and is higher for more distant future years because 

ual, 

lf. 

e 

used by U.S. federal agencies in regulatory evaluations. Under Executive Order 12866, federal 

agencies are required, to the extent permitted by law, “to assess both the costs and the benefits of 

antify, 

e 

f the 

 

ru

benefits of each alternative that was considered. Since direct estimates of the economic

from reducing CO2 or other GHG emissions are generally not reported in published li

the impacts of climate change, these benefits are typically assumed to be the “mirror im

the estimated incremental costs resulting from an increase in those emissions. Thus, the b

from reducing CO2 emissions are usually measured by the savings in estimated economic

damages that an equivalent increase in emissions would otherwise have caused. 

The “social cost of carbon” (SCC) is intended to be a monetary measure of the increm

damage resulting from increased carbon dioxide (CO2) emissions, including loss

agricultural productivity, the economic damages caused by adverse effects on human healt

property losses and damages resulting from sea level rise, and changes in the economic val

ecosystem services. The SCC is

e

the damages caused by an additional ton of emissions increase with larger existing 

concentrations of CO2 in the earth’s atmosphere. Reductions in CO2 emissions that are projected 

to result from lower fuel consumption, refining, and distribution during each future year are 

multiplied by the estimated SCC appropriate for that year, which is used to represent the value of

eliminating each ton of CO2 emissions, to determine the total economic benefit from reduced

emissions during that year. These benefits are then discounted to their present value as us

using a discount rate that is consistent with that used to develop the estimate of the SCC itse

For this final rule, NHTSA has relied on estimates of the SCC developed by a federal 

interagency working group convened for the specific purpose of developing new estimates to b

the intended regulation and, recognizing that some costs and benefits are difficult to qu

propose or adopt a regulation only upon a reasoned determination that the benefits of th

intended regulation justify its costs.” The group’s purpose in developing new estimates o

 

 Differences between forecast annual U.S. imports of crude petroleum and refined products among these three 

-

petroleum, and average 85% over the forecast period spanned by 

259

scenarios range from 24-89% of differences in projected annual gasoline and diesel fuel consumption in the U.S. 

These differences average 49% over the forecast period spanned by AEO 2009. 260 Differences between forecast annual U.S. imports of crude petroleum among these three scenarios range from 67

97% of differences in total U.S. refining of crude 

AEO 2009. 261 This figure is calculated as 0.50 + 0.50*0.9 = 0.50 + 0.45 = 0.95. 
415

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ide 

ve small, or “marginal,” 

pacts on cumulative global emissions, as most federal regulatory actions can be expected to 

re the 

nerate 

d 

 

reflect increasing knowledge of the science and economics of climate 

pacts. Technical experts from numerous agencies met on a regular basis to consider public 

 literature. In 

5 percentile SCC estimate across all 

ree models at a 3 percent discount rate, is included to represent the possibility of higher-thanapproximation that is reasonable for policies that have effects on emissions that are small relative 

SCC was to allow federal agencies to incorporate the social benefits of reducing carbon diox

(CO2) emissions into cost-benefit analyses of regulatory actions that ha

im

have. 

The interagency group convened on a regular basis to consider public comments, explo

technical literature in relevant fields, and discuss key inputs and assumptions in order to ge

SCC estimates. Agencies that actively participated in the interagency process included the

Environmental Protection Agency, and the Departments of Agriculture, Commerce, Energy, 

Transportation, and Treasury. This process was convened by the Council of Economic Advisers 

and the Office of Management and Budget, with active participation and regular input from the 

Council on Environmental Quality, National Economic Council, Office of Energy and Climate 

Change, and Office of Science and Technology Policy. The main objective of this process was 

to develop a range of SCC values using a defensible set of input assumptions that are grounde

in the existing literature. In this way, key uncertainties and model differences can more 

transparently and consistently inform the range of SCC estimates used in the rulemaking process.

The interagency group developed its estimates of the SCC estimates while clearly 

acknowledging the many uncertainties involved, and with a clear understanding that they should

be updated over time to 

im

comments, explore the technical literature in relevant fields, and discuss key model inputs and 

assumptions. The main objective of this process was to develop a range of SCC values using a

defensible set of input assumptions grounded in the existing scientific and economic

this way, key uncertainties and model differences transparently and consistently can inform the 

range of SCC estimates used in the rulemaking process. 

The group ultimately selected four SCC values for use in regulatory analyses. Three values are 

based on the average SCC from three integrated assessment models, using discount rates of 2.5, 

3, and 5 percent. The fourth value, which represents the 9 th

th

expected impacts from temperature change that lie further out in the tails of the distribution of 

SCC estimates. Table VIII-7 summarizes the interagency group’s estimates of the SCC during 

various future years. The SCC estimates reported in the table assume that the marginal damages 

from increased emissions are constant for small departures from the baseline emissions path, an 

to cumulative global carbon dioxide emissions. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VIII-7 

Social Cost of CO2 Emissions, 2010 – 2050 (2007 dollars) 

Discount Rate 5% 3% 2.5% 3% 

Source Average Average Average 95th Percentile

2010 4.7 21.4 35.1 64.9 

2015 5.7 23.8 38.4 72.8 

2020 6.8 26.3 41.7 80.7 

2025 8.2 29.6 45.9 90.4 

2030 9.7 32.8 50.0 100.0 

2035 11.2 36.0 54.2 109.7 

2040 12.7 39.2 58.4 119.3 

2045 14.2 42.1 61.7 127.8 

2050 15.7 44.9 65.0 136.2 

As Table VIII-7 shows the four SCC estimates selected by the interagency group for use in 

regulatory analyses are $5, $21, $35, and $65 (in 2007 dollars) for emissions occurring in the 

year 2010. The first three estimates are based on the average SCC across models and socioconomic and emissions scenarios at the 5, 3, and 2.5 percent discount rates, respectively. The 

impacts from temperature change 

rther out in the tails of the SCC distribution. For this purpose, the group elected to use the 

3 

e 

, the 

s 

ed for 

e

fourth value is included to represent the higher-than-expected 

fu

SCC value for the 95th percentile at a 3 percent discount rate. 

The central value identified by the interagency group is the average SCC across models at the 

percent discount rate, or $21 per metric ton in 2010. To capture the uncertainties involved in 

regulatory impact analysis, however, the group emphasized the importance of considering th

full range of estimated SCC values. As the table also shows, the SCC estimates also rise over 

time; for example, the central value increases to $24 per ton of CO2 in 2015 and $26 per ton of 

CO2 in 2020. 

The interagency process is committed to updating these estimates as the science and economic

understanding of climate change and its impacts on society improves over time. Specifically

group have set a preliminary goal of revisiting the SCC values within two years or at such time 

as substantially updated models become available, and to continue to support research in thi

area. U.S. federal agencies will periodically review and reconsider estimates of the SCC us

cost-benefit analyses to reflect increasing knowledge of the science and economics of climate 

impacts, as well as improvements in modeling. 

Details of the process used by the interagency group to develop its SCC estimates, complete 

results including year-by-year estimates of each of the four values, and a thorough discussion of 

their intended use and limitations is provided in the document Social Cost of Carbon for 
417

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

s 

s 

, 

increase 

he net effect of stricter CAFE standards on total emissions 

 emission 

ated 

the fuel 

conomy rebound effect. 

Emission factors in the MOVES database are expressed in the form of grams per vehicleRegulatory Impact Analysis Under Executive Order 12866, Interagency Working Group on 

Social Cost of Carbon, United States Government, February 2010.262

Benefits from Reducing Emissions of Criteria Air Pollutants 

Car and light truck use, fuel refining, and fuel distribution and retailing also generate emission

of certain criteria air pollutants, including carbon monoxide (CO), hydrocarbon compound

(usually referred to as “volatile organic compounds,” or VOC), nitrogen oxides (NOx), fine 

particulate matter (PM2.5), and sulfur dioxide (SO2). While reductions in fuel refining and 

distribution that result from lower fuel consumption will reduce emissions of criteria pollutants

additional vehicle use associated with the rebound effect from higher fuel economy will 

emissions of these pollutants. Thus t

of each criteria pollutant depends on the relative magnitudes of reduced emissions in fuel 

refining and distribution, and increases in emissions from vehicle use. Because the relationship 

between emission rates (emissions per gallon refined of fuel or mile driven) in fuel refining and 

vehicle use is different for each criteria pollutant, the net effect of fuel savings from increased 

CAFE standards on total emissions of each pollutant is likely to differ. 

NHTSA estimates the increase in emissions of each criteria air pollutant from additional vehicle 

use by multiplying the increase in total miles driven by cars and light trucks of each model year 

and age by their estimated emission rates per vehicle-mile of each pollutant. These

rates differ between cars and light trucks as well as between gasoline and diesel vehicles, and 

both their values for new vehicles and the rates at which they increase with age and accumul

mileage can vary among model years. With the exception of SO2, NHTSA calculated the 

increase in emissions of these criteria pollutants from added car and light truck use by 

multiplying the estimated increases in their vehicles’ use during each year over their expected 

lifetimes by per-mile emission rates appropriate to each vehicle type, fuel used, model year, and 

age as of that future year. 

These emission rates were developed by U.S. EPA using its recently-developed Motor 

Vehicle Emission Simulator (MOVES 2010). The MOVES model assumes that the permile rates at which these pollutants are emitted are determined by EPA regulations and 

the effectiveness of catalytic after-treatment of engine exhaust emissions, and are thus 

unaffected by changes in car and light truck fuel economy. As a consequence, the effects 

of required increases in fuel economy emissions of these pollutants from car and light 

truck use are determined entirely by the increases in driving that result from 

e

hour of operation. To convert these emission factors to grams per mile for use in 

NHTSA’s calculations, MOVES was run for the year 2050, and was programmed to 

report aggregate emissions from vehicle start and running exhaust. EPA analysts selected 

the year 2050 in order to generate emission factors that were representative of lifetime 

 

262 This document is available at 

http://www2.eere.energy.gov/buildings/appliance_standards/commercial/pdfs/sem_finalrule_appendix15a.pdf (last 

accessed March 2, 2010). 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ollutant. The resulting emission rates represent average values across the nation, and 

corporate typical temperature variations over an entire calendar year. These national 

pecific differences in fuel composition, as well as in the 

resence and type of vehicle inspection and maintenance programs.264 

ght trucks that is projected to occur under that alternative. As with other impacts, the 

rude oil extraction and transportation, fuel refining, and fuel storage and 

ansportation. The reduction in emissions during each of these phases depends on the extent to 

 

 imported crude oil as a feedstock are assumed to reduce emissions during fuel 

fining, storage, and distribution, because each of these activities would be reduced. Finally, 

average emission rates for vehicles meeting the agency’s Tier 2 emission standard.263 

Separate estimates were developed for each vehicle type and model year, as well as for 

each state and month, in order to reflect the effects of regional and temporal variation in 

temperature and other relevant variables on emissions. 

The MOVES emissions estimates were then summed to the model year level and divided

by average distance traveled in order to produce per-mile emission factors for each 

p

in

average rates also reflect county-s

p

Emission rates for the criteria pollutant SO2 were calculated by NHTSA using average 

fuel sulfur content estimates supplied by EPA, together with the assumption that the 

entire sulfur content of fuel is emitted in the form of SO2. These calculations assumed 

that national average gasoline and diesel sulfur levels would remain at current levels.265 

Total SO2 emissions under each alternative CAFE standard were calculated by applying 

the resulting emission rates directly to annual gasoline and diesel fuel use by cars and 

li

changes in emissions of criteria air pollutants resulting from alternative increases in 

CAFE standards for MY 2012-2016 cars and light trucks were calculated as the 

difference between emissions under each alternative that would increase CAFE standards 

and emissions under the baseline alternative, which would extend the MY 2011 standards 

to apply to future model years. 

Emissions of criteria air pollutants also occur during each phase of fuel production and 

distribution, including c

tr

which fuel savings result in lower imports of refined fuel, or in reduced domestic fuel refining.

To a lesser extent, they also depend on whether reductions in domestic gasoline refining are 

reflected in reduced imports of crude oil or in reduced domestic extraction of petroleum. 

NHTSA’s analysis assumes that reductions in imports of refined fuel would reduce criteria

pollutant emissions during fuel storage and distribution only. Reductions in domestic fuel 

refining using

re

 

263 Because all light-duty emission rates in MOVES 2010 are assumed to be invariant after MY 2010, a 

calendar-year 2050 run produced a full set of emission rates that reflect anticipated deterioration in the 

effectiveness of vehicles’ emission control systems with increasing age and accumulated mileage for postMY 2010 vehicles. 

264 The national mix of fuel types includes county-level market shares of conventional and reformulated gasoline, as 

well as county-level variation in sulfur content, ethanol fractions, and other fuel properties. Inspection/maintenance 

programs at the county level account for detailed program design elements such as test type, inspection frequency, 

gram coverage by vehicle type and age. 

ams per gallon of diesel. 

and pro

265 These are 30 and 15 parts per million (ppm, measured on a mass basis) for gasoline and diesel respectively, 

which produces emission rates of 0.17 grams of SO2 per gallon of gasoline and 0.10 gr
419

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

uring all four phases of fuel production and distribution.266

 

ass 

e estimates of fuel energy content reported by GREET. The resulting emission rates 

ere applied to the agency’s estimates of fuel consumption under each alternative CAFE 

tandard to develop estimates of total emissions of each criteria pollutant during fuel production 

nges in fuel consumption on domestic 

nd imported sources of fuel supply discussed above were then employed to calculate the effects 

mestic emissions of 

ach criteria pollutant. 

Finally, NHTSA calculated the net changes in domestic emissions of each criteria pollutant by 

summing the increases in its emissions projected to result from increased vehicle use, and the 

reductions in emissions anticipated to result from lower domestic fuel refining and 

distribution.269 As indicated previously, the effect of adopting higher CAFE standards on total 

emissions of each criteria pollutant depends on the relative magnitudes of the resulting reduction 

in emissions from fuel refining and distribution, and the increase in emissions from additional 

vehicle use. Although these net changes vary significantly among individual criteria pollutants, 

the agency projects that on balance, adopting higher CAFE standards would reduce emissions of 

all criteria air pollutants except carbon monoxide (CO). 

The net changes in domestic emissions of fine particulates (PM2.5) and its chemical precursors 

(such as NOx, SOx, and VOCs) are converted to economic values using estimates of the 

reductions in health damage costs per ton of emissions of each pollutant that is avoided, which 

were developed and recently revised by EPA. These savings represent the estimated reductions 

 

reduced domestic fuel refining using domestically-produced crude oil is assumed to reduce 

emissions d

NHTSA estimated the reductions in criteria pollutant emissions from producing and distributing

fuel that would occur with alternative CAFE standards using emission rates obtained by EPA

from Argonne National Laboratories’ Greenhouse Gases and Regulated Emissions in 

Transportation (GREET) model.267 The GREET model provides separate estimates of air 

pollutant emissions that occur in four phases of fuel production and distribution: crude oil 

extraction, crude oil transportation and storage, fuel refining, and fuel distribution and storage.268

EPA modified the GREET model to change certain assumptions about emissions during crude 

petroleum extraction and transportation, as well as to update its emission rates to reflect adopted

and pending EPA emission standards. The agency converted these emission rates from the m

per fuel energy content basis on which GREET reports them to mass per gallon of fuel supplied

using th

w

s

and distribution. The assumptions about the effects of cha

a

of reductions in fuel use from alternative CAFE standards on changes in do

e

266 In effect, this assumes that the distances crude oil travels to U.S. refineries are approximately the same regardless 

of whether it travels from domestic oilfields or import terminals, and that the distances that gasoline travels from 

refineries to retail stations are approximately the same as those from import terminals to gasoline stations. 

267 Argonne National Laboratories, The Greenhouse Gas and Regulated Emissions from Transportation (GREET) 

Model, Version 1.8, June 2007, available at http://www.transportation.anl.gov/software/GREET/index.html (last 

accessed April 20, 2008). 

268 Emissions that occur during vehicle refueling at retail gasoline stations (primarily evaporative emissions of 

volatile organic compounds, or VOCs) are already accounted for in the “tailpipe” emission factors used to estimate 

the emissions generated by increased light truck use. GREET estimates emissions in each phase of gasoline 

production and distribution in mass per unit of gasoline energy content; these factors are then converted to mass per 

gallon of gasoline using the average energy content of gasoline. 

269 All emissions from increased vehicle use are assumed to occur within the U.S., since CAFE standards would 

apply only to vehicles produced for sale in the U.S. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

in the value of damages to human health lower atmospheric concentrations and 

population expos t that contributes 

to atmospheric PM2.5 concentrations are red d. The value of reductions in the risk of 

premature death due to exposure to fine particu pollution (PM2.5) account for a majority of 

EPA’s es 5 related emissions, although the val avoiding 

other hea so included in these estimates se values 

do not i s reduction in re and 

environm and welfare related to 

other crit d air toxics. EPA estimates d rent PMrelated pe vehicle use than for reductio missions 

of that occu and distribution. NHTSA applies these sepa es to its 

estimates ction and bution to 

determine ese pol 

EPA projec reducing emissions of criteria pol om both 

mobile sou nd stationary sources such as f eries and 

storage fa flect risin e levels, 

which are for reduced re to 

health threa population growth, which incr opulation 

exposure to

D Add

 resulting from

ure to air pollution that occur when emissions of each pollutan

uce

late 

timated values of reducing PM2. ue of 

lth impacts related to PM2.5 exposure is al . The

nclude a number of unquantified benefits, such a

ctions in health 

the welfa

ental impacts of PM2.5 pollution, or redu impacts 

eria pollutants (ozone, NO2, and SO2) an iffe

r-ton values for reducing emissions from ns in e

r during fuel production rate valu

 of changes in emissions from vehicle use and fuel produ distri

 the net change in total economic damages from emissions of th lutants. 

ts that the per-ton values for lutants fr

rces (including motor vehicles) a ue

lities will increase over time. Thes

l refin

ci e projected increases re g incom

 assumed to increase affected individuals’ willingness to pay exposu

ts from air pollution, as well as future es p

 future levels of air pollution. 

eas

ed Costs from Congestion, Crashes, and Noise

While it pro d w 

economy re ntribute to increased traffic congestion, m e 

crashes, and n contribute to traffic conge 

delays by in y-traveled roadways during el 

periods, d and on where it 

occurs. B g the number of crashes and disabled vehicles, added driving can also 

increase the ften result from these incidents, although the extent to ally 

does so agai n when and where the added travel occurs. 

In either cas e higher costs on drivers and other vehicle oc the 

form of in considered as an 

additiona mic cost associated with the rebound effect. Because drivers do not take these 

added costs eciding when to make trips or where they travel, th be 

accounted f y as a cost of the added driving associated with the rebou

Increased p truck use due to the rebound effect may also in e costs 

associated ccount of the potential co ey (and 

the other oc ssi ity of being involved in a crash when 

they decide to make additional trips. However, they probably do not consider all of the potential 

y 

vides some benefits to drivers, increased vehicle use associate ith the fuel

bound effect can also co otor vehicl

 highway noise. Additional vehicle use ca stion and

creasing recurring congestion on heavil peak trav

epending on how the additional travel is distributed over the day

y increasin

 delays that o which it actu

n depends o

e, added delays impos cupants in 

creased travel time and operating expenses, and these should be

l econo

into account in d ey must 

or separatel nd effect. 

assenger car and light crease th

 with traffic crashes. Drivers presumably take a

cupants of their vehicles) face from the po bil

sts th

costs they impose on occupants of other vehicles and on pedestrians when crashes occur, so an

increase in these “external” crash costs must be considered as another cost of additional reboundeffect driving. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Like in eased delay costs, any increase in these external crash costs caused by added driving is 

likely t epend on the traffic conditions under which it takes place, since crashes are more 

frequen heavier traffic, but their severity may be reduced by the slower speeds at which 

heavier Thus estimates of the increase in external crash costs from the 

bound effect also need to account for when and where the added driving occurs. 

f 

nd 

nomic costs on those it affects, and 

ese added costs are unlikely to be taken into account by drivers of the vehicles that cause it. 

d 

 in 

e of cars and light trucks that are borne 

y persons other than their drivers. FHWA’s “Middle” estimates for congestion, crash, and 

s 

ee closely with some other 

recent estimates. For example, recent published search conducted by Resources for the Future 

ese 

cr

o d

t in

 traffic typically moves. 

re

Finally, added vehicle use from the rebound effect may also increase traffic noise. Noise 

generated by vehicles causes inconvenience, irritation, and potentially even discomfort to 

occupants of other vehicles, to pedestrians and other bystanders, and to residents or occupants o

surrounding property. Because none of these effects are likely to be taken into account by the 

drivers whose vehicles contribute to traffic noise, they represent additional externalities 

associated with motor vehicle use. 

Although there is considerable uncertainty in estimating its value, the added inconvenience a

irritation caused by increased traffic noise imposes some eco

th

Thus any increase in noise costs resulting from added vehicle use must be included together with

other increases in external costs of additional rebound-effect driving. 

NHTSA’s analysis uses estimates of the congestion, crash, and noise costs caused by increase

travel in automobiles, pickup trucks, and vans developed by the Federal Highway 

Administration.270 These estimates are intended to measure the increases in external costs – that 

is, the “marginal” external costs – from added congestion, property damages and injuries

traffic crashes, and noise levels caused by additional usag

b

noise costs imposed by passenger cars are 5.4 cents, 2.3 cents and 0.1 cents per additional 

vehicle mile when expressed in 2007 dollars.271 For pickup trucks and vans, FHWA’s estimate

correspond to 4.8 cents, 2.6 cents, and 0.1 cents per additional vehicle-mile. 

The Federal Highway Administration’s estimates of these costs agr

 re

(RFF) estimates marginal congestion and external crash costs for increased light-duty vehicle use 

in the U.S. to be 3.9 and 3.4 cents per vehicle-mile when converted to 2007 dollars.272 Th

estimates incorporate careful adjustments of congestion and crash costs that are intended to 

reflect the traffic conditions under which additional driving is likely to take place, as well as its 

likely effects on both the frequency and severity of motor vehicle crashes. 

 

0

 These estimates were developed by FHWA for use in its 1997 Federal Highway Cost Allocation Study. 

 Federal Highway Administration, 1997 Federal Highway Cost Allocation Study, Tables V-22, V-23, and V-24, 

http://www.fhwa.dot.gov/policy/hcas/final/index.htm

27

 

271

. The higher congestion cost for automobiles than for light 

trucks reflects the larger fraction of auto than of light truck use that occurs within congested urban areas. 272 Ian W.H. Parry and Kenneth A. Small, “Does Britain or the U.S. Have the Right Gasoline Tax?” Discussion 

Paper 02-12, Resources for the Future, March 2002, pp. 19 and Table 1, http://www.rff.org/rff/Documents/RFF-DP02-12.pdf. 
422

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

FHWA’s estimates of added costs for con s , and noise are multiplied by the 

estimated increa e affected 

model years’ lifetimes to yield the estim estion, crash, and noise externality 

sts. The resulting yearly estimates are then summed to obtain their lifetime values. The value 

of these increased costs varies among mode the alternative increases in CAFE 

stand in this ec es in v depend o

improvements in fuel econom uld re pecifi

e Discount R

gestion, crashe

ses in passenger car and light truck use due during each year of th

ated increases in cong

co

l years and 

ards considered analysis, b

y that wo

ause the increas

sult in s

ehicle use

c model years unde

n the 

r each alternative. 

E. Th ate

Discounting future fuel sa

their value to society whe

immediately. The di

vi er benefits is intended to account for the reduction in 

n ferred u me future da her than receiv

scount s the percent decline in the value of these benefits – as 

rspe ch ye y are deferre the future. In ting 

ative in CAFE standards for MY 2012-2016 passenger cars and 

as em iscoun f 3% per yea agency has a ed 

 of these benefi t estimates to the use of a 7 percent discount rate. 

The primary reason that NH ected 3 percent as the appropriate rate for discounting 

s from increas tandards at most or all hicle manufact ’ costs 

ith higher C dards are likely to be reflected in higher sales pr for 

icle models. B g sale for new ca ight trucks, C

ll thus primaril hicle pu and other pr consumption de ons. 

economic theory and nce on nting indica the future ben nd 

 of regulations that main private c ption should discounted at the ial rate 

e preference.273 

guidance also indic appea count future consumption at an ge 

at is, adjusted to rem ct of i n) rate of abo ercent when th ce 

 about its likely le akes i onable estim f the social rate e 

ce.274 Thus NHTSA ha mployed t ent rate to t projected f

resulting from igher CAFE standards for MY 6 passeng nd 

ght trucks. 

 

One important exception to the 3% discount rate the rates used to discount benefits from 

reducing CO2 emissions from the years in which reduced emissions occur, which span the 

lifetimes of model year 2012-16 cars and light trucks, to their present values. In order to ensure 

consistency in the derivation and use of the interagency group’s estimates of the unit values of 

reducing CO2 emissions, the benefits from reducing those emissions during each future year are 

discounted using the same “intergenerational” discount rates that were used to derive each of the 

alternative unit values of reducing CO2 emissions. As Table VIII-7 above shows, these rates are 

5 percent for the interagency group’s lowest estimate of the SCC, 3 percent for its central and 

 

ngs and oth

they are de ntil so te, rat ed 

 rate expresse

ctive – for ea

 increases

viewed from today’s pe ar the d into evalua

the benefits from altern

light trucks, NHTSA h

the sensitivity

ployed a d

t and co

t rate o r. The lso test

s

TSA has sel

future benefit

for complying w

ed CAFE s

AFE stan

 is th of ve urers

ices

their new veh

regulation wi

y increasin

y affect ve

s prices

rchases

rs and l

ivate

AFE 

cisi

Both OMB guida discou te that efits a

costs

of tim

ly affect onsum be soc

OMB ates that savers r to dis avera

real (th ove the effe nflatio ut 3 p ey fa

little risk vel, which m t a reas ate o of tim

preferen

enefits and costs 

s e

h

he 3 perc discoun

 2012-201

uture 

b er cars a

li

273 Id. 274 Office of Management and Budget, Circular A-4, “Regulatory Analysis,” September 17, 2003, 33. Available at

http://www.whitehouse.gov/omb/circulars/a004/a-4.pdf (last accessed July 24, 2009).
423

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

highest estimates, and 5 percent for the esti tween the group’s central and highest 

estim

Because there is some uncertainty about the extent to which veh nufacturers w

to recover their costs for complying with higher CAFE standards by increasing vehicle sales 

r, NHTSA ha the sensitivity of these benefit and cost estimates to the 

 percent disco B indicates econom

l i riate discount rate to apply to future benefits and costs 

f is “... ace or alter pital in ate 

s that ently averages about 7 percent.275 Thus the agency has 

o nd co ates for alte MY 2012-20 FE 

a 7 pe discount rate. NHTSA seeks comment on whether it 

FE stand a disco of 3 perce ercent, or an a ive 

mary of Valu timat its

mate lying be

ates. 

icle ma ill be able 

prices, howeve

use of a higher

s also tested 

unt rate. OM guidance that the real y-wide 

opportunity cost of capita

when the primary effect o

sector,” and estimate

s the approp

a regulation to displ the use of ca the priv

this rate curr

f its benefit a

rcent rea

also tested the sensitivity st estim rnative 16 CA

standards to the use of 

should evaluate CA

value. 

l

ards using unt rate nt, 7 p lternat

F. Sum es used to Es e Benef

marizes th value estimate b . 

 

Table VIII-8 sum e economic s used to enefits

275 Id. 
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T 

nomic se ompu 2007$) 

Fuel Economy Rebound Effect 10%

able VIII-8

Eco Values U d for Benefits C tations (

"Gap" between t -road est and on MPG 20%

Value of refueling r ($ pe -hour) time pe r vehicle $ 24.64

Annual growth in average vehicle use 1.15%

Fuel Prices (2012 ge, $/g -50 avera allon) 

Retail gasoline price $3.66

Pre-tax gasoline price $3.29

Economic Benefi du ts from Re cin ports ($/ga g Oil Im llon) 

"Monopsony" Component $ 0.00

Price Shock Component $ 0.17

Military Security ent Compon $ 0.00

Total Economic Costs ($/gallon) $ 0.17

Emission Damage Costs (weighted $/metric , $/ton or ton)

Carbon monoxide $ 0

Volatile organic ds (VO compoun C) $ 1,300 

Nitrogen oxide ehicle s (NOx) – v use $ 5,300

Nitrogen oxides fuel produ and distribution $5,100 (NOx) – ction 

Particulate matter (PM2.5) – vehicle use $ 290,000

Particulate matter (PM2.5) – fuel pr tion and distri n $ 240,00 oduc butio 0

Sulfur dioxide (SO2) $ 31,000

Carbon dioxide (CO2) emissions in 2010 $ 21

Annual Increase in CO2 Damage Cost variable

External Costs from Additional bile Use ( -

mile) 

 Automo $/vehicle

Congestion $ 0.054

Accidents $ 0.023

Noise $ 0.001

Total External Costs $ 0.078

External Costs from Additional Light Truck Use ($/vehiclemile) 

Congestion $0.048

Accidents $0.026

Noise $0.001

Total External Costs $0.075

Discount Rate Applied to Future Benefits276 3%

 

276 Future benefits from reducing CO2 emissions are discounted using the same “intergenerational” discount rates 

that were used to derive each of the alternative SCC estimates used to value reductions in those emissions. As Table 

VIII-7 above shows, these rates are 5 percent for the interagency group’s lowest estimate of the SCC, 3 percent for 

its central and highest estimates, and 5 percent for the estimate lying between the group’s central and highest 

estimates. 
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G. Benefits Estimates

alculated sep passenger cars and light trucks under each alternative 

ent for each cove is proposa les VIII-9 10, 

s nd light truck CAFE standards under the preferred 

o 12-20 tables in ndiscounted

ent val ted 3 percent. They also show changes in the physical 

odu lues. e values in bles reflect 

onsumpti ssions and their resulting economic impacts, which 

om the p hile p alues repre reasing emis

ise or crash sev their added costs. The net social benefit from these 

shown o ine in e. 

ative fo cars w ave 35.7 billi llons of fuel an vent 

380 million metric tons of ta emissions over the lifetime of the passenger cars sold 

ears, c the fu gs and emis eductions tha 

ndards remain adjusted b e for MYs . The pr

ative for light trucks 4 b llons of fue event 275 million metric 

 tailpipe CO2 emission e lifetime e light trucks during those model years, 

pared to the fuel savings ssions red ns that would o if the standard

ed at the adjusted b s 201 6. 

total value of societal e prefe lternative fo nger cars and rucks 

2 billion277 over the MY Thi ate of societa fits 

es direct impacts from ons as well as ies, and al s 

 societal costs resulting from the reb ect. Fuel sav account for t 

nd CO2 emissions account for 8 percent of the societal benefits. 

Tables VIII-11 and VIII-12 summarize the societal benefits for all alternatives for passenger cars 

and light trucks at the 3 percent and 7 percent discount rates, respectively. As would be 

expected, benefit levels parallel the increasing stringency of the various alternatives that were 

examined. The TC=TB scenario produces benefits that exceed the other alternatives because that 

methodology allows technologies that are cost effective to pay for some technologies that are not 

cost effective. Table VIII-13 summarizes the fuel savings from all alternatives for passenger 

cars and light trucks. 

 

Benefits were c

CAFE requirem

arately for

model year red by th l. In Tab and VIIIthe societal impacts for pa

alternative is shown for m

well as their net pres

senger car a

del years 20 16. These clude u values as 

ues discoun

ced these va

on or emi

units of measure that pr Negativ these ta net 

reductions in fuel c

represent benefits fr

congestion, no

roposal, w

erity an

ositive v sent inc sions, 

d

societal impacts is n the Total l each tabl

The preferred altern r passenger 

ilpipe CO

ould s on ga d pre

2

ompared to 

ed at the 

during those model y

occur if the sta

el savin

aselin

sions r

2012-2016

t would

eferred 

altern would save 25. illion ga l and pr

tons of

com

s over th

and emi

 of th

uctio

sold

ccur s 

remain aseline for MY 2-201

The benefits of th rred a r passe light t

is $18 lifetime of the

low uel c

2012-16 fleet. s estim l bene

includ

ffsetting

er f umption 

ound eff

 externalit

ings 

so reflect

o 78 percen

a

277 The $182 billion estimate is based on a 3% discount rate for valuing future impacts. 
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T 

ime Be Pr ative b ar -- 

Pass ars

 

MY 2012 

ffect Undiscou ed 

Disco lue 

@ 3% 

Disco alue 

@ 7% 

able VIII-9

Lifet nefits for eferred Altern

enger C

y Model Ye

Societal E Physical 

Units 

nt

Value 

Present 

unted Va

Present 

unted V

Lifetime Fuel 

Expenditures 

2,395,587 

(kgal) $6,573 $5,290 $4,156 

Consumer Surplus fro

Additional Dr

m 

iving ( 

6,826,369 

kmiles) $491 $396 $312 

Refueling Time Value 22,168,301 

(hours) $546 $452 $365 

Petroleum Marke

Externalities 

t 2,395,587 

(kgal) $385 $315 $251 

Congestion Costs 6,826,369 

(kmiles) -$356 -$292 -$234 

Noise Costs 6,826,369 

(kmiles) -$7 -$6 -$4 

Crash Costs 6,826,369 -$ -$107 (kmiles) 163 -$133 

CO2 25 (mmT) $643 $516 $516 

CO 183,679 

(tons) $0 $0 $0 

VOC 21,787 ons) (t $35 $28 $21 

NOX 10,764 (tons) $69 $52 $39 

PM 530 (tons) $154 $117 $86 

SOX 2,975 (tons) $112 $91 $73 

Total $8,482 $6,826 $5,474 
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MY 2013 

Societal Effect Physical 

Units 

Undiscounted 

Value 

Present 

Discounted Value 

@ 3% 

Present 

Discounted Value 

@ 7% 

Lifetime Fuel 

Expenditures 

5,152,718 

(kgal) $14,551 $11,814 $9,353 

Consumer Surplus from 

Additional Driving 

13,859,078 

(kmiles) $1,075 $874 $693 

Refueling Time Value 44,980,471 

(hours) $1,108 $920 $746 

Petroleum Market 

Externalities 

5,152,718 

(kgal) $828 $680 $546 

Congestion Costs 13,859,078 

(kmiles) -$733 -$603 -$485 

Noise Costs 13,859,078 

(kmiles) -$14 -$11 -$9 

Crash Costs 13,859,078 

(kmiles) -$327 -$268 -$215 

CO2 54 (mmT) $1,453 $1,174 $1,174 

CO 173,993 

(tons) $0 $0 $0 

VOC 37,362 (tons) $59 $48 $38 

NOX 15,020 (tons) $96 $75 $57 

PM 1,112 (tons) $324 $257 $199 

SOX 6,353 ons) (t $239 $196 $158 

Total $18,660 $15,155 $12,255 
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Societal Ef

Units Discounted Value 

@ 3% 

Present 

Discounted Value 

@ 7% 

MY 2014 

fect Physical Undiscounted Present 

Value 

Lifetim

Expe

e Fuel 

nditures 

7,232,873

(kgal) $20,836 $16,914 $13,395 

Consumer Surplus from 

Additional Driving 

19,545,328 

(kmiles) $1,532 $1,246 $988 

Refueling Time Value 62,083,457 $1,530 $1,269 $1,029 (hours) 

Petroleum Market 7 $1,162 $954 $766 Externalities ,232,873

(kgal) 

Congestion Costs 19,545,328 -$1,032 -$849 -$682 (kmiles) 

Noise Costs 19,545,328 -$20 -$16 -$13 (kmiles) 

Crash Costs 19,545,328 -$461 -$379 -$304 (kmiles) 

CO2 77 (mmT) $2, $1 102 $1,696 ,696 

CO 160,287 

(tons) $0 $0 $0 

VOC 4 ) 8,830 (tons $78 $63 $50 

NOX 17,864 (tons) $114 $90 $69 

PM 1,547 (tons) $451 $362 $284 

SOX 8,901 (tons) $335 $275 $221 

Total $26,627 $ 6 21,62 $17,499 
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MY 2015 

Societal Effect Physical 

Units 

Undiscounted 

Value 

Present 

Discounted Value 

@ 3% 

Present 

Discounted Value 

@ 7% 

Lifetime Fuel 

Expenditures 

9,446,003 

(kgal) $27,649 $22,471 $17,816 

Consumer Surplus from 

Additional Driving 

25,402,984 

(kmiles) $2,010 $1,636 $1,300 

Refueling Time Value 80,958,399 

(hours) $1,995 $1,656 $1,343 

Petroleum Market 

Externalities 

9,446,003 

(kgal) $1,517 $1,247 $1,001 

Congestion Costs 25,402,984 

(kmiles) -$1,343 -$1,106 -$888 

Noise Costs 25,402,984 

(kmiles) -$25 -$21 -$17 

Crash Costs 25,402,984 

(kmiles) -$599 -$492 -$395 

CO2 101 (mmT) $2,816 $2,274 $2,274 

CO 143,844 

(tons) $0 $0 $0 

VOC 61,141 (tons) $97 $79 $63 

NOX 20,851 (tons) $133 $106 $82 

PM 1,982 (tons) $577 $467 $368 

SOX 11,612 ns) (to $437 $359 $288 

Total $35,264 $28,677 $23,235 
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MY 2016 

Societal Effect Physical 

Units 

Undiscounted 

Value 

Present 

Discounted Value 

@ 3% 

Present 

Discounted Value 

@ 7% 

Lifetime Fuel 

Expenditures 

11,432,923 

(kgal) $33,971 $27,655 $21,958 

Consumer Surplus from 

Additional Driving 

30,779,447 

(kmiles) $2,449 $1,997 $1,589 

Refueling Time Value 96,330,156 

(hours) $2,374 $1,972 $1,601 

Petroleum Market 

Externalities 

11,432,923 

(kgal) $1,837 $1,511 $1,214 

Congestion Costs 30,779,447 

(kmiles) -$1,632 -$1,344 -$1,081 

Noise Costs 30,779,447 

(kmiles) -$31 -$25 -$20 

Crash Costs 30,779,447 

(kmiles) -$723 -$595 -$478 

CO2 123 (mmT) $3,487 $2,820 $2,820 

CO 125,778 

(tons) $0 $0 $0 

VOC 71,893 (tons) $114 $93 $75 

NOX 23,524 (tons) $150 $120 $94 

PM 2,365 (tons) $689 $561 $447 

SOX 14,045 ons) (t $528 $435 $349 

Total $43,214 $35,200 $28,567 
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MY 2012-2016, Passenger Cars Combined 

Societal Effect Physical 

Units 

Undiscounted 

Value 

Present 

Discounted Value 

@ 3% 

Present 

Discounted Value 

@ 7% 

Lifetime Fuel 

Expenditures 

35,660,103 

(kgal) $103,581 $84,145 $66,679 

Consumer Surplus from 

Additional Driving 

96,413,205 

(kmiles) $7,557 $6,149 $4,882 

Refueling Time Value 306,520,784 

(hours) $7,553 $6,269 $5,085 

Petroleum Market 

Externalities 

35,660,103 

(kgal) $5,729 $4,708 $3,779 

Congestion Costs 96,413,205 

(kmiles) -$5,096 -$4,194 -$3,370 

Noise Costs 96,413,205 

(kmiles) -$96 -$79 -$64 

Crash Costs 96,413,205 

(kmiles) -$2,273 -$1,868 -$1,499 

CO2 380 (mmT) $10,502 $8,479 $8,479 

CO 787,580 (tons) $0 $0 $0 

VOC 241,013 (tons) $383 $311 $247 

NOX 88,022 (tons) $561 $443 $341 

PM 7,536 (tons) $2,195 $1,763 $1,384 

SOX 43,887 (tons) $1,651 $1,357 $1,089 

Total $132,246 $107,483 $87,031 
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T 0 

ime Be Pr ative b ar -- 

Lig ks 

 

MY 2012 

ffect Un d 

Value Discounted Value Discounted Value 

able VIII-1

Lifet nefits for eferred Altern

ht Truc

y Model Ye

Societal E Physical 

Units 

discounte Present 

@ 3% 

Present 

@ 7% 

Lifetime Fuel 

Expenditures 

1,805,043 

(kgal) $5,102 $3,974 $3,041 

Consumer Surplus from 

g 

4,054,226 $384 $300 $230 Additional Drivin (kmiles) 

Refueling Time Value 1 $315 $255 $202 2,795,747

(hours) 

Petroleum Market $290 $231 $181 Externalities 1,805,043 

(kgal) 

Congestion Costs 4,054,226 

(kmiles) -$195 -$155 -$121 

Noise Costs 4,054,226 

(kmiles) -$4 -$3 -$3 

Crash Costs - 4,054,226 

(kmiles) $105 -$84 -$66 

CO2 19 (mmT) $523 $405 $405 

CO 36,333 ons) (t $0 $0 $0 

VOC 11,557 (tons) $18 $14 $11 

NOX 3,686 (tons) $23 $18 $14 

PM 388 (tons) $113 $89 $68 

SOX 2,217 (tons) $83 $66 $52 

Total $6,549 $5,110 $4,015 
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MY 2013 

Societal Effect Physical 

Units 

Undiscounted 

Value 

Present 

Discounted Value 

@ 3% 

Present 

Discounted Value 

@ 7% 

Lifetime Fuel 

Expenditures 

3,698,295 

(kgal) $10,702 $8,364 $6,428 

Consumer Surplus from 

Additional Driving 

7,806,595 

(kmiles) $804 $630 $486 

Refueling Time Value 23,242,410 

(hours) $573 $463 $368 

Petroleum Market 

Externalities 

3,698,295 

(kgal) $594 $473 $371 

Congestion Costs 7,806,595 

(kmiles) -$375 -$299 -$234 

Noise Costs 7,806,595 

(kmiles) -$8 -$6 -$5 

Crash Costs 7,806,595 

(kmiles) -$203 -$162 -$127 

CO2 40 (mmT) $1,099 $851 $851 

CO 25,256 (tons) $0 $0 $0 

VOC 22,147 (tons) $35 $28 $22 

NOX 5,894 (tons) $38 $30 $23 

PM 767 (tons) $223 $177 $137 

SOX 4,537 (tons) $171 $136 $107 

Total $13,653 $10,684 $8,427 
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Societal Effec

Units ounted Value 

@ 3% 

Present 

Discounted Value 

@ 7% 

MY 2014 

t Physical Undiscounted Present 

Value Disc

Lifetime Fuel 

Expe

5,281, 

(kgal) 15,558 $12,168 $ nditures 

256 $ 9,362 

Co from 

A

11,323,656 

(kmiles) $1,153 $905 nsumer Surplusdditional Driving $698 

Re 33,659,128 

(hours) fueling Time Value $829 $670 $533 

Pe

Ex

5, 848 troleum Market 

ternalities 

281,256

(kgal) $ $676 $530 

Co 11,323,656 

( ngestion Costs 544 -$433 kmiles) -$ -$339 

N 11,323,656 

(kmiles) oise Costs -$11 -$9 -$7 

Cr s 11,323,656 

(kmiles) ash Cost -$294 -$235 -$184 

CO2 57 ) (mmT $1,606 $1,244 $1,244 

CO 1,07 s) 8 (ton $0 $0 $0 

VOC 30,5 s) 14 (ton $48 $39 $30 

NOX 7,2 s) 36 (ton $46 $37 $29 

PM 1,0 s) 82 (ton $315 $250 $196 

SOX 6,4 s) 76 (ton $244 $194 $152 

Total $19,800 $15,506 $12,243 
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Societal Effec

Units ounted Value 

@ 3% 

Present 

Discounted Value 

@ 7% 

MY 2015 

t Physical Undiscounted Present 

Value Disc

Lifetime Fuel 

Expenditures 

6,504,296 

(kgal) $19,458 $15,229 $11,726 

Consumer Surplus from 

ng (kmiles) $1,424 $1,118 $863 Additional Drivi

13,804,723

Refueling Time Value 40,605,771 ,001 $643 (hours) $1 $808

Petroleum Market 

Externalities 

6 6 ,04 $653 ,504,29

(kgal) $1 5 $832

Congestion Costs 13,804,723 

( 663 -$528 - kmiles) -$ $414 

Noise Costs 13,804,723 

( 14 kmiles) -$ -$11 -$9 

Crash Costs 13,804,723 

(kmile -$359 -$286 -$22 s) 4 

CO2 7 ) 1 (mmT $2,022 $1,566 $1,566 

CO -38,6 ons) 32 (t $0 $0 $0 

VOC 36, ns) 395 (to $58 $46 $36 

NOX 7,6 s) 76 (ton $49 $40 $32 

PM 1,3 s) 38 (ton $390 $310 $243 

SOX 7,9 s) 73 (ton $300 $239 $187 

Total $24,711 $19,364 $15,302 
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MY 2016 

Societal Effect Physical Present Present 

ted Value 

@ 7% 

Units Value Discounted Value Discoun

Undiscounted 

@ 3% 

Lifetime Fuel 

Expenditures 

8,061,224 

(kgal) $24,479 $19,169 $14,769 

Consumer Surplus from 0

les) 0 Additional Driving 

17,154,5 5 $1, (kmi 770 $1,39 $1,074 

Refueling Time Value ,269

rs) $1,2 78 49,147(hou 11 $9 $778 

Petroleum Market 

Externalities 

8,061,224 

l) $1,2 32 (kga 95 $1,0 $809 

Congestion Costs 17,154,505

les) -$823 -$656 (kmi -$514 

Noise Costs 17,154,505 

(kmiles) -$17 -$14 -$11 

Crash Costs 17,154,505 

s) -$355 -$278 (kmile -$446 

CO2 88 (mmT 2 ) $ ,561 $1,984 $1,984 

CO - (ton 84,105 s) $0 $0 $0 

VOC 4 3,994 (tons) $70 6 $5 $44 

NOX 8 (tons) ,618 $55 5 $4 $37 

PM 1,661 (tons $48 ) 4 $385 $301 

SOX 9,878 (tons) $372 $296 $232 

Total $31,010 $24,310 $19,225 
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 Physical 

Units 

Undiscounted 

Value 

Present 

Discounted Value 

Present 

Discounted Value 

MY 2012-2016, Combined Light Trucks 

Societal Effect

@ 3% @ 7% 

Lifetime Fuel 

Expenditures 

25,350,115 

(kgal) $75,299 $58,903 $45,327 

Consumer Surplus from 

Additional Driving 

54,143,706 

(kmiles) $5,535 $4,342 $3,351 

Refueling Time Value 159,450,326 

(hours) $3,929 $3,174 $2,523 

Petroleum Market 

xternalities 

25,350,115 

(kgal) $4,072 $3,244 $2,543 E

Congestion Costs 54,143,706 

(kmiles) -$2,599 -$2,070 -$1,623 

Noise Costs 54,143,706 

(kmiles) -$54 -$43 -$34 

Crash Costs 54,143,706 

(kmiles) -$1,408 -$1,121 -$879 

CO2 275 (mmT) $7,812 $6,049 $6,049 

CO -60,070 (tons) $0 $0 $0 

VOC 144,608 (tons) $230 $183 $144 

NOX 33,109 (tons) $211 $170 $134 

PM 5,236 (tons) $1,525 $1,210 $945 

SOX 31,081 (tons) $1,169 $931 $730 

Total $95,722 $74,974 $59,212 
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2013 MY 2014

Table VIII-11 

Present Value of Lifetime Social Benefits by Alternative 

(millions of 2007 dollars) 

(3 percent discount rate) 

Alternative 

MY 

2012 

MY 

MY 2015 MY 2016

5-Year 

Total 

Passenger Cars 

Preferred Alternative 6,826 15,155 21,626 28,677 35,200 107,483 

3% Annual Increase 3,397 8,374 12,331 16,760 23,122 63,984 

4% Annual Increase 4,186 11,006 17,315 24,469 32,309 89,286 

5% Annual Increase 6,152 15,404 24,075 32,114 40,905 118,649 

6% Annual Increase 7,071 18,062 28,137 37,552 47,754 138,576 

7% Annual Increase 8,038 20,627 32,225 42,010 52,606 155,507 

Max Net Benefits 8,019 20,896 31,683 39,863 48,228 148,689 

Total Cost = Total 

Benefit 8,666 22,374 33,916 42,737 51,659 159,352 

Light Trucks 

Preferred Alternative 5,110 10,684 15,506 19,364 24,310 74,974 

3% Annual Increase 687 3,920 7,635 11,604 14,940 38,786 

4% Annual Increase 2,590 7,361 12,580 17,089 21,830 61,450 

5% Annual Increase 4,003 10,407 17,686 23,206 28,324 83,626 

6% Annual Increase 4,893 13,933 22,031 28,987 34,727 104,571 

7% Annual Increase 5,634 16,326 25,550 32,714 38,229 118,453 

Max Net Benefits 7,528 18,302 25,913 31,563 34,835 118,141 

Total Cost = Total 

Benefit 7,631 18,954 27,294 33,381 37,262 124,522 
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Pre e 

(7 percent d rate) 

Alternative MY 2012 MY 2013

Table VIII-12 

sent Value of Lifetime Social Benefits by Alternativ

(millions of 2007 dollars) 

iscount 

MY 2014 MY 2015 MY 2016 5-Year Total 

Passenger Cars 

Preferred Alternative 5,474 12,255 17,499 23,235 28,567 87,031 

3% Annual Increase 2,727 6,778 9,980 13,585 18,774 51,844 

4% Annual Increase 3,356 8,904 14,015 19,838 26,241 72,353 

5% Annual Increase 4,941 12,472 19,493 26,030 33,185 96,122 

6% Annual Increase 5,667 14,612 22,763 30,402 38,735 112,180 

7% Annual Increase 6,448 16,692 26,080 34,028 42,669 125,917 

Max Net Benefits 6,134 16,378 25,041 31,517 38,120 117,191 

Total Cost = Total Benefit 6,957 18,112 27,453 34,625 41,897 129,044 

Light Trucks 

Preferred Alternative 4,015 8,427 12,243 15,302 19,225 59,212 

3% Annual Increase 545 3,099 6,035 9,178 11,823 30,679 

4% An al Increase 2,035 5,802 9,927 13,500 17,260 nu 48,524 

5% Annual Increase 3,129 8,189 13,929 18,300 22,365 65,913 

6% Annual Increase 3,823 10,966 17,349 22,842 27,385 82,366

7% Annual Increase 4,404 12,838 20,108 25,767 30,132 93,248 

Max Net Benefits 5,736 12,761 18,525 22,485 25,290 84,797 

Total Cost = Total Benefit 6,039 14,926 21,502 26,237 29,295 97,999
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Table VIII-13 

Fuel Savings over Lifetimes of Model Year 2012-2016 Passenger Cars 

and Light Trucks with Alternative Increases in CAFE Standards 

(million gallons) 

Passenger Cars

Alternative MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 Total 

Preferred Alternative 2,396 5,153 7,233 9,446 11,433 35,660 

3% Annual Increase 1,197 2,845 4,120 5,509 7,490 21,161 

4% Annual Increase 1,476 3,740 5,787 8,046 10,475 29,524 

5% Annual Increase 2,157 5,230 8,066 10,630 13,381 39,463 

6% Annual Increase 2,520 6,200 9,530 12,589 15,770 46,609 

7% Annual Increase 2,855 7,086 10,933 14,080 17,419 52,374 

Max Net Benefits 2,848 7,159 10,731 13,324 15,893 49,956 

Total Cost = Total 

Benefit 3,071 7,673 11,492 14,295 17,086 53,619 

Light Trucks 

Alternative MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 Total 

Preferred Alternative 1,805 3,698 5,281 6,504 8,061 25,350 

3% Annual Increase 234 1,349 2,589 3,882 4,935 12,988 

4% Annual Increase 916 2,557 4,298 5,751 7,251 20,773 

5% Annual Increase 1,434 3,631 6,076 7,856 9,463 28,460 

6% Annual Increase 1,758 4,869 7,584 9,859 11,677 35,747 

7% Annual Increase 2,019 5,718 8,813 11,139 12,866 40,555 

Max Net Benefits 2,688 6,395 8,919 10,735 11,700 40,437 

Total Cost = Total 

Benefit 2,724 6,621 9,392 11,348 12,507 42,591 

H. Potential Impacts of the Final Standards on Consumer Welfare

There are two reasonable viewpoints for evaluating the costs and benefits of the increase in 

CAFE standards: the private perspective of vehicle buyers themselves on the higher fuel 

economy levels the final rule would require, and the economy-wide or “social” perspective on

the costs and benefits of requiring higher fuel economy. The agency’s analysis of benefits from

requiring higher fuel efficiency, presented previously in this Chapter, includes some categories 

that extend throughout the U.S. economy, such as reductions in the energy security costs 

associated with U.S. petroleum imports and in the economic damages expected to result from 

climate change. In contrast, other categories of benefits – principally the economic value of 

future fuel savings projected to result from higher fuel economy – will be experienced 

exclusively by the initial purchasers and subsequent owners of vehicle models whose fuel 
DELIB

441

higher fuel economy represent 

an imp ant share of the total economic benefits from raising CAFE standards, NHTSA 

fuel 

s 

g with increased CAFE standards for 

those m del years by increasing vehicle sales prices. As the table shows, the agency’s estimates 

, 

economy manufacturers elect to improve as part of their strategies for complying with higher 

CAFE standards. 

Although the economy-wide or “social” benefits from requiring 

ort

estimates that benefits to vehicle buyers themselves will significantly exceed the costs of 

complying with the stricter fuel economy standards this rule establishes, as Chapter X shows. 

Since the agency also assumes that the costs of new technologies manufacturers will employ to 

improve fuel economy will ultimately be shifted to vehicle buyers in the form of higher purchase 

prices, NHTSA concludes that the benefits to vehicle buyers from requiring higher fuel 

efficiency will far outweigh the costs they will be required to pay to obtain it. However, this 

raises the question of why current purchasing patterns do not result in higher average fuel 

economy, and why stricter fuel efficiency standards should be necessary to achieve that goal. 

As an illustration, Table VIII-14 reports the agency’s estimates of the average lifetime values of 

fuel savings for MY 2012-2016 passenger cars and light trucks calculated using future retail 

prices, which are those likely to be used by vehicle buyers to project the value of fuel savings 

they expect from higher fuel economy. The table compares NHTSA’s estimates of the average

lifetime value of fuel savings for cars and light trucks to the price increases it projects to result a

manufacturers attempt to recover their costs for complyin

o

of the present value of lifetime fuel savings (discounted using the OMB-prescribed 3% rate) 

outweigh projected vehicle price increases for both cars and light trucks in every model year

even under the assumption that all of manufacturers’ technology outlays are passed on to buyers 

in the form of higher selling prices for new cars and light trucks. By model year 2016, NHTSA 

projects that average lifetime fuel savings will exceed the average price increase by more than 

$2,000 for cars, and by more than $2,700 for light trucks. 

Table VIII-14 

Value of Lifetime Fuel Savings vs. Average Technology Cost Increase/Vehicle

ERATIVE DOCUMENT – DO NOT RELEASE 

2012 2013 2014 2015 2016

Value of Fuel Savings $759 $1,469 $1,954 $2,480 $2,932

Average Price Increase $505 $573 $690 $799 $907

Difference $255 $897 $1,264 $1,680 $2,025

Value of Fuel Savings $828 $1,634 $2,277 $2,887 $3,700

Average Price Increase $322 $416 $621 $752 $961

Difference $506 $1,218 $1,656 $2,135 $2,739

Light Trucks

Passsenger 

Cars

Model Year Fleet Measure

 Assuming these comparisons are accurate, they raise the question of why current vehicle 

purchasing patterns do not result in average fuel economy levels approaching those that this rule 

would require, and why stricter CAFE standards should be necessary to increase the fuel 

economy of new cars and light trucks. They also raise the question of why manufacturers do not 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

, since 

s in Table VIII-14 suggest that doing so would reduce the effective price of 

purcha ng many new vehicle models, and thus to increase sales of new vehicles. More 

her 

arisons 

 because 

HTSA has incorrectly estimated some components of the benefits from saving fuel, or because 

er 

oad 

 

s are evaluated over different time horizons to the estimated 

increas in its price. This table shows that as reported previously in Table VIII-15, when fuel 

d 

e 

out 

elect to provide higher fuel economy even in the absence of increases in CAFE standards

the comparison

si

specifically, why would potential buyers of new vehicles hesitate to make investments in hig

fuel economy that would produce the substantial economic returns illustrated by the comp

presented in Table VIII-14? And why would manufacturers voluntarily forego opportunities to

increase the attractiveness, value, and competitive positioning of their car and light truck models 

by improving their fuel economy? 

One explanation for this apparent paradox is that NHTSA’s estimates of benefits and costs from 

requiring manufacturers to improve the fuel efficiency of their vehicle models do not match 

potential vehicle buyers’ assessment of the likely benefits and costs from requiring higher fuel 

efficiency. This could occur because the agency’s underlying assumptions about some of the 

factors that affect the value of fuel savings differ from those made by potential buyers,

N

the agency has failed to account for some potential costs of achieving higher fuel economy. 

For example, buyers may not value increased fuel economy as highly as the agencies’ 

calculations suggest, because they have shorter time horizons than the full vehicle lifetimes 

assumed by NHTSA and EPA, or because they discount future fuel future savings using high

rates than those prescribed by OMB for evaluating federal regulations. Potential buyers may also 

anticipate lower fuel prices in the future than those forecast by the Energy Information 

Administration, or may expect larger differences between vehicles’ rated and actual on-r

MPG levels than the agencies estimate. 

To illustrate the first of these possibilities, Table VIII-15 shows the effect of differing 

assumptions about vehicle buyers’ time horizons for assessing the value of future fuel savings.

Specifically, the table compares the average value of fuel savings from purchasing a MY 2016 

car or light truck when fuel saving

e 

savings are evaluated over the entire expected lifetime of a MY 2016 car (approximately 14 

years) or light truck (about 16 years), their discounted present value (using the OMB-prescribe

3% discount rate) lifetime fuel savings exceeds the estimated average price increase by more 

than $2,000 for cars and by more than $2,700 for light trucks. 

If buyers are instead assumed to evaluate fuel savings over a 10-year time horizon, however, th

present value of fuel savings exceeds the projected price increase for a MY 2016 car by ab

$1,300, and by somewhat more than $1,500 for a MY 2016 light truck. Finally, Table VIII-15

shows that under the assumption that buyers value fuel savings only over the length of time for 

which they typically finance new car purchases (slightly more than 5 years during 2009), the 

value of fuel savings exceeds the estimated increase in the price of a MY 2016 car by only about 

$350, and the corresponding difference is reduced to slightly more than $500 for a MY 2016 

light truck. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VIII-15 

Value of Fuel Savings vs. Vehicle Price Increases 

with Alternative Assumptions about Vehicle Buyer Time Horizons 

Expected 

Lifetime (1) 10 Years Average Loan 

Term (2)

Fuel Savings $2,932 $2,180 $1,254

Price Increase $907 $907 $907

Difference $2,025 $1,273 $347

Fuel Savings $3,700 $2,508 $1,484

Price Increase $961 $961 $9

MY 2016 

Passenger 

Car

MY 2016 

Value over Alternative Time Horizons

Vehicle Measure

61 Light Truck Difference $2,739 $1,547 $523

(1) Expected lifetimes are approximately 14 years for cars and 16 years for light trucks. 

(2) Average term on new-vehicle loans made by auto finance companies during 2009 

was 62 months; see Board of Governors of the Federal Reserve System, Federal Reserve 

Statistical Release G. 19, Consumer Credit, 

http://www.federalreserve.gov/releases/g19/Current/ last accessed March 1, 2010.

Potential vehicle buyers may also discount future fuel future savings using higher rates than 

those typically used to evaluate federal regulations. OMB guidance prescribes that future

benefits and costs of regulations that mainly affect private consumption decisions, as will be the

case if manufacturers’ costs for complying with higher fuel economy standards are passed on to 

vehicle buyers, should be discounted using a consumption rate of time preference.278 OMB 

e fuel 

2016 passenger cars and light trucks as an example. As Table VIII-14 showed previously, 

average future fuel savings discounted at the OMB 3% consumer rate exceed the agency’s 

t the 

estimates that savers currently discount future consumption at an average real or inflationadjusted rate of about 3 percent when they face little risk about its likely level, which makes it a 

reasonable estimate of the consumption rate of time preference. However, vehicle buyers may

view the value of future fuel savings that results from purchasing a vehicle with higher fuel 

economy as risky or uncertain, or they may instead discount future consumption at rates 

reflecting their costs for financing the higher capital outlays required to purchase more fuelefficient models. In either case, they may discount future fuel savings at rates well above the 3%

assumed in NHTSA’s evaluation. 

Table VIII-16 shows the effect of higher discount rates on vehicle buyers’ evaluation of th

savings projected to result from the CAFE standards established by this rule, again using MY 

estimated price increases by more than $2,000 for MY 2016 passenger cars and by more than 

$2,700 for MY 2016 light trucks. If vehicle buyers instead discount future fuel savings a

average new-car loan rate during 2009 (6.7%), however, these differences decline to slightly

 

278 Office of Management and Budget, Circular A-4, “Regulatory Analysis,” September 17, 2003, 33. Available at

http://www.whitehouse.gov/omb/assets/regulatory_matters_pdf/a-4.pdf (last accessed March 1, 2009). 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

le alternative assumption, because buyers are likely to finance the increases in 

purchase prices resulting from compliance with higher CAFE standards as part of the process 

se 

more than $1,400 for cars and $1,900 for light trucks, as Table VIII-16 illustrates. This is a 

particularly plausib

financing the vehicle purchase itself. Finally, as the table also shows, discounting future fuel 

savings using a consumer credit card rate (which averaged 13.4% during 2009) reduces the

differences to less than $800 for a MY 2016 passenger car and less than $1,100 for the typical 

MY 2016 light truck. Thus even at relatively high discount rates, the higher fuel economy levels 

required by this final rule would generate significant net benefits to vehicle buyers. 

Table VIII-16 

Value of Fuel Savings vs. Vehicle Price Increases 

with Alternative Assumptions about Consumer Discount Rates

OMB 

Consumer 

Rate (3%)

New Car 

Loan Rate 

(6.7%; 1)

OMB 

Investment 

Rate (7%)

Credit Card 

Rate 

(13.4%; 2

Fuel Savings $2,932 $2,336 $2,300 $1,669

Price Increase $907 $907 $907 $907

Difference $2,025 $1,429 $1,393 $762

Fuel Savings $3,700 $2,884 $2,836 $2,030

Price Increase $961 $961 $961 $961

Difference $2,739 $1,923 $1,875 $1,069

(1) Average rate on 48-month new-vehicle m

Vehicle Measure

MY 2016 

Passenger 

Car

MY 2016 

Light Truck

Consumer 

)

loans ade by commercial banks during 2009 was 6.72%; 

Value at Alternative Discount Rates

see Board of Governors of the Federal Reserve System, Federal Reserve Statistical Release G. 19, 

Consumer Credit, http://www.federalreserve.gov/releases/g19/Current/ last accessed March 1, 2010.

(2) Average rate on consumer credit card accounts at commercial banks during 2009 was13.4%; see 

Board of Governors of the Federal Reserve System, Federal Reserve Statistical Release G. 19, 

Consumer Credit, http://www.federalreserve.gov/releases/g19/Current/ last accessed March 1, 2010.

Combinations of a shorter time horizon and a higher discount rate could further reduce or even 

eliminate the difference between the value of fuel savings and the agency’s estimates of 

increases in vehicle prices. One plausible combination would be for buyers to discount fuel 

savings over the term of a new car loan, using the interest rate on that loan as a discount rate. 

Doing so would reduce the amount by which future fuel savings exceed the estimated increase in 

ers surveyed by Kubik 

the prices of MY 2016 vehicles to about $340 for passenger cars and $570 for light trucks. Some 

evidence suggests directly that vehicle buyers may employ combinations of higher discount rates 

and shorter time horizons than the agency assumes; for example, consum

(2006) reported that fuel savings would have to be adequate to pay back the additional purchase 
445

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

rice of a more fuel-efficient vehicle in less than 3 years to persuade a typical buyer to purchase 

l 

ables such as future fuel prices or the 

appropriate discount rate differ sufficiently from the assumptions used by the agency, potential 

costs 

rrently available models offer. 

Althou e specific economic values that vehicle buyers attach to individual vehicle attributes 

of 

ges 

s of complying with stricter CAFE standards. 

at 

ain 

ed the 

“constant performance and utility” costs for technologies that manufacturers could employ to 

increase the fuel efficiency of cars or light trucks. Although NHTSA has revised its estimates of 

p

it. 279 As these comparisons and evidence illustrate, reasonable alternative assumptions about 

how consumers might evaluate the major benefit from requiring higher fuel economy can 

significantly reduce its magnitude from the agency’s estimate. 

Many plausible combinations of shorter time horizons, higher discount rates, and lower 

expectations about future fuel prices or annual vehicle use and fuel savings could make potentia

buyers hesitant or even unwilling to purchase vehicles offering the fuel economy levels this rule 

will require. At the same time, they would also cause vehicle buyers’ collective assessment of 

how the benefits from requiring higher fuel economy compare to the costs they will be required

to pay for it to differ significantly from NHTSA’s assessment of the aggr4egate benefits and 

costs of this rule. If consumers’ views about critical vari

vehicle buyers might conclude that the value of fuel savings and other benefits they will 

experience from higher fuel economy are not sufficient to justify the increase in purchase prices

they expect to pay. This would not only explain why their current choices among available 

models do not result in average fuel economy levels approaching those this rule would require, 

but in extreme cases might also call into question NHTSA’s conclusion that the total – that is, 

private plus economy-wide – economic benefits from raising CAFE standards exceed the 

of complying with higher fuel economy requirements. 

Another possibility is that achieving the fuel economy improvements required by stricter fuel 

economy standards might require manufacturers to forego planned future improvements in 

performance, carrying capacity, safety, or other features of their vehicle models that represent 

important sources of utility to vehicle owners. In extreme cases, manufacturers might even find 

it necessary to change the levels of these attributes that some cu

gh th

such as fuel economy, performance, passenger- and cargo-carrying capacity, and other sources 

vehicles’ utility are difficult to infer from their purchasing decisions and vehicle prices, chan

in vehicle attributes can significantly affect the overall utility that vehicles offer to potential 

buyers. Compromises in these or other highly-valued attributes would be viewed by potential 

buyers as an additional cost of improving fuel economy that the agency has failed to 

acknowledge or include in its estimates of the cost

As indicated in its previous discussion of technology costs, NHTSA has approached this 

potential problem by developing cost estimates for fuel economy-improving technologies th

include allowances for any additional manufacturing costs that would be necessary to maint

the reference fleet (or baseline) levels of performance, comfort, capacity, or safety of light-duty

vehicle models to which those technologies are applied. In doing so, the agency follow

precedent established by the 2002 NAS Report on improving fuel economy, which estimated 

manufacturers’ costs for some technologies significantly for use in this rulemaking, these revised 

estimates are still intended to represent costs that would allow manufacturers to maintain the 

 

279 Kubik, M. (2006). Consumer Views on Transportation and Energy. Second Edition. Technical Report: National 

Renewable Energy Laboratory.
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ate allowance for the necessary investments by manufacturers to maintain 

baselin evels of these critical vehicle attributes. If this is the case, the true economic costs of 

achievi g higher fuel economy would include the opportunity costs to vehicle owners of any 

sacrifices in vehicles’ performance, carry utility that accompanied increases in 

their fu mate 

the true economic costs of com n standards. 

Finally, vehicle buyers may simply prefer the choices of vehicle models they now have available 

to the combinations of price, fuel economy, and other attributes that manufacturers are likely to 

offer when required to achieve higher overall fuel economy. If this is the case, their choices 

among models – and even some buyers’ decisions about whether to purchase a new vehicle – 

will respond accordingly, and their responses to these new choices will reduce their overall 

welfare. Some may buy models with combinations of price, fuel efficiency, and other attributes 

that they consider less desirable than those they would otherwise have purchased, while others 

may simply postpone buying a new vehicle. It is also possible that manufacturers may 

discontinue some currently popular vehicle models or styles as part of their efforts to comply 

with requirements for higher fuel efficiency. Although the losses in buyers’ welfare associated 

with these responses cannot be large enough to offset the estimated value of fuel savings 

reported in the agencies’ analyses, they could significantly reduce the benefits from requiring 

manufacturers to achieve higher fuel efficiency, particularly in combination with the other 

possibilities outlined previously. 

An entirely different explanation for buyers’ reluctance to invest in higher fuel economy despite 

the large economic return it appears to promise i that the agency’s assertion that the benefits 

n 

en 

performance, carrying capacity, and utility of vehicle models while improving their fuel 

economy. 

The agency readily acknowledges the difficulty of estimating technology costs that include 

adequate provision for the accompanying changes in vehicle design that are necessary to 

maintain performance, capacity, and utility. While NHTSA believe that its cost estimates for 

fuel economy-improving technologies are sufficient to prevent significant compromises in other 

attributes of the vehicle models to which manufacturers apply them, it is possible that these costs 

do not include adequ

e l

n

ing capacity, and

el economy. In that event, the agencies’ estimated technology costs would underesti

plying with stricter fuel economy emissio

s 

buyers will experience from higher fuel economy far outweigh the costs they will pay to acquire 

it is indeed correct, yet certain plausible – if short-sighted – aspects of normal behavior 

nevertheless make buyers reluctant to purchase vehicles whose higher fuel economy offers a

attractive return. For example, consumers’ understandable aversion to the prospect of losses 

from making investments that do not produce their expected returns may exaggerate their 

uncertainty about the value of future fuel savings sufficiently to make purchasing a more fuelefficient vehicle seem unattractive even when doing so is likely to be a sound economic decision. 

Greene et al. (2009) find that the expected net present value of increasing the fuel economy of a 

passenger car from 28 to 35 miles per gallon falls from $405 when calculated using standard net 

present value calculations, to nearly zero when uncertainty regarding future cost savings is tak

to account.280 in 

 

280 Greene, D., J. German, and M. Delucchi (2009). “Fuel Economy: The Case for Market Failure” in Red

Climate Impacts in the Transportation Sector, Sperling, D., and J. Cannon, eds. Springer Science. Surprising

ucing 

ly, the 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

o 

ulting fuel savings when those are discounted at 7% 

ver the vehicle’s expected lifetime. Although the wide variation in these estimates partly 

ed, 

her 

 to its fuel economy, and 

ompare these two. In either case, although the agency’s estimates of the average value of fuel 

savings that will result from requiring cars and light trucks to achieve higher fuel economy may 

be correct, they are not likely to be large enough to lead a sufficient number of buyers to 

purchase vehicles with higher fuel economy to increase average fuel economy from its current 

levels. 

Defects in the market for cars and light trucks could also lead manufacturers to undersupply fuel 

economy, even in cases where many buyers were willing to pay the increased prices necessary to 

provide it. Most obviously, an absence of vigorous competition among producers of cars and 

light trucks may lead manufacturers to undersupply attributes that contribute to the overall 

quality of new vehicles, including fuel economy, because such “imperfect” competition reduces 

producers’ profit incentive to supply the level of fuel economy that buyers are willing to pay for. 

Incomplete or “asymmetric” access to information on vehicle attributes such as fuel economy – 

whereby manufacturers of new vehicles or sellers of used cars and light trucks have more 

complete knowledge of vehicles’ actual fuel economy levels, or of the value of purchasing 

higher fuel economy, than do potential buyers – may also prevents sellers of new or used 

vehicles from capturing its full value. In this situation, the level of fuel efficiency provided in 

 

Another possible reconciliation of the agency’s claim that the average vehicle buyer will 

experience large fuel savings from the higher CAFE standards this rule establishes with the fact 

that the average fuel economy of vehicles currently purchased falls well short of the new 

standards is that the values consumers place on the future savings they expect to obtain from 

higher fuel economy vary widely. As an illustration, one recent review of consumers’ 

willingness to pay for improved fuel economy found estimates that varied from less than 1% t

almost ten times the present value of the res

281 o

undoubtedly reflects methodological and measurement differences among the studies survey

it probably also reflects the fact that the expected savings from purchasing a vehicle with hig

fuel economy vary widely among individuals, because they travel different amounts, have 

different driving styles, or have different expectations about future fuel prices. 

This is likely to be reflected in the fact that buyers with high valuations of increased fuel 

economy already purchase vehicle models that offer it, while those with lower values of fuel 

economy emphasize other vehicle attributes in their purchasing decisions. A related possibility 

is that because the effects of differing fuel economy levels are relatively modest when compared 

to those provided by other, more prominent features of new vehicles – passenger and cargocarrying capacity, performance, safety, etc. – it is simply not in many shoppers’ interest to spend 

the time and effort necessary to determine the economic value of higher fuel economy, attempt to 

isolate the component of a new vehicle’s selling price that is related

c

authors find that uncertainty regarding the future price of gasoline appears to be less important than uncertainty 

surrounding the expected lifetimes of new vehicles. 

281 Greene, David L., “How Consumers Value Fuel Economy: A Literature Review,” Draft report to U.S. 

Environmental Protection Agency, Oak Ridge National Laboratory, December 29, 2009; see Table 10, p. 37. 

and Jin-Tan Liu (1988). “Automotive Fuel Economy Improvements and Consumers’ Surplus.” Transportation 

Research Part A 22A(3): 203-218. The study actually calculated the willingness to pay for reduced vehicle operating 

costs, of which vehicle fuel economy is a major component.
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

the markets for new or used vehicles mig tently lower than that demanded by 

potential b

 is also possible that deliberate decisions by manufacturers of cars and light trucks, rather than 

constraints on the combinations of fuel economy, carrying capacity, and performance that 

manufacturers can offer using current technologies, limit the range of fuel economy available to 

buyers within individual vehicle market segments, such as full-size automobiles, small SUVs, or 

minivans. As an illustration, once a potential buyer has decided to purchase a minivan, the range 

of fuel economy among current models extends only from 18 to 24 MPG.282 Manufacturers 

might make such decisions if they underestimate the premiums that shoppers in certain market 

segments are willing to pay for more fuel-efficient versions of the vehicle models thy currently 

offer to prospective buyers within those segments. If this occurs, manufacturers may fail to 

supply levels of fuel efficiency as high as those buyers are willing to pay for, and the average 

fuel efficiency of their entire new vehicle fleets could remain below the levels that potential 

buyers demand and are willing to pay for. 

Finally, some research suggests that the consumers’ apparent unwillingness to purchase more 

fuel efficient vehicles stems from their inability to value future fuel savings correctly. For 

example, Larrick and Soll (2008) find evidence that consumers do not understand how to 

translate changes in fuel economy, which is denominated in miles per gallon, into resulting 

changes in fuel consumption, measured in gallons per time period.283 Sanstad and Howarth 

(1994) argue that consumers appear optimize behavior without full information by resorting to 

imprecise but convenient rules of thumb, which can cause many buyers to underestimate the 

value of fuel savings, particularly from significant increases in fuel economy.284 If the behavio

identified in these studies is indeed widespread, en the agency’s calculations suggesting that 

ing 

at 

estimating the value of fuel savings and omitting potential reductions 

ht remain persis

uyers. 

It

r 

th

the benefits to vehicle owners from requiring higher fuel economy significantly exceeds the costs

of providing it may indeed be correct, yet the resulting difference is still insufficient to motivate 

buyers to purchase a mix of car or light truck vehicle models whose average fuel economy 

approaches those required by this rule. 

 

The agency has been unable to resolve the question of why the apparently large differences 

between its estimates of benefits from requiring higher fuel economy and the costs of supplying 

it do not result in higher average fuel economy for new cars and light trucks. One explanation is 

that NHTSA’s estimates are reasonable, and the market for fuel economy is simply not operat

efficiently. However, the agency acknowledges that this situation may also reflect the fact th

some combination of over

in the welfare of vehicle buyers means that it has incorrectly characterized the impact of the 

CAFE standards this rule establishes on consumers. To recognize this possibility, this section 

presents an alternative accounting of the benefits and costs of CAFE standards for MY 2012-

2016 passenger cars and light trucks and discusses its implications. 

 

282 This is the range of combined city and highway fuel economy levels from lowest (Toyota Siena 4WD) to high

(Mazda 5) available for model year 2010; http://www.fueleconomy.gov/feg/bestworstEPAtrucks.htm (last access

February 15, 2010). 

est 

ed 

3

 Larrick, R. P., and J.B. Soll (2008). “The MPG illusion.” Science 320: 1593-1594. 

 Sanstad, A., and R. Howarth (1994). “’Normal’ Markets, Market Imperfections, and Energy Efficiency.” Energy 

Policy 22(10): 811-818. 

28

284
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

able VIII-17 displays the economic impacts of the rule from the perspective of potential buyers, 

d by 

 As the table shows, the total 

enefits to vehicle buyers (line 4) consist of the value of fuel savings at retail fuel prices (line 1), 

c 

g (line 3). As the zero entries in line 5 of the table 

uggest, the agency’s estimate of the retail value of fuel savings reported in line 1 is assumed to 

ere is no reduction in the total 

rivate benefits to vehicle owners, so that net private benefits to vehicle buyers (line 6) are equal 

s Table VIII-17 also shows, the decline in fuel tax revenues (line 7) that results from reduced 

ts 

conomy-wide or “social” 

erspective. Thus the sum of lines 1 and 7 is the savings in fuel production costs that was 

of Table VIII-17 report the value of 

ductions in air pollution and climate-related externalities resulting from lower emissions during 

rts of crude petroleum and 

fined fuel. Line 12 reports the costs of increased congestion delays, accidents, and noise that 

 (line 

 externalities, and increased costs from added driving. 

AFE 

The net total benefits (line 15 of the table) resulting from the rule consist 

f the sum of private (line 6) and social (line 13) benefits, minus technology costs (line 14); as 

sly in 

vehicle 

uyers, with only a small share distributed throughout the remainder of the U.S. economy. In 

 

T

and also reconciles the estimated net benefits of the rule as they are likely to be viewe

vehicle buyers with its net benefits to the economy as a whole.

b

the economic value of vehicle occupants’ savings in refueling time (line 2), and the economi

benefits from added rebound-effect drivin

s

be correct, and no losses in consumer welfare from changes in vehicle attributes (other than those

from increases in vehicle prices) are assumed to occur. Thus th

p

to total private benefits (reported previously in line 4). 

A

fuel purchases is in effect an external cost from the viewpoint of vehicle buyers, which offse

part of the benefits of fuel savings when those are viewed from the e

285 p

reported previously as the value of fuel savings at pre-tax prices in the agency’s usual accounting 

of benefits and costs (see Chapter X). Lines 8 and 9 

re

fuel production and consumption, while line 10 reports the savings in energy security 

externalities to the U.S. economy from reduced consumption and impo

re

result from additional driving due to the fuel economy rebound effect; net social benefits

13) is thus the sum of the change in fuel tax revenues, the reduction in environmental and energy

security

Line 14 of Table VIII-17 shows manufacturers’ technology outlays for meeting higher C

standards for passenger cars and light trucks, which represent the principal cost of requiring 

higher fuel economy. 

o

expected, the figures reported in line 15 of the table are identical to those reported previou

the agency’s customary format (see Chapter X). 

Table VIII-17 highlights several important features of this rule’s economic impacts. First, 

comparing the rule’s net private (line 6) and external (line 13) benefits makes it clear that 

virtually all of the benefits from requiring higher fuel economy are experienced by 

b

turn, the vast majority of private benefits stem from fuel savings, which highlights the 

importance of the many assumptions the agency uses to estimate and value future fuel savings 

 es and 

sfer, 

omic cost or benefit. Representing the change in fuel tax revenues in effect as 

n economy-wide cost is necessary to offset the portion of fuel savings included in line 1 that represents savings in 

el tax payments by consumers. This prevents the savings in tax revenues from being counted as a benefit from the 

economy-wide perspective. 

285 Strictly speaking, fuel taxes represent a transfer of resources from consumers of fuel to government agenci

not a use of economic resources. Reducing the volume of fuel purchases simply reduces the value of this tran

and thus cannot produce a real econ

a

fu
450

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

in

its are small because the value of reductions in 

alities is almost exactly offset by the decline in fuel tax 

revenues and the increased costs associated with added vehicle use via the rebound effect of 

higher fuel economy. As a consequence, the net economic benefits of the rule mirror closely its 

benefits to private vehicle buyers and the technology costs for achieving higher fuel economy, 

again highlighting the importance of correctly valuing fuel savings from the perspective of those 

who experience them and accounting for any other effects of the rule on the economic welfare of 

vehicle buyers. 

Table VIII-17 

Private, Social, and Total Benefits and Costs of MY 2012-16 CAFE Standards: 

Passenger Cars plus Light Trucks 

result g from higher fuel economy, as well as of the assumption that the rule has no adverse 

impacts on vehicle buyers. External benef

environmental and energy security extern

2012 2013 2014 2015 2016

1 Value of Fuel Savings (at Retail Fuel Prices) $10.5 $22.9 $32.9 $42.5 $52.7 $161.6

2 Savings in Refueling Time $0.7 $1.4 $1.9 $2.5 $3.0 $9.4

3

4

5

6

7

8

9

10

11

12

13

14

15

Entry Model Year Total, 2012

Consumer Surplus from Added Driving $0.7 $1.5 $2.2 $2.8 $3.4 $10.5

Total Private Benefits (=1+2+3) $11.9 $25.8 $37.0 $47.8 $59.0 $181.5

Reduction in Private Benefits $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

Net Private Benefits (=1+2) $11.9 $25.8 $37.0 $47.8 $59.0 $181.5

Change in Fuel Tax Revenues -$1.3 -$2.7 -$3.8 -$4.8 -$5.9 -$18.5

Reduced Health Damages from Criteria Emissions $0.5 $0.9 $1.3 $1.6 $2.0 $6.4

Reduced Climate Damages from CO2 Emissions $0.9 $2.0 $2.9 $3.8 $4.8 $14.5

Reduced Energy Security Externalities $0.5 $1.2 $1.6 $2.1 $2.5 $8.0

Reduction in Externalities (=8+9+10) $1.9 $4.1 $5.9 $7.6 $9.3 $28.8

Increased Costs of Congestion, etc. -$0.7 -$1.3 -$1.9 -$2.4 -$3.0 -$9.4

Net Social Benefits (=7+11+12) $0.0 $0.1 $0.1 $0.3 $0.5 $1.0

Technology Costs $5.9 $7.9 $10.5 $12.5 $14.9 $51.7

Net Total Benefits (=6+12-14) $6.0 $17.9 $26.6 $35.5 $44.6 $130.7

-

2016

As discussed in detail previously, it is possible that NHTSA has overestimated the value of fuel 

vings to buyers and subsequent owners of the cars and light trucks to which higher CAFE 

andards will apply. It is also possible that the agency has failed to identify and value 

ductions in consumer welfare that could result from buyers’ responses to higher vehicle prices 

or changes in vehicle attributes that manufacturers make as part of their efforts to achieve higher 

el economy. To acknowledge these possibilities and examine their potential impact on the 

sa

st

re

fu

rule’s benefits and costs, Table IV.G.6-5 shows the rule’s cumulative economic impacts for MY 

2012-16 passenger cars and light trucks under varying assumptions about the agency’s potential 

overestimation of fuel savings and the value of potential changes in vehicle attributes such as 

performance, carrying capacity, or safety. 

Table VIII-18 accounts for both potential overestimation of the value of fuel savings to vehicle 

buyers and the possible omission of welfare losses from changes in other vehicle attributes in the 

entry labeled “Reduction in Private Benefits” (line 5). Although the examples reported 
451

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

le overestimation of fuel 

savings using specific alternatives to the agency’s assumptions, NHTSA has been unable to 

 fuel 

r 

ffect of these possibilities using different assumptions 

bout the fraction of total private benefits to vehicle buyers that might be offset by some 

ule’s total 

f 

d 

set 

line 6) would be 

duced to slightly less than half of the agency’s original estimate, while its net total benefits 

 shows, if 

previously in Tables VIII-15 and VIII-16 illustrated sources of possib

determine exactly how buyers’ time horizons or discount rates might differ from those assumed 

in its analysis. Nor has NHTSA analyzed how vehicle buyers’ expectations about future

prices or differences between fuel economy ratings and actual on-road fuel economy might diffe

from those it employs to estimate the value of fuel savings. Finally, NHTSA has not attempted 

to project changes in vehicle attributes other than fuel economy, or to estimate the economic

value of resulting losses in vehicle utility. 

Instead Table VIII-18 illustrates the e

a

combination of these factors. As it shows, if there is no offset to private benefits, the r

and net private and social benefits are as shown in the last column of Table IV.G.6-4 above. 

However, if these factors combine to offset even as much as 25% of the agency’s estimate o

total private benefits (line 5), the rule’s net private (line 6) and net total (line 15) benefits woul

be reduced, but are still substantially positive. The table also shows that if losses in consumer 

welfare from changes in vehicle attributes or an overestimate of the value of fuel savings off

as much as half of the rule’s estimated private benefits, its net private benefits (

re

(line 15) would decline to less than one-third of the original estimate. As the table also

these factors combined to offset a sufficiently high fraction of the rule’s total private benefits, its 

net total benefits could decline to zero or even become negative. 
452

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table VIII-18 

Effect of Overestimation of Fuel Sa ngs or Omission of Welfare Losses 

on Net Private and Total Benefits MY 2012-2016 CAFE Standards 

vi

of

None 2

61.6 $1

5 %

uel Saving 1

ueling Time $9.4 $9.4 $9. $9.4

ro Dr $1 $10 10.5

 (=1 $18 81. 1.5 5

en $0 $45 90.7 1

1+ $18 36. 90.7

eve $1 1 18.5

ma ri ssi $ $6. 6.4

e Dam C ion $1 4.5

1 y Secur nal $ $8 8.0

1 n in Externalitie 0) $2 8.8

1 s of Congestio tc. -$9.4 -$9.4 -$9.4 $9.4

1 11 $1 $1. .0

1 $5 $51 51.7

1 +12 $13 $85 0.0

vate Benefits Offset by 

imation of Fuel Savings or Omission 

elfare Losses to Vehicle Buyers Entry

Fraction of Pri

Overest

of W

% 50

61.6 $16

75%

1 Value of F s (at Retail Fuel Prices) $ 1.6 $161.6

2 Savings in Ref 4

3 Consumer Surplus f m Added iving 0.5 .5 $ $10.5

4 Total Private Benefits +2+3) 1.5 $1 5 $18 $181.

5 Reduction in Private B

6 Net Private Benefits (=

efits

2)

.0 -

1.5 $1

.4 -$

1 $

-$136.

$45.4

7 Change in Fuel Tax R nues - 8.5 -$ 8.5 -$ -$18.5

8 Reduced Health Da ges from C teria Emi ons 6.4 4 $ $6.4

9 Reduced Climat

ced Energ

ages from O2 Emiss s 4.5 $14.5 $1 $14.5

0 Redu

1 Reductio

ity Exter

s (=8+9+1

ities 8.0

8.8 $28

.0 $

.8 $2

$8.0

$28.8

2 Increased Cost n, e -

3 Net Social Benefits (=7+ +12) .0 0 $1 $1.0

4 Technology Costs 1.7 .7 $ $51.7

5 Net Total Benefits (=6 -14) 0.7 .3 $4 -$5.4

It ize TS s t ti te e ic 

im le as ve d t ws pos 

ex likely. The ag s at to th cu at

va e, and the design of the CA standar (e.g., the f tprint 

cu rds d id nu for g 

wi av n ta e d ve ibu han 

fu co sed A at to at i es 

of e p t t at rfor

saf att s c nc u ef

hi 

Ne ncy fe i nt w its f 

ho are likely to va sav e s n sse

performance, utility, or safety of cars and light trucks subject to this rule will occur. As this 

nalysis indicates, the implications of such uncer ainty for the magnitude of economic benefits 

ely to result from the CAFE standards this rul establishes are significant. NHTSA is 

ommitted to developing improved methods to estimate the value of improvements in fuel 

omy, as well as the magnitude and economic consequences of accompanying changes in 

other vehicle attributes, as part of its future CAFE rulemaking activities. 

is important to emphas that NH A view he alterna ve estima s of this rul ’s econom

pacts presented in Tab VIII-18 illustrati only, an hat it vie this last sibility as

tremely un ency ha tempted develop e most ac rate estim es of the 

lue of fuel savings that are possibl

 th

FE ds oo

rves), the stringency of e standa , the lea time prov

n

ed to ma facturers complyin

th the new standards h

el economy will not be

e all bee

mpromi

ilored to

. NHTS

sure that

 has also

esirable

tempted 

hicle attr

ensure th

tes other t

ts estimat

 technology costs includ adequate rovisions to preven he degrad ion of pe mance, 

ety, or other valuable ributes a onseque es of man facturers’ forts to comply with 

gher CAFE standards.

vertheless, the age els that it s importa to ackno ledge uncertainty in estimates o

w buyers lue fuel ings, as w ll as in it conclusio that no lo s in the 

a

lik

t

e 

c

econ
453

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

References 

Argonne National from 

Transportation (GREET) Model, Versi 2. 

Greene, David L., “Vehicle Use and Fuel Economy: How Big is the Rebound Effect?” The 

Energy Journal, 13:1 (1992), 11 . 

Gree ald W. Jone and Pau . Leiby The Ou for U.S. O ependence, 

ORN tio r y

Gree . Ka R u m n

Hous Ene n

Gree liya h o n 00

ORN Rid n t 

Haug than, and Soum k l s t E r the 

Unite nergy Journa 17:2, 10 126. 

Jones S. er U nd rom 

Impr Th J 4 )

Leiby Jon n ee, and Rus O ts

Asse d Co N , r 1, 

1997

Pickr ., “Description F g r r se

Forec l Transportation Systems Center, U Department of 

Tran

Pulle ning eh st G g

Anal of U ve E c 3

Smal r, K “ to e ce use 

Gas E il e o n s oa rnia 

Envi n Age th y s

U.S. Department of Energy, Program Analysis Methodology Office of Transportation 

Technology: Quality Metrics 2002, Final Report Office of Transportation Technologies, May 9, 

2001. 

U.S. Environmental Protection Agency, MOBILE Motor Vehicle Emission Factor Model, 

version 6.2, November 2002 

Laboratories, The Greenhouse Gas and Regulated Emissions

on 1.6, February 200

7-143

ne, David L., Don s, l N , tlook il D

L-6873, Oak Ridge Na nal Labo atory, Ma 11, 1995. 

ne, David L., James R hn, and obert C. Gibson, “F el Econo y Rebou d Effect for 

ehold Vehicles,” The rgy Jour al, 20:3 (1999), 1-31. 

ne, David L., and Nata I. Tishc ishyna, C sts of Oil Depende ce: A 20 Update, 

L/TM-2000/152, Oak ge Natio al Labora ory, May 2000. 

hton, Jona odip Sar ar, “Gaso ine Tax a a Correc ive Tax: stimates fo

d States,” The E l, 3-

, Clifton T., “Another Look at U. Passeng Vehicle se and the ‘Rebou ’ Effect f

oved Fuel Efficiency,” e Energy ournal, 1 :4 (1993 , 99-110. 

, Paul N., Donald W. es, T. Ra dall Curl sell Lee, il Impor : An 

ssment of Benefits an sts, OR L-6851, Oak Ridge National Laboratory Novembe

. 

ell, Don H of VMT orecastin Procedu e for ‘Ca Talk’ Ba Line 

asts,” manuscript, Volpe Nationa .S.

sportation, 1994. 

r, S.L., and L.A. Gree

ysis Using Nine Years

, “Hous

.S. Sur

old Adju

y Data,”

ment to 

nergy E

asoline Pr

onomics,

ice Chan

21:1, pp.

es: An 

7-52. 

l, K.A. and VanDende . (2005) A Study Evaluat the Effect of Redu d Greenho

missions on Vehicle M es Travel d”, State f Califor ia Air Re ources B rd, Califo

ronmental Protectio ncy, and e California Energ Commis ion. 

, 
454

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

IX. IMPACT OF WEIGHT REDUCTION ON SAFETY 

Placeholder, section forthcoming 
455

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

X. NET BENEFITS AND SENSITIVIT SES 

his chapter compares the costs of technologies needed to make improvements in fuel economy 

ith the potential benefits, expressed in total costs (millions of dollars) from a societal 

erspective for each model year. The costs do not include CAFE fines estimated to be paid by 

manufacturers to NHTSA, since these are t ents. Thus, the total costs shown in this 

section do not matc al costs and 

benefits compared to the adjusted base payback period is calculated, from 

the consumer’s perspective. Finall so performed on some of the 

assumptions made in this analysis. 

Table s the total inc al c m f d ) fro cieta

persp provides t otal be fits at a 3 percent t r from a societal 

persp ro t 3

disco dol he ed M

Table l be a t a pe for 

all ve le X s r u

milli roje t o 1

Total able w r e n

techn cturer pp e v F th ired 

unde aggressive alter T p r the 

Total enefit alternat e are 1.9 mes tho er t Preferr Alternati r 

light ts a m r t e

altern efe ter

In Ta time l b m igher 

bene mo si o l th

aggre r the e e a g fits 

rough the d iv

Table X-5 present the e c iv

altern rnati , results a net b efit to s iety. In Table X-3, 

the c c g i y

from % In te i th ost = 

Total et b fo e r de icle 

types are $ io n

Y ANALY

T

w

p

ransfer paym

h the total costs shown in Chapter VII. These are increment

line of MY 2011. A 

y, sensitivity analyses are al

 X-1 provide rement osts (in illions o ollars m a so l 

ective. Table X-2 he t ne discoun ate

ective for all vehicles p duced. Table X-3 shows the otal net benefits at a percent 

unt rate in millions of lars for t project fleet of sales for MY 2012 – Y 2016. 

 X-4 provides the tota nefits at 7 percen discount rate from societal rspective

hicles produced. Tab

ons of dollars for the p

-5 show

cted flee

the total ne

 of sales f

t benefits 

r MY 20

at a 7 pe

2 – MY 2

cent disco

016. 

nt rate in 

 costs follow a predict pattern ith costs ising to r flect the more expe sive 

ologies that manufa s must a ly in ord r to achie e the CA E levels at are requ

r the more natives. otal com liance costs for the passenge cars under

 Cost = Total B iv ti se und he ed ve. Fo

trucks, compliance cos

r

re 2.7 ti

r

es highe under the Total Cos = Total B nefit 

ative than under the P red Al native. 

bles X-2 and X-4, life societa enefits follow a si ilar predictable pattern, with h

fits associated with the re expen ve techn logies that are enab ed under e more 

ssive alternatives. Fo combin d fleet, th TC=TB lternative produces ross bene

ly 1.55 times those of Preferre Alternat e. 

s X-3 and net ben fits to society produ ed by each alternat e. Each 

ative, including the Preferred Alte

 pa

ve in en oc

ombined net benefit for

 3

ssenger ars and li ht trucks under all f ve model ears ranges 

 $80 billion under the

 Benefit alternative. N

Annual 

enefits 

crease al

r the Pref

rnative to

rred Alte

 $170 bill

native (th

on under

e total un

e Total C

r both veh

 and all model years) 131 bill n at the 3% discou t rate. 
456

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Incremen spective 

(Millions of 2007 Dollars) 

MY 12 MY 13

Table X-1 

tal Total Cost – Societal Per

Alternative 20 20 MY 2014 MY 2015 MY 2016 5-Year Total 

Passenger Cars 

Preferred Alternative $4,148 $5,411 $6,855 $8,221 $9,534 $34,170 

3% Annual Increase $1,622 $2,341 $3,142 $4,047 $5,222 $16,375 

4% Annual Increase $2,148 $3,455 $4,944 $6,561 $8,031 $25,138 

5% Annual Increase $3,074 $5,288 $7,426 $9,410 $11,403 $36,601 

6% Annual Increase $4,504 $7,196 $10,567 $13,546 $16,130 $51,943 

7% Annual Increase $5,263 $8,985 $13,451 $16,627 $19,898 $64,224 

Max Net Benefits $5,217 $8,837 $12,535 $14,930 $17,050 $58,568 

TC = TB $5,674 $9, 9 $13,898 $16 73 $19,403 $65,427 77 ,6

Light Trucks 

Preferred Alternative $1,754 $2,479 $3,657 $4,318 $5,369 $17,578 

3% Annual Increase $8 $463 $1,371 $2,009 $2,719 $6,570 

4% Annual Increase $968 $1,747 $2,975 $3,714 $4,647 $14,051 

5% Annual Increase $2,407 $3,791 $6,103 $6,833 $7,614 $26,749 

6% Annual Increase $2,950 $5,646 $8,157 $9,813 $11,226 $37,793 

7% Annual Increase $3,260 $7,298 $10,020 $12,478 $14,074 $47,130 

Max Net Benefits $4,149 $7,370 $9,698 $11,163 $11,648 $44,028 

TC = TB $4,247 $7,891 $10,464 $12 30 $13,218 $48,149 ,3

Passenger Cars & Light Trucks 

Preferred Alternative $5,903 $7,890 $10,512 $12,539 $14,904 $51,748 

3% Annual Increase $1,630 $2,804 $4,513 $6,057 $7,941 $22,944 

4% Annual Increase $3,116 $5,202 $7,919 $10,275 $12,678 $39,189 

5% Annual Increase $5,482 $9,079 $13,529 $16,243 $19,017 $63,350 

6% Annual Increase $7,455 $12,842 $18,724 $23,359 $27,356 $89,736 

7% Annual Increase $8,524 $16,283 $23,471 $29,104 $33,972 $111,354 

Max Net Benefits $9,366 $16,207 $22,233 $26,092 $28,698 $102,597 

TC = TB $9,921 $17,670 $29,003 $32,620 $113,577 $24,362 
457

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Table X-2 

s by Alternative 

3 % Discount Rate 

Alternative 

MY 

2012 

MY 

2013 

MY 

2014 

MY 

2015 

MY 

2016 

5-Year 

Total 

Present Value of Lifetime Societal Benefit

(Millions of 2007 Dollars) 

Passenger Cars 

Preferred Alternative $6,826 $15,155 $21,626 $28,677 $35,200 $107,483 

3% Annual Increase $3,397 $8,374 $12,331 $16,760 $23,122 $63,984 

4% Annual Increase $4,186 $11,006 $17,315 $24,469 $32,309 $89,286 

5% Annual Increase $6,152 $15,404 $24,075 $32,114 $40,905 $118,649 

6% Annual Increase $7,071 $18,062 137 $28, $37,552 $47,754 $138,576 

7% Annual Increase $8,038 $20,627 $32,225 $42,010 $52,606 $155,507 

Max Net Benefits $8,019 $20,896 $31,683 $39,863 $48,228 $148,689 

TC = TB $ 22,374 $33,916 8,666 $ $42,737 $51,659 $159,352 

Light Trucks 

Preferred Alternative $5,110 $10,684 $15,506 $19,364 $24,310 $74,974 

3% Annual Increase $687 $3,920 $7,635 $11,604 $14,940 $38,786 

4% Annual Increase $ 7,361 $12,580 2,590 $ $17,089 $21,830 $61,450 

5% Annual Increase $ 10,407 $17,686 4,003 $ $23,206 $28,324 $83,626 

6% Annual Increase $4,893 $13,933 $22,031 $28,987 $34,727 $104,571 

7% Annual Increase $5,634 $16,326 $25,550 $32,714 $38,229 $118,453 

Max Net Benefits $ 18,302 $25,913 7,528 $ $31,563 $34,835 $118,141 

TC = TB $7,631 $18,954 $27,294 $33,381 $37,262 $124,522 

Passenger Cars & Light Trucks 

Preferred Alternative $11,936 $25,840 $37,132 $48,040 $59,509 $182,457 

3% Annual Increase $4,085 $12,294 $19,966 $28,364 $38,062 $102,770 

4% Annual Increase $6 $18,367 $29,895 ,776 $41,559 $54,139 $150,735 

5% Annual Increase $10,155 $25,811 $41,760 $55,320 $69,229 $202,275 

6% Annual Increase $11,964 $31,995 $50,168 $66,539 $82,481 $243,147 

7% Annual Increase $13,672 $36,953 $57,776 $74,724 $90,835 $273,960 

Max Net Benefits $15,547 $39,198 $57,596 $71,426 $83,063 $266, 830

TC = TB $16,297 $41,328 $61,209 $76,118 $88,922 $283,874 
458

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Table X-3 

Net Total Benefits 

Over the Vehicle’s Lifetime – Present Value 

3% Discount Rate 

(Millions of 2007 Dollars) 

Alternative MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 5-Year Total 

Passenger Cars 

Preferred Alternative $2,677 $9,745 $14,770 $20,455 $25,665 $73,313 

3% Annual Increase $1,776 $6,033 $9,188 $12,713 $17,900 $47,609 

4% Annual Increase $2,038 $7,551 $12,371 $17,909 $24,278 $64,147 

5% Annual Increase $3,077 $10,116 $16,649 $22,704 $29,502 $82,048 

6% Annual Increase $2,567 $10,866 $17,570 $24,005 $31,624 $86,633 

7% Annual Increase $2,775 $11,642 $18,775 $25,383 $32,709 $91,283 

Max Net Benefits $2,802 $12,059 $19,148 $24,933 $31,179 $90,121 

TC = TB $2,992 $12,595 $20,017 $26,064 $32,257 $93,925 

Light Trucks 

Preferred Alternative $3,356 $8,205 $11,849 $15,045 $18,940 $57,396 

3% Annual Increase $679 $3,458 $6,264 $9,595 $12,222 $32,217 

4% Annual Increase $1,622 $5,614 $9,605 $13,375 $17,183 $47,399 

5% Annual Increase $1,596 $6,616 $11,582 $16,373 $20,710 $56,877 

6% Annual Increase $1,943 $8,287 $13,874 $19,174 $23,501 $66,779 

7% Annual Increase $2,373 $9,028 $20,236 $24,155 $71,324 $15,531 

Max Net Benefits $3,379 $10,932 $16,215 $20,400 $23,186 $74,112 

TC = TB $3,384 $11,063 $16,830 $21,050 $24,045 $76,373 

Passenger Cars & Light Trucks 

Preferred Alternative $6,033 $17,950 $26,619 $35,501 $44,606 $130,709 

3% Annual Incre ase $2,455 $9,490 $15,453 $22,307 $30,121 $79,826 

4% Annual Increase $3,660 $13,165 $21,976 $31,284 1,461 $111,546 $4

5% Annual Increase $4,673 $16,732 $28,231 $39,076 0,213 $138,925 $5

6% Annual Increase $4,509 $19,154 $31,444 $43,180 5,125 $153,412 $5

7% Annual Increase $5,148 $20,670 $34,305 $45,619 6,864 $162,606 $5

Max Net Benefits $6,181 $22,991 $35,363 $45,333 4,365 $164,233 $5

TC = TB $6,377 $23,658 $36,847 $47,114 6,301 $170,297 $5
459

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

A

Table X-4 

Present Value of Lifetime Societal Benefits by Alternative 

7 % Discount Rate 

(Millions of 2007 Dollars) 

lternative 

MY 

2012 

MY 

2013 

MY 

2014 

MY 

2015 

MY 

2016 

5-Year 

Total 

Passenger Cars 

Preferred Alternative $5,474 $12,255 $17,499 $23,235 $28,567 $87,031 

3% Annual Increase $2,727 $6,778 $9,980 $13,585 $18,774 $51,844 

4% Annual Increase $3,356 $8,904 $14,015 $19,838 $26,241 $72,353 

5% Annual Increase $4,941 $12,472 $19,493 $26,030 $33,185 $96,122 

6% Annual Increase $5,667 $14,612 $22,763 $30,402 $38,735 $112,180 

7% Annual Increase $6,448 $16,692 $26,080 $34,028 $42,669 $125,917 

Max Net Benefits $6,134 $16,378 $25,041 $31,517 $38,120 $117,191 

TC = TB $6,957 $18,112 $27,453 $34,625 $41,897 $129,044 

Light Trucks 

Preferred Alternative $4,015 $8,427 $12,243 $15,302 $19,225 $59,212 

3% Annual Increase $545 $3,099 $6,035 $9,178 $11,823 $30,679 

4% Annual Increase $2,035 $5,802 $9,927 $13,500 $17,260 $48,524 

5% Annual Increase $3,129 $8,189 $13,929 $18,300 $22,365 $65,913 

6% Annual Increase $3,823 $10,966 $17,349 $22,842 $27,385 $82,366 

7% Annual Increase $4,404 $12,838 $20,108 $25,767 $30,132 $93,248 

Max Net Benefits $5,736 $12,761 $18,525 $22,485 $25,290 $84,797 

TC = TB $6,039 $14,926 $21,502 $26,237 $29,295 $97,999 

Passenger Cars & Light Trucks 

P ferred Alternative re $9,490 $20,682 $29,742 $38,538 $47,791 $146,243 

3% Annual Increase $3,272 $9,877 $16,014 $22,763 $30,597 $82,523 

4% Annual Increase $5,390 $14,706 $23,942 $33,338 $43,500 $120,877 

5% Annual Increase $8,070 $20,661 $33,422 $44,330 $55,551 $162,035 

6% Annual Increase $9,490 $25,579 $40,111 $53,245 $66,120 $194,545 

7% Annual Increase $10,852 $29,530 $46,187 $59,795 $72,801 $219,165 

Max Net Benefits $11,870 $29,140 $43,566 $54,002 $63,410 $201,988 

TC = TB $12,997 $33,037 $48,955 $60,862 $71,193 $227,044 
460

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Over the Vehicle’s Lifetime – Present Value 

MY 2012 MY 2013

Table X-5 

Net Total Benefits 

7% Discount Rate 

(Millions of 2007 Dollars) 

Alternative MY 2014 MY 2015 MY 2016 5-Year Total 

Passenger Cars 

Preferred Alternative $1,326 $6,844 $10,644 $15,014 $19,032 $52,861 

3% Annual Increase $1,106 $4,436 $6,838 $9,537 $13,552 $35,469 

4% Annual Increase $1,208 $5,449 $9,071 $13,277 $18,210 $47,215 

5% Annual Increase $1,867 $7,184 $12,067 $16,620 $21,782 $59,521 

6% Annual Increase $1,163 $7,416 $12,196 $16,856 $22,605 $60,237 

7% Annual Increase $1,185 $7,707 $12,629 $17,401 $22,771 $61,693 

Max Net Benefits $1,170 $7,894 $12,838 $16,969 $21,583 $60,454 

TC = TB $1,283 $8,333 $13,555 $17,952 $22,495 $63,617 

Light Trucks 

Preferred Alternative $2,261 $5,948 $8,586 $10,984 $13,855 $41,635 

3% Annual Increase $537 $2,636 $4,664 $7,169 $9,104 $24,110 

4% Annual Increase $1,067 $4,055 $6,952 $9,786 $12,613 $34,473 

5% Annual Increase $722 $4,398 $7,826 $11,467 $14,751 $39,164 

6% Ann ease ual Incr $872 $5, , 321 $9 192 $13,029 $16,159 $44,573 

7% Annual Increase $1,143 $5,54 $10,088 13,289 $16,058 $46,119 0 $

Max Net Benefits $1,647 $6,58 $10,195 12,936 $15,123 $46,482 1 $

TC = TB $1,579 $7,46 $10,988 13,982 $16,229 $50,241 3 $

Passenger Cars & Light Trucks 

Preferred Alternative $3,587 $12,792 $19,230 $25,998 $32,888 $94,495 

3% Annual Increase $1,642 $7,07 $11,501 16,706 $22,656 $59,579 3 $

4% Annual Increase $2,274 $9,50 $16,023 23,064 $30,822 $81,688 4 $

5% Annual Increase $2,589 $11,583 $19,89 28,087 $36,534 $98,685 3 $

6% Annual Increase $2,035 $12,737 $21,387 $29,885 $38,764 $104,810 

7% Annual Increase $2,328 $13,247 $22,71 30,690 $38,829 $10 7 $ 7,812 

Max Net Benefits $2,818 $14,475 $23,033 $29,904 $36,706 $106,936 

TC = TB $2,863 $15,795 $24,54 31,933 $38,724 $11 3 $ 3,858 
461

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Breakdown of costs and benefits for the preferred alternative

Table X-6 provides a breakdown of the costs and benefits for the preferred alternative using a 3 

percent and 7 percent discount rate, respectively. 

Table X-6 

Preferred Alternative 

Cost and Benefit Estimates 

MY 2012-2016 Combined 

Passenger Cars and Light Trucks Combined 

($ millions) 

 Undiscounted Discounted 

3% 

Discounted

7% 

Technol

Cos

ogy $51,748 $51,748 $51,748 

ts 

 

Benefits 

Lifetim

Exp

e Fuel 178,880 143,048 112,005 

enditures 

Consum

Sur

Addi

Driving 

er 13,092 10,491 8,233 

plus from 

tional 

Refueli

ime V

ng 

alue 

11,482 9,443 7,608 

T

Petroleum 

Market 

Externalities 

9,801 7,952 6,322 

Congestion 

Costs 

-7,694 -6,264 -4,993 

Noise Costs -151 -122 -97 

Crash Costs -3,681 -,2989 -2,378 

CO2 18,314 14,528 14,528 

CO 0 0 0 

VOC 612 494 391 

NOX 722 612 475 

PM 3,720 2,974 2,329 

SOX 2,820 2,288 1,819 

Total 227,967 182,457 146,243 

 

Net Benefits $128,992 $89,638 
462

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Payback Period 

The “payback period” represents the length of time required for a vehicle buyer to

through savings in fuel use, the higher cost of purchasing a more fuel-efficient ve Thus, 

only these two factors are considered (purchase pric vings). When a h AFE 

standard requires a manufacturer to improve the fuel e y of vehi dels, the 

manufacturer’s added costs for doing so are general in es f m

While buyers of these models pay high e v eir im ved f

economy lowers the consu s for hasing pe e

may recoup the higher pur s r e f sa s in 

th requ repay th igher cost ying ls referred to a he buyer’ payback pe d. 

s payback n e in e in s p pric

 in its fuel the r of driv ar, eta

e calculate pe ing nom eme ver

ated to th ard, t retai

ber of cle iven as t hes atio

umer ive tive ly g

nefit e e . Th aso es f s a

isco res e, s ers onl er 

y a T ack est an for

ffe ativ pa ds f 16 a n in

Table X-7 

Pa iod 201 Ve

(in years) 

Pass Li

 recoup, 

hicle. 

igher C

cle mo

or these 

pro

r time, buy

ving

a more fue

e and fuel sa

conom

ly reflected

purchase thes

 fuel to o

 these vehicl

e h

some of its

 higher pric

ehicles, th

rate them. Ov

s in the form o

 of bu

odels. 

uel 

ers 

er prices to

 purc

they pay fo

ired to

mer’s cost

chase price

outlays for fuel. The leng of time

efficient vehicle i s t s rio

The length of thi

the improvement

 period depe ds on th itial increas a vehicle’ urchase e, 

economy, numbe miles it is en each ye and the r il 

price of fuel. W d payback riods us the fuel eco y improv nt and a age 

price increase estim result from e stand he future l gasoline prices, and 

estimates of the num miles vehi s are dr each year hey age. T e calcul ns 

are taken from a cons

are included on the be

’s perspect

s side of th

, not a socie

quation

tal perspec

e price of g

. Thus, on

line includ

asoline sav

uel taxe

ings 

nd 

future savings are not d unted to p ent valu ince consum generally y consid and 

respond to what they pa t the pump. he payb periods are imated as average all 

manufacturers for the di rent altern es. The yback perio or MY 20 re show

Table X-7. 

yback Per for MY 6 Average hicles 

enger Cars ght Trucks

Prefer ativ red Altern e 3.3 2.2 

3% An ase nual Incre 2.7 2.1 

4% Annua ncrease l I 3.0 2.5 

5% An ase nual Incre 3.4 3.2 

6% An ase nual Incre 4.2 3.9 

7% An ase nual Incre 4.8 4.6 

Max Net Benefits 4.4 4.0 

Total Cost Benefi = Total t 4.8 4.3 
463

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

yses 

performed nsit alys ine i ssu . W

ith respect to the following economic parameters: 

asoline: The main analysis (i.e., the Reference Case) uses the AEO 2010 

 Refe es or t aso abl ). I

al am fec the Hig Ca

r ate d. A case bec AE

se ide fere orec

s a 3 percent discount rate e mpg levels. It 

 presents benefi 7 p isco his sho t th

ls would be w nefits alue er nt et th

he standa

d effect: an e rce jec

es trav co ile eas n l

e eff g a nt o t reb ct in

O2 d m ny: ana $21 on 

 pe oun qua enef cin is

all tify efit g f pti e 

sis, we examine the following values and discount rates applied only to 

l cost of ca lue ben e ar val ich 

 time. These values can be translated into cents per gallon by multiplying 

 0.0089, givin in s: 

2) = $ er g unte

9 = $0 per ga ount use mai

O = per oun 

ti f 

($64.90 per ton CO2) x 0.0089 = $0.5776 per gallon discounted at 3% 

5) Military security: The main analysis $0 p r gallon to quantify the military security 

benefits of reducing fuel consumption. In he sensitivity analysis, we examine the impact 

of using a value of 5 cents per gallon instead. 

6) Consumer Benefit: The main analysis assumes there is no loss in consumer surplus with 

vehicles that have an increase in price and higher fuel economy. This sensitivity analysis 

assumes that there is a 25, 50, or 75 percent loss in consumer surplus – equivalent to the 

 

Sensitivity Anal

The agency has several se ivity an es to exam mportant a mptions e 

examine sensitivity w

1) The price of g

Early Release rence Case timate f he price of g line (see T e VIII-4 n 

this sensitivity an

Low Price Case fo

ysis we ex

ecast estim

ine the ef

s instea

t of using 

EO 2009 

AEO 2009

s are used

h Price

ause the

se or 

O 

2010 Early Relea only prov s the Re nce Case f ast. 

2) Discount rate: The main analysis use to set th

also ts using a ercent d unt rate. T sensitivity ws wha e 

mpg leve

levels of t

hen be

rd. 

are v d using a 7 p cent discou rate to s e 

3) The reboun The main alysis uses a rebound eff ct of 10 pe nt to pro t 

increased mil eled as the st per m driven decr es. In the se sitivity ana ysis, 

we examine th ect of usin 5 perce r 15 percen ound effe stead. 

4) The values of C benefits an onopso The main lysis uses .35 per t

discounted at a 3 rcent disc t rate to ntify the b its of redu g CO2 em sions 

and $0.190 per g on to quan the ben s of reducin uel consum on. In th

sensitivity analy

the socia rbon to va carbon efits. Thes e the 2010 ues, wh

increase over

by 286 g the follow g value

($4.72 per ton CO x 0.0089 0.042 p allon disco d at 5% 

($21.35 per ton CO

analysis) 

2) x 0.008 .190 llon disc ed at 3% ( d in the n 

($35.06 per ton C 2) x 0.0089 $0.312 gallon disc ted at 2.5%

And a 95th percen le estimate o

e

 t

286 The molecular weight of Carbon (C) is 12, the molecular weight of Oxygen (O) is 16, thus the molecular weight 

of CO2 is 44. One ton of C = 44/12 tons CO2 = 3.67 tons CO2. 1 gallon of gas weighs 2,819 grams, of that 2,433 

grams are carbon. $1.00 CO2 = $3.67 C and $3.67/ton * ton/1000kg * kg/1000g * 2433g/gallon = (3.67 * 2433) / 

1000 * 1000 = $0.0089/gallon 
464

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

assumption that consumers will on alculated benefits they will achieve at 75, 

50, or 2

 

Varying each of the above 6 parameters in isolation results in a variety of economic sc os. 

These are listed in Table X-8 below along with the preferred alternative, together wit

additional scenarios that use values from the first 5 para produce the lowes

highest valued benefits. 

7) In addition, the agency performed two on an st, in les X

11 and X-12, the agency a e i hat a re

factor of 1.5 for all techn n al tead sing

odolo ). PE fact lts in h cost fo

e technologies. The CM methodology does not include profits, while e RPE 

tor methodology does. T m ogy results in an overall markup f 

 compared to the ark r fro ble cost of 1.5. Sec 

3, we will separat min ensit the ben f redu teria

s and vehicle safet ernat es of cal life. 

Ta 8 

itiv alyse

Fue

Pric

sc

Ra

Rebo

Ef SCC

ly value the c

5 percent, respectively, of their main analysis estimates. 

enari

h two 

t and 

Tab

alent (RPE

 of u

estimates 

meters that 

al sensitivity 

having 

 the various 

or resu

additi

mpact t

d have o

The R

alyses. Fir

tail price equiv

ternatives ins

igher 

-

) 

r 

nalyzed th

ologies woul

the indirect cost meth gy (ICM

each of th I th

fac

1.2

he ICM

 RPE m

ethodol

up facto

 factor o

 to 1.25 ond, in

Table X-1

m varia

ely exa e the s ivity of efits o cing cri

pollutant y to alt e valu statisti

ble XSens ity An s 

Name l Di

e 

ount 

te 

und 

fect 

Monopsony 

ct 

tary 

Effe rity 

Mili

Secu

Reference Refere 3 10 $20 nce % % 0¢/gal gal 0¢/

High Fuel Price High 3 1 $20 % 0% 0¢/gal al 0¢/g

Low Fuel Price Low 3 1 $20 % 0% 0¢/gal gal 0¢/

7% Discount Rate Refere 7 1 $20 nce % 0% 0¢/gal gal 0¢/

5% Rebound Effect Refere 3 5 $20 nce % % 0¢/gal gal 0¢/

15% Rebound Effect Refere 3 1 $20 nce % 5% 0¢/gal gal 0¢/

$56/ton CO2 Value Refere 3% 10% $56 nc e 0¢/gal gal 0¢/

$10/ton CO2 Refere 3 10 $10 nce % % 0¢/gal al 0¢/g

5¢/gal Military Security 

Value Refere 3 10% nce % $20 0¢/gal al 5¢/g

Lowest Discounted 

Benefits Low 7 15% $10 % 0¢/gal gal 0¢/

Highest Discounted

Benefits High 3 5 $56 % % 0¢/gal gal 5¢/

25% Consumer Benefit Refere 3 10 $20 nce % % 0¢/gal 0¢/gal

50% Consumer Benefit Refere 3 10 $20 nce % % 0¢/gal 0¢/gal

75% Consumer Benefit Refere 3 10 $20 nce % % 0¢/gal gal 0¢/

For these cases, sensitivity an

9 presents the achieved fuel econ

alyse er n t red A e only e Xom eh ice in total b total coss were p

y, per-v

formed o

icle pr

he Prefer

crease, 

lternativ

enefits,

. Tabl

t, 
465

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

ifetim ctio 2 e s that w lt u e 

mic scena th eved nomy r-vehic

ts only the l year 2 results, this m ear showed the 

nefits, cost savi d C s re s, the

ive model rathe thei for MY refl total 

 the various ec nomic assum tions. 

nts the percentage es fr Pre lternati nomic

he items in Table rom table nclude owin ing 

rying the economic eter g the ered va

conomic assum s ha ilar ef n the pa r car a t 

s. 

nomic assum s ha st no on achi el eco with

narios havin fect e tha pg. 

omic assum s ha ost, a impact o cle co l 

 or emissio ion none e effect large

tin vary nom ters i nefits ging

to the 09 H orecast bene a 

her la pac enefi red wit % disc te (-

nefits at ent %). 

rs value the s a d at e mai sis ass ons, 

l exceed co

6) Changing all economic parameters simultaneously to the lowest or highest values, among 

the values considered (not including the lue of consumer benefits), changes benefits by 

at about 56%. However impacts to other ntities, such as cost, are much smaller, 

lifetime fuel savings, and the l e redu ns in CO mission ould resu nder th

standards from the econo rios. For e achi fuel eco and pe le price 

increase, the table presen

greatest impacts. For be

mode

s, fuel 

016 

ngs, an

 since 

O emission

odel y

2 duction

r values 

 table 

presents totals over the f years, r than 2016, to ect the 

impact of the standards that would result from o p

Table X-10 prese

assumptions for t

 chang

X-9. F

om the

 these 

ferred A

s, we co

ve eco

 the foll g regard

the impact of va param s amon consid lues: 

1) The various e ption ve sim fects o ssenge nd ligh

truck standard

2) Varying the eco

none of the sce

ption

g an ef

s almo

of mor

impact 

n 0.2 m

eved fu nomy,

3) Varying the econ ption s, at m small n vehi sts, tota

costs, fuel saved n reduct s with of thes s being r than 10 

percent. 

4) The largest change resul g from ing eco ic parame

f

s on be . Chan

the fuel price forecast 

combined +44.2%. Ot

 AEO 20

rge im

igh Price

ts on b

 Case 

ts occur

impacts 

h the 7

fits by 

ount ra

19.8%), valuing be 75 perc (-22.3 

5) Even if consume benefit chieve 25% of th n analy umpti

total benefits stil sts. 

va

qua

resulting in increases or decreases of 7% or less. 

Regarding the lower fuel savings and CO2 emissions reductions predicted by the sensitivity 

analysis as fuel price increases, which initially may seem counterintuitive, we note that there are

some counterbalancing factors occurring. As fuel price increases, people will drive less and so 

fuel savings and CO2 emissions reductions may decrease. 
466

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

(mpg, Per-Vehicle C missions Reduced) 

Econo tions 

MY 201

Achieved 

mpg 

MY 2016 

PerVehicle 

Cost 

MY 

20

Benefits

Discounted 

3%, in 

Millions of 

$ 

2012-

ost 

(Societal 

rspective)

, in Millions 

of $ 

MY 

2012-

Fu

Sav

in 

Milli

of 

Gallons 

MY 2012-

2016 CO2 

Emissions 

Reduced, 

in mmT 

Table X-9 

Sensitivity Analyses 

ost, Total Benefits, Total Cost, Fuel Saved, & CO2 E

mic Assump

6 

2012-

16 MY 

, 2016 C

Pe

2016 

el 

ed, 

ons 

Passenger Cars 

Preferred 37. $907 $107,48 $34,170 35,66 380 2 3 0 

High Fuel Price 37.4 $960 $154,052 $36,080 34,374 360 

Low Fuel Price 37.2 $907 $101,243 $34,170 35,660 380 

7% Discount Rate 37.2 $907 $87,031 $34,170 35,660 380 

5% Rebound Effect 37.2 $907 $112,569 $34,170 37,284 398 

15% Rebound Effect 37.2 $907 $102,397 $34,170 34,036 362 

$4.72/ton CO2 Value 37.2 $907 $100,964 $34,170 35,660 380 

$35.06/ton CO2 Value 37.2 $907 $112,788 $34,170 35,660 380 

$64.90/ton CO2 Value 37.2 $907 $124,921 $34,170 35,660 380 

5¢/gal Military 

Security Value 37.2 $907 $108,875 $34,170 0 380 35,66

Lowest Discounted 

Benefits 37.0 $858 29 $46,3 $32,561 7 358 33,54

Highest Discounted 

Benefits 37.4 $960 $166,258 $36,080 32 35,9 377 

25% Consumer Benefit 37.2 $907 $35,060 $34,170 35,660 380 

50% Consumer Benefit 37.2 $907 $59,201 $34,170 35,660 380 

75% Consumer Benefit 37.2 $907 $83,342 170 $34, 35,660 380 

Light Trucks 

Preferred 28.5 $961 $74,974 $17,578 25,350 275 

High Fuel Price 28.6 $991 $108,996 $19,069 24,826 261 

Low Fuel Price 28.5 $961 $70,544 $17,578 25,350 275 

7% Discount Rate 28.5 $961 $59,212 $17,578 25,350 275 

5% Rebound Effect 28.5 $961 $78,065 $17,578 26,543 288 

15% Rebound Effect 28.5 $961 $71,882 $17,578 24,158 262 

$4.72/ton CO2 Value 28.5 $961 $70,311 $17,578 25,350 275 

$35.06/ton CO2 Value 28.5 $961 $78,779 $17,578 25,350 275 

$64.90/ton CO2 Value 28.5 $961 $87,408 $17,578 25,350 275 
467

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

 275 

5¢/gal Military 

Security Value 28.5 $961 $75,933 $17,578 25,350 

Lowest Discounted 

Benefits 28.3 $865 $31,669 $15,391 23,746 257 

Highest Discounted 

Benefits 28.6 $991 $117,253 $19,069 25,989 274 

25% Consumer Benefit 28.5 $961 $25,159 $17,578 25,350 275 

50% Consumer Benefit 28.5 $961 $41,764 $17,578 25,350 275 

75% Consumer Benefit 28.5 $961 $58,369 $17,578 25,350 275 

Passenger Cars & Light Trucks Combined 

Preferred 33.7 $926 $182,457 $51,748 61,010 655 

High Fuel Price 33.8 $970 $263,048 $55,149 59,200 621 

Low Fuel Price 33.7 $926 $171,787 $51,748 61,010 655 

7% Discount Rate 33.7 $926 $146,243 $51,748 61,010 655 

5% Rebound Effect 33.7 $926 $190,634 $51,748 63,826 686 

15% Rebound Effect 33.7 $926 $174,279 $51,748 58,194 624 

$4.72/ton CO2 Value 33.7 $926 $171,276 $51,748 61,010 655 

$35.06/ton CO2 Value 33.7 $926 $191,567 $51,748 61,010 655 

$64.90/ton CO2 Value 33.7 $926 $212,329 $51,748 61,010 655 

5¢/gal Military 

Security Value 33.7 $926 $184,808 $51,748 61,010 655 

Lowest Discounted 

Benefits 33.5 $861 $77,998 $47,952 57,293 615 

Highest Discounted 

Benefits 33.8 $970 $283,511 $55,149 61,921 651 

25% Consumer Benefit 33.7 $926 $60,219 $51,748 61,010 655 

50% Consumer Benefit 33.7 $926 $100,965 $51,748 61,010 655 

75% Consumer Benefit 33.7 $926 $141,711 $51,748 61,010 655 
468

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Economic Assumptions 

MY 2016 

Achieved 

mpg 

MY 

2016 

PerVehicle 

Cost 

MY 2012-

2016 

Benefits, 

Discounted 

3%, in 

Millions of 

$ 

MY 2012-

2016 Cost 

(Societal 

Perspective), 

in Millions 

of $ 

MY 

2012-

2016 

Fuel 

Saved, 

in 

Millions 

of 

Gallons 

MY 2012-

2016 CO2 

Emissions 

Reduced, 

in mmT 

Table X-10 

Sensitivity Analyses – Percentage Change from the Reference Case 

Passenger Cars 

Preferred Base Base Base Base Base Base 

High Fuel Price 0.4% 5.8% 43.3% 5.6% -3.6% -5.2% 

Low Fuel Price 0.0% 0.0% -5.8% 0.0% 0.0% 0.0% 

7% Discount Rate 0.0% 0.0% -19.0% 0.0% 0.0% 0.0% 

5% Rebound Effect 0.0% 0.0% 4.7% 0.0% 4.6% 4.7% 

15% Rebound Effect 0.0% 0.0% -4.7% 0.0% -4.6% -4.7% 

$4.72/ton CO2 Value 0.0% 0.0% -6.1% 0.0% 0.0% 0.0% 

$35.06/ton CO2 Value 0.0% 0.0% 4.9% 0.0% 0.0% 0.0% 

$64.90/ton CO2 Value 0.0% 0.0% 16.2% 0.0% 0.0% 0.0% 

5¢/gal Military Security Value 0.0% 0.0% 1.3% 0.0% 0.0% 0.0% 

Lowest Discounted Benefits -0.5% -5.4% -56.9% -4.7% -5.9% -5.7% 

Highest Discounted Benefits 0.4% 5.8% 54.7% 5.6% 0.8% -0.7% 

25% Consumer Benefit 0.0% 0.0% -67.4% 0.0% 0.0% 0.0% 

50% Consumer Benefit 0.0% 0.0% -44.9% 0.0% 0.0% 0.0% 

75% Consumer Benefit 0.0% 0.0% -22.5% 0.0% 0.0% 0.0% 

Light Trucks 

Preferred Base Base Base Base Base Base 

High Fuel Price 0.1% 3.1% 45.4% 8.5% -2.1% -4.9% 

Low Fuel Price 0.0% 0.0% -5.9% 0.0% 0.0% 0.0% 

7% Discount Rate 0.0% 0.0% -21.0% 0.0% 0.0% 0.0% 

5% Rebound Effect 0.0% 0.0% 4.1% 0.0% 4.7% 4.8% 

15% Rebound Effect 0.0% 0.0% -4.1% 0.0% -4.7% -4.8% 

$4.72/ton CO2 Value 0.0% 0.0% -6.2% 0.0% 0.0% 0.0% 

$35.06/ton CO2 Value 0.0% 0.0% 5.1% 0.0% 0.0% 0.0% 

$64.90/ton CO2 Value 0.0% 0.0% 16.6% 0.0% 0.0% 0.0% 

5¢/gal Military Security Value 0.0% 0.0% 1.3% 0.0% 0.0% 0.0% 

Lowest Discounted Benefits -0.7% -10.0% -57.8% -12.4% -6.3% -6.5% 
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Highest Discounted Benefits 0.1% 3.1% 56.4% 8.5% 2.5% -0.2% 

25% Consumer Benefit 0.0% 0.0% -66.4% 0.0% 0.0% 0.0% 

50% Consumer Benefit 0.0% 0.0% -44.3% 0.0% 0.0% 0.0% 

75% Consumer Benefit 0.0% 0.0% -22.1% 0.0% 0.0% 0.0% 

Passenger Cars & Light ombined Trucks C 

Preferred Base Base Base Base Base Base 

High Fuel Price 0.3% 4.8% 44.2% 6.6% -3.0% -5.1% 

Low Fuel Price 0.0% 0.0% -5.8% 0.0% 0.0% 0.0% 

7% Discount Rate 0.0% 0.0% -19.8% 0.0% 0.0% 0.0% 

5% Rebound Effect 0.0% 0.0% 4.5% 0.0% 4.6% 4.7% 

15% Rebound Effect 0.0% 0.0% -4.5% 0.0% -4.6% -4.7% 

$4.72/ton CO2 Value 0.0% 0.0% -6.1% 0.0% 0.0% 0.0% 

$35.06/ton CO2 Value 0.0% 0.0% 5.0% 0.0% 0.0% 0.0% 

$64.90/ton CO2 Value 0.0% 0.0% 16.4% 0.0% 0.0% 0.0% 

5¢/gal Military Security Value 0.0% 0.0% 1.3% 0.0% 0.0% 0.0% 

Lowest Discounted Benefits -0.6% -7.0% -57.3% -7.3% -6.1% -6.0% 

Highest Discounted Benefits 0.3% 4.8% 55.4% 6.6% 1.5% -0.5% 

25% Consumer Benefit 0.0% 0.0% -67.0% 0.0% 0.0% 0.0% 

50% Consumer Benefit 0.0% 0.0% -44.7% 0.0% 0.0% 0.0% 

75% Consumer Benefit 0.0% 0.0% -22.3% 0.0% 0.0% 0.0% 

In addition, the agency analyzed the impact that having a retail price equivalent (RPE) factor of 

1.5 for all technologies would have on the various alternatives instead of using the indirect cost 

methodology (ICM) resulting in an overall price increase multiplier from variable cost of 1.2 to 

1.25, with special attention being paid to the preferred alternative and the maximum net benefit 

alternative. Table X-11 shows the impact on the MY 2016 achieved mpg level for passenger 

cars and light trucks by changing the cost markup factors used in the Volpe model. The big 

difference is in mpg for the maximum net benefit alternative. Having a higher cost for 

technologies limits how many technologies are cost effective. Table X-12 shows the impacts on 

costs and benefits for the preferred alternative comparing the preferred alternative using the ICM 

method to the RPE method. 
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Achieved mpg level 

nce 

Table X-11 

Comparing Different Cost Mark-up Methodologies 

(Achieved mpg levels) 

ICM Method 

(Main analysis) 

RPE Method 

(Sensitivity) 

Differe

(mpg) 

Passenger Car 

Preferred Al

37.21 37.17 0.04 

ternative 

Passenger Car 

Maximum Net Benefits 

Alternative 

39.77 39.21 0.56 

 

Light Truck 

Preferred Alternative 

28.53 28.36 .17 

Light Trucks 

Maximum Net Benefits 

Altern

30.63 30.04 .59 

ative 

 

Table X-12 

Sensitivity Analyses 

(mpg, Per-Vehicle Cost, Total Benefits, Total Cost, Fuel Saved, & CO2 Emissions Reduced) 

s 

 2012-

6 CO2 

issions 

duced, 

Economic Assumptions in mmT 

MY 2016 

Achieved 

mpg 

MY 

2016 

PerVehicle 

Cost 

MY 2012-

2016 

Benefits, 

Discounted 

3%, in 

Millions of 

$ 

MY 2012-

2016 Cost 

(Societal 

Perspective), 

in Millions 

of $ 

MY 

2012-

2016 

Fuel 

Saved, 

in 

Millions 

of 

Gallon

MY

201

Em

Re

Passenger Cars

Preferred 37.21 $907 $107,483 $34,170 35,660 380 

RPE method 37.17 $1,136 $102,589 $41,804 34,052 363 

Light trucks

Preferred 28.53 $961 $74,974 $17,578 25,350 275 

RPE method 28.36 $1,141 $74,510 $20,476 25,210 273 

Sensitivity Analysis, Value of Statistical Life
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The 

gulations issued from 

numerous agencies including DOT, EPA, OSHA, CPSC, etc., and issues guidance for agencies 

to u

ensure y various regulatory agencies, OMB has 

not ta

recomm

assign 

The De os for the various 

mo , DOT established a VSL of $5.8 million with 

sup m $8.4 million in recognition of uncertainty found 

ove measured in 2007 dollars). Although DOT recently 

rev d denominated in 2008 dollars, 

and h

rule would still be highly cost-beneficial using the DOT VSL of $5.8 million. 

A for 

te is 

 

s noted in the DOT guidance, however, the uncertainty surrounding the VSL is notable, and 

should be recognized in regulatory analyses. Accordingly, NHTSA has prepared this sensitivity 

 

The value associated with preventing a fatality is measured by the Value of a Statistical Life 

(VSL), defined as the value of preventing one random fatality among a population at risk. 

Office of Management and Budget (OMB) reviews and approves re

se in analyzing the impacts of their regulations. Although OMB guidance generally seeks to 

a level of consistency in the issues addressed b

es blished a common VSL for use across all government agencies. Instead, OMB 

ends that each agency develop and justify its own VSL. As a result, different agencies 

different values to saving a life in their regulations. 

partment of Transportation (DOT) has issued a series of guidance mem

des within the department. In February 2008

ple entary calculations at $3.2 million and 

r a range of studies (these figures are

ise its central estimate of VSL to $6.0 million, this figure is

 w en adjusted to 2007 dollars remains at $5.8 million. 

By contrast, EPA uses VSL of $7.6 million (2007 dollars), which is 30% higher than DOT’s 

central estimate, although still within the upper estimate recommended by DOT to recognize 

uncertainty. The differing VSLs across agencies should be judged as arising from different 

conclusions regarding the validity of the various studies on VSL, rather than a function of the 

different at-risk populations that they represent. 

Within the CAFE FRIA, VSL is used for two different purposes, once to value benefits-per-ton 

from reducing emissions of criteria pollutants in Chapter VIII, and once to value potential safety 

impacts in Chapter IX. The potential safety impacts calculation is discussed outside the Volpe 

model, in order to emphasize the uncertainty surrounding this issue. It is examined separately 

and put in context of the overall net benefits derived from the Volpe model. The basic 

conclusion is that the safety impacts are highly uncertain, but, even under the upper bound 

estimate, the 

The benefits-per-ton values for reducing emissions of criteria pollutants were derived by EP

use by both EPA and NHTSA in this rulemaking activity. These estimates were based on an 

estimate of VSL derived previously by EPA and reported in its Guidelines for Preparing 

Economic Analyses (see Technical Support Document, Section 4.B.11.b.).287 This estima

$6.3 million in 2000 dollars, which corresponds to $7.6 million when expressed in 2007 dollars.

NHTSA agreed to use the estimates of per-ton benefits from reducing air pollutant emissions 

derived by EPA in this rulemaking, despite their reliance on a VSL estimate higher than that 

endorsed by DOT. 

A

c Analyses. EPA 

sf/webpages/Guidelines.html/$file/cover.pdf (last accessed March 4,2010). 

287 U.S. Environmental Protection Agency (U.S. EPA). 2000. Guidelines for Preparing Economi

240-R-00-003. National Center for Environmental Economics, Office of Policy Economics and Innovation. 

Washington, DC. September. Available at

http://yosemite.epa.gov/ee/epa/eed.n
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analysis, which examines the values of both safety mortality impact and mortality benefits from 

reducing criteria pollutant emissions under the complete range of DOT VSL values, as well as 

the EPA value. Table X-13 summarizes these estimates: 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

Sensitivity Analysis of Alte f 2007$, MYs 2012-2016) 

ssumed VSL Source V f Fata

Impacts288

Value of Mortality 

Ben rom R

Emissions of Criteria 

ollutan

Table X-13 

rnate VSLs (millions o

A

(2007$) 

alue o lity efits f educed 

Air P ts 

$3.2 million DOT Lower Estim $ 2,055 ate 182 – $3,125 

$5.8 million DOT Central Estimate $317 – 3,581 $5,185 

$7.6 million EPA Est imate $411 – 4,637 $6,557 

$8.4 million DOT Upper Estimate $452 – 5,107 $7,194 

As mentioned above, the safety cts ar ly un and sed

model. Although t ts be re u e V odel, pac 

small. Specifically, b r ucin ature ity account r 9 f E

estimates of tota ing c emis epen the po

DOT’s estimate of er est sed to c e

benefits of reducing s, which mea substi DO imate o ould

r benefits estimates by 21% (23% of 90-91%). Our estimates of the total 

b cing emissions of criteria air po ts would be redu by this e 

percentage. Since sent 3. % of to enefits the sta ds, ma s 

change would re e % 3

 

 

 impa

ollutan

e high

nefits a

certain

sed in th

are not u

olpe m

 in the Volp

 their im

e 

he criteria p t is very

enefits f

l benefits from

om red

c

g prem

a

 mortal

, d

 fo

 on

0-91% o

fic

PA’s 

 redu

23% low

riteri

than the 

ns that

sions

imate u

tuting

ding

by EPA 

T’s est

 speci

onstruct th

f VSL w

llutant. 

the VSL is per-ton 

 emission

educe the per-ton

enefits from redu llutan

tal b

ced

ndar

sam

these repre 1-3.3 from king thi

duce total ben fits by 0.7 (21% of .0-3.3%).

288 Note that calculations for safety impacts are based on comprehensive costs, which include economic impacts in 

addition to VSL estimates, such as medical care costs, legal costs, insurance administrative costs, etc. These costs 

are based on previous NHTSA studies of motor vehicle crash costs, and add $300,000 to each VSL. However, costs 

associated with nonfatal injuries are not accounted for in this calculation. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

D 

t. 

g in 

at the 

, 

ot 

ict the extent to which manufacturers might use them, particularly 

gic 

stantial concerns remain about how to develop a 

s, 

g enefits and costs. Some manufacturers make substantial use of the carry 

s 

 the 

XI. FLEXIBILITIES IN MEETING THE STANDAR

In this context, CAFE credits refer to flexibilities allowed under the Energy Policy and 

Conservation Act (EPCA) provisions governing use of Alternative Motor Fuels Act (AMFA) 

credits, the use of credit carry forward and carry back provisions, credit transfers between a 

manufacturer’s fleets, and credit trades among different manufacturers. Because EPCA 

prohibits NHTSA from considering these flexibilities when determining the stringency of CAFE

standards, NHTSA did not consider these flexibilities when it developed alternatives for this 

rulemaking. 

Under the Energy Independence and Security Act (EISA), AMFA credits are being phased ou

The allowable credits are reduced so that by 2020 such credits will no longer be allowed under 

law. However, AMFA credits are allowed during the years affected by this rulemaking. 

Manufacturers building dual-fuel vehicles are entitled to a CAFE benefit of up to 1.2 mp

2012 to 2014, 1.0 mpg in 2015, and 0.8 mpg in 2016 for each fleet. NHTSA estimates th

impact of the use of AMFA credits could result in an average reduction of almost 1.0 mpg in 

achieved average fuel economy in model years 2012 through 2016, and a related increase in CO2

emissions. 

Regarding credits other than AMFA credits (e.g., CAFE credits earned through over-compliance

credits transferred between fleets, and credits acquired from other manufacturers), we do n

have a sound basis to pred

since the credit transfer and credit trading programs have been only recently authorized, and

credit transfers could involve complex interactions with multi-year planning.289

Such questions are similar to, though possibly less tractable than, the behavioral and strate

questions that were entailed in representing manufacturers’ ability to “pull ahead” the 

implementation of some technologies, and that would be involved in attempting to estimate 

CAFE-induced changes in market shares. Although the Volpe model has been modified to 

account for multi-year planning effects, sub

credible market share model for integration into the modeling system NHTSA has used to

analyze the costs and effects of credit transfers and credit trading. The agency continues to 

consider how a market share model could be integrated into future CAFE analyses. 

We believe that some manufacturers are likely to take advantage of these flexibility mechanism

thereby reducin b

forward and carry back credit flexibilities today. Many manufacturers make dual fuel vehicle

today and earn credits. These vehicles are in their MY 2008 and MY 2011 baselines. Other 

manufacturers regularly exceed CAFE standards applicable to one or both fleets, and allow

corresponding excess CAFE credits to expire. Finally, still other manufacturers regularly pay

civil penalties for noncompliance, even when producing dual-fuel vehicles would substantially 

reduce the magnitude of those penalties. 

 

289 For example, if a manufacturer is planning to redesign many vehicles in MY 2013, but few vehicles in MY 2015 

chnologies in MY 2013 in order to carry them forward to facilitate compliance in MY 2015. 

when standards will also be significantly more stringent, the benefits (in terms of reducing regulatory burden) of 

using some flexibilities in MY 2013 (e.g., credit transfers) could be outweighed by the benefits of applying extra 

te
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These 

ethanol in the fuel 

and adjusts the engine operating parameters. 

Fuel System - Plastic Gas Tank, updating components like seals and gaskets to be ethanol 

d some fuel system materials may be 

eased fuel pressure 

line powered vehicle. The analysis did not 

ehicles because for the most part they are already in the MY 2011 

be greater under more stringent standards. As 

r manufacturers to face greater cost increases, and for some, 

 technological implementation, costs could rise substantially. The 

conomic advantage of employing allowed flexibilities increases and could affect manufacturer 

. A critical factor in addressing the fuel and emissions impacts of such 

ions, the 

gency has used the Volpe model to estimate costs and effects if every manufacturer is assumed 

ing 

There are vehicle costs to provide the dual fuel capability of using either E85 or gasoline. 

costs are incremental to the average vehicle costs of a gasoline vehicle. The additional or 

redesigned components necessary for E85 capability may include: 

• Flexible Fuel Sensor or Oxygen Sensor - Determines the amount of 

•

capable, increased vapor storage capacity, an

changed to stainless steel because ethanol in E-85 is corrosive. 

• Low Emission Hardware or Improved Evaporative Emission Systems 

• Fuel Injectors and Pressure Regulators 

• Valve Seat Materials and Rings 

• Fuel Rail Changes to allow for incr

• Cold start enhancement 

Combined, the agency estimates that these needed improvements would increase the consumer 

cost of a vehicle by $100 to $175 (in $2007), even though the manufacturers are charging the 

same price for a dual-fueled automobile as for a gaso

include a cost for dual-fueled v

adjusted baseline. 

We expect that use of flexibilities w

 potential fo

ould tend to

stringency increases, the

depending on its level of

e

behavior in this regard

flexibilities is that the likely extent of utilization cannot be assumed constant across the 

alternatives. 

To gauge the potential upper end of differences that could result from these provis

a

to take full advantage of the FFV credit provisions throughout MY 2012-2016, under both the 

baseline (MY 2011) and preferred alternative. The analysis indicates that full use of the 

provisions could (a) reduce the average achieved fuel economy by 1.1 in MY 2016, and by 0.6-

1.1 mpg in earlier model years, (b) reduce technology outlays by about $14 billion (28%) dur

MY 2012-2016, (c) reduce average price increases by $173-$207 during MY 2012-2016, (d) 

reduce fuel saved during MY 2012-2016 by 2,377 million gallons (3.9%), and (e) increase by 

18.7 mmt. (2.9%) CO2 emissions avoided during MY 2012-2016.290,291

 

290 Estimated differences in costs and prices do not include incremental costs to produce FFVs. 291 With FFV credits, our analysis includes application of diesel engines at lower volumes than when FFV credits ar

excluded. Because diesel fuel contains more carbon than gasoline, this difference in diesel application causes a 

e 

slight reduction in CO2 emissions. 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

s from 

Table XI-1 shows those potential impacts on passenger cars and light trucks combined. The 

achieved fuel economy of the fleet and costs are lower if one does not consider the credit

dual-fueled vehicles. We could show many tables supporting these estimates, but we chose just 

to show some summary highlights. 
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Preferred Alternative 

Table XI-1 

Potential Impact of Dual-Fueled Vehicle Credits 

2012 2013 2014 2015 2016 Total 

Average Achieved FE (mpg) 

With FFVs 28.7 29.7 30.6 31.5 32.6 

Without FFVs 29.3 30.6 31.7 32.6 33.7 

Differ

 

ence (0.6) (0.9) (1.1) (1.1) (1.1) 

Technology Outlays ($millions) 

With FFVs 

 

3,675 

 

5,123 

 

7,271 

 

9,478 

 

11,921 

 

37,468 

Without FFVs 5,903 7,890 

 

10,512 

 

12,539 

 

14,904 

 

51,748 

Difference 

 

(2,228) 

 

(2,767) 

 

(3,241)

 

(3,061) 

 

(2,983) 

 

(14,280) 

Price Increases ($) 

With FFVs 261 333 458 589 737 

Without FFVs 434 513 665 782 926 

Difference 

 

(173) 

 

(180) 

 

(207) 

 

(193) 

 

(189) 

Fuel Savings (mil. of gallons) 

With FFVs 4,919 8,236 11,349 15,041 19,092 58,637 

 

Without FFVs 

 

4,201 

 

8,851 

 

12,518 

 

15,950 

 

19,494 

 

61,014 

Difference 

 

718 

 

(615) 

 

(1,169) 

 

(909) 

 

(402) 

 

(2,377) 

Avoided CO2 (mmt) 

With FFVs 52.8 89.1 123.1 163.4 207.6 636.0 

Without FFVs 43.9 94.4 134.3 171.7 210.4 654.7 

Difference 

 

8.9 

 

(5.3) 

 

(11.2) 

 

(8.3) 

 

(2.8) 

 

(18.7)

 
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

e 

variety of often conflicting sources. Best estimates were selected based on the 

mes, 

, oil 

y 

s 

ilitates a more informed 

The analysis is based on the actual processes used to derive net benefits as described in the 

previous chapters. Each variable (e.g., cost of technology) in the mathematical model represents 

an uncertainty factor that would potentially alter the modeling outcomes if its value was 

changed. We assume that these variables are independent of each other. The confidence 

intervals around the costs and benefits of technologies reflect independent levels of uncertainty 

regarding costs and benefits, rather than linked probabilities dependent on higher or lower 

quality versions of a specific technology. 

The uncertainties of these variables are described by appropriate probability distribution 

functions based on available data. If data are not sufficient or not available, professional 

judgments are used to estimate the probability distributions of these uncertainty factors. A 

complete description of the formulas and methods used in the CAFE model is available in the 

public docket.293 

After defining and quantifying the major uncertainty factors, the next step is to simulate the 

model to obtain probabilistic results rather than single-value estimates. In the uncertainty 

analysis, CAFE levels were kept constant; in other words, we did not change the CAFE 

standards for each run based on net benefits. The simulation process was run repeatedly for 

20,000 trials under each discount rate scenario. Each complete run is a trial. For each trial, the 

 

XII. PROBABILISTIC UNCERTAINTY ANALYSIS 

OMB Circular A-4 requires formal probabilistic uncertainty analysis of complex rules wher

there are large, multiple uncertainties whose analysis raises technical challenges or where effects 

cascade and where the impacts of the rule exceed $1 billion. CAFE meets all of these criteria. 

This chapter identifies and quantifies the major uncertainties in the preliminary regulatory impact 

analysis and estimates the probability distribution of the benefits, costs, and net benefits of the 

compliance options selected for the proposed rule for MY 2012-2016 passenger car and light

truck CAFE standards. Throughout the course of the main analysis, input values were selected

from a 

preponderance of data and analyses available, but there is inevitably a level of uncertainty in 

these selections. Some of these inputs contributed less to the overall variations of the outco

and, thus, are less significant. Some inputs depend on others or are closely related (e.g.

import externalities), and thus can be combined. With the vast number of uncertainties 

imbedded in this regulatory analysis, this uncertainty analysis identifies only the major 

independent uncertainty factors having appreciable variability and impact on the end results and 

quantifies them by their probability distributions. These newly defined values are then randoml

selected and fed back into the model to determine the net benefits using the Monte Carlo 

statistical simulation technique.292 The simulation technique induces the probabilistic outcome

accompanied with degrees of probability or plausibility. This fac

decision-making process. 

292 See, for example, Morgan, MG, Henrion, M, and Small M, “Uncertainty: A Guide to Dealing with Uncertainty in 

Quantitative Risk and Policy Analysis,” Cambridge University Press, 1990. 

293 CAFE Compliance and Effects Modeling System Documentation, Volpe Center, U.S. Dept. of Transportation, 

July 2005, pp. 27-46 and C-22 to C-35. Available at http://www.nhtsa.dot.gov (last accessed March 4, 2010).
479

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

simulation first randomly selects a value fo certainty factors based on their 

probability distributions. The sel models to forecast results. In 

addition to the simulation results e pro al es t gree of certainty (or 

confidence, credibility). The d of c y e on-maker with an additional 

piece of important information whi alu for sults. 

Simulation Models and Un inty s

A Monte Carlo simulation was ucte the m tem that was developed 

to estimate the impacts of high FE en rib evious chapters. The focus 

of the simulation model was va n ar e c nc parameters and their 

resulting impact on the key ou ram el , a nefits. Net benefits 

measure the difference betwee he t r at be saved in fuel and other 

benefits and (2) the total costs rule

The agency reviewed the inputs and rela t e t E model to determine the 

factors that are the major sourc unc . S rs entified as potentially 

contributing to uncertainty to t imat cts er standards, although not all 

were ultimately selected to be run in the ion

(1) Technology costs; 

(2) Technology effectiveness; 

(3) Fuel prices; 

(4) The value of oil consumpti na

(5) Greenhouse gas emissions 

(6) The rebound effect. 

Technology Costs 

The costs incurred by manufact to m hei es new CAFE levels are 

assumed to be passed on to con in m prices. These technology 

costs are the primary determin the cost of impro el economy. 

Thirty-nine different technolog ere d a le s to comply with higher 

CAFE standards. These techn s w rib ap arlier in this analysis. The 

expected cost values were used e m ysi e uncertainty analysis the technology 

complexity ratings that were de ed ate fa ere used to distinguish 

between levels of uncertainty t e ex rom olo are relatively simple and 

those that are more uncertain. rat re d d , Medium, and High based 

on the characteristics of each s c tec y. proach assumes that low complexity 

technologies would tend to hav re ith well know nderstood supply chains, 

resource availability, and manu ring ues, which w ply a more narrow range of 

potential cost variation compar high exi ol hich would have a broader 

range of uncertainty. In previo alys e og FRIA for MY 2011), cost 

variation averaging 31% (based on NAS technol gy estimates) was assumed to represent 3 

standard deviations across all technologies. For is analysis, we are assuming that this average 

r each of the un

ected values are then fit into the

, th

egree

gram 

ertain

so estimat

provides th

he de

t decis

ch to ev

i

 with ate the ecast re

certa Factor

cond d using CAFE odeling sys

er CA requirem ts desc ed in pr

riatio ound th hosen u ertainty

tput pa eters, fu savings nd net be

n (1) t otal dolla value th would 

of the . 

tionships hat driv he CAF

es of ertainty ix facto were id

he est ed impa of high CAFE 

 simulat : 

on exter lities; 

and; 

urers odify t r vehicl to meet

sumers the for of higher new car 

ant of overall ving fu

ies w examine s possib method

ologie ere desc ed in Ch ter V e

 in th ain anal s. For th

velop to estim markup ctors w

hat ar pected f techn gies that 

These ings we esignate as Low

pecifi

e matu

hnolog

costs w

This ap

n and u

factu techniq ould im

ed to compl ty techn ogies, w

us an es of thes

o

 technol ies (see

th
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DELIBERATIVE DOCUMENT – DO NOT RELEASE 

tion represents 2 standard deviations, and applying 1 standard deviation for low complexity 

technologies, 2 for medium complexity te 3 standard deviations for high 

complexity technologies. This results in ranges 15.5% for low, 31% for medium, and 46.5% 

for high complexity technologies. The uncertainty model assumes a normal distribution for these 

cost ranges. Figure XII-1 graphically demonstrates the distributions of a hypothetical sample of 

three of the technologies. 

Figure XII-1 

Normal Distributions for 3 Different Technologies 

manufacturers to meet the higher CAFE standards, and will thus determine how much additional 

varia

chnologies, and

of

Aero Drag Reduction ($38-59)

0.10

0.15

0.20

0.25

0.30

Probabilit

Cylinder Deactivation on OHV ($23-34)

Improved Accessories ($76-193)

y Density

0.05

0.00

$0 $20 $40 $60 $80 $100 $120 $140 $160

Retail Price Increase ($)

Technology Effectiveness 

The modifications adopted by manufacturers to enable their vehicles to meet new CAFE levels 

will improve fuel efficiency and reduce the cost of operating the more efficient vehicles. The 

effectiveness of each technology determines how large an impact it will have towards enabling 

improvement is needed and which additional technologies will be required to achieve full 

compliance. In selecting the likely path that manufacturers will choose to meet CAFE, the 
481

DELIBERATIVE DOCUMENT – DO NOT RELEASE 

al 

y 

 earlier in this 

nalysis. Chapter V also summarizes the estimated range of effectiveness for these technologies. 

Crank mounted Integrated Starter Generator 

 there 

e 

he analysis attempts to measure impacts that occur as much as 40 years in the future and 

n 

CAFE model tests the interaction of technology costs and effectiveness to achieve an optim

(cost-minimizing) technological solution. Technology effectiveness is thus a primary 

determinant of the overall cost and benefit of improving fuel economy. 

As noted above, thirty-nine different technologies were examined as possible methods to compl

with higher CAFE standards. These technologies were described in Chapter V

a

The expected values (mid-range values) were used in the main analysis. For the uncertainty 

analysis, the full range of effectiveness estimates is used except where the specified range was 

regarded as too narrow by expert opinion. These were adjusted to the ‘default’ range (29%). 

These technologies are: 

Combustion Restart 

Turbocharging and Downsizing 

Exhaust Gas Recirculation (EGR) Boost 

Conversion to Diesel following CBRST 

Conversion to Diesel following TRBDS 

Dual Clutch or Automated Manual Transmission 

12V Micro-Hybrid 

Belt mounted Integrated Starter Generator 

Plug-in Hybrid 

The fuel consumption improvement ranges were regarded as either tight or were non-existent for 

these technologies because the values developed for them were not done with a mind toward 

what the average value should be (by vehicle class) and were not done with an eye towards 

uncertainty analysis. 

As was done with costs, the average variation of all technologies where a range is specified was 

used as 3 standard deviations to be used as the default variation. For all technologies where

is no range specified, this default variation was used. The uncertainties model assumes a normal

distribution for these values, with each end of the range being three standard deviations from th

mean (or expected) value. 

Fuel Prices 

Higher CAFE standards will result in reduced gasoline consumption, which will translate into 

lower vehicle operating costs for consumers. The value of this reduced fuel consumption is a 

direct function of fuel prices. Fuel prices are thus a primary determinant of the overall social 

benefit that will result from improving fuel economy. 

T

estimating gasoline prices this far in advance is an uncertain process. In the main analysis, the 

agency utilized predicted fuel prices from the Energy Information Administration’s (EIA) 

publication Annual Energy Outlook 2010 Early Release (AEO). The main analysis is based o

the AEO 2010 Reference Case scenario, which represents EIA’s current best estimate of future

fuel prices. For the uncertainty analysis, the Agency examined two other AEO scenarios from 
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only contain the Reference 

ase forecast, so the LOP and HOP for 2010 are not yet available. The LOP scenario was 

ility that the EIA’s Reference Case predictions could overestimate 

ty 

 

g 

I-1 

trated 

ed 

ere 

 

the 2009 version, the Low Oil Price scenario (LOP) and the High Oil Price scenario (HOP). The 

2009 LOP and HOP were employed because AEO Early Releases 

C

chosen to allow for the possib

the price of gasoline in the future. However, previous escalation in the price of gasoline resulted

in prices that exceeded those estimated by EIA for their reference case. To reflect the possibili

of significantly higher prices, the Agency selected the HOP case, which among the AEO 2009

scenarios comes closest to matching the highest prices seen during the recent gasoline price 

surge, and which gives the highest gasoline price forecasts among all AEO 2009 scenarios 

 

Each of these scenarios was applied as a discrete input (i.e., draws were not made from amon

the three scenarios separately for each future year). Rather, for each draw, one of the three

scenarios was chosen and applied across the full vehicle life for each model year. The 

probability of selection for each of the three scenarios was modeled using discrete weights of 50

percent for the Reference Case, and 25 percent for both the LOP and HOP cases. Table XI

lists the AEO gasoline price forecasts under each scenario. These same prices are demons

graphically (in 2007 economics) in Figure XII-2. Note that these prices include Federal, State, 

and local fuel taxes. For the uncertainty analysis, taxes were removed because they are view

as transfer payments (see discussion in Chapter VIII). Estimated retail prices are shown h

because they are a better reference point for most readers. 

 

 
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High 

Table XII-1 

AEO 2009 Gasoline Price Scenarios 

Year Low Reference

2011 $2.194 $2.473 $3.361

2012 $2.103 $2.609 $3.627

2013 $2.082 $2.844 $3.914

2014 $2.044 $2.954 $4.241

2015 $2.028 $3.004 $4.496

2016 $2.033 $3.072 $4.656

2017 $2.035 $3.135 $4.838

2018 $2.041 $3.185 $4.935

2019 $2.025 $3.222 $5.003

2020 $2.024 $3.268 $5.043

2021 $2.038 $3.295 $5.039

2022 $2.061 $3.337 $5.080

2023 $2.083 $3.365 $5.138

2024 $2.051 $3.380 $5.145

2025 $2.055 $3.419 $5.195

2026 $2.054 $3.457 $5.258

2027 $2.049 $3.491 $5.301

2028 $2.051 $3.541 $5.362

2029 $2.044 $3.585 $5.417

2030 $2.036 $3.602 $5.472

2031 $2.037 $3.644 $5.517

2032 $2.038 $3.690 $5.562

2033 $2.039 $3.723 $5.607

2034 $2.040 $3.768 $5.653

2035 $2.042 $3.829 $5.700

2036 $2.043 $3.866 $5.746

2037 $2.044 $3.904 $5.794

2038 $2.045 $3.942 $5.841

2039 $2.046 $3.981 $5.889

2040 $2.047 $4.020 $5.937

2041 $2.049 $4.059 $5.986

2042 $2.050 $4.099 $6.035

2043 $2.051 $4.139 $6.084

2044 $2.052 $4.180 $6.134

2045 $2.053 $4.221 $6.184

2046 $2.055 $4.262 $6.235

2047 $2.056 $4.304 $6.286

2048 $2.057 $4.346 $6.338

2049 $2.058 $4.389 $6.390

2050 $2.059 $4.432 $6.442
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Figure XII-2 

Oil Consumption Externalities 

Reduced fuel consumption can benefit society by lowering the world market price for oil, 

reducing the threat of petroleum supply disruptions, and reducing the cost of maintaining 

military security in oil producing regions and operating the strategic petroleum reserve. These 

benefits are called “externalities” because they are not reflected directly in the market price of 

fuel. A full description of these externalities is included in Chapter VIII under “Other Economic 

Benefits from Reducing Petroleum Use.” These factors increase the net social benefits from 

reduced fuel consumption. Although they represent a relatively small portion of overall social 

benefits, there is a significant level of uncertainty as to their values. 

Monopsony costs represent the reduced value of payments from U.S. oil purchasers to foreign oil 

suppliers that results when lower U.S. oil demand reduces the world price of petroleum, beyond 

e savings from reduced purchases of petroleum itself.294 However, consistency w TSA’s 

se of estimates of the global benefits from reducing emissions of CO2 and other greenhouse 

ases in this analysis requires the use of a global perspective for assessing their net value. From 

is perspective, reducing these payments simply results in a transfer of resources from foreign 

 

th

u

ith NH

g

th

294 The reduction in payments from U.S. oil purchasers to domestic petroleum producers is not included as a benefit, 

since it represents a transfer that occurs entirely within the U.S. economy. 
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il suppliers to U.S. purchasers (or more properly, in a savings in the value of resources 

reviously transferred from U.S. purchasers to foreign producers), and provides no real savings 

 resources to the global economy. Thus NHTSA’s analysis of the benefits from adopting 

higher CAFE standards for MY 2012-201 t trucks excludes the reduced value of 

monopsony payments consumption by 

these vehicles, and they are likewise not included in the uncertainty analysis. 

The second component of external economic costs imposed by U.S. petroleum imports arises 

partly because an increase in oil prices triggered by a disruption in the supply of imported oil 

reduces the level of output that the U.S. economy can produce. The reduction in potential U.S. 

economic output depends on the extent and duration of the increases in petroleum product prices 

that result from a disruption in the supply of imported oil, as well as on whether and how rapidly 

these prices return to pre-disruption levels. Even if prices for imported oil return completely to 

their original levels, however, economic output will be at least temporarily reduced from the 

level that would have been possible without a disruption in oil supplies. A more complete 

discussion of price shock is provided in Chapter V, where is estimated that each gallon of fuel 

saved that results in a reduction in U.S. petroleum imports (either crude petroleum or refined 

fuel) will reduce the expected costs of oil supply disruptions to the U.S. economy by $0.078 to 

$0.269, with the actual value most likely to be $0.169 per gallon. For the uncertainty analysis, 

this central value is used with a normal distribution and a standard deviation of $0.06. 

A third imported oil externality is military security. In Chapter VIII, NHTSA thus concludes 

that the levels of U.S. military activity and expen itures are likely to remain unaffected by even 

relatively large changes in light duty vehicle fuel consumption. As a consequence, the agency’s 

analysis of alternative CAFE standards fo 6 does not include savings in budgetary 

outlays to support omy and the 

resulting fuel savings. 

Nevertheless, the agency conducted a sensitivity analysis of the potential effect of assuming that 

some reduction in military spending would result from fuel savings and reduced petroleum 

imports in order to investigate its impacts on the standards and fuel savings. Assuming that the 

preceding estimate of total U.S. military costs for securing Persian Gulf oil supplies is correct, 

and that approximately half of these expenses could be reduced in proportion to a reduction in 

U.S. oil imports from the region, the estimated savings would range from $0.02 to $0.08 (in 2007 

dollars) for each gallon of fuel savings that was reflected in lower U.S. imports of petroleum 

from the Persian Gulf. If the Persian Gulf region is assumed to be the marginal source of supply 

for U.S. imports of crude petroleum and refined products, then each gallon of fuel saved might 

reduce U.S. military outlays by $0.05 per gallon, the midpoint of this range. NHTSA employs 

this estimate in its sensitivity analysis, and examines it further as part of this uncertainty analysis, 

assuming a 25% probability for this alternate impact. 

Table XII-3 lists the range of values that were examined for oil consumption extern ities. The 

expected values were used in the main analysis. oth the value of reducing U.S. de and on the 

world market price for oil and the value of reduced threat of supply disruptions were derived 

from a study by Leiby (2008) (see Chapter VIII). For reasons noted in Chapter VIII, military 

security is not specifically valued in this analysis. A normal distribution was assumed for the 

o

p

in

6 cars and ligh

 by U.S. oil consumers that might result from lower fuel 

d

r MY 2012-201

 U.S. military activities among the benefits of higher fuel econ

al

B m
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range of values for oil consumption externalities with the low and high values assumed to be two 

standard deviations from the mean, based stimates. 

Greenhouse Gas Emissions 

Emissions of carbon dioxide and other greenhouse gases (GHGs) occur throughout the process 

of producing and distributing transportation fuels, as well as from fuel combustion itself. By 

reducing the volume of fuel consumed by passenger cars and light trucks, higher CAFE 

standards will thus reduce GHG emissions generated by fuel use, as well as throughout the fuel 

supply cycle. Lowering these emissions is likely to slow the projected pace and reduce the 

ultimate extent of future changes in the global climate, thus reducing future economic damages 

that changes in the global climate are otherwise expected to cause. Further, by reducing the 

probability that climate changes with potentially catastrophic economic or environmental 

impacts will occur, lowering GHG emissions may also result in economic benefits that exceed 

the resulting reduction in the expected future economic costs caused by gradual changes in the 

earth’s climatic systems. In Chapter VIII, a more complete discussion of greenhouse gas 

emissions is presented along with a variety of estimates. The central estimate used in the 

analysis is $21.35 per metric ton. Additional scenarios could also be examined. The Low SCC 

value case assumes $4.52/metric ton. The high value case assumes $35.06/metric ton. In 

addition, a 95th percentile case assuming $64.90/metric ton was examined. SCC wa not 

included in this uncertainty analysis based on recommendations from the interagenc orking 

group that produced the SCC values employed i e agency’s main analysis. 

The Rebound Effect 

By reducing the amount of gasoline used ost of operating a vehicle, higher CAFE 

standards are exp hicle. This 

“rebound effect” impacts net societal benefits because the increase in miles driven offsets a 

portion of the gasoline savings that results from more fuel-efficient vehicles. Although 

consumers derive some value from this extra driving, it also leads to increases in crash, 

congestion, noise, and pollution costs associated with driving. Most recent estimates of the 

magnitude of the rebound effect for light duty vehicles fall in the range of 10-20 percent (i.e., 

increasing vehicle use will offset 10-20 percent of the fuel savings resulting from an 

improvement in fuel economy), but studies also show that the rebound effect has been gradually 

decreasing over time. A more complete discussion of the rebound effect is included in Chapter 

VIII. The agency employed a rebound effect of 10 percent in the main analysis. For the 

uncertainty analysis, a range of 0 to 21 percent is used and employed in a slightly skewed Beta 

distribution which produced a mean of approximately 10.1 percent. The skewed distribution 

reflects the agency’s belief that the more credible studies that differ from the 10 percent value 

chosen for the main analysis fall below this value (i.e., are more negative) and differ by more 

substantial margins than the upper range of credible values. Table XII-3 summarizes the 

economic parameters used in the uncertainty analysis. 

on the Leiby e

s

y w

n th

and, thus, the c

ected to result in a slight increase in annual miles driven per ve
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Table XII-3 

Monte Carlo Specific Parameters 

Discount Rates (%) 0.03, 0.07 

Fuel Path Randomization Parameters 

Low 25% 

Reference 50% 

High 25% 

Rebound Effect Randomization Parameters 

Alpha Shape 6.00 

Beta Shape 6.50 

Scale -0.21 

Base 0.00 

Monopsony Randomization Parameters 

Mean $ - 

Standard Deviation $ - 

Price Shock Randomization Parameters 

Mean $0.17 

Standard Deviation $0.06 

Military Security Randomization Parameters 

Alternative Cost $0.05 

Alternative Cost Pro ty babili 25% 

 

 Draws 

Because of the complexity of the CAFE model, t e computer time required to perform the 

uncertainty analysis was significant. The uncert nty analysis conducted a total of 40,000 trials 

(20,000 for each discount rate) Figures X 2 graphically illustrate the draw 

results for a sample of the 81 varia ess rates, 39 technology costs, 

the fuel price scenario, oil import externalities, and the rebound effect) that were examined. 

 

Modeling Results – Trial

h

ai

II- 3 through XII-1

bles (39 technology effectiven
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Figure II-3 

Monte Carlo Draw Profile, Passenger Car Costs 

 X

Monte Carlo Draw Profile, Passenger Car Effectiveness 

Figure XII-4 

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Figure X

Monte Carlo Draw Profile ger sts 

II-5 

, Passen Cars, Co

Figure XII-6 

Monte Carlo Draw Profile, Passenger Cars, Effectiveness 

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Figure XII-7 

Monte Carlo Draw Profile, Passenger Cars, Costs 

Figure X

Profile, Pass ar en

II-8 

Monte Carlo Draw enger C s, Effectiv ess 

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Figure X

rlo Dr ile

x Fuel P h 

II-9 

Monte Ca

Preta

aw Prof

rice Pat

 

Figure XII-10

Monte Carlo Draw Profile 

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Figure XII

Monte Carlo Draw

-11 

 Profile 

Figure XII

Monte Carlo Dra

-12 

w Profile 
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 XII-3 

 ults, Economic 

M

 Table

 Monte Carlo Draw Res

Economic Inputs 

Inputs 

inimum Maximum M t ean S dDev 

Rebound Effect -0.2071 -0.0058 -0.1012 0.0336 

Military Security Cost 0 0.0500 0.0125 NA 

Price Shock Cost 0.00056 0.4166 0.1695 0.0574 

 
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nte Carlo Draw Results, Pa g 

Minim axim ean dDev 

Table XII-4 

 Mo ssenger Car Technolo y Costs

Technology um M um M St

Low Friction Lubricants $ $ $ $0. 2.70 4.21 3.43 18 

Engine Friction Reduction $9.90 $1 $1 $0. 5.01 2.57 65 

VVT - Coupled Cam Phasing (CCP) on SOHC $ $ $ $2. 35.88 53.93 45.08 31 

Discrete Variable Valve Lift (DVVL) on SOHC $1 $16 $13 $6. 07.66 5.79 4.89 93 

Cylinder Deactivation on SOHC $ $3 $2 $1. 21.87 4.23 7.75 43 

VVT - Intake Cam Phasing (ICP) $ $5 $4 $2. 36.03 6.60 5.11 31 

VVT - Dual Cam Phasing (DCP) $ $ $ $1. 30.18 45.89 38.31 98 

Discrete Variable Valve Lift (DVVL) on DOHC $ $1 $1 $7 106.30 67.83 35.05 .00 

Continuously Variable Valve Lift (CVVL) $1 $43 $27 $42. 10.64 0.11 2.93 48 

Cylinder Deactivation on DOHC $ $3 $2 $1. 22.47 3.22 7.76 44 

Cylinder Deactivation on OHV $ $3 $2 $1. 22.03 3.57 7.96 46 

VVT - Coupled Cam Phasing (CCP) on OHV $ $4 $4 $2. 32.17 9.76 0.85 11 

Discrete Variable Valve Lift (DVVL) on OHV $93.29 $1 $1 $6 40.91 17.50 .14 

Conversion to DOHC with DCP $2 $32 $26 $13. 15.86 9.32 6.14 72 

Stoichiometric Gasoline Direct Injection (GDI) $ $ $ $3 46.24 70.10 58.53 .05 

Combustion Restart $67.52 $1 $1 $12 71.46 17.52 .24 

Turbocharging and Downsizing $2 $6 $4 $45 55.55 05.14 31.95 .01 

Exhaust Gas Recirculation (EGR) Boost $83.19 $214.81 $ $1 144.39 4.75 

Conversion to Diesel following TRBDS $561.61 $1,361.58 $ $10 973.21 0.70 

Conversion to Diesel following CBRST $ $2,1 $1,5 $160 927.72 68.72 48.84 .15 

6-Speed Manual/Improved Internals $2 $29 $25 $12. 03.11 9.79 0.04 96 

Improved Auto. Trans. Controls/Externals $47.90 $ $ $3 71.87 60.12 .08 

Continuously Variable Transmission $ $3 $2 $25. 153.58 61.09 49.91 57 

6/7/8-Speed Auto. Trans with Improved Internals $94.85 $1 $11 $6. 48.12 9.38 11 

Dual Clutch or Automated Manual Transmission ($4 ($ ($2 1.91) 16.84) 9.45) $3.01 

Electric Power Steering $ $1 $1 $5 83.92 27.15 06.45 .50 

Improved Accessories $74.26 $1 $1 $13 89.87 27.58 .13 

12V Micro-Hybrid $ $4 $3 $33 197.71 86.70 26.26 .58 

Belt mounted Integrated Starter Generator $165.18 $395.40 $ $2 285.53 9.58 

Crank mounted Integrated Starter Generator $ $5 $3 $48 1,495.44 ,462.30 ,155.31 8.49 

Power Split Hybrid $970.47 $4 $2 $40 ,119.34 ,604.72 5.94 

2-Mode Hybrid $1,680.53 $ $ 6,684.12 4,123.51 $640.63 

Plug-in Hybrid $5,566.05 $22,676 14,432 ,233. .11 $ .92 $2 13 

Material Substitution (1.50%) $ $1 $1 $0. 1.20 .83 .48 08 

Material Substitution (5% to 10% Cum) $ $1 $1 $0. 1.16 .76 .48 08 
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Low Rolling Resistance Tires $4.62 $ $ $0. 6.86 5.72 30 

Low Drag Brakes $ $ $6 $3. 49.51 78.70 2.90 27 

Secondary Axle Disconnect - Ladder Frame $ $10 $8 $4. 68.41 3.85 6.82 48 

Aero Drag Reduction $37.52 $56.93 $47.62 $2.44 

 
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I-5 

s 

Table XI

 Monte Carlo Draw Results, Passenger Car Fuel Economy Improvement Rate

Technology Minimum Maximum Mean StdDev 

Low Friction Lubricants 0.003297 0.006774 0.004995 0.000482 

Engine Friction Reduction 0.008521 0.021392 0.014992 0.001665 

VVT - Coupled Cam Phasing (CCP) on SOHC 0.006288 0.035075 0.020001 0.003321 

Discrete Variable Valve Lift (DVVL) on SOHC 0.006296 0.035190 0.019994 0.003324 

Cylinder Deactivation on SOHC 0.024234 0.031422 0.027501 0.000835 

VVT - Intake Cam Phasing (ICP) 0.008412 0.021828 0.015010 0.001671 

VVT - Dual Cam Phasing (DCP) 0.018200 0.033227 0.025002 0.001670 

Discrete Variable Valve Lift (DVVL) on DOHC 0.006924 0.034950 0.019980 0.003372 

Continuously Variable Valve Lift (CVVL) 0.012571 0.040441 0.025013 0.003328 

Cylinder Deactivation on DOHC 0.000004 0.006493 0.002512 0.000828 

Cylinder Deactivation on OHV 0.036372 0.058994 0.047018 0.002676 

VVT - Coupled Cam Phasing (CCP) on OHV 0.009095 0.015660 0.012514 0.000839 

Discrete Variable Valve Lift (DVVL) on OHV 0.001294 0.031847 0.015009 0.003331 

Conversion to DOHC with DCP 0.007506 0.028947 0.017508 0.002507 

Stoichiometric Gasoline Direct Injection (GDI) 0.018807 0.031099 0.025000 0.001680 

Combustion Restart 0.013562 0.031892 0.022523 0.002169 

Turbocharging and Downsizing 0.024579 0.054987 0.040107 0.003853 

Exhaust Gas Recirculation (EGR) Boost 0.022579 0.051500 0.037481 0.003621 

Conversion to Diesel following TRBDS 0.036928 0.088725 0.060763 0.005850 

Conversion to Diesel following CBRST 0.082338 0.187326 0.132273 0.012778 

6-Speed Manual/Improved Internals 0.003016 0.006991 0.004994 0.000481 

Improved Auto. Trans. Controls/Externals 0.013181 0.027517 0.019989 0.001670 

Continuously Variable Transmission 0.004942 0.021321 0.013475 0.002168 

6/7/8-Speed Auto. Trans with Improved Internals 0.010834 0.039515 0.023982 0.003324 

Dual Clutch or Automated Manual Transmission 0.028697 0.064629 0.047186 0.004561 

Electric Power Steering 0.008688 0.022226 0.014990 0.001664 

Improved Accessories 0.008283 0.021049 0.015003 0.001662 

12V Micro-Hybrid 0.016744 0.037837 0.026042 0.002524 

Belt mounted Integrated Starter Generator 0.029620 0.070075 0.049013 0.004721 

Crank mounted Integrated Starter Generator 0.054397 0.118287 0.087782 0.008466 

Power Split Hybrid 0.054487 0.135468 0.093148 0.010177 

2-Mode Hybrid 0.023122 0.083804 0.051415 0.007172 

Plug-in Hybrid 0.297300 0.655074 0.464704 0.045203 

Material Substitution (1.50%) 0.003163 0.007165 0.005254 0.000509 

Material Substitution (5% to 10% Cum) 0.023032 0.050878 0.037269 0.003621 

Low Rolling Resistance Tires 0.008821 0.021629 0.014999 0.001668 
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Low Drag Brakes 0.004359 0.011278 0.007508 0.000841 

Secondary Axle Disconnect - Ladder Frame 0.009262 0.015969 0.012505 0.000831 

Aero Drag Reduction 0.018791 0.030834 0.024981 0.001673 

 
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ght Truck Technology Costs 

Table XII-6 

 Monte Carlo Draw Results, Li

Technology Minimum Maximum Mean StdDev 

Low Friction Lubricants $2.70 $4.21 $3.43 $0.18 

Engine Friction Reduction $9.90 $15.01 $12.57 $0.65 

VVT - Coupled Cam Phasing (CCP) on SOHC $35.88 $53.93 $45.08 $2.31 

Discrete Variable Valve Lift (DVVL) on SOHC $99.43 $153.12 $124.58 $6.40 

Cylinder Deactivation on SOHC $21.87 $34.23 $27.75 $1.43 

VVT - Intake Cam Phasing (ICP) $36.03 $56.60 $45.11 $2.31 

VVT - Dual Cam Phasing (DCP) $32.07 $48.75 $40.70 $2.11 

Discrete Variable Valve Lift (DVVL) on DOHC $98.17 $154.99 $124.73 $6.46 

Continuously Variable Valve Lift (CVVL) $107.99 $419.79 $266.38 $41.46 

Cylinder Deactivation on DOHC $22.47 $33.22 $27.76 $1.44 

Cylinder Deactivation on OHV $20.85 $31.76 $26.46 $1.38 

VVT - Coupled Cam Phasing (CCP) on OHV $20.85 $32.25 $26.48 $1.37 

Discrete Variable Valve Lift (DVVL) on OHV $28.66 $43.29 $36.10 $1.89 

Conversion to DOHC with DCP $201.34 $307.16 $248.23 $12.80 

Stoichiometric Gasoline Direct Injection (GDI) $43.02 $65.22 $54.45 $2.83 

Combustion Restart $67.52 $171.46 $117.52 $12.24 

Turbocharging and Downsizing $325.83 $771.55 $550.73 $57.38 

Exhaust Gas Recirculation (EGR) Boost $83.19 $214.81 $144.39 $14.75 

Conversion to Diesel following TRBDS $654.05 $1,585.69 $1,133.40 $117.27 

Conversion to Diesel following CBRST $1,094.80 $2,559.29 $1,827.77 $188.99 

6-Speed Manual/Improved Internals $203.11 $299.79 $250.04 $12.96 

Improved Auto. Trans. Controls/Externals $47.90 $71.87 $60.12 $3.08 

Continuously Variable Transmission $153.58 $361.09 $249.91 $25.57 

6/7/8-Speed Auto. Trans with Improved Internals $117.02 $182.75 $147.28 $7.54 

Dual Clutch or Automated Manual Transmission ($11.18) ($4.49) ($7.86) $0.80 

Electric Power Steering $83.92 $127.15 $106.45 $5.50 

Improved Accessories $74.26 $189.87 $127.58 $13.13 

12V Micro-Hybrid $218.58 $538.07 $360.70 $37.12 

Belt mounted Integrated Starter Generator $165.18 $395.40 $285.53 $29.58 

Crank mounted Integrated Starter Generator $1,918.40 $7,007.18 $4,047.71 $626.65 

Power Split Hybrid $1,170.26 $4,967.40 $3,140.96 $489.51 

2-Mode Hybrid $2,072.14 $8,241.74 $5,084.42 $789.92 

Plug-in Hybrid $6,326.49 $25,774.17 $16,404.77 $2,538.23 

Material Substitution (1.50%) $1.20 $1.83 $1.48 $0.08 

Material Substitution (5% to 10% Cum) $1.16 $1.76 $1.48 $0.08 

Low Rolling Resistance Tires $4.62 $6.86 $5.72 $0.30 
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Low Drag Brakes $49 $78.70 $62.90 $3.27 .51 

Secondary Axle Disconnect - Ladder Frame $68.41 $103.85 $86.82 $4.48 

Aero Drag Reduction $37.52 $56.93 7.62 $2.44 $4

 
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 Tab

 Monte Carlo ement Rates 

Technology m Maximum Mean StdDev 

le XII-7 

 Draw Results, Light Truck Fuel Economy Improv

Minimu

Low Friction L ts ubrican 0.003297 774 04995 0.000482 0.006 0.0

Engine Friction Reduction 0.0085 39 21 0.021 2 0.014992 0.001665 

VVT - Coupled Cam Phasing (CCP) on SOHC 2 0.006 8 35 8 0.0 07 0 5 0.02 001 0.003321 

Discrete Variable Valve Lift (DVVL) on SOHC 0.00629 519 9994 0.003324 6 0.03 0 0.01

Cylinder Deactivation on SOHC 0.02423 42 7501 0.000835 4 0.031 2 0.02

VVT - Intake Cam Phasing (ICP) 0.008412 82 0.021 8 .01501 0 0 0.001671 

VVT - Dual Cam Phasing (DCP) 0.018200 0.033227 0.025002 0.001670 

Discrete Variable Valve Lift (DVVL) on DOHC 0.006924 0.034950 0.019980 0.003372 

Continuously Variable Valve Lift (CVVL) 0.01257 044 5013 0.003328 1 0.04 1 0.02

Cylinder Deactivation on DOHC 0.00000 64 512 0.000828 4 0.00 93 0.002

Cylinder Deactivation on OHV 0.03637 89 018 0.002676 2 0.05 94 0.047

VVT - Coupled Cam Phasing (CCP) on OHV 0.009095 .015660 .012514 0.000839 0 0

Discrete Variable Valve Lift (DVVL) on OHV .001294 0.031847 0.015009 0.003331 0

Conversion to DOHC with DCP 0.007506 0.028947 0.017508 0.002507 

Stoichiometric Gasoline Direct Injection (GDI) 0.01880 109 5000 0.001680 7 0.03 9 0.02

Combustion Restart 0.01356 18 523 0.002169 2 0.03 92 0.022

Turbocharging and Downsizing 0.01402 37 6 .031 0 9 .02288 0 8 0.002199 

Exhaust Gas Recirculation (EGR) Boost 0.022579 0.051500 0.037481 0.003621 

Conversion to Diesel following TRBDS 0.036928 0.088725 0.060763 0.005850 

Conversion to Diesel following CBRST 0.07265 529 6714 0.011275 3 0.16 1 0.11

6-Speed Manual/Improved Internals 0.00301 69 994 0.000481 6 0.00 91 0.004

Improved Auto. Trans. Controls/Externals 0.01318 75 989 0.001670 1 0.02 17 0.019

Continuously Variable Transmission 0.004942 .021321 .013475 0.002168 0 0

6/7/8-Speed Auto. Trans with Improved Internals 0.010834 0.039515 0.023982 0.003324 

Dual Clutch or Automated Manual Transmission 0.020683 0.046581 0.034009 0.003288 

Electric Power Steering 0.00868 222 4990 0.001664 8 0.02 6 0.01

Improved Accessories 0.00828 10 003 0.001662 3 0.02 49 0.015

12V Micro-Hybrid 0.01844 16 682 0.002780 1 0.04 72 0.028

Belt mounted Integrated Starter Generator 0.028024 0.066299 0.046372 0.004466 

Crank mounted Integrated Starter Generator 0.068298 0.148515 0.110214 0.010630 

Power Split Hybrid 0.054487 0.135468 0.093148 0.010177 

2-Mode Hybrid 0.026160 0.094817 0.058171 0.008115 

Plug-in Hybrid 0.297300 0.655074 0.464704 0.045203 

Material Substitution (1.50%) 0.003163 0.007165 0.005254 0.000509 

Material Substitution (5% to 10% Cum) 0.030551 0.067486 0.049435 0.004803 

Low Rolling Resistance Tires 0.008821 0.021629 0.014999 0.001668 
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Low Drag Brakes 0.0043 0.011 8 0 8 0.000841 59 27 .00750

Secondary Axle Disconnect - Ladder Frame 0.009262 0.015969 0.012505 0.000831 

Aero Drag Reduction 0.018791 030834 4981 0.001673 0. 0.02

Modeling Resu

Tables XII-8 an elin ts for fuel saved, total c societal 

benefits, and net benefits for passenger cars a espectively under a 7% discount rate. 

They also indic t be d II-11 

summarize thes dis T ar ted in 

Figures XII-13 er c r the Alte 7 percent for 

MY 2016. Alth en of t g ou ibutions are 

similar for the l nt disco nd f de well. The 

humped shape t ene et benefi reflects the three different 

gasoline price scenarios. About half of all dr elected from the AEO Reference Case, 

while about one th i were drawn 

from the High O his produ epar s wh t the 

increasing impa e p ely h rice The 

following discu of esen se ta e combined 

passenger car an e 7 typic lowe d 3 percent 

(typically upper

Fuel Savings

lts – Output 

d XII-9 summarize the mod g resul osts, 

nd trucks r

ate the probability that ne

 a 3%

nefits excee

cou . 

zero. Tables

he ts 

XII-10 and X

e same results under e tra

through XII-16 for p

nt rate

ars unde

se resul

Preferred

 also illus

asseng rnative at

ough not shown here, the g eral shape he resultin tput distr

ight trucks, the 3 perce unt rate, a or other mo l years as

hat occurs for both social b fits and n ts

aws were s

 quarter were drawn from e Low Oil Pr ce scenario and one quarter

il Price scenario. T ces three s ate hump ich reflec

ct on benefits from the thre

range

rogressiv igher oil p

t e

 scenarios.

ssions summarize the 

d light truck across bo

 results pr

 percent (

ed in th

ally the 

bles for th

th th r range) an

 range) discount rates.295 

: T t M e

trucks) will exp 5,853 mi 5,297 lion fuel savings 

over their usefu les c 7,4 illion and 

10,722,104 mill ings ov eful l MY icles will 

experience betw d 14 io f ngs over their 

useful lifespan. pe een 13, 9,284 and 1 2,026 million 

gallons of fuel s ifes 16 veh l etween 

16,766,243 and ns s e Over the 

combined lifesp years, bet 4 tril 0.3t lons of fuel 

will be saved. 

Total Costs

he analysis indicates tha Y 2012 vehicles (both pass nger cars and light 

erience between 3,15 llion and ,310 mil gallons of

l lifespan. MY 2013 vehic will experien e between 37,996 m

ion gallons of fuel sav er their us ifespan. 

n gallons o

 2014 veh

een 10,354,918 million an fue avi

 MY 2015 vehicles will ex

,434,026 mill l s

rience betw 8,08

pan. MY 20

27

avings over their useful l

21,718,166 million gallo

icles wil

 over their us

 experience b

of fuel saving ful lifespan. 

an of the five model ween 51. lion and 7 rillion gal

: Th ner 2012 pa nger cars and light trucks will 

pay between $3,838million and $7,968 million i er vehicle prices to purchase vehicles with 

improved fuel efficiency. MY 2013 owners will etween $5,867 million and $10,731 

million more. MY 2014 owners will pay between $7,559 million and $13,840 million more. 

MY 2015 owners will pay between $9,162 million and $16,536 million more. MY 2016 owners 

will pay between $11,297 million and $19,262 million more. Owners of all five model years 

 

e analysis indicates that ow s of MY sse

n high

 pay b

295 In a few cases the upper range results were obtained fro the 7% rate and the lower range results were obtained 

from the 3% rate. While this may seem counterintuitive, i rom the random selection process that is inherent 

in the Monte Carlo technique. 

m

t results f
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vehicles combined will pay between $37. billion in higher vehicle prices to 

purchase vehicles w

Societal Benefits:

9 billion and $68.2

ith improved fuel efficiency. 

 The analysis indicates that ch ges to MY 2012 passenger cars and light 

trucks to me oposed CAFE standards wil e over ietal be lued 

between $4,229 million and $22,407 millio 3 vehicles will produce benefits valued 

between $10 on. e r s valued 

between $13 3 million. pro s valued 

between $18 illion. M 6 vehi l prod efits valued 

between $22 million. e com fespa five model 

years, societ 69.1 bil $320. n will uced. 

Net Benefits

an

et the pr l produc all soc nefits va

n. MY 201

,126 million and $47,722 milli

,16

 MY 2014 v

M 5 vehi

hicles will p

l 

oduce benefit

,975 million and $66 Y 201 cles wil d efit uce ben

,087 million and $83,333 m

,703 million and $101,174

Y 201

Over th

cles wil

bined li

uce ben

n of the 

al benefits valued between $ lion and 8 billio be prod

: The uncertainty analysis indi e net impact of the higher CAFE 

requirement cars and w e of $2,012 

million and 38 million. Th least cent c that changes 

made to MY he higher tanda prod t benefit. 

The net imp ement 2013 a ne of between 

$2,033 milli 286 mill re is rcent that 

changes mad chie standar ll produ a net benefit. 

The net impa equire Y 2014 will be a net benefit of between 

$3,756 milli 4,448 mi i e that 

changes mad les to achieve th r CAF ards w uce a net 

benefit. The AFE req r 5 wi t benefit of 

between $6, 1 million. T 0 pe rtaint anges made 

to MY 2015 FE standa produc net benefi he net impact 

of the higher 2 et bene t of between 51 million 

and $84,920 rcent cer a to ehicles to 

achieve the duce a ne ve o higher 

CAFE stand its rangin 8.5 to $26 on. There is 

at least

cates that th

s for MY 2012 passenger light trucks ill be betwe n a net cost 

a net benefit of $16,1 ere is at a 78 per ertainty

 2012 vehicles to achieve t

 requir

CAFE s rds will uce a ne

act of the higher CAFE s for MY

io e

 will be

a 1 pe

t benefit 

on and a net benefit of $38, cer inty 

e to MY 2013 vehicles to a

n. Th

e CAFE

00

ds wi

ta

ve th ce

ct of the higher CAFE r ments for M

on and a net benefit of $5 llion. There s a 100 perc nt certainty 

e to MY 2014 vehic e highe E stand ill prod

 net impact of the higher C uirements fo MY 201 ll be a ne

084 million and $69,46 here is 10 rcent ce y that ch

 vehicles to achieve the CA

 CAFE requirements for MY 

rds will

 a n

e a

fi

t. T

016 will be $8,6

 million. There is 100 pe

CAFE standards will pro

tainty that ch

t benefit. O

nges made 

r all five m

 MY 2016 v

del years, the

ards will produce net benef g from $1 billion 3.3 billi

 a 78 s wil a ne l benefit in 

each

 percent certainty that higher CAFE standard l produce t societa

 of the model years covered by this final rule. In most ye prob 100%. ars, this ability is
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U

Item Mean Low High 

Table XII-8 

NCERTAINTY ANALYSIS RESULTS, PASSENGER CARS

(7% Discount Rate) 

MY 2012 

Fuel Saved (mill. gall.) 2,351,600 1,708,714 2,966,529 

Total Cost ($mill.) $4,183 $2,770 $5,384 

Societal Benefits ($mill.) $5,576 $2,292 $10,261 

Net Benefits ($mill.) $ - 1,393 $2,168 $6,324

% Certainty Net Ben. > 0 78% 

MY 2013 

Fuel Saved (mill. gall.) 5,101,261 4,241,046 6,006,703 

Total Cost ($mill.) $5,445 $4,255 $6,779 

Societal Benefits ($mill.) $12,588 $5,682 $21,969 

Net Benefits ($mill.) $7,143 $170 $16,280

% Certainty Net Ben. > 0 100% 

MY 2014 

Fuel Saved (mill. gall.) 7,085,206 5,951,278 8,124,710 

Total Cost ($mill.) $6,829 $5,244 $8,408 

Societal Benefits ($mill.) $17,806 $8,023 $30,965 

Net Benefits ($mill.) $10,977 $1,249 $23,938

% Certainty Net Ben. > 0 100% 

MY 2015 

Fuel Saved (mill. gall.) 9,107,029 7,720,755 10,515,156

Total Cost ($mill.) $8,057 $6,233 $9,990 

Societal Benefits ($mill.) $2 $ 5 3,241 10,574 $40,04

Net Benefits ($mill.) $15,184 $2,751 $31,402

% Certainty Net Ben. > 0 100% 

MY 2016 

Fuel Saved (mill. gall.) 11,268,179 9,840,046 12,649,674

Total Cost ($mill.) $9,461 $7,356 $12,014

Societal Benefits ($mill.) $2 $ 4 9,110 13,287 $49,45

Net Benefits ($mill.) $19,650 $4,404 $39,532

% Certainty Net Ben. > 0 100% 
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Table XII-9 

UNCERTAINTY ANALYSIS RESULTS, LIGHT TRUCKS

(7% Discount Rate) 

Item Mean Low High 

MY 2012 

Fuel Saved (mill. gall.) 1,794,729 1,4 2,245 47,139 ,130

Total Cost ($mill.) $1,703 $1,075 $2,584 

Societal Benefits ($mill.) $4,156 $1,937 $7,634 

Net Benefits ($mill.) $2,453 $5, $156 448 

% Certainty Net Ben. > 0 100% 

MY 2013 

Fuel Saved (mill. gall.) 3,805,850 3,196,950 4,611,444

Total Cost ($mill.) $2,541 $1,708 $3,589 

Societal Benefits ($mill.) $9,011 $4,444 $16,318 

Net Benefits ($mill.) $6,470 $ $13 1,833 ,010 

% Certainty Net Ben. > 0 100% 

MY 2014 

Fuel Saved (mill. gall.) 5,246,353 4,403,640 6,201,065

Total Cost ($mill.) $3,555 $2,398 $5,096 

Societal Benefits ($mill.) $12,644 $5,952 $22,334 

Net Benefits ($mill.) $9,089 $ $18 2,507 ,269 

% Certainty Net Ben. > 0 100% 

MY 2015 

Fuel Saved (mill. gall.) 6,512,008 5,558,529 7,441,376

Total Cost ($mill.) $4,292 $2,929 $5,901 

Societal Benefits ($mill.) $15,919 $7,513 $28,049 

Net Benefits ($mill.) $11,626 $ $23 3,333 ,292 

% Certainty Net Ben. > 0 100% 

MY 2016 

Fuel Saved (mill. gall.) 7,947,335 6,926,197 8,817,021

Total Cost ($mill.) $5,214 $3,941 $6,718 

Societal Benefits ($mill.) $19,600 $9,416 $32,950 

Net Benefits ($mill.) $14,386 $27 $4,247 ,807 

% Certainty Net Ben. > 0 100% 
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UNCERTAINTY ANALYSIS ARS AND LIGHT TRUCKS

(7% Discount Rate) 

Item Mean Low High 

Table XII-10 

RESULTS, PASSENGER C

MY 2012 

Fuel Saved (mill. gall.) 4,146,329 3,155,853 5,211,659 

Total Cost ($mill.) $5,886 $3,845 $7,968 

Societal Benefits ($mill.) $9,732 $4,229 $17,895 

Net Benefits ($mill.) $3,846 -$2,012 $11,772 

% Certainty Net Ben. > 0 94% 

MY 2013 

Fuel Saved (mill. gall.) 8,907,111 7,437,996 10,618,147 

Total Cost ($mill.) $7,986 $5,963 $10,368 

Societal Benefits ($mill.) $21,599 $10,126 $38,287 

Net Benefits ($mill.) $13,613 $2,033 $29,290 

% Certainty Net Ben. > 0 100% 

MY 2014

Fuel Saved (mill. gall.) 12,3 59 10,354,918 14,325,775 31,5

Total Cost ($mill.) $10,384 $7,642 $13,504 

Societal Benefits ($mill.) $3 ,450 $13,975 $53,299 0

Net Benefits ($mill.) $2 ,066 $3,756 $42,207 0

% Certainty Net Ben. > 0 100% 

MY 2015 

Fuel Saved (mill. gall.) 15,619,037 13,279,284 17,956,532 

Total Cost ($mill.) $12,349 $9,162 $15,891 

Societal Benefits ($mill.) $39,160 $18,087 $68,094 

Net Benefits ($mill.) $26,810 $6,084 $54,694 

% Certainty Net Ben. > 0 100% 

MY 2016 

Fuel Saved (mill. gall.) 19,215,514 16,766,243 21,466,695 

Total Cost ($mill.) $14,675 $11,297 $18,732 

Societal Benefits ($mill.) $48,710 $22,703 $82,404 

Net Benefits ($mill.) $34,036 $8,651 $67,339 

% Certainty Net Ben. > 0 100% 
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Table XII-11 

UNCERTAINTY ANALYSIS R ULTS, PASSENGER CARS

(3% Disc nt Rate) 

Item Mean Low High 

ES

ou

MY 2012 

Fuel Saved (mill. gall.) 2,384,741 1,774,115 2,990,158 

Total Cost ($mill.) 4,202 2,747 5,379 

Societal Benefits ($mill.) 7,041 2,982 12,519 

Net Benefits ($mill.) 2,839 -1,316 8,562 

% Certainty Net Ben. > 0 91% 

MY 2013 

Fuel Saved (mill. gall.) 5,153,970 4,272,330 6,089,001 

Total Cost ($mill.) 5,516 4,115 6,878 

Societal Benefits ($mill.) 15,713 7,186 26,921 

Net Benefits ($mill.) 10,197 1,842 20,890 

% Certainty Net Ben. > 0 100% 

MY 2014 

Fuel Saved (mill. gall.) 7,162,064 5,964,138 8,271,039 

Total Cost ($mill.) 6,939 5,163 8,667 

Societal Benefits ($mill.) 22,210 10,205 38,008 

Net Benefits ($mill.) 15,271 3,440 30,520 

% Certainty Net Ben. > 0 100% 

MY 2015 

Fuel Saved (mill. gall.) 9,183,889 7,723,966 10,555,661

Total Cost ($mill.) 8,179 6,304 10,405 

Societal Benefits ($mill.) 28,858 13,264 48,823 

Net Benefits ($mill.) 20,679 5,289 39,859 

% Certainty Net Ben. > 0 100% 

MY 2016 

Fuel Saved (mill. gall.) 11,323,825 9,912,630 12,715,882

Total Cost ($mill.) 9,579 7,470 12,359 

Societal Benefits ($mill.) 35,954 16,578 60,044 

Net Benefits ($mill.) 26,376 7,779 49,538 

% Certainty Net Ben. > 0 100% 
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ANALYSIS RESULTS, LIGHT TRUCKS

(3% Discount Rate) 

Item Mean Low High 

Table XII-12 

UNCERTAINTY

MY 2012 

Fuel Saved (mill. gall.) 1,813,345 1,447,105 2,307,152

Total Cost ($mill.) 1,748 1,091 2,494 

Societal Benefits ($mill.) 5,342 2,505 9,888 

Net Benefits ($mill.) 3,593 762 7,576 

% Certainty Net Ben. > 0 100% 

MY 2013 

Fuel Saved (mill. gall.) 3,835,210 3,234,224 4,633,103

Total Cost ($mill.) 2,607 1,752 3,853 

Societal Benefits ($mill.) 11,507 5,581 20,801 

Net Benefits ($mill.) 8,900 3,069 17,396 

% Certainty Net Ben. > 0 100% 

MY 2014 

Fuel Saved (mill. gall.) 5,292,250 4,493,060 6,162,987

Total Cost ($mill.) 3,645 2,396 5,173 

Societal Benefits ($mill.) 16,128 7,563 28,155 

Net Benefits ($mill.) 12,483 4,198 23,928 

% Certainty Net Ben. > 0 100% 

MY 2015 

Fuel Saved (mill. gall.) 6,560,161 5,690,703 7,526,400

Total Cost ($mill.) 4,388 3,029 6,131 

Societal Benefits ($mill.) 20,243 9,557 34,510 

Net Benefits ($mill.) 15,855 5,399 29,602 

% Certainty Net Ben. > 0 100% 

MY 2016 

Fuel Saved (mill. gall.) 7,970,500 6,937,291 9,002,284

Total Cost ($mill.) 5,292 3,945 6,903 

Societal Benefits ($mill.) 24,799 11,856 41,130 

Net Benefits ($mill.) 19,507 6,724 35,382 

% Certainty Net Ben. > 0 100% 
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HT TRUCKS

(3% Discount Rate) 

Table XII-13 

UNCERTAINTY ANALYSIS RESULTS, PASSENGER CARS AND LIG

Item Mean Low High 

MY 2012 

Fuel Saved (mill. gall.) 4,198,086 3,221,220 5,297,310 

Total Cost ($mill.) $5,950 $3,838 $7,873 

Societal Benefits ($mill.) $12,383 $5,487 $22,407 

Net Benefits ($mill.) $6,432 -$554 $16,138 

% Certainty Net Ben. > 0 99.9% 

MY 2013 

Fuel Saved (mill. gall.) 8,989,180 7,506,554 10,722,104 

Total Cost ($mill.) $8,123 $5,867 $10,731 

Societal Benefits ($mill.) $27,220 $12,767 $47,722 

Net Benefits ($mill.) $19,097 $4,911 $38,286 

% Certainty Net Ben. > 0 100% 

MY 2014 

Fuel Saved (mill. gall.) 12,454,314 10,457,198 14,434,026 

Total Cost ($mill.) $10,584 $7,559 $13,840 

Societal Benefits ($mill.) $38,338 $17,768 $66,163 

Net Benefits ($mill.) $27,754 $7,638 $54,448 

% Certainty Net Ben. > 0 100% 

MY 2015 

Fuel Saved (mill. gall.) 15,744,050 13,414,669 18,082,061 

Total Cost ($mill.) $12,567 $9,333 $16,536 

Societal Benefits ($mill.) $49,101 $22,821 $83,333 

Net Benefits ($mill.) $36,534 $10,688 $69,461 

% Certainty Net Ben. > 0 100% 

MY 2016 

Fuel Saved (mill. gall.) 19,294,325 16,849,921 21,718,166 

Total Cost ($mill.) $14,871 $11,415 $19,262 

Societal Benefits ($mill.) $60,753 $28,434 $101,174 

Net Benefits ($mill.) $45,883 $14,503 $84,920 

% Certainty Net Ben. > 0 100% 
DELIBERATIVE

509

FIGURE II-13 

Mod ile 

X

el Output Prof

 

FIGURE XII-14 

Model Output Profile 

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DELIBERATIVE

510

FIGURE XII-15 

Model Output Profile 

FIGURE XII-16 

Model Output Profile 

 DOCUMENT – DO NOT RELEASE 
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511

XIII. 12BREGULATORY FLEXIBILITY ACT AND UNFUNDED MANDATES 

REFORM ACT ANALYSIS 

A. Regulatory Flexibility Act 

The Regulatory Flexibility Act of 1980 (5 U.S.C §601 et seq.) requires agencies to evaluate the 

potential effects of their proposed and final rules on small business, small organizations and 

small Government jurisdictions. 

5 U.S.C §603 requires agencies to prepare and make available for public comments initial and 

final regulatory flexibility analysis (RFA) describing the impact of proposed and final rules on 

small entities. Section 603(b) of the Act specifies the content of a RFA. Each RFA must 

contain: 

1. A description of the reasons why action by the agency is being considered; 

2. A succinct statement of the objectives of, and legal basis for a final rule; 

3. A description of and, where feasible, an estimate of the number of small entities to which 

the final rule will apply; 

4. A description of the projected reporting, recording keeping and other compliance 

requirements of a final rule including an estimate of the classes of small entities which 

will be subject to the requirement and the type of professional skills necessary for 

preparation of the report or record; 

5. An identification, to the extent practicable, of all relevant Federal rules which may 

duplicate, overlap or conflict with the final rule; 

6. Each final regulatory flexibility analysis shall also contain a description of any significant 

alternatives to the final rule which accomplish the stated objectives of applicable statutes 

and which minimize any significant economic impact of the final rule on small entities. 

1. Description of the reason why action by the agency is being considered

NHTSA is proposing this action to improve vehicle fuel economy. 

2. Objectives of, and legal basis for, the final rule

The Energy Policy and Conservation Act requires the agency to set light truck fuel economy 

standards every year and allows the agency to update passenger car fuel economy standards. The 

Energy Independence and Security Act (EISA) mandates the setting of separate standards for 

passenger cars and for light trucks at levels sufficient to ensure that the average fuel economy of 

the combined fleet of all passenger cars and light trucks sold by all manufacturers in the U.S. in 

model year 2020 equals or exceeds 35 miles per gallon. 

 

3. Description and estimate of the number of small entities to which the final rule will apply

The final rule will affect motor vehicle manufacturers. There are no light truck manufacturers 

that are small businesses. However, there are six domestically owned small passenger car 

manufacturers. 

 

Business entities are defined as small business using the North American Industry Classification 

System (NAICS) code, for the purpose of receiving Small Business Administration assistance. 
DELIBERATIVE DOCUMENT – DO NOT RELEASE 

512

One of the criteria for determining size, as stated in 13 CFR 121.201, is the number of employees 

in the firm. For establishments primarily engaged in manufacturing or assembling automobiles, 

light and heavy duty trucks, buses, motor homes, or motor vehicle body manufacturing, the firm 

must have less than 1,000 employees to be classified as a small business. 

We believe that the rulemaking would not have a significant economic impact on the small 

vehicle manufacturers because under Part 525, passenger car manufacturer making less than 

10,000 vehicles per year can petition NHTSA to have alternative standards set for those 

manufacturers. Those manufacturers that currently don’t meet the 27.5 mpg standard can 

petition the agency for relief. If the standard is raised, it has no meaningful impact on these 

manufacturers; they still must go through the same process and petition for relief. Other small 

manufacturers (Tesla and Fisker) make electric vehicles or hybrid vehicles that will pass the final 

rule. 

Currently, there are six small passenger car motor vehicle manufacturers in the United States. 

Table X1II-1 provides information about the 6 small domestic manufacturers in MY 2007. All 

are small manufacturers, having much less than 1,000 employees. 
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513

Table XIII-1 

Small Vehicle Manufacturers 

Manufacturer Employees Estimated 

Sales 

Sale Price Range Est. Revenues* 

Fisker 

Automotive** N/A 

15,000 

projected $80,000 N/A 

Mosler 

Automotive 25 20 $189,000 $2,000,000 

Panoz Auto 

Development 

Company 50 150 

$90,000 to 

$125,000 $16,125,000 

Saleen Inc. 170 1,000#

$39,000 to 

$59,000 $49,000,000 

Saleen Inc. 170 16## $585,000 $9,000,000 

Standard 

Taxi*** 35 N/A $25,000 $2,000,000 

Tesla Motors, 

Inc. 250 2,000 

$65,000 to 

$100,000 N/A 

* Assuming an average sales price from the sales price range. 

** Fisker Automotive is a joint venture of Quantum Fuel Systems Technologies Worldwide, 

Inc. and Fisker Coachbuild, LLC. 

*** Standard Taxi is a subsidiary of the Vehicle Production Group LLC. 35 employees is the 

total for VPG LLC. 

#

 Ford Mustang Conversions 

The agency has not analyzed the impact of the final rule on these small manufacturers 

individually. However, assuming those that do not meet the final rule would petition the agency, 

rather than meet the final rule, the cost is not expected to be substantial. 

4. A description of the projected reporting, record keeping and other compliance requirements of 

a final rule including an estimate of the classes of small entities which will be subject to the 

requirement and the type of professional skills necessary for preparation of the report or record. 

This final rule includes no new requirements for reporting, record keeping of other compliance 

requirements. 

5. An identification, to the extent practicable, of all relevant Federal rules which may duplicate, 

overlap, or conflict with the final rule 

EPA and NHTSA are proposing joint rules which complement each other. We know of no other 

Federal rules which duplicate, overlap, or conflict with the final rule. 
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514

6. A description of any significant alternatives to the final rule which accomplish the stated 

objectives of applicable statutes and which minimize any significant economic impact of the 

final rule on small entities. 

There are no other alternatives that can achieve the stated objectives without installing fuel 

economy technologies into the vehicle. 

25BB. Unfunded Mandates Reform Act 

Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) requires Federal agencies 

to prepare a written assessment of the costs, benefits, and other effects of a proposed or final rule 

that includes a Federal mandate likely to result in the expenditure by State, local, or tribal 

governments, in the aggregate, or by the private sector, of more than $100 million in any one 

year (adjusted for inflation with base year of 1995). Adjusting this amount by the implicit gross 

domestic product price deflator for 2006 results in $126 million (116.043/92.106 = 1.26). Before 

promulgating a rule for which a written statement is needed, section 205 of UMRA generally 

requires NHTSA to identify and consider a reasonable number of regulatory alternatives and 

adopt the least costly, most cost-effective, or least burdensome alternative that achieves the 

objectives of the rule. The provisions of section 205 do not apply when they are inconsistent 

with applicable law. Moreover, section 205 allows NHTSA to adopt an alternative other than the 

least costly, most cost-effective, or least burdensome alternative if the agency publishes with the 

final rule an explanation why that alternative was not adopted. 

This final rule will not result in the expenditure by State, local, or tribal governments, in the 

aggregate, of more than $126 million annually, but it will result in the expenditure of that 

magnitude by vehicle manufacturers and/or their suppliers. In promulgating this final rule, 

NHTSA considered a variety of alternative average fuel economy standards lower and higher 

than those proposed. NHTSA is statutorily required to set standards at the maximum feasible 

level achievable by manufacturers based on its consideration and balancing of relevant factors 

and has concluded that the final fuel economy standards are the maximum feasible standards for 

the passenger car and light truck fleets for MYs 2012-2016 in light of the statutory 

considerations. 

 

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