BMW Group • Chrysler LLC • Ford Motor Company • General Motors 

Mazda • Mercedes-Benz, USA • Mitsubishi Motors • Porsche • Toyota • Volkswagen 

1401 Eye Street, NW, Suite 900, Washington, DC 20005-6562 • Phone 202.326.5500 • Fax 202.326.5567 • www.autoalliance.org 

 April 28, 2008 

Mr. Chester J. France 

Director, Assessment and Standards 

Division 

Office of Transportation and Air Quality 

U.S. Environmental Protection Agency 

2000 Traverwood Drive 

Ann Arbor, MI 48105 

K. John Holmes, Ph.D. 

Senior Staff Officer 

Board on Energy and Environmental Systems 

National Research Council 

500 5th Street, NW 

Washington, DC 20001 

Ms. Julie Abraham 

Director, Office of International Policy 

and Harmonization 

Room 5208-NPP-01 

400 Seventh St. S.W. 

Washington, DC 20590 

Re: Sierra Research Basic Analysis of the Cost and Long-Term Impact of the Energy 

Independence and Security Act Fuel Economy Standards 

Dear Mr. France, Ms. Abraham, and Dr. Holmes: 

Our purpose in writing this letter is to provide for your deliberations a report completed by 

Sierra Research using their VEHSIM model and cost data developed by Martec. The 

objective of the report is to determine the expected changes in vehicle design and price 

associated with meeting the new CAFE standards required by EISA 2007 on individual 

manufacturers and on a fleet average basis. Given the timing, this analysis does not 

specifically address the NPRM released on April 22, 2008. We intend to provide NHTSA 

with a supplemental analysis specifically addressing the proposed standards. In order to 

accomplish that objective, the following tasks were performed: 

1. Developing a baseline for each of 11 manufacturers against which the design changes 

necessary to meet more stringent CAFE standards would be compared. 

2. Developing attribute-based standards that might be adopted by the Department of 

Transportation. 

3. Determining the incremental increase in vehicle prices associated with the deployment of 

design changes intended to increase CAFE levels.
Mr. Chester J. France 

Ms. Julie Abraham 

Dr. K. John Holmes 

April 28, 2008 

Page 2 of 2 

4. Determining the optimum sequence of design changes that would increase vehicle fuel 

economy in the most cost-effective manner. 

5. Performing vehicle simulation modeling to accurately determine the combination of 

design changes necessary for each manufacturer to comply with the new standards. 

6. Determining the net increase in vehicle price associated with the design changes 

necessary to meet the new standards. 

7. Evaluating the cost-effectiveness of the new standards from the perspective of vehicle 

owners under a range of gasoline price forecasts. 

Please contact me if you have any questions or would like additional information. 

 

 

Sincerely, 

Julie C. Becker 

Vice President 

Environmental Affairs 

cc: Mr. Kenneth Katz, Lead Engineer for CAFE 

The Hon. James Allen Nussle, Director, Office of Management and Budget 

Mr. Robert J. Myers, Associate Assistant Administrator , Office of Air and Radiation 

Ms. Margo Tsirigotis Oge, Office of Transportation and Air Quality 
Report No. SR2008-04-01

Basic Analysis of the Cost and 

Long-Term Impact of the Energy 

Independence and Security Act 

Fuel Economy Standards 

April 24, 2008

prepared by: 

Sierra Research, Inc. 

1801 J Street 

Sacramento, California 95811 

(916) 444-6666
Report No. SR2008-04-01 

BASIC ANALYSIS OF THE COST AND LONG-TERM IMPACT OF 

THE ENERGY INDEPENDENCE AND SECURITY ACT 

FUEL ECONOMY STANDARDS

 

April 24, 2008 

 Principal authors: 

 Thomas C. Austin 

 Thomas R. Carlson 

James M. Lyons 

Sierra Research, Inc. 

1801 J Street 

Sacramento, CA 95811 

(916) 444-6666 
BASIC ANALYSIS OF THE COST AND LONG-TERM IMPACT OF 

THE ENERGY INDEPENDENCE AND SECURITY ACT 

FUEL ECONOMY STANDARDS

Table of Contents

Page

1. SUMMARY................................................................................................................ 1 

2. INTRODUCTION ...................................................................................................... 3 

2.1 Background......................................................................................................... 3 

2.2 Project Objectives............................................................................................... 4 

2.3 Organization of the Report.................................................................................. 5 

3. BASELINE FLEET DEVELOPMENT...................................................................... 6 

3.1 Supporting Data Sources and Assembly............................................................. 6 

3.2 Classification of Vehicle Types........................................................................ 12 

3.3 Determination of Advanced Technology Penetrations..................................... 17 

3.4 Baseline Fleet Tabulations................................................................................ 19 

4. DETERMINATION OF NEW STANDARDS ........................................................ 22 

4.1 Key Assumptions.............................................................................................. 22 

4.2 Development of Footprint-Based Reformed Standard Models ........................ 23 

4.3 Comparison of Attribute Models...................................................................... 26 

4.4 Calculation of Fuel Economy Targets .............................................................. 28 

5. TECHNOLOGY ASSESSMENT............................................................................. 33 

5.1 Key Considerations........................................................................................... 33 

5.2 Benefits of Individual Technologies................................................................. 35 

6. TECHNOLOGY COST ESTIMATES..................................................................... 50 

6.1 Overview........................................................................................................... 50 

6.2 Sources of Individual Estimates........................................................................ 52 

6.3 Cost-Effectiveness............................................................................................ 57 

7. VEHICLE SIMULATION MODELING ................................................................. 59 

7.1 Modeling Approach .......................................................................................... 59 

7.2 VEHSIM Modeling........................................................................................... 61 

-i- 
8. COMPLIANCE ANALYSIS.................................................................................... 66 

8.1 Technology Deployment................................................................................... 66 

8.2 Compliance Calculations.................................................................................. 71 

8.3 Cost-Effectiveness Analysis............................................................................. 74 

8.4 Summary of Results.......................................................................................... 78 

9. REFERENCES ......................................................................................................... 81 

APPENDIX A Detailed Baseline Fleet Tabulations 

APPENDIX B Detailed Cost-Effectiveness Analysis Results 

-ii- 
List of Figures

Figure Page

Figure 4-1 Passenger Car Fuel Consumption vs. Footprint............................................ 27 

Figure 4-2 Light-Duty Truck Fuel Consumption vs. Footprint...................................... 28 

Figure 5-1 VEHSIM Model Structure ............................................................................ 36 

Figure 5-2 Cal-Urban Driving Cycle Speed-Time Trace ............................................... 40 

Figure 5-3 EPA Urban (City) Driving Cycle Speed-Time Trace ................................... 40 

Figure 5-4 Cal-Rural Driving Cycle Speed-Time Trace................................................. 41 

Figure 5-5 EPA Highway Driving Cycle Speed-Time Trace ......................................... 41 

Figure 5-6 Predicted vs. Actual Fuel Economy for 2007 Model Year Gasoline Cars.... 45 

-iii- 
List of Tables

Table Page

Table 1-1 Compliance Analysis for Footprint-Based Standards with Transfer Between 

Cars and Trucks to Reduce Compliance Cost..................................................................... 2 

Table 3-1 Frontal Area Regression Statistics.................................................................. 11 

Table 3-2 Passenger Car Categories............................................................................... 13 

Table 3-3 Light-Truck Categories .................................................................................. 16 

Table 3-4 Baseline Fleet Advanced Technology Penetrations (%) by Vehicle Category 

for All Manufacturers ....................................................................................................... 19 

Table 3-5 Characteristics of the MY2006 U.S. Light-Dutya

 Vehicle Fleet.................... 21 

Table 4-1 Vehicle Attribute Models Evaluated .............................................................. 26 

Table 4-2 Passenger Car Attribute Models and Comparison Statistics.......................... 26 

Table 4-3 Light-Duty Truck Attribute Models and Comparison Statistics .................... 27 

Table 4-4 Baseline Fleet Fuel Economy and Sales Fractions by Manufacturer............. 29 

Table 4-5 MY2020 Reformed Fuel Economy Requirements by Manufacturer – 

Footprint-Based Approach................................................................................................ 31 

Table 5-1 VEHSIM Runs for Vehicles With VVLT and Cylinder Deactivation........... 38 

Table 5-2 Estimates of Achievable Fuel Consumption Reductions Assuming Engine 

Size Adjustments for Constant Acceleration Performance............................................... 39 

Table 5-3 Typical Midsize Vehicle Weight Reduction Potential with Ultralight Steel and 

Aluminum ......................................................................................................................... 43 

Table 6-1 Long-Term Estimates of Retail Price Increase for Various Technologies.... 52 

Table 6-2 Harbour and Associates Engine Cost Estimates a .......................................... 57 

Table 6-3 Long-Term Estimates of Cost-Effectiveness for Various Technologies 

Applied to a Mid-Size Car and Pickup Truck................................................................... 58 

Table 7-1 Technology Combinations Modeled by Vehicle Type for Compliance with 

Federal EISA CAFE Standards......................................................................................... 59 

-iv- 
-vTable 7-2 Comparison of Reported and Simulated MY2006 Baseline Fuel Economy by 

Individual Vehicle Category Across All Manufacturers .................................................. 63 

Table 7-3 Sample Technology Combination Simulation Summary for Chrysler CSWs 65 

Table 8-1 Base Long-Term Technology Costs (Based on Midsize Sedan/Wagon with 

3,226 lb Reference Weight).............................................................................................. 68 

Table 8-2 Technology Deployment Sequence for Chrysler MSWs ............................... 70 

Table 8-3 Results Sheet Layout for Chrysler Fleet Compilation.................................... 72 

Table 8-4 Compliance Sheet Layout for Chrysler Using a Footprint-Based Standard... 73 

Table 8-5 Compliance Analysis for Footprint-Based Standards No Credit Transfer 

Between Cars and Trucks to Reduce Compliance Cost.................................................... 79 

Table 8-6 Compliance Analysis for Footprint-Based Standards With Credit Transfer 

Between Cars and Trucks to Reduce Compliance Cost.................................................... 80 
1. SUMMARY 

For the 2007 model year, Corporate Average Fuel Economy (CAFE) standards were 22.2 

miles per gallon (mpg) for light-duty trucks (≤8,500 pounds gross vehicle weight) and 

27.5 mpg for passenger cars. With a 50/50 sales mix of cars and light trucks, the fleet 

average standard would be 25 mpg. In December of 2007, the President signed House of 

Representatives Bill 6 (HR6), The Energy Independence and Security Act of 2007 

(EISA). EISA requires fleet average fuel economy to increase to at least 35 mpg by 

model year 2020. (It also requires sport utility vehicles above 8,500 pounds to be subject 

to CAFE standards for the first time.) 

Currently, the same mpg standards apply to each manufacturer. Under EISA that will not 

be the case. The mpg values that each manufacturer must meet will ultimately depend on 

the form of the new standards adopted by the National Highway Traffic Safety 

Administration (NHTSA). NHTSA has already adopted “footprint” based standards for 

light-duty trucks that can be used starting in 2011.*

 Under those standards, 

manufacturers who produce vehicles with smaller footprints must achieve a higher mpg 

level. We have analyzed the potential impacts of EISA based on the assumption that 

NHTSA maintains footprint-based standards for trucks and adopts similar footprint-based 

standards for passenger cars. 

On April 22, 2008, NHTSA announced a Notice of Proposed Rulemaking (NPRM) 

proposing footprint-based standards for passenger cars and light trucks for model years 

2011 through 2015. However, this report was prepared prior to the NPRM and addresses 

only the long term cost of increasing fleet average fuel economy to 35 mpg by model 

year 2020. A supplemental analysis will be prepared that addresses the 2011 – 2015 

standards contained in the NPRM. 

Detailed vehicle simulation modeling of the footprint-based standards necessary to 

achieve a fleet average of 35 mpg by 2020 indicates that extensive changes in engine, 

transmission, and body designs will likely be required by all manufacturers to comply 

with the new standards. In fact, the level of design changes required may exceed the 

availability of engineering and capital resources for some companies. 

As shown in Table 1-1, we have estimated that the increase in average vehicle price (cars 

and trucks averaged together) to meet footprint-based standards equivalent to a 35 mpg 

fleet average will be approximately $3,500. This estimate assumes individual 

manufacturers will transfer credits between their car and truck production to minimize the 

 

*

 “Footprint” is defined as the wheelbase multiplied by the average track width. 

-1- 
cost of compliance. However, even with such credit transfers, manufacturer-specific 

price increases are highly variable. One manufacturer is expected to be able to comply 

with a price increase of $1,233 per vehicle while several other manufacturers are 

expected to require price increases above $5,000 per vehicle. The difference in price 

increase is directly related to the percentage of hybrid vehicles required to achieve 

compliance, which ranges from 0% to over 80%. 

Table 1-1 

Compliance Analysis for Footprint-Based Standards with 

Transfer Between Cars and Trucks to Reduce Compliance Cost

Hybrid Retail Price

Manufacturer 2006 Actual New Standard Fraction Equiv Cost 5-Year 20-Year

BMW 25.76 39.26 4.37% $2,089 $7.79 $5.05

Chrysler 23.16 32.80 37.27% $5,254 $8.58 $5.93

Daimler 23.18 36.49 44.45% $5,438 $10.00 $6.51

Ford 22.97 33.54 22.46% $4,430 $7.52 $5.12

GM 24.38 34.01 20.21% $4,028 $6.67 $4.52

Honda 27.57 35.27 0.00% $1,233 $4.54 $3.05

Hyundai 27.68 39.00 1.38% $2,496 $7.38 $4.85

Nissan 24.90 35.43 8.70% $3,183 $7.19 $4.80

Porsche 22.09 38.73 80.91% $7,453 $11.61 $7.71

Toyota 28.32 36.25 0.00% $2,023 $6.63 $4.41

VW 29.27 42.17 1.21% $2,172 $8.81 $5.67

Composite: 25.09 35.00 13.54% $3,505 $7.12 $4.80

CAFE Fuel Economy (mpg) Break-Even Retail Fuel Price

Light-Duty Vehicle (and MDPV) Sales-Weighted Averages

The last two columns of Table 1-1 show the fuel price at which the increase in vehicle 

price is offset by the reduction in fuel cost realized by the average motorist. 

(Calculations shown in the table account for an appropriate discount rate, the “rebound 

effect,”*

 and the percent of vehicles scrapped over time.) On average, fuel prices would 

have to increase to $7.12 per gallon before the price increase is offset by the fuel savings 

during the first five years of ownership. Even if consumers were to value the fuel savings 

over a 20-year period of time, fuel prices would have to be at $4.80 per gallon before the 

price increase is offset by the fuel savings. 

### 

 

*

 The rebound effect is the additional driving induced by vehicles with higher fuel economy. Studies 

indicate that a 2% increase in travel is associated with a 10% reduction in fuel cost. 

-2- 
2. INTRODUCTION 

House of Representatives Bill 6 (HR6), The Energy Independence and Security Act of 

2007 (EISA), was signed by the President on December 19, 2007. Title I of the Act is 

entitled “Energy Security Through Improved Vehicle Fuel Economy.” Subtitle A of 

Title I addresses “Increased Corporate Average Fuel Economy Standards.” As stated in 

the press release issued by the White House, “It specifies a national standard of 35 miles 

per gallon by 2020, which will increase fuel economy standards by 40 percent and save 

billions of gallons of fuel.” 

At the request of the Alliance of Automobile Manufacturers, Sierra Research has 

analyzed the vehicle design changes that may be required to comply with the new 

Corporate Average Fuel Economy (CAFE) standards that will be adopted by the 

Department of Transportation pursuant to EISA. 

2.1 Background

The 2007 model year CAFE standards were 22.2 mpg for light-duty trucks and 27.5 mpg 

for passenger cars. Since there was approximately a 50/50 sales mix of cars and light 

trucks, the average fuel economy of the 2007 models was approximately 25 mpg. EISA 

requires that the average fuel economy of “the total fleet of passenger and non-passenger 

automobiles” be raised to at least 35 mpg by model year 2020, which is an increase of 

40%. 

“Non-passenger automobiles” is a new term under the federal fuel economy statutes. The 

legal definition is cumbersome, but “non-passenger automobiles” are vehicles that have 

previously been called “light-duty trucks” plus Sport Utility Vehicles (SUVs) that are up 

to 10,000 pounds gross vehicle weight. Under the current regulations, all trucks above 

8,500 pounds GVWR are exempt from fuel economy standards. Under EISA, pickup 

trucks above 8,500 pounds remain exempt, but SUVs between 8,500 and 10,000 pounds 

GVWR become subject to regulation for the first time. As under the current regulations, 

there may still be separate standards for passenger cars and “trucks” (now called nonpassenger automobiles), but the statutory fuel economy minimum applies to the salesweighted average of cars and trucks together. 

A significant change in the CAFE standards that must be adopted under EISA is that the 

Secretary of Transportation is directed to set standards for both cars and trucks “based 

on 1 or more vehicle attributes related to fuel economy and express each standard in the 

-3- 
form of a mathematical function.” In other words, manufacturers are no longer going to 

be subject to the same “miles per gallon” standard. The form of the standard that will 

apply to passenger cars is yet to be defined, but based on previous National Highway 

Traffic Safety Administration (NHTSA) experience in setting attribute-based standards 

for 2008-2011 model year trucks, manufacturers of larger vehicles will not have to 

achieve as high a fuel economy level as manufacturers of smaller vehicles. 

Although Congress didn’t specify the form of the new attribute-based standards, it did 

impose a limit to the break that can be given to manufacturers of larger passenger cars. 

Every manufacturer is required to achieve at least “92 percent of the average fuel 

economy projected by the Secretary for the combined domestic and nondomestic 

passenger automobile fleets manufactured for sale in the United States by all 

manufacturers.” In other words, when the fleet average standard for passenger cars 

reaches 35 mpg, every manufacturer has to achieve at least 32.2 mpg. 

One thing that Congress did not change is the test procedure used to determine 

compliance with the new standards. Compliance will be based on a combination of the 

36 year old EPA “City” test with the 34 year old EPA “Highway” test based on the 

assumptions that only 55% of all driving occurs in urban areas (which was true about 30 

years ago) and that non-urban fuel economy can be characterized using a driving cycle 

that was intentionally designed to reflect vigorous enforcement of a nationwide 55 mph 

speed limit. As a result, actual fuel economy in customer service will be somewhat lower 

than fuel economy measured using the CAFE test procedures. 

How the new CAFE standards to be adopted under EISA will affect individual 

manufacturers is uncertain for several reasons. First, 35 mpg is the minimum standard 

for 2020; the Secretary of Transportation is obligated to adopt a more stringent standard 

if feasible. There is no minimum or maximum ramp-up rate specified in the law for the 

standards that will apply between 2011 and 2020. In analyzing the potential impact of 

the new standards, it was necessary to make a number of assumptions regarding the form 

of the standard, the relative stringency of the standards for cars and trucks, and whether 

the 2020 fleet average standard will be set above 35.0 mpg. There is also uncertainty 

regarding the extent to which trading of credits between manufacturers (which is allowed 

under the law) will actually occur.*

2.2 Project Objectives

The overall objective of the project was to determine the expected changes in vehicle 

design and price associated with meeting the new CAFE standards required by EISA on 

both an individual manufacturer and fleet average basis. To accomplish this overall 

objective, the following tasks were performed: 

 

*

 The maximum increase in any compliance category attributable to transferred credits is 1.0 mpg for model 

years 2011 through 2013, 1.5 mpg for model years 2014 through 2017, and 2.0 mpg for 2018 and 

subsequent model years. 

-4- 
1. Developing a baseline for each of 11 manufacturers against which the design 

changes necessary to meet more stringent CAFE standards would be compared. 

2. Developing attribute-based standards that might be adopted by the Department of 

Transportation. 

3. Determining the incremental increase in vehicle prices associated with the 

deployment of design changes intended to increase CAFE levels. 

4. Determining the optimum sequence of design changes that would increase vehicle 

fuel economy in the most cost-effective manner. 

5. Performing vehicle simulation modeling to accurately determine the combination 

of design changes necessary for each manufacturer to comply with the new 

standards. 

6. Determining the net increase in vehicle price associated with the design changes 

necessary to meet the new standards. 

7. Evaluating the cost-effectiveness of the new standards from the perspective of 

vehicle owners under a range of gasoline price forecasts. 

2.3 Organization of the Report

Following this introduction, Section 3 describes the work that was done to develop a 

“baseline” against which the effect of more stringent CAFE standards would be 

evaluated. Section 4 describes how the potential footprint-based standard for passenger 

cars was developed. Section 5 describes the fuel economy benefits that were estimated 

for each technology and how combinations of technologies were evaluated using a 

vehicle simulation model. Section 6 describes the methodology used to estimate the 

increase in vehicle price associated with individual technologies and how the deployment 

sequence for technologies was determined based on the price increase per percent 

reduction in fuel consumption. Section 7 provides details regarding the vehicle 

simulation modeling that was performed. Section 8 contains the manufacturer-specific 

compliance analysis results, showing the increase in vehicle price for each manufacturer 

and for the fleet as a whole for a variety of attribute-based standards. Finally, Section 9 

contains a list of references cited throughout the report. 

Appendix A provides detailed specifications for the model year 2006 baseline. 

Appendix B contains detailed results of the compliance cost calculations and the costeffectiveness analysis. 

### 

-5- 
3. BASELINE FLEET DEVELOPMENT 

An important initial element in the analysis consisted of the development of a detailed 

fleet database that characterized the specifications, technology implementation, and fuel 

economy performance of light-duty vehicles and medium-duty passenger vehicles subject 

to CAFE standards under EISA. 

In earlier work1 for the Alliance, baseline fleet characterizations had been developed for 

the 2003 model year that had been updated with partial specification data for selected 

2004-2006 model year vehicles. Under the current analysis, updated baseline fleet 

characterizations were developed for Model Year (MY) 2006, the most recent model year 

for which complete data were available at the time of the effort. 

The list of vehicle specifications for which baseline data were assembled was broader 

than in the 2003 baseline fleet developed earlier to support analysis of attribute-based 

reformed fuel economy/CO2 standards. In addition to the “basic” parameters in the 2003 

baseline (e.g., sales, fuel economy, curb weight, frontal area, drag, displacement, power, 

etc.), data for additional vehicle attributes such as footprint, height, and interior volume 

were assembled under this effort. Although the current analysis is focused only on 

footprint-based standards, we have compiled detailed information on other attributes that 

could be used in the development of other forms of attribute-based standards. 

The effort consisted of identifying and assembling supporting datasets, classification of 

vehicle types, accounting for existing penetration of “advanced” fuel economy 

technologies (as defined under this effort), and tabulation of the detailed data. Each of 

these elements is described in the following sub-sections. 

3.1 Supporting Data Sources and Assembly

To determine the design changes and associated costs needed to comply with new CAFE 

standards, baseline vehicle fleet data were assembled at the most disaggregate level 

possible. Vehicle specifications and sales data were compiled by vehicle model, body 

style, engine size, and transmission. (For some models, further breakdowns by trim level 

were also possible.) 

As noted above, MY2006 was identified as that for which complete data were available. 

Although vehicle specification and fuel economy data were available for MY2007 (in 

addition to MY2006), finalized sales data were not. The “CAFE Sales” database 

-6- 
exchanged between NHTSA and manufacturers to track current CAFE compliance was 

not available in “final” form for MY2007 at the time this element of the analysis was 

performed. Only mid-model year sales were available, and given that these mid-year 

data are based on sales estimates, a decision was made to use the MY2006 final sales data 

with one exception. During the study, Chrysler staff indicated to Sierra that their 

MY2006 passenger car sales were anomalous due to early introduction of the MY2007 

Dodge Caliber and, as such, were not likely to represent the longer-term mix of sales. 

Based on input from Chrysler, a decision was made to use MY2007 sales (provided by 

Chrysler) to represent all Chrysler group passenger cars. 

Each of the data sources that were used to assemble the updated baseline fleet database is 

described below. 

AutoSite Pro*

 – The subscription-based AutoSite Pro data developed by the Automotive 

Information Center provides a detailed database of vehicle specifications and attributes at 

the individual vehicle model, body style, engine size, and transmission level. (These data 

were supplied to Sierra under the study effort by General Motors.) The AutoSite 

database contained data for over 100 vehicle specifications at this level. These 

specifications included: 

• Weight (curb, towing capacity and GVWR); 

• Engine size, power, torque and number of cylinders; 

• EPA vehicle class (e.g., compact, midsize, large, special purpose, etc.); 

• Valvetrain configuration (OHV, OHC, DOHC) and number of valves; 

• Driveline (front, rear or all wheel drive) ; 

• Transmission type and number of gears; 

• Aspiration method (natural, turbocharged, supercharged) ; 

• Fuel type (gasoline, Diesel or hybrid electric) ; 

• Passenger and cargo volumes; 

• Rear axle ratio; and 

• Dimensions (height, width, length, front and rear track width and wheelbase). 

NHSTA CAFE Sales – The MY2006 “CAFE Sales” database exchanged between 

NHSTA and manufacturers to track existing CAFE compliance was also supplied to 

Sierra by General Motors for use under this study. As noted earlier, the database 

received was the “final” sales version for MY2006. These sales data are stratified by the 

following elements: 

• Manufacturer/make; 

• Model/nameplate; 

• Alternative fuel-certified vehicle (yes or no); 

• EPA vehicle class; 

• Engine size and power; and 

 

*

 Or a similar subscription service accessible by the Alliance members. 

-7- 
• Unadjusted combined CAFE fuel economy.*

Polk Registrations – Detailed new vehicle registration data for all 50 states were also 

acquired from R.L. Polk. Since Polk tracks new registrations, rather than sales, and sales 

of an individual model year spans a period substantially greater than one year, it was 

necessary to obtain monthly Polk registrations over a broader period to capture “full” 

MY2006 sales (as new registrations). Polk registrations for MY2006 vehicles were 

pulled for the period from January 2005 through February 2007† to represent “full” 

model year sales. 

The Polk registration data are disaggregated based on the following attributes: 

• State (of registration); 

• Make; 

• Model; 

• Body style; 

• GVWR class (0=pass. car, 1=≤6000 lb, 2=6,001-10,000 lb, 3=10,001-14,000 lb); 

• Number of cylinders; 

• Fuel type (gasoline, FFV, Diesel , hybrid electric); and 

• Aspiration method (natural or turbocharged). 

As noted by the GVWR attribute, Polk data are provided for passenger cars, light-duty 

trucks (≤6000 lb), and heavy-duty trucks in the 2A (6,001-10,000 lb) and 2B (10,001-

14,000 lb) GVWR classes. Thus the Polk database includes medium-duty passenger 

vehicles in the 8,501-10,000 lb GVWR range that are not included in the current CAFE 

databases. (Medium-duty passenger vehicles are covered under the new legislation, but 

not current CAFE regulations.) 

EPA CAFE Test Results – Model-year-specific CAFE city and highway fuel economy 

test data were downloaded from EPA’s official fuel economy web site.2

 These data are 

available at the vehicle make, model/nameplate, body and drive train type, engine size, 

number of cylinders, fuel type, and transmission level. For flexible-fueled (E85) 

vehicles, separate fuel economy results for both gasoline and the alternative fuel are 

included in the CAFE test results database. (As discussed later, fuel economy results for 

alternative-fuel vehicles in the baseline fleet were based on the gasoline test data, rather 

than either that of the alternative fuel or the CAFE credit-based value.) The EPA fuel 

economy database includes both adjusted and unadjusted City, Highway, and Combined 

(with 55/45 City/Highway weighting) fuel economy. 

EPA Test Car List – The MY2006 Test Car List database compiled by EPA contains 

vehicle specification, fuel economy, and dynamometer setting data from official 

 

*

 Both “actual” and “final” fuel economy values are given. For conventional-fuel vehicles, these values are 

identical. For flexible fuel vehicles (FFVs), actual values refer to fuel economy based on gasoline. Final 

values refer to the way FFV fuel economy is calculated under CAFE. 

†

 February 2007 was the latest month for which complete data were available at the time these data were 

obtained. 

-8- 
certification testing at the vehicle model, engine size, and transmission level. This 

database provided equivalent test weight (ETW) data in the baseline fleet; ETW data 

were not available in any of the other datasets. (Rear axle ratio data in the Test Car List 

database were also used to cross-check those contained in the Autosite Pro database.) 

ATA Database – Aerodynamic wind tunnel test measurements for a number of late model 

vehicles from all major manufacturers were provided by General Motors in a confidential 

database. Measured frontal areas and aerodynamic drag coefficients for nearly 150 

vehicles between model years 2003 and 2008 were available from this database. They 

were used to develop regression-based estimates of frontal area from vehicle width and 

height as described in greater detail later in this sub-section and to fill in drag coefficients 

when these data were not available from automotive Internet sites (which are described 

below). 

Automotive Internet Sites – A series of Internet sites3,4,5,6 that provide free automotive 

content were also used to supply additional vehicle specifications that were not contained 

in any of the other data sources. These sites were exhaustively “mined” by querying 

vehicle model-specific web pages that provided aerodynamic data (drag coefficients and 

frontal area), transmission gear ratios, and body type trucks (i.e., unibody vs. body-onframe). For some models, manufacturer web sites were also searched to obtain complete 

vehicle specification data. 

The manufacturer and third-party web sites were also searched to identify specific 

“advanced” fuel economy technologies that have begun to penetrate the U.S. vehicle fleet 

as explained later in Section 3.3. 

Assembly of Data – The process of assembling the information from each of these 

sources into a comprehensive database representing the MY2006 baseline fleet began 

with the AutoSite data. A master spreadsheet was initially populated with the detailed 

specifications and attributes by vehicle manufacturer, model, body style, engine size, and 

transmission from the AutoSite database. The CAFE Sales, EPA CAFE Test Results, and 

EPA Test Car List data were then imported into separate individual sheets within the 

master spreadsheet. Common fields in each sheet—such as manufacturer/make, model, 

engine size and transmission—were used in conjunction with “lookup” formulas to load 

the data from these sheets into the master “fleet” sheet. Renaming of entries in these 

fields in each file was sometimes necessary to make naming conventions for the common 

fields consistent across each sheet (e.g., model “LACROSSE” vs. “LACROSSE/ 

ALLURE” or transmission “A5” vs. “L5”). In this manner, most of the additional data 

were merged into a single, master fleet sheet. Aerodynamic data, gear ratios, and truck 

body type classifications were manually entered into the master sheet from the ATA 

database and various web sites. The master sheet contained a total of 1,167 individual 

vehicle records (617 car records and 550 truck records). 

Vehicle sales at the individual model, engine, and transmission level were generally 

loaded directly from the CAFE Sales sheet. However, the CAFE Sales database did not 

separate sales of the some model (and engine size/transmission) by body style (e.g. sedan 

-9- 
vs. wagon). In these cases, the Polk data (which included registrations by body style) 

were used to ratio the total sales for a model/engine/transmission combination from the 

CAFE Sales database by body style. 

The next step in assembling the baseline fleet spreadsheet consisted of computing values 

for several attributes based on the values of other data fields. Examples of these 

computations are listed below: 

• Footprint (ft2

) = Wheelbase × (Track front + Track rear) / 2 

• Interior Volume (ft3

) = Passenger Volume + Cargo Volume 

• “Box” Volume (ft3) = Height × Width × Length 

• Power/Weight Ratio (hp/lb) = Power / Curb Weight 

• Rolling Radius (ft) = [WRad + (TWidth × TAspect) / (100 × 25.4)] × 0.96 / 12 

where: WRad is the wheel radius (in inches), TWidth is the tire width (in millimeters), 

and TAspect is the tire aspect ratio. 

For the Interior Volume calculations, both “EPA” and “Manufacturer” values for 

passenger and cargo volumes were available from the AutoSite database although there 

were often missing entries for a number of vehicle models. In addition, where both EPA 

and Manufacturer values of these volumes were available there was often inconsistencies 

between the two (e.g., EPA values were sometimes higher and at other times lower). It 

also appears that passenger and cargo volumes were often combined into one entry for 

selected models. Given these apparent inconsistencies, “best” estimates of Interior 

Volume were made by summing passenger and cargo volumes. (The auto web sites were 

also used to corroborate the passenger and cargo volume values from the AutoSite 

database, where available.) 

Box Volume and Power/Weight Ratio (P/W) were calculated to support classification of 

each vehicle into one of 13 different passenger car or 12 different light truck categories 

discussed in greater detail in the next sub-section. 

Vehicle engines were also classified into either of two distinct categories: 

1. Overhead Valve (OHV) (usually 2 valves per cylinder); or 

2. Overhead Cam (OHC) (usually 4 valves per cylinder)*

 

Vehicle frontal area (required for vehicle simulation modeling) was not available in any 

of the databases except for roughly 150 models between MY2003 and MY2008 from the 

ATA database. Website specifications also rarely included vehicle frontal areas. As a 

result, frontal area was estimated for the remaining models in the fleet based on 

 

*

 In the appendices, “2V” is sometimes used to represent OHV engines and “4V” is sometimes used to 

represent OHC engines. 

-10- 
regressions of vehicle height and width using those 150 models for which actual data 

available. The regression-based frontal area was developed using the following form: 

))(())(( F 10 ++= 2 WCHCCA

where the estimated frontal area AF (in ft2

) is based on a multiple-linear fit of vehicle 

height H (in inches) and width W (in inches) and C0, C1 and C2 are the least-squares fitted 

coefficients. 

Table 3-1 shows the resulting regression and correlation coefficients. To account for the 

effects of fundamental design differences on frontal area, separate regressions were 

developed for each of four vehicle types: (1) cars, (2) minivans, (3) pickups; and 

(4) sport utility vehicles (SUVs). 

Table 3-1 

Frontal Area Regression Statistics

Regression Coefficients 

Vehicle Type C0 C1 C2

Sample Size 

(N) 

Correlation 

(R2) 

Cars -16.28 0.3738 0.2672 78 0.85 

Minivans -29.25 0.5927 0.2620 9 0.95 

Pickups -21.79 0.4720 0.2753 22 0.88 

SUVs -30.14 0.6270 0.2382 36 0.92 

As shown in Table 3-1, frontal area is well correlated to vehicle height and width. Using 

these regressions, frontal area was estimated for the remaining vehicle models in the 

baseline fleet for which actual data were not available. 

One other vehicle parameter needed in the vehicle simulation modeling that was 

generally not available from the aforementioned databases was the rolling friction (or 

rolling resistance) coefficient, Cf. Vehicle model-specific rolling resistance was backcalculated in the baseline fleet using track road load horsepower at 50 mph (TRLHP) data 

that Sierra has compiled in a detailed lookup table for use in setting dynamometers in 

IM240-based Inspection and Maintenance programs. This “I/M Lookup Table” database 

contains TRLHP data by model year, vehicle model, engine size, and transmission. 

Under a steady speed on level terrain and assuming no wind, road load power PROAD is 

given by: 

-11- 
ROAD ( ROLL += AERO ) vFFP

v

vCA gmCP DF

ROAD f )] 2 ()[(

2 ρ = +

where FROLL and FAERO are the rolling resistance and aerodynamic drag forces, 

respectively, Cf is the rolling resistance coefficient, m is the mass (in kg), g is the 

gravitational constant, ρ is the density of air (in kg/m3

), AF is the frontal area (in m2), CD

is the aerodynamic drag coefficient and v is the vehicle speed (in m/s). At a steady speed 

of 50 mph and in British Engineering units we have: 

5502

0765.0 )4667.150(

550

4667.150 3

××

××××

+

××× = gWCf CA TRLHP DF

where W is the vehicle test weight (in lb), the density of air at one U.S. standard 

atmosphere is 0.0765 lb/ft3, the frontal area AF is expressed in ft2 units, and the 

gravitational constant g is 32.174 ft/s2

. 

Consistent with SAE practice, a factor of 1.03 was assumed to represent the effective 

increase in mass due to driveline rotational inertia. In addition, the drive train power loss 

was assumed to be a constant percentage of the rolling resistance power loss and was 

estimated at 16.2% (of the rolling resistance power loss). 

Given these assumptions and vehicle test weight, frontal area, and drag coefficient, the 

equation above was solved for the rolling resistance coefficient (Cf ) of each individual 

vehicle. (Drag coefficients were not available for 99 of the nearly 1,200 vehicles in the 

baseline fleet. In these instances, rolling resistance coefficients could not be backcalculated and were set to missing values.) 

Two other key elements in assembling the baseline fleet consisted of categorizing each 

vehicle using a scheme that improves on EPA’s size class distinctions and accounting for 

penetrations of advanced technologies in the MY2006 fleet. Each of these elements is 

described in the following two sub-sections. 

3.2 Classification of Vehicle Types

The classification scheme used in the federal Fuel Economy Guide fails to distinguish 

between cars and light-duty trucks with fundamentally different characteristics. For 

example, the “small car” category contains high-performance sports sedans, convertibles, 

and “economy” cars. It is therefore necessary to consider the extent to which certain 

technology changes conflict with the maintenance of vehicle characteristics that are 

critical to market success. 

A revised classification scheme was used that divided passenger cars into 13 different 

categories and light trucks into 12 different categories. The overall objective of the 

-12- 
classification scheme was to preserve the size class distinctions used in the Fuel 

Economy Guide published by the federal government, while recognizing some of the 

important distinctions between vehicles that are ignored in the Fuel Economy Guide. 

Passenger Car Categories – Table 3-2 presents the classification scheme used for 

passenger cars. By comparing our classification scheme with vehicle categories used in 

the federal Fuel Economy Guide, an obvious difference is that we distinguish between 

sports cars and other small cars, sports/luxury sedans and other sedans, and 

coupes/convertibles and sedans. 

Table 3-2 

Passenger Car Categories

This Analysis EPA Class Examples 

Mini Cars Mini-Compact Mini Cooper 

Subcompact Sedans/Wagons Subcompact, Small Wagon Volkswagen Beetle 

Compact Sedans/Wagons Compact, Small Wagon Chevrolet Cobalt 

Mid-Size Sedans/Wagons Mid-Size Sedan, Mid-Size 

Wagon Chrysler Sebring 

Large Sedans/Wagons Large Sedan, Large Wagon Ford Crown Victoria

Small Coupes/Convertibles Two-Seater, Mini-Compact Chrysler Crossfire 

Mid-Size Coupes/Convertibles Subcompact, Compact Toyota Camry 

Solara 

Large Coupes/Convertibles Mid-Size or Large Sedan Chevrolet Monte 

Carlo 

Small Sports/Luxury Sedans Subcompact, Compact BMW 330i 

Mid-Size Sports/Luxury Sedans Mid-Size Sedan Cadillac CTS 

Large Sports/Luxury Sedans Large Sedan Mercedes S500 

Sports/GT Cars Two-Seater, Mini-Compact, 

Subcompact 

Mazda MX-5 

(Miata) 

High Performance 

Sports/GT Cars 

Two-Seater, Mini-Compact, 

Subcompact Chevrolet Corvette 

In contrast, the federal scheme categorizes vehicles based primarily on the number of 

seats and the interior volume. This leads to the following vehicles being put in the same 

category: 

• Mercedes SL55 AMG and Honda Insight are both considered “two-seaters”; 

-13- 
• Ford Mustang and Chevy Cobalt are both considered “subcompacts”; 

• Mini Cooper and Porsche 911 Carrera are both considered “mini-compacts”; and 

• BMW 330i and Ford Focus are both considered “compacts.” 

Obviously, these vehicle groupings are inconsistent with the market segment in which 

they actually compete. This leads to absurd conclusions about the fuel economy 

improvement that could be achieved if all vehicles had fuel economy ratings equivalent 

to what could be achieved by a “typical” vehicle using an optimum combination of 

technologies. Assuming that a high-performance sports car could remain commercially 

viable when redesigned to achieve the same fuel economy as a low-performance 

economy car is unreasonable. 

As described below, the definitions of the passenger car categories we have used to 

represent the fleet were created to account for characteristics that could significantly 

affect fuel economy, including power-to-weight ratio and styling features. 

Mini-Cars are passenger cars not covered by another class definition that have an interior 

volume the same as those in the EPA “mini-compact” category. Although numerous car 

models are classified as mini-compacts by EPA, our classification scheme moves most of 

these models into other categories (e.g., sports/GT, small coupes/convertibles). Under 

our classification scheme, mini-cars are sedan-type vehicles smaller than subcompacts, 

such as the Mini Cooper, and two-passenger vehicles, like the Honda Insight, that do not 

meet our definition of “sports car” (see below). 

Subcompact Sedans/Wagons - Sedans are passenger cars that provide similar 

accommodations in front and rear seats and that have a cargo compartment of lower 

average height than the greenhouse (the area surrounded by windows). Station wagons 

are sedans with a greenhouse extended to the rear of the vehicle to facilitate larger cargo 

volume or a third row of seating. Subcompact Sedans/Wagons are sedans, other than 

sports/luxury sedans, that have interior volumes the same as those in the EPA “subcompact” category and station wagon derivatives of such vehicles. 

Compact Sedans/Wagons are sedans, other than sports/luxury sedans, that have interior 

volumes the same as those in the EPA “compact” category and station wagon derivatives 

of such vehicles. 

Mid-Size Sedans/Wagons are sedans, other than sports/luxury sedans, that have interior 

volumes the same as those in the EPA “mid-size” category and station wagons that have 

interior volumes the same as those in the EPA “mid-size” category. 

Large Sedans/Wagons are sedans, other than sports/luxury sedans, that have interior 

volumes the same as those in the EPA “large” category and station wagons that have 

interior volumes the same as those in the EPA “large” category. 

-14- 
Small Coupes/Convertibles - Coupes are two-door, fixed roof or “T-top” configuration 

passenger cars, other than sports cars or sports/GT cars, with two- or “2+2” passenger 

seating or otherwise more limited rear seating and cargo space than typical of sedans with 

equivalent overall passenger compartment volume. Convertibles are passenger cars, 

other than sports cars or sports/GT cars, with fold-away or completely stowable tops. 

Small Coupes/Convertibles are coupes and convertibles with interior volumes the same 

as those in the EPA “mini-compact” category. 

Mid-Size Coupes/Convertibles are coupes and convertibles with interior volumes the 

same as those in the EPA “sub-compact” and “compact” categories. 

Large Coupes/Convertibles are coupes and convertibles with interior volumes the same 

as those in the EPA “mid-size” and “large” categories. 

Small Sports/Luxury Sedans/Wagons - Sports sedans/wagons are sedans and wagons 

with relatively high power-to-weight ratios (no more than 16 pounds curb weight per 

horsepower) and that are usually designed for cornering and braking performance 

superior to that typical of conventional sedans. Sports sedans/wagons may also 

incorporate luxury features. Luxury sedans/wagons are sedans and wagons, other than 

sports sedans and wagons, that incorporate numerous luxury features (such as powerassisted seats, steering, windows, and door locks; standard leather upholstery; automated 

climate control; and numerous decorative items [e.g., metallic paint, wood-trimmed 

interiors, aluminum wheels, etc.]) as standard equipment and that have no more than 19 

pounds curb weight per horsepower. Luxury sedans/wagons usually incorporate 

suspension systems designed to maximize ride quality when driven sedately. Small 

Sports/Luxury Sedans/Wagons are sports sedans/luxury sedans with interior volumes the 

same as those in the EPA “sub-compact” and “compact” categories. 

Mid-Size Sports/Luxury Sedans/Wagons are sports sedans/luxury sedans with interior 

volumes the same as those in the EPA “mid-size” category. 

Large Sports/Luxury Sedans/Wagons are sports sedans/luxury sedans with interior 

volumes the same as those in the EPA “large” category. 

Sports/GT Cars are small, two- or “2+2” passenger coupes and convertibles designed for 

cornering and braking performance superior to that typical of conventional sedans and 

that have more than 13 pounds curb weight per horsepower. Interior volumes for these 

vehicles are generally in the EPA size class for two-seaters, mini-compacts, or 

subcompacts. 

High Performance Sports/GT Cars are sports/GT cars with no more than 13 pounds curb 

weight per horsepower. 

Light-Truck Categories – The biggest problem with the EPA classification scheme for 

trucks was the total lack of distinction between different size SUVs. To account for the 

significant differences that exist, we classify SUVs as small, medium, or larger based on 

-15- 
the product of their length, width, and height. In contrast, we eliminate the distinction 

between passenger and cargo vans within the EPA classification scheme and we 

eliminate the distinction between 2-wheel drive and 4-wheel drive minivans. We classify 

all vans as either small or large based on the product of length, width, and height because 

there are relatively few 4-wheel drive vans and relatively few differences between small 

passenger and cargo vans and minivans. EPA classifies pickup trucks as small or 

standard based on their gross vehicle weight. We classify pickup trucks as small or larger 

based on the product of their length, width, and height. Table 3-3 compares the truck 

category definitions used in this analysis to the EPA categories; descriptions of each 

category follow. 

Table 3-3 

Light-Truck Categories

This Analysis EPA Class Examples 

Small Van Passenger Van, Cargo Van, 

Minivan 2WD, Minivan 4WD Dodge Caravan 

Large Van Passenger Van, Cargo Van Chevrolet Express 

Small Pickup 2WD Small Pickup 2WD Mazda B3000 

Small Pickup 4WD Small Pickup 4WD Ford Ranger (Regular Cab)

Large Pickup 2WD Standard Pickup 2WD Ford F150 

Large Pickup 4WD Standard Pickup 4WD Dodge Ram 1500 

Small SUV 2WD SUV 2WD Chevrolet HHR 

Small SUV 4WD SUV 4WD Jeep Wrangler SE 

Mid-Size SUV 2WD SUV 2WD Nissan Pathfinder 

Mid-Size SUV 4WD SUV 4WD Toyota 4-Runner 

Large SUV 2WD SUV 2WD Ford Expedition 

Large SUV 4WD SUV 4WD Chevrolet Suburban 

Small 2WD Pickup Trucks are 2-wheel-drive light-duty trucks with an uncovered cargo 

bed and for which the product of length, height, and width is ≤550 cubic feet. 

Small 4WD Pickup Trucks are 4-wheel-drive light-duty trucks with an uncovered cargo 

bed and for which the product of length, height, and width is ≤550 cubic feet. 

-16- 
Large 2WD Pickup Trucks are 2-wheel-drive light-duty trucks with an uncovered cargo 

bed and for which the product of length, height, and width is >550 cubic feet. 

Large 4WD Pickup Trucks are 4-wheel-drive light-duty trucks with an uncovered cargo 

bed and for which the product of length, height, and width is >550 cubic feet. 

Small Vans are light-duty trucks with a fully enclosed passenger and cargo space that are 

designed to maximize interior volume per unit of length through the use of relatively tall 

roofs and engines installed transversely or recessed into the passenger/cargo compartment 

and for which the product of length, height, and width is ≤680 cubic feet. 

Large Vans are light-duty trucks with a fully enclosed passenger and cargo space that are 

designed to maximize interior volume per unit of length through the use of relatively tall 

roofs and engines installed transversely or recessed into the passenger/cargo compartment 

and for which the product of length, height, and width is >680 cubic feet. 

Small 2WD Sport/Utility Vehicles are light-duty trucks, other than pickup trucks and 

vans, incorporating relatively high ground clearance and 2-wheel drive, and for which the 

product of length, height, and width is ≤450 cubic feet. 

Small 4WD Sport/Utility Vehicles are light-duty trucks, other than pickup trucks and 

vans, incorporating relatively high ground clearance and 4-wheel drive, and for which the 

product of length, height, and width is ≤450 cubic feet. 

Mid-Size 2WD Sport/Utility Vehicles are light-duty trucks, other than pickup trucks and 

vans, incorporating relatively high ground clearance and 2-wheel drive, and for which the 

product of length, height, and width is >450 cubic feet and ≤600 cubic feet. 

Mid-Size 4WD Sport/Utility Vehicles are light-duty trucks, other than pickup trucks and 

vans, incorporating relatively high ground clearance and 4-wheel drive, and for which the 

product of length, height, and width is >450 cubic feet and ≤600 cubic feet. 

Large 2WD Sport/Utility Vehicles are light-duty trucks, other than pickup trucks and 

vans, incorporating relatively high ground clearance and 2-wheel drive, and for which the 

product of length, height, and width is >600 cubic feet. 

Large 4WD Sport/Utility Vehicles are light-duty trucks, other than pickup trucks and 

vans, incorporating relatively high ground clearance and 4-wheel drive, and for which the 

product of length, height, and width is >600 cubic feet. 

3.3 Determination of Advanced Technology Penetrations

During the update of the baseline fleet, several technologies affecting fuel economy that 

had minimal penetration in 2003 (and were treated as non-baseline compliance 

-17- 
technologies) had to be specifically accounted for because they have achieved significant 

volume. These technologies included the following: 

• Variable valve lift or variable valve lift and timing (VVLT); 

• Hybrid electric vehicles (HYB); 

• Cylinder deactivation (DEAC); and 

• Automated manual and continuously-variable transmissions (AMT/CVT). 

(As discussed later, technology benefits of AMTs and CVTs were roughly similar. Thus, 

their penetrations were combined and treated together.) 

Even in cases where penetration of these technologies across the U.S. market is relatively 

modest, there is significant penetration for one or more individual manufacturers. To 

ensure an accurate estimate for the design changes needed by each manufacturer to 

comply with new reformed CAFE standards, it was necessary to properly account for 

advanced technology fractions in the baseline fleet. By exhaustively querying 

manufacturer and third-party automotive web sites, the presence oR absence of each of 

these four advanced technologies in the MY2006 fleet at the individual vehicle model 

level was determined. In the master baseline fleet spreadsheet, a column for each 

technology was established and values of either “0” (not present) or “1” (technology 

present) were entered for each of the nearly 1,200 vehicle models in the baseline fleet. 

Table 3-4 presents a tabulation of the sales-based technology penetrations by vehicle 

category across all manufacturers. Subtotals are also shown for all passenger cars, all 

vans, all pickups, all SUVs, and all light-duty trucks. As highlighted at the bottom of 

Table 3-4, the MY2006 baseline fleet contains roughly 3% cylinder deactivation, 13% 

variable valve lift and timing, 5% AMT or CVT, and almost 2% hybrids across all 

manufacturers on a sales basis. 

-18- 
Table 3-4 

Baseline Fleet Advanced Technology Penetrations (%) by 

Vehicle Category for All Manufacturers

Sales-Based Advanced Tech. Percentages 

Subfleet 

Cylinder 

Vehicle Category Code Deac. VVLT 

AMT/ 

CVT HYB 

Cars Mini Cars MINI 0.00% 100.00% 24.56% 2.04%

Cars Subcompact Sedans/Wagons SCSW 0.00% 18.66% 0.00% 0.00%

Cars Compact Sedans/Wagons CSW 0.00% 7.03% 19.38% 6.36%

Cars Mid-size Sedans/Wagons MSW 0.00% 14.01% 0.29% 0.00%

Cars Large Sedans/Wagons LSW 2.19% 0.00% 4.91% 0.00%

Cars Small Coupes/Convertibles SCC 0.00% 40.92% 12.84% 0.00%

Cars Mid-size Coupes/Convertibles MCC 0.00% 13.50% 0.00% 0.00%

Cars Large Coupes/Convertibles LCC 21.87% 0.00% 0.00% 0.00%

Cars Small Sports/Luxury Sedan/Wagon SSL 0.00% 45.29% 0.78% 0.00%

Cars Mid-size Sports/Luxury Sedan/Wagon MSL 1.80% 23.58% 1.28% 0.73%

Cars Large Sports/Luxury Sedan/Wagon LSL 12.43% 6.42% 0.68% 0.00%

Cars Sports/GT Cars SC 0.00% 15.41% 1.30% 0.00%

Cars Hi-Performance Sports/GT Cars HPSC 0.00% 22.09% 2.52% 0.00%

Cars All Passenger Cars All PCs 1.27% 13.83% 6.17% 1.71%

Vans Small Vans SVAN 12.79% 17.56% 0.00% 0.00%

Vans Large Vans LVAN 0.00% 0.00% 0.00% 0.00%

Vans All Vans All Vans 11.79% 16.19% 0.00% 0.00%

PUs Small 2WD Pickups S2P 0.00% 0.00% 0.00% 0.00%

PUs Small 4WD Pickups S4P 0.00% 0.00% 0.00% 0.00%

PUs Large 2WD Pickups L2P 3.31% 0.79% 0.00% 0.09%

PUs Large 4WD Pickups L4P 5.56% 9.26% 0.00% 0.19%

PUs All Pickup Trucks All PUs 4.04% 4.61% 0.00% 0.13%

SUVs Small 2WD SUVs S2SU 0.00% 0.00% 0.00% 0.00%

SUVs Small 4WD SUVs S4SU 0.00% 46.43% 0.00% 0.00%

SUVs Mid-Size 2WD SUVs M2SU 1.67% 9.48% 9.86% 2.49%

SUVs Mid-Size 4WD SUVs M4SU 3.12% 23.74% 6.79% 3.92%

SUVs Large 2WD SUVs L2SU 4.43% 0.00% 0.00% 0.00%

SUVs Large 4WD SUVs L4SU 4.11% 0.50% 0.00% 0.00%

SUVs All Sport Utility Vehicles All SUVs 2.71% 14.10% 5.56% 2.35%

LDTs All Light-Duty Trucks All LDTs 4.50% 11.76% 3.13% 1.36%

All Light-Duty Vehicles All LDVs 2.93% 12.77% 4.61% 1.53%

3.4 Baseline Fleet Tabulations

Once the MY2006 baseline fleet spreadsheet database was assembled, a series of detailed 

vehicle characteristics were tabulated for use in the vehicle simulation modeling and 

-19- 
compliance analysis elements of the effort. These tabulations were prepared for the 

entire U.S. light-duty (and medium-duty passenger) vehicle fleet. 

Parent manufacturer groupings defined under the existing CAFE program were assumed 

to apply under new CAFE rules. For example, the Ford group consists of Aston Martin, 

Ford, Jaguar, Land Rover, Lincoln, Mazda, Mercury, and Volvo. Manufacturer 

groupings were also applied at the nameplate level, consistent with current practice (e.g. 

the Mitsubishi Raider pickup built for Chrysler was included in Chrysler’s fleet). 

Mean values for each vehicle characteristic were sales-weighted, based on the 

disaggregated fleet data assembled at the vehicle model, body style, engine size, and 

transmission level. (All fuel economy-related metrics were properly harmonically 

weighted.) 

Table 3-5 contains a summary of sales-weighted average characteristics of the MY2006 

U.S. light-duty*

 vehicle baseline fleet by vehicle category obtained from the abovedescribed approach. As shown, “unadjusted” combined City/Highway passenger car and 

light truck fuel economy is 29.38 mpg and 22.04 mpg, respectively. 

The sales-weighted fuel economy estimates for the passenger car and light truck fleets 

shown in Table 3-5 match the values published by EPA7 in its “Fuel Economy Trends” 

report for MY2006 to within 0.2 mpg for cars and 0.1 mpg for trucks. This difference is 

likely explained by the fact that the Chrysler passenger car data in our baseline fleet were 

based on MY2007 rather than MY2006 sales data. (As noted earlier, MY2007 sales were 

used instead of MY2006 to address a sales anomaly in Chrysler’s MY2006 passenger car 

fleet.) It is also unclear whether the unadjusted (i.e., laboratory) fuel economy values 

published by EPA include credits for alternative fuel vehicles that NHTSA applies when 

calculating official CAFE results. (As stated earlier, our baseline fleet fuel economy 

excludes the alternative fuel adjustment applied under CAFE.) 

More detailed tabulations similar to that presented in Table 3-5 were also prepared for the 

entire U.S. fleet and individually for each of the following 11 parent manufacturers for 

which the new CAFE compliance analysis was conducted: 

1. BMW (BMW, Mini, Rolls-Royce); 

2. Chrysler (Chrysler, Dodge, Jeep); 

3. Daimler (Maybach, Mercedes-Benz); 

4. Ford (Aston Martin, Ford, Jaguar, Land Rover, Lincoln, Mazda, Mercury, Volvo); 

5. GM (Buick, Cadillac, Chevrolet, GMC, Hummer, Isuzu, Pontiac, Saab, Saturn); 

6. Honda (Acura, Honda); 

7. Hyundai (Hyundai, Kia); 

8. Nissan (Infiniti, Nissan); 

9. Porsche; 

10. Toyota (Lexus, Scion, Toyota); and 

11. Volkswagen (Audi, Bentley, Bugatti, Lamborghini, Volkswagen). 

 

*

 Medium-duty passenger vehicles were also included. 

-20- 
Table 3-5 

Characteristics of the MY2006 U.S. Light-Dutya

 Vehicle Fleet

Passenger Cars 

Unadj. Fuel Econ. (mpg)

No. Name 

Test 

Vehs. 

 %Car 

Sales 

%LDV

Sales City Hwy Wtd 

Curb

Wt (lb)

Power

(hp) 

Disp 

(cid) %2V 

%Auto

Trans 

1 MINI 6 0.55% 0.27% 28.45 43.21 33.62 2,612 142.6 96.8 0.00% 21.10%

2 SCSW 38 8.77% 4.27% 28.46 42.14 33.33 2,856 138.4 123.5 0.95% 73.87%

3 CSW 137 25.87% 12.59% 29.36 42.88 34.21 2,901 144.4 126.7 12.14% 67.75%

4 MSW 76 26.58% 12.94% 24.71 39.17 29.63 3,226 177.9 164.4 20.81% 95.80%

5 LSW 21 11.70% 5.69% 22.54 37.56 27.48 3,615 221.5 214.4 50.44% 94.90%

6 SCC 34 0.94% 0.46% 22.75 36.35 27.35 3,363 194.6 158.5 0.00% 43.66%

7 MCC 33 2.37% 1.15% 22.53 36.21 27.15 3,374 204.8 189.1 21.10% 87.51%

8 LCC 3 0.53% 0.26% 22.54 37.69 27.52 3,370 240.6 245.3 100.00% 100.00%

9 SSL 72 5.52% 2.69% 21.70 34.75 26.11 3,494 253.0 196.7 7.37% 83.25%

10 MSL 70 8.05% 3.92% 21.30 35.12 25.88 3,632 254.7 202.1 3.88% 95.93%

11 LSL 36 6.05% 2.95% 19.47 32.05 23.64 4,019 285.2 262.1 23.43% 99.32%

12 SC 22 0.99% 0.48% 22.16 35.31 26.62 2,991 214.6 172.7 0.00% 45.29%

13 HPSC 69 2.09% 1.02% 19.55 31.91 23.68 3,331 331.3 268.4 20.84% 55.90%

All Cars 617 100% 48.68% 24.58 38.62 29.39 3,253 192.2 170.5 18.26% 83.64%

Light Trucks

Unadj. Fuel Econ. (mpg)

No. Name 

Test 

Vehs. 

%Truck 

Sales 

%LDV

Sales City Hwy Wtd 

Curb

Wt (lb)

Power

(hp) 

Disp 

(cid) %2V 

%Auto

Trans 

1 SVAN 37 14.43% 7.41% 20.39 32.79 24.57 4,216 210.6 213.1 54.79% 100.00%

2 LVAN 23 1.22% 0.63% 16.52 24.08 19.24 5,156 260.4 311.5 98.30% 100.00%

3 S2P 37 2.56% 1.32% 21.29 31.95 25.05 3,434 174.5 177.2 16.98% 76.46%

4 S4P 10 0.04% 0.02% 18.83 27.14 21.84 3,568 177.2 190.2 51.06% 78.02%

5 L2P 85 12.55% 6.44% 17.18 25.53 20.14 4,680 259.2 286.6 57.81% 88.55%

6 L4P 84 12.93% 6.64% 16.58 24.38 19.37 4,901 270.9 293.6 52.86% 96.05%

7 S2SU 8 3.24% 1.66% 24.71 36.64 28.95 3,163 155.9 144.2 0.00% 94.71%

8 S4SU 7 1.56% 0.80% 19.36 27.96 22.47 3,427 184.5 196.1 48.93% 68.17%

9 M2SU 75 15.06% 7.73% 21.03 31.51 24.73 3,829 211.8 198.8 19.28% 87.89%

10 M4SU 112 24.18% 12.41% 19.39 28.86 22.75 4,188 230.5 213.1 22.47% 91.12%

11 L2SU 30 4.22% 2.17% 16.53 25.63 19.68 4,863 267.9 282.4 45.96% 100.00%

12 L4SU 42 8.00% 4.10% 15.99 23.96 18.83 5,137 272.1 285.3 46.04% 99.52%

All Trucks 550 100% 51.32% 18.71 28.14 22.04 4,343 234.3 237.0 38.38% 92.76%

All Light-Duty Vehicles 

Test Unadj. Fuel Econ. (mpg)

Vehs. Wtd 

Curb

Wt (lb)

Power

(hp) 

Disp 

City Hwy (cid) %2V 

%Auto

Trans 

All LDVs 1,267 21.17 32.43 25.09 3,812 213.8 204.6 28.58% 88.32%

a Also includes medium-duty passenger vehicles.

These detailed baseline fleet tabulations by individual manufacturer are contained in 

Appendix A. 

### 

-21- 
4. DETERMINATION OF NEW STANDARDS 

After updating the baseline fleet database to reflect model year 2006 data (and accounting 

for advanced technology penetrations within the baseline), the next major task in the 

analysis consisted of calculating manufacturer-specific fuel economy targets in MY2020 

based on assumptions regarding how the discretion provided under EISA might be used 

by the Secretary of Transportation. 

4.1 Key Assumptions

EISA contains several open-ended provisions and leaves unspecified a number of 

implementation issues to be determined by the Secretary of Transportation. In the 

absence of a proposed rulemaking by NHTSA, it was necessary to make several specific 

assumptions regarding how the provisions of the legislation will be implemented. These 

assumptions reflect our best estimate of reasonable implementation requirements and are 

listed and described below. 

• Combined 35 mpg Fleet Fuel Economy – EISA requires the Transportation 

Secretary to set a minimum fleet-wide fuel economy standard for cars and trucks 

combined of 35 mpg by model year 2020. Although the Secretary has authority 

to set a higher standard under EISA, it has been assumed that the combined 

standard will be 35 mpg in 2020. 

• Constant Baseline – Independent of EISA, market forces may result in higher fuel 

economy in the future, especially if fuel prices remain at current (April 2008) 

levels. Forecasting the design changes resulting from such market forces was 

beyond the scope of our analysis. We have therefore estimated the necessary 

design changes and associated costs incremental to our 2006 baseline with the 

exception that increased use of ultralight steel was assumed to offset any increase 

in vehicle weight that might be associated with the production of larger vehicles 

meeting more stringent safety standards. In other words, the projected baseline

for model year 2020 in the absence of any new CAFE regulations*

 was essentially 

assumed to be represented by the MY2006 baseline fleet developed as described 

 

*

 In November 2007, the U.S. Ninth Circuit Court of Appeals remanded the MY2008-2011 light truck rule 

back to NHTSA for reconsideration. Thus at the time of this analysis, no attempt was made to project 

further regulatory-triggered fleet fuel economy changes beyond MY2007. (Baseline fleet light truck fuel 

economy of 22.04 mpg is roughly identical to the MY2007 CAFE standard of 22.2 mpg when alternative 

fuel vehicle fuel economy is adjusted as defined under CAFE.) 

-22- 
earlier in the report. Vehicle attributes and sales mixes were also assumed to 

remain constant. (Under earlier GHG regulatory impact analysis1

 sponsored by 

the Alliance, Sierra had projected historical increases in vehicle weight, 

power/weight ratio and use of dual overhead cam [DOHC] engines to continue 

between MY2003 and MY2009. These trends were projected to match 

assumptions made by the California Air Resources Board [CARB] in its analysis 

of California’s GHG vehicle emission standards. For this analysis of federal 

CAFE standards, there was no need to match CARB GHG assumptions.)

• Equal Improvement for Cars and Trucks – EISA requires that separate standards 

be set for cars and for light-duty trucks in a manner that produces a light-duty 

fleet-wide composite fuel economy of 35 mpg in 2020. There are an infinite 

number of combinations of car and light truck standards that, when salesweighted together, yield 35 mpg. The legislation leaves the decision on setting 

the specific car and truck standards that equate to 35 mpg fleet-wide to the 

Secretary of Transportation. In the absence of draft rulemaking from NHTSA, it 

was assumed that these separate standards would be set by requiring the same 

percentage increase in car and truck fuel economy between the 2006 baseline and 

2020. (As shown later in this section, this increase was calculated to be just 

below 40%.) 

• Reformed Standards Patterned After Earlier Light Truck Standards – In its March 

2006 rulemaking, NHTSA introduced the concept of “Reformed” CAFE 

standards in setting fuel economy requirements for MY2008-2011 light trucks. 

Under Reformed CAFE, fuel economy standards were determined on the basis of 

a measure of individual vehicle size called “footprint,” defined as the product of 

wheelbase and average track width. (By contrast, earlier unreformed CAFE was 

simply a single fuel economy standard applied to all manufacturers.) Reformed 

standards were developed under this effort using a conceptually similar approach 

to that employed by NHSTA in the MY2008-2011 light truck rule. Namely, 

footprint-based standards were developed using a mathematically consistent 

approach to that described in the MY2008-2011 light truck rule. 

Given these specific assumptions, footprint-based models (one for cars and one for 

trucks) were developed using the 2006 baseline fleet database. These models were then 

used to calculate manufacturer-specific fuel economy targets for cars and light trucks in 

2020. Each of these steps is described in the following sub-sections. 

4.2 Development of Footprint-Based Reformed Standard Models

The first step in determining EISA-based fuel economy targets consisted of generating 

footprint-based models for cars and trucks. The approach used was consistent with that 

employed by NHTSA in setting reformed standards for MY2008-2011 light-duty trucks. 

-23- 
Under that rulemaking, NHTSA selected vehicle footprint (the product of wheelbase and 

average track width) as the attribute the agency felt should be used to define vehicle-tovehicle differences in fuel economy standards. Although NHTSA considered several 

other attributes such as weight and power/weight ratio, these were rejected due to safety 

and political concerns. 

The MY2006 baseline fleet database contains a detailed series of vehicle specification 

data (including sales and official fuel economy results) for nearly 1,200 individual 

vehicle “configurations” (i.e., combinations of vehicle model, body style, engine, and 

transmission). Since EISA requires establishment of separate car and light truck 

standards, the first step in development of footprint-based models consisted of dividing 

the baseline fleet into two separate datasets: 

1. Passenger cars; and 

2. Light-duty trucks (and medium-duty passenger vehicles). 

Separate models were then developed for each of the two sub-fleets. This process 

consisted of importing the car and light truck sub-fleet datasets (initially in spreadsheet 

form) into SAS® datasets. (Statistical Analysis Software, developed by the SAS Institute, 

Inc. is a multi-platform software package that contains an exhaustive library of preprogrammed statistical analysis and data tabulation procedures.) A set of SAS programs 

(Make_AttModels_*.sas) were then written and executed to develop least-squares curve 

fits of footprint against fuel consumption on an individual vehicle basis. (In its earlier 

light truck rulemaking, NHTSA developed attribute models on the basis of fuel 

consumption instead of fuel economy. This was done to more simply translate the results 

to estimates of fuel savings.) The SAS “NLIN” library procedure was used to develop 

the best fitted car and truck models. 

Functional Forms – The basic mathematical form used for each individual model was the 

power curve shown below: 

)( 2

10

C

i ×+= AttCCFC i

where FCi is the fuel consumption (in gallons/100 miles) of vehicle i, Atti is the value of a 

given attribute (e.g., footprint) for vehicle i and C0, C1, and C2 are least squares-fitted 

coefficients for that attribute model (and sub-fleet). 

A general power curve of this form was chosen as an efficient way to evaluate both linear 

and non-linear relationships between each attribute and fuel consumption; if a linear 

relationship does exist, the best-fitted version of this model will produce a zero or nearzero value for the “exponent” coefficient C2. A constrained logistic function was also 

evaluated for footprint-based car and truck models in order to replicate the exact form 

used earlier by NHTSA for light trucks. This constrained logistic equation is listed 

below: 

-24- 
] 1 ) 11 ( 1 [ )/((

)/((

121

0 43

43

CCFP

CCFP

i

e

e

CCC

CFC i

−

−

+

×−++=

where e is the exponential function, FPi is the footprint for vehicle i and C0 through C4

are the fitted coefficients. 

This constrained version of the logistic function flattens out at both ends of the range of 

vehicle footprint (coefficients C3 and C4 establish the portion of the footprint spectrum 

where the curve flattens) and was specifically chosen by NHTSA to provide a 

disincentive to designing vehicles with very small or large footprints. 

Vehicle Weighting – In addition to the functional forms, another key issue in attribute 

modeling involved whether to weight the individual vehicle data points in determining 

the best fit models. In the earlier light-truck reformed standards rule, it appears that 

NHTSA chose to develop its attribute model fits by sales-weighting each individual data 

point. 

Under this effort, an intentional decision was made not to weight the individual vehicle 

data points. This choice was made because fitted attribute models based on sales 

weighting are much more dependent on the sales mix in existence at the time the models 

are developed. Any real underlying relationship between fuel consumption and a given 

attribute is less evident when individual vehicle data points are weighted based on current 

sales, or even projected product plans and sales (which are still highly uncertain, 

especially under volatile economic and energy market conditions). 

Thus, all least-squares model fits were developed under this effort on an un-weighted 

basis. It is believed that these un-weighted models provide more robust representations 

of how each attribute (or attribute combinations) explains vehicle-to-vehicle variations in 

fuel consumption (or economy), irrespective of the current sales market. (As described 

later in Section 4.4, sales-weighting is used to calculate each manufacturer’s fuel 

economy targets under a reformed standard.) 

Attributes Evaluated – Table 4-1 lists the attribute models that were evaluated separately 

for cars and light trucks. The attributes (i.e., the independent variables) in each model are 

listed in the leftmost column. The next column identifies whether the model was fitted 

using a zero intercept, i.e., with C0 set equal to zero. (Some models were tested both 

ways, with or without setting the intercept coefficient to zero, to assess the importance of 

allowing the best fitted curve to intersect the y-axis at a point other than the origin.) The 

third column lists the unique identifying name given to each model. (Zero-intercept 

attribute model variations include a “z” in the identifying name.) The rightmost column 

indicates the functional form of each evaluated model. 

-25- 
Table 4-1 

Vehicle Attribute Models Evaluated 

Zero Intercept 

(C0) Model Name 

Functional 

Attribute(s) Form 

Footprint No FP-L Logistic 

Footprint Yes FPz-L Logistic 

Footprint No FP-P Power 

4.3 Comparison of Attribute Models

Passenger Car Models - Table 4-2 lists the best-fit coefficients determined for each model 

and presents sum-of-squared error (SSE) and correlation (R2

) results for each passenger 

car attribute model for comparison. 

Table 4-2 

Passenger Car Attribute Models and Comparison Statistics 

Least-Squared Fitted Coefficients 

Model Name C0 C1 C2 C3 C4 SSE R2

FP-L -0.1233 0.3000 0.1862 48.0495 3.80975 359.8 0.213

FPz-L 0.3115 0.1906 48.0495 3.80975 359.8 0.213

FP-P -0.9770 0.1709 0.8800 365.0 0.202

Figure 4-1 presents the scatter plot of footprint against actual passenger car fuel 

consumption. Each point in Figure 4-1 represents an individual vehicle (i.e., the 

combination of make, model, body style, engine size, and transmission) in the baseline 

fleet. As the figure indicates, the correlation between footprint and fuel consumption is 

poor. An example of this problem is illustrated by the dashed vertical line, arbitrarily 

drawn at the 44 ft2

 point on the footprint axis. As noted in Figure 4-1, a 1.8L 5-speed 

manual Honda Civic has the same footprint as a 4.2L 6-speed automated manual Maserati 

GT/Gransport. Under a footprint-based reformed standard, both would have to meet the 

same fuel economy level, even though the lower-powered Civic has over twice the fuel 

economy of the GT/Gransport (39.0 mpg vs. 17.1 mpg CAFE). 

As illustrated by the above example, if reformed standards are based on an underlying 

attribute model that is as poorly correlated with fuel economy as is footprint for 

passenger cars, the following effects can be expected: 

-26- 
1. Conflicts will arise between market-based customer preferences and attribute 

model-induced design strategies necessary to comply with fuel economy 

standards; and 

2. Reformed standards for model year 2020 calculated from an attribute model 

developed either from current baseline data or projected product plans and sales 

forecasts will result in large variations in manufacturer-specific fuel economy 

targets if the model is ill-fitted to the fleet. 

Model Year 2006 Passenger Car Fuel Consumption vs. Footprint

R2 = 0.215

0

1

2

3

4

5

6

7

8

9

10

0 10 20 30 40 50 60 70

Footprint (ft2)

Fuel Consumption (gal / 100 miles)

80

Honda Civic 1.8L, M5

Maserati GT/Gransport 4.2L, MTA6

Light-Duty Truck Models – Table 4-3 below presents a comparison of curve fits for the 

same attribute model forms applied to the baseline light-duty truck fleet. 

Table 4-3 

Light-Duty Truck Attribute Models and Comparison Statistics 

Least-Squared Fitted Coefficients 

Model Name C0 C1 C2 C3 C4 SSE R2

FP-L 0.23629 0.31942 0.2 46.9463 4.67459 175.6 0.382

FPz-L 0.297 0.19097 46.9466 4.67452 175.6 0.382

FP-P -17.62 15.03 0.09 879.9 0.355

Figure 4-1 

Passenger Car Fuel Consumption vs. Footprint 

-27- 
A similar scatter plot of actual fuel consumption against footprint is shown for the lightduty truck baseline fleet in Figure 4-2. By comparing Figure 4-2 with Figure 4-1 it is 

apparent that fuel consumption is better correlated with footprint for light-duty trucks. 

Model Year 2006 Light-Duty Truck Fuel Consumption vs. Footprint

R2 = 0.362

0

1

2

3

4

5

6

7

8

9

10

0 10 20 30 40 50 60 70

Footprint (ft2)

Fuel Consumption (gal / 100 miles)

Figure 4-2 

Light-Duty Truck Fuel Consumption vs. Footprint 

80

4.4 Calculation of Fuel Economy Targets

The final step of this study element consisted of applying each of the selected attribute 

model equations to each manufacturer’s baseline passenger car and light truck fleet data 

to calculate the expected fuel economy targets they will need to meet in 2020 under the 

assumed implementation provisions of EISA. Since EISA requires a minimum 35 mpg 

fleet-wide composite standard for passenger cars and light-duty trucks (as well as 

medium-duty passenger vehicles), these calculations were performed in a manner in 

which the separate fuel economy targets for each manufacturer (and sub-fleet) yielded 

this composite standard when combined on a sales-weighted basis. 

As reported earlier in Table 3-5, the MY2006 baseline light-duty vehicle fleet fuel 

economy was 25.09 mpg. Since the standard in 2020 is 35 mpg fleet-wide, this translates 

to a relative improvement of 39.49% [(35/25.09)-1] over the baseline. As stated earlier in 

Section 4.1, this same relative improvement was assumed in translating the fleet-wide 

standard to implicit targets for the passenger car and light-duty truck sub-fleets. 

-28- 
Also from Table 3-5, the baseline fuel economy for passenger cars and light-duty trucks 

able 4-4 lists the baseline passenger car, light truck, and light-duty vehicle fleet fuel 

 4-4 

ill 

Table 4-4 

Baseline Fleet Fuel Economy and Sales Fractions by Manufacturer

is 29.39 mpg and 22.04 mpg, respectively. The same 39.49% improvement was then 

applied to each sub-fleet to yield 2020 targets of 40.99 mpg for passenger cars and 

30.74 mpg for light trucks. 

T

economy and sales fractions by manufacturer that were tabulated from the MY2006 

database described in Section 3. (Note that the specific manufacturers listed in Table

represent over 99.9% of all U.S. light-duty vehicles sold in MY2006. To keep the table 

simpler, only these manufacturers are shown.) The calculation of new reformed targets 

was based on the entire U.S. light-duty vehicle fleet, for which totals are listed at the 

bottom of Table 4-4. (Thus summed values of sales across the listed manufacturers w

not exactly match those at the bottom of the table.) 

Passenger Cars Light-Duty Trucks Light-Duty Vehicles 

Parent 

Manufacturer 

U.S

Sales % ( 

U

 Sales % ( 

U

Sales % (

. PC FE 

Sales mpg)

.S. LT FE

Sales 

.S. LDV FE

mpg) Sales mpg)

BMW 309,425 4.30% 26.886 60,643 0.80% 21.219 370,068 2.50% 25.759

CHRYSLER 513,185 7.13% 27.593 1,487,885 19.60% 21.927 2,001,070 13.53% 23.146

DAIMLER 195,064 2.71% 24.433 69,436 0.91% 20.270 264,500 1.79% 23.183

FORD 1 1 ,067,739 4.83% 27.693 1,418,473 18.69% 20.355 2,486,212 16.81% 22.969

GM 1,610,801 22.37% 28.497 1,863,203 24.55% 21.676 3,474,004 23.49% 24.382

HONDA 585,226 8.13% 31.644 662,394 8.73% 24.758 1,247,620 8.43% 27.573

HYUNDAI 488,393 6.78% 30.468 245,214 3.23% 23.416 733,607 4.96% 27.681

MITSUBISHI 101,433 1.41% 29.311 33,176 0.44% 23.926 134,609 0.91% 27.770

NISSAN 635,417 8.82% 28.822 451,130 5.94% 20.901 1,086,547 7.35% 24.904

PORSCHE 24,081 0.33% 25.212 15,706 0.21% 18.564 39,787 0.27% 22.090

SUBARU 64,655 0.90% 27.770 153,159 2.02% 27.097 217,814 1.47% 27.293

SUZUKI 69,867 0.97% 29.497 46,728 0.62% 24.058 116,595 0.79% 27.046

TOYOTA 1,2 1 04,012 6.72% 34.499 1,071,479 14.12% 23.577 2,275,491 15.38% 28.321

VW 324,832 4.51% 29.787 12,213 0.16% 20.049 337,045 2.28% 29.272

All Mfrs 7 10 ,201,578 0.00% 29.388 7,5 10 90,840 0.00% 22.036 14 10 ,792,418 0.00% 25.092

anufacturer-specific reformed fuel economy targets in 2020 were computed by 

ble 4-4. 

r and light 

l 

M

applying the footprint-based model equation to the baseline data represented in Ta

These equations were not applied directly to the summarized results in Table 4-4, but to 

the underlying data by individual vehicle. The attribute model-predicted fuel 

consumption was then sales-weighted across each manufacturer’s passenger ca

truck fleets and inverted to produce a model-based estimate of manufacturer fleet fuel 

economy. A global adjustment was then applied to these “attribute equation” based fue

economy values to make them equivalent to the actual fuel economy of the fleet. (This 

adjustment step is necessary because the attribute models are least-squared curve fits of 

-29- 
-30- 

ootprint 

% to 

able 4-5 is an excerpt of a spreadsheet called NewStds.xls where these calculations were 

ilar 

irst, each manufacturer’s passenger car fleet fuel economy calculated from the attribute 

actual fuel economy on an un-weighted vehicle basis. To the extent that highperformance vehicles in the fleet have relatively low fuel economy per unit of f

and relatively low sales, the equations will produce a fleet average fuel economy that is 

lower than the true, sales-weighted average.) These adjusted “baseline target” fuel 

economy values are then multiplied by the relative improvement percentage of 39.49

translate the results from the baseline to model year 2020. These steps are best illustrated 

with actual data. 

T

performed. Table 4-5 shows these calculations using the constrained logistic footprint 

attribute model (FP-L). In the table, the rows and columns are labeled as in the 

spreadsheet. Passenger car calculations are shown in Columns B through H. Sim

computations for light-duty trucks are contained in Columns J through P. Light-duty 

fleet composite calculations are given in Columns R through V. 

F

model is shown under the heading “Attribute Equation” (Column E). The actual baseline 

fuel economy reported earlier in Table 4-4 is shown in Column D. As stated above, the 

values shown were computed by applying the attribute equation to estimate fuel 

consumption separately for each vehicle based on its footprint. These individual 

were then used to compute a sales-weighted average, which was then inverted to get 

attribute-based estimated fuel economy for each manufacturer’s passenger car fleet. N

that the sales-weighted average of 25.74 mpg at the bottom of this column is less than the 

actual average for the entire passenger car fleet (29.39 mpg) listed at the bottom of 

Column D. Note also that the average fuel economy calculated from the equation is

higher than the actual fuel economy for manufacturers like Porsche who produce 

primarily high performance vehicles. (As shown in Column D of Table 4-5, Porsc

actual baseline passenger car fuel economy is 25.2 mpg, but the fuel economy calculated

based on the footprint equation is 29.7 mpg. The value of 29.7 mpg is what Porsche’s 

fuel economy would be if it had the same relationship between fuel economy and 

footprint as the average of all vehicles in the fleet.) As shown in cell E38, a multip

1.142 (29.39 ÷ 25.74) is necessary to make the fleet average fuel economy calculated 

from the footprint equation match the actual fleet average. This multiplier was then 

applied to the values for each manufacturer in Column E to produce adjusted “Baseli

Target” fuel economy values shown in Column F. By definition, the adjusted fuel 

economy across all manufacturers at the bottom of Column F now matches the actu

baseline passenger car fleet fuel economy shown at the bottom of Column D. 

results 

ote 

he’s 

lier of 

ne 

al 

ext, MY2020 fuel economy targets for each manufacturer shown in boldface in Column 

fuel 

N

G were simply calculated by applying the relative improvement of 39.49% described 

earlier to each value in Column F. These are the manufacturer-specific passenger car 

economy targets required in 2020 under EISA using a footprint-based reformed model. 
Table 4-5 

MY2020 Reformed Fuel Economy Requirements by Manufacturer – Footprint-Based App

31323335373839404142434445464849505152535456

A B C D E FGH J K L MNOP R S 

Form: FP-L

Equation: FC = C0 + [1/C1 + (1/C2 - 1/C1) x EXP((FP-C3)/C4) / (1 + EXP((FP-C3)/C4)]

Multiplier: 1.142 Multiplier: 1.018

Parent 

Manufacturer

U.S. MY06 

PC Sales

% of Mfr 

LDV Sales

Baseline FE 

(mpg)

Attribute 

Equation

Baseline 

Target

Target 

(mpg)

% FE 

Change

U.S. MY06 

LDT Sales

% of Mfr 

LDV Sales

Baseline FE 

(mpg)

Attribute 

Equation

Baseline 

Target

Target 

(mpg)

% FE 

Change

U.S. MY06 

LDV Sales

% of 

LDV S

BMW 309,425 83.61% 26.886 25.610 29.237 40.782 51.68% 60,643 16.39% 21.219 23.229 23.636 32.969 55.38% 370,068 2

CHRYSLER 513,185 25.65% 27.593 23.800 27.171 37.901 37.35% 1,487,885 74.35% 21.927 22.087 22.475 31.349 42.97% 2,001,070 13

DAIMLER 195,064 73.75% 24.433 24.973 28.511 39.769 62.77% 69,436 26.25% 20.270 20.882 21.248 29.638 46.22% 264,500 1FORD 1,067,739 42.95% 27.693 25.051 28.600 39.893 44.06% 1,418,473 57.05% 20.355 21.097 21.467 29.943 47.10% 2,486,212 16

GM 1,610,801 46.37% 28.497 25.315 28.900 40.312 41.46% 1,863,203 53.63% 21.676 21.109 21.479 29.961 38.22% 3,474,004 23HONDA 585,226 46.91% 31.644 25.880 29.546 41.213 30.24% 662,394 53.09% 24.758 22.038 22.425 31.279 26.34% 1,247,620 8

HYUNDAI 488,393 66.57% 30.468 26.770 30.562 42.630 39.92% 245,214 33.43% 23.416 23.488 23.900 33.337 42.37% 733,607 4

MITSUBISHI 101,433 75.35% 29.311 26.977 30.798 42.960 46.57% 33,176 24.65% 23.926 24.138 24.561 34.259 43.19% 134,609 0NISSAN 635,417 58.48% 28.822 25.492 29.103 40.594 40.85% 451,130 41.52% 20.901 21.165 21.537 30.041 43.73% 1,086,547 7

PORSCHE 24,081 60.52% 25.212 29.675 33.878 47.256 87.43% 15,706 39.48% 18.564 21.377 21.752 30.341 63.44% 39,787 0

SUBARU 64,655 29.68% 27.770 28.574 32.621 45.502 63.86% 153,159 70.32% 27.097 25.512 25.959 36.210 33.63% 217,814 1

SUZUKI 69,867 59.92% 29.497 28.662 32.722 45.642 54.74% 46,728 40.08% 24.058 24.733 25.167 35.105 45.92% 116,595 0

TOYOTA 1,204,012 52.91% 34.499 26.991 30.814 42.982 24.59% 1,071,479 47.09% 23.577 21.720 22.101 30.828 30.76% 2,275,491 15VW 324,832 96.38% 29.787 26.879 30.687 42.804 43.70% 12,213 3.62% 20.049 21.320 21.694 30.260 50.92% 337,045 2All Mfrs 7,201,578 48.68% 29.388 25.742 29.388 40.993 39.49% 7,590,840 51.32% 22.036 21.656 22.036 30.737 39.49% 14,792,418 100

LDV FUEL ECONOMY STANDARDS UNDER NEW CAFE ALTERNATIVES - HOUSE ENERGY BILL (H.R. 6)

Passenger Cars Light-Duty Trucks (& MDPVs) LDV Fle

-31- 
Finally, Column H shows the relative change in fuel economy resulting from these targets 

for each manufacturer compared to the manufacturer’s actual (MY2006) baseline 

passenger car fuel economy contained in Column D. As shown in Column H, required 

improvements between 2006 and 2020 range from 24.6% (Toyota) to 87.4% (Porsche) 

and are dictated by the distribution of footprint within each manufacturer’s passenger car 

fleet. (Note the sales-weighted average computed at the bottom of Column H matches 

the overall improvement percentage of 39.49%.) 

Similar calculations are shown in Columns L through P for light-duty trucks. Column O 

lists the required fuel economy targets in 2020 for each manufacturer’s light truck fleet. 

In Column P, the range of improvement percentages between 2006 and 2020 is shown for 

each manufacturer. Although the range is not as wide for light trucks as passenger cars, it 

is still significant, from 26.3% (Honda) to 63.4% (Porsche). 

Finally in Columns R through V, composite light-duty vehicle fleet results are shown. 

The composite fuel economy standards for each manufacturer are given in Column U and 

were computed from harmonic sales-weighted averages of each manufacturer’s sales 

splits between cars and trucks. For example, BMW’s composite fleet standard of 39.257 

mpg shown in cell U40 was calculated from sales fractions in cells C40 and K40 and fuel 

economy targets in cells G40 and O40 as follows: 

dardS BMW 257.39 mpg )]969.32/%39.16()782.40/%61.83[(

1

tan = + =

As stated earlier, these compliance calculations were performed only for 2020. 

Alternative fuel credit provisions under EISA would be completely phased out by 2020. 

Thus they were not treated in this analysis. 

(Section 8 of the report presents a detailed discussion of the compliance analysis and 

results.) 

### 

-32- 
5. TECHNOLOGY ASSESSMENT 

This section of the report documents the assessment of technologies considered for 

improving light-duty vehicle fuel economy. 

5.1 Key Considerations

An evaluation of the technology changes that should be considered for increasing fuel 

economy from vehicles using an internal combustion engines has to consider the fact that 

maximum fuel economy is achieved by minimizing propulsion energy requirements and 

maximizing the efficiency with which fuel is converted to mechanical energy. 

Propulsion energy requirements are primarily determined by the size, shape, and weight 

of the vehicle, and the rolling resistance of the tires. Fuel conversion efficiency is 

determined by the design of the engine, the power required to run engine accessories, the 

design of the “drive train” through which engine power is transmitted to the drive wheels, 

and whether a supplemental energy storage and delivery (“hybrid”) system is used in 

conjunction with the engine. 

Minimizing Propulsion Energy Requirements - Based on the results produced by a 

vehicle simulation model (described below), changes in propulsion energy requirements 

can be accurately estimated for specified vehicles. For a typical midsized passenger car, 

a 10% reduction in its weight will improve fuel economy by about 3.9% while 

simultaneously increasing the performance of the vehicle. A 10% weight reduction 

combined with resizing the engine for constant performance will improve fuel economy 

by about 7.6%. 

By reducing frontal area and streamlining the shape of the vehicle, less power is required 

to maintain any given speed, which improves fuel economy. For a typical midsized 

passenger car, a 10% reduction in aerodynamic drag will improve fuel economy by about 

1.5%. A 10% aerodynamic drag reduction combined with resizing the engine for 

constant performance will improve fuel economy by about 1.6%. (The benefits of 

resizing for constant performance are not significant because aerodynamic drag has 

relatively little effect on the engine size required to achieve a specified level of 

acceleration performance.) 

Less power, and therefore less fuel, is also required if rolling resistance is reduced. For a 

typical midsized passenger car, a 10% reduction in rolling resistance will improve fuel 

-33- 
economy by about 1.8%. A 10% rolling resistance reduction combined with resizing the 

engine for constant performance will improve fuel economy by about 1.9%. 

Increasing Engine Efficiency –The most significant factor in overall power train 

efficiency is engine efficiency. Both gasoline and Diesel engines are most efficient when 

they are run at relatively high load, producing close to the maximum available power at a 

particular engine speed. Engines are least efficient at idle, when they are producing no 

power but still must burn fuel to overcome internal friction and throttling losses to keep 

running.*

 

At high load, losses associated with internal friction and throttling are minimized. 

Throttling losses are not significant in Diesel engines but are a major source of 

inefficiency in gasoline engines, in which restriction of intake airflow is the method used 

to control power output. Smaller, less powerful engines are therefore more efficient 

because they need to be run at a higher load to propel the vehicle. However, the required 

maximum engine power is dictated by the desired level of maximum vehicle performance 

(e.g., acceleration rate, towing capacity). 

After the engine power level needed to achieve the desired performance level has been 

established, fuel economy can be improved by a number of different techniques, 

including the following: 

1. Using design features that minimize the engine size required to achieve the 

desired power level (e.g., 4-valve cylinder heads and gasoline direct injection); 

2. Running the engine at the lowest speed at which the required power can be 

achieved to minimize the throttling losses associated with low power levels; 

3. Using variable valve lift and timing to minimize the throttling loss associated with 

part-load operation; 

4. Deactivating cylinders to minimize the throttling loss associated with producing 

low power levels; 

5. Using gasoline direct injection (GDI) to achieve higher efficiency through 

increased compression ratio (as noted above, GDI also enables some engine 

downsizing); 

6. Reducing engine friction and parasitic losses; 

7. Turning the engine off during periods of zero power demand (idle and 

deceleration) and using battery power to run accessories; and 

8. Replacing some or all of the power that would otherwise be required from the 

engine during some driving modes by using energy recovered with a regenerative 

braking system (hybrid system). 

The techniques to reduce throttling losses are applicable only to gasoline engines. The 

other techniques are equally applicable to gasoline and diesel engines. 

 

*

 Throttling losses in gasoline engines are caused by the power required for the piston to draw air through 

the restriction of a partially closed throttle. 

-34- 
Improved Transmissions – Transmissions can reduce fuel consumption by keeping the 

engine closer to its power peak during full throttle operation. This can be accomplished 

by using a larger number of gears or a continuously variable transmission (CVT). This 

enables the size of the engine to be reduced to maintain a specified level of performance. 

Transmission design changes can also improve fuel economy by providing higher 

efficiency of power transmission to the drive wheels. Finally, “aggressive shift logic” 

(ASL), involving earlier upshifts under part load operation, can be used to reduce 

throttling losses (at the expense of noise, vibration and harshness [NVH] and 

driveability). 

The efficiency of automatic transmissions is typically less than that of manual 

transmissions because of the losses that occur in the torque converter. The torque 

converter is the hydraulic coupling that can be used to increase torque at low engine 

speeds and provide for a smooth launch and smooth shifts. However, the efficiency loss 

associated with the fluid coupling reduces overall transmission efficiency. Efficiency can 

be improved by mechanically “locking up” the torque converter earlier or replacing the 

torque converter with a friction clutch of the type used on a manual transmission. A 

transmission with an automatically controlled friction clutch is referred to as an 

automated manual transmission (AMT). 

5.2 Benefits of Individual Technologies

Based on the available techniques for improving fuel economy described above, it is 

apparent that small, lightweight vehicles can achieve higher fuel economy than larger, 

heavier vehicles because of their reduced propulsion energy requirements. The use of 

smaller engines also improves fuel economy due to the associated reductions in throttling 

losses and engine friction. However, our analysis has been focused on what can be 

achieved with design changes that do not restrict vehicle size or performance in order to 

minimize the adverse effect on market demand that would be associated with the loss of 

functionality and performance. We therefore assume that model mix and performance 

remain essentially unchanged. 

In cases where a technology change would increase performance (e.g., replacing a 5-

speed transmission with a 6-speed), our analysis assumes engine downsizing to maintain 

constant 0-30 and 0-60 mph acceleration performance for passenger cars, minivans, and 

unibody sport utility vehicles. For pickup trucks and body-on-frame SUVs, maintaining 

towing performance was used as a constraint. 

We have evaluated all of the technologies described above using a vehicle simulation 

model called VEHSIM. VEHSIM was originally developed by General Motors 

Corporation, became public domain under a U.S. Department of Transportation funded 

project, and has subsequently been enhanced by Sierra Research to incorporate routines 

to simulate vehicle cold start and warmup and to make it more computationally efficient. 

The version of the VEHSIM model used here calculates the fuel economy for a specified 

vehicle design over any specified driving cycle. The model can be configured to simulate 

-35- 
vehicles of different sizes, weights, and shapes, using a variety of different engines and 

transmissions. A schematic showing the basic structure of the model is shown in 

Figure 5-1. 

Figure 5-1 

VEHSIM Model Structure 

Based on the specified vehicle design, the model calculates the instantaneous power 

required at the drive wheels to maintain the specified speed-time profile. Based on the 

tire size, axle ratio, and axle efficiency, the drive wheel power and speed are translated 

into the speed and power required at the output of the transmission. Based on the 

transmission gearing, shift logic, torque converter speed ratio, and efficiency, the power 

and speed at the input of the transmission are computed. Total engine load is determined 

by adding accessory losses to the required transmission input. Finally, the instantaneous 

fuel consumption rate is determined from the engine map.*

 The fuel consumption is 

computed 20 times a second by interpolation between the individual data points 

contained on the map. Fuel economy is calculated by integrating the instantaneous 

 

*

 “Engine map” is a term of art used to describe a tabular or graphical presentation of fuel consumption or 

fuel efficiency as a function of engine speed and load. VEHSIM uses a tabular engine map with fuel 

consumption in units of pounds per hour shown for the full range of engine speeds (from idle to maximum 

speed) and loads (from negative loads experienced under deceleration to full load). 

-36- 
consumption over a specified driving cycle. To compute city/highway combined fuel 

economy, approximately 45,000 individual calculations are combined. 

The baseline engine maps used in VEHSIM were a composite of maps provided by 

several large-volume vehicle manufacturers. Alternative engine maps have been 

developed for cylinder deactivation and various types of variable valve lift and timing 

based on information published in the technical literature and confidential information 

provided by vehicle manufacturers. Transmission modules have been configured to 

represent different numbers of gears, gear ratios, torque converter characteristics, and 

shift logic. Hybrid vehicles are simulated by continuously accounting for the capture and 

use of regenerative braking energy. Engine fuel consumption is set to zero when energy 

captured by the regenerative braking system is sufficient to meet vehicle power demand, 

as when running accessories at idle with the combustion engine shut off. (The extent to 

which regenerative braking energy is used to reduce fuel consumption is a function of 

maximum battery power, motor/generator size, and the amount of energy the specified 

battery can deliver without being discharged to the point that battery life is adversely 

affected.) As described below, the VEHSIM model has been validated for a variety of 

specific vehicle models and it accurately estimates the average fuel economy of the entire 

baseline vehicle fleet. 

In addition to simulating fuel economy, VEHSIM can be used to estimate the acceleration 

performance or top speed of a vehicle. Rather than having the model determine the 

engine speed and load required for a particular driving cycle, the user specifies a zero 

initial speed and wide-open-throttle. The model then determines the resultant speed-time 

profile as the vehicle accelerates to the maximum achievable speed. 

Although the model is capable of simulating variations in roadway grade, wind speed, 

and surface conditions, simulations run during this study assumed zero wind speed, level 

terrain, and paved roads (which is consistent with the conditions simulated during official 

fuel economy tests). However, the model was also used to evaluate the effect of fuel 

efficiency improvement technologies on the ability of vehicles to maintain freeway 

cruising speeds on grades (i.e., “gradeability”). 

In cases where a technology was already in production, the accuracy of the model in 

representing the technology changes was checked by comparing model results to CAFE 

data. Table 5-1 presents the results for simulations of continuously variable valve lift and 

timing and cylinder deactivation compared to the actual performance of vehicles using 

those technologies. As shown, the VEHSIM predictions matched actual CAFE test 

results within 2%, which is less than the variability in test results that would be expected 

from two different drivers testing the same car in two different laboratories. 

The use of a vehicle simulation model to evaluate the individual technologies was 

important because it allowed for all technologies to be evaluated using a consistent, 

representative baseline. The fuel economy benefit of a particular technology cannot be 

accurately evaluated just by comparing test results from two different vehicles, one of 

-37- 
Table 5-1 

VEHSIM Runs for Vehicles With VVLT and Cylinder Deactivation

Specification BMW 745i (VVLT) Chrysler 300C (DeAct) 

Weight 4376 4046 

Frontal Area 25.09 23.96 

Drag Coefficient 0.29 0.35 

Rolling Friction Coefficient 0.0105 0.0100 

Rolling Radius 1.023 1.145 

Displacement 268 345 

Axle Ratio 3.38 2.82 

Valve Train OHC Continuously 

Variable Lift & Timing 

OHV with Cylinder 

Deactivation 

Transmission 6-Speed Automatic 5-Speed Automatic 

Modeled CAFE 24.5 22.7 

Actual CAFE 24.4 23.1 

Simulation Error +0.5% -1.7% 

which uses the technology and one of which does not, unless both vehicles are otherwise 

identical and representative of typical vehicles. 

When evaluating combinations of technologies, the use of a vehicle simulation model is 

absolutely essential. Interactions between the technologies cannot be accurately assessed 

without a vehicle simulation model. 

Table 5-2 presents fuel consumption reductions achievable through the application of a 

variety of individual design changes based on estimates made using VEHSIM. (Later, 

Section 7 provides more detail on how combinations of technology were modeled.) The 

table shows the reduction in fuel consumption for both a typical midsize passenger car 

and for a fleet average pickup truck. 

Fuel consumption reduction estimates shown in Table 5-2 have been made on the basis of 

both the CAFE test procedures and actual California driving patterns. This distinction is 

significant for certain technologies that provide greater benefits on the 30-year old CAFE 

test procedures than in actual driving. As our research has demonstrated, the CAFE test 

procedures are no longer representative in terms of speeds, time at idle, and acceleration 

rates. (Although the referenced study was focused on California driving patterns, data 

collected in other states more closely match California driving patterns than the CAFE 

test procedures.) 

-38- 
Table 5-2 

Estimates of Achievable Fuel Consumption Reductions 

Assuming Engine Size Adjustments for Constant Acceleration Performance 

Mid-Size Car Pickup Truck 

Technology CAFE Actual CAFE Actual 

Ultra-Light Steel Body and Suspensiona,b -3.3% -3.2% -1.2% -1.5% 

Aluminum Body vs. Ultralight Steelb -5.3% -5.2% -1.9% -1.9% 

Reduced Parasitics I -0.5% -0.5% -0.5% -0.5% 

Reduced Parasitics II -2.0% -2.0% -2.0% -2.0% 

Discrete Variable Valve Lift & Timing -6.3% -3.8% -6.8% -4.2% 

Continuously Variable Valve Lift & Timing -11.4% -6.1% -12.4% -6.7% 

Cylinder Deactivation (>4 cylinders only) -7.5% -4.3% -8.8% -4.8% 

Gasoline Direct Injection-Stoichiometric -5.9% -4.8% -6.2% -5.1% 

Turbocharging (with engine resize) 0.3% 2.7% -0.3% 2.8% 

OHC Engine Replaces OHV Enginec -8.6% -6.6% n/a n/a 

5-Speed Automatic w/ASL (vs. 4-Speed) -6.2% -3.6% -6.0% -3.6% 

Automatically Shifted Manual Transmission -4.0% -4.0% -4.4% -4.2% 

Electric Power Steering -1.8% -1.4% -1.1% -0.9% 

Higher Efficiency Alternator -0.9% -0.6% -0.6% -0.5% 

Mild Hybrid (42 volt, 10 kW) -7.3% -3.6% -4.5% -2.1% 

Strong Hybrid (7 kW battery power/1000 lbs.) -28.7% -23.4% -22.1% -20.8% 

Diesel Engine (turbocharged, direct injection) -21.3% -22.4% -18.6% -18.5% 

a

 Ultralight steel benefits assume 50% of the technology is already in the baseline. 

b

 Lesser benefits apply to trucks with body-on-frame construction. c

 Benefits do not apply to trucks if towing capacity is maintained. 

The differences between the driving patterns used in the CAFE test procedures and 

current driving patterns in customer service are reflected in the speed time profiles shown 

in Figures 5-2, 5-3, 5-4, and 5-5. (Note that differences in the length of the cycles are not 

relevant. The length of the Cal-Urban and Cal-Rural cycles was based on the minimum 

length necessary to adequately represent the in-use data from which the cycles were 

developed.) 

Figures 5-2 and 5-3 show the speed-time traces for the new California urban cycle (called 

Cal-Urban) and the EPA Urban (City) cycle, respectively. The Cal-Urban cycle has top 

speeds in excess of 70 mph and includes several acceleration-deceleration “hills” with a 

top speed in excess of 40 mph. In contrast, the EPA Urban cycle has a top speed of 56.7 

mph and, with the exception of this hill of the cycle, has no other travel above about 35 

mph. (Although the Cal-Urban cycle is shorter than the EPA Urban cycle, cycle length is 

not a factor in emissions or fuel economy measured over the cycle, which are expressed 

per mile of travel.) 

-39- 
Figure 5-2 

Cal-Urban Driving Cycle Speed-Time Trace 

0

10

20

30

40

50

60

70

80

90

0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400

Time (sec)

Speed (mph)

Figure 5-3 

EPA Urban (City) Driving Cycle Speed-Time Trace 

0

10

20

30

40

50

60

70

80

90

0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400

Time (sec)

Speed (mph)

-40- 
Figure 5-4 

Cal-Rural Driving Cycle Speed-Time Trace 

0

10

20

30

40

50

60

70

80

90

0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400

Time (sec)

Speed (mph)

Figure 5-5 

EPA Highway Driving Cycle Speed-Time Trace 

0

10

20

30

40

50

60

70

80

90

0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400

Time (sec)

Speed (mph)

-41- 
Figures 5-4 and 5-5 provide a similar comparison of speed-time traces for the new 

California rural (Cal-Rural) and EPA Highway cycles, respectively. Like the urban 

comparison, the Cal-Rural cycle has more high speed travel than its counterpart, the EPA 

Highway cycle, and dramatically so. The maximum speed of the Cal-Rural cycle is over 

80 mph and includes extended periods over 60 mph. By contrast, the EPA Highway 

cycle, which represents enforcement of a 55 mph speed limit, never exceeds 60 mph. 

Weight Reduction – As shown in Table 5-2, our analysis indicates that a 3.3% reduction 

in fuel consumption could be achieved through the use of ultralight steel in midsize 

sedans. This reduction is relative to a baseline fleet that already uses lightweight steel 

closures and has 50% penetration of ultralight steel bodies and suspensions. Lesser 

reductions are available in trucks using body on frame construction. Greater reductions 

are available with the use of aluminum. The weight reductions that lead to the fuel 

consumption benefits shown in the table are described below. 

As shown in Table 5-3, a 10% reduction in total vehicle weight is associated with 

maximizing the use of ultralight steel in an all new unibody vehicle that already uses 

lightweight closures. The overall weight reduction accomplished with the use of 

ultralight steel results from a 25% reduction in the weight of components designed and 

produced using ultralight steel, which includes the body and suspension, combined with 

an ability to reduce the weight of other vehicle systems (e.g., drivetrain, wheels, etc.) 

because of the lower weight of the body and suspension. We have used a 1.25 factor to 

account for this “compounding” effect of weight reduction. The increasing use of 

ultralight steels is an evolutionary process that, as noted above, we estimate would be 

50% complete in the absence of more stringent CAFE standards. 

With body-on-frame construction, we estimate the weight reduction potential from the 

body is approximately half of the weight reduction potential for unibody construction. 

Since most vehicles with body-on-frame construction are designed to carry or tow heavy 

loads the theoretical benefits of compounding are reduced, so we ignore compounding. 

This reduces the total weight reduction potential for ultralight steel to 5.5%. Since half of 

the pickup trucks are estimated to have ultralight steel in the baseline case, the reduction 

in fuel consumption, as shown in Table 5-2, is 1.2% on the CAFE test procedure. 

Aluminum unibody vehicles can be approximately 50% lighter than unibody vehicles 

constructed from conventional, mild steel. When aluminum closures are accounted for, 

the incremental reduction in weight over ultralight steel is an additional 7.9% over a mild 

steel baseline vehicle (an additional 8.8% reduction over ultralight steel). As shown in 

Table 5-2, the corresponding reduction in fuel consumption is 5.3%. 

For body-on-frame construction, we estimate the use of aluminum can achieve an 

additional 3.8% reduction in weight can be achieved over a mild steel baseline vehicle 

using lightweight closures, bringing the total weight reduction to 9.3% relative to a 

vehicle that does not have an ultralight steel body and suspension. As shown in Table 

5-2, the reduction in fuel consumption over ultralight steel is 1.9%. 

-42- 
Table 5-3 

Typical Midsize Vehicle Weight Reduction Potential 

with Ultralight Steel and Aluminum 

-------------- Weight Reduction ------------- 

Baseline 

(lbs) 

ULS 

Category Unibody 

ULS on 

Frame 

Al 

Unibody 

Al on 

Frame 

Body in White 640 160 80 320 160 

Drivetrain 576 n.a. 

Suspension 384 96 96 96 96 

Interior 352 n.a. 

Trim/Hardware/Glass 224 n.a. 

Wheels and Tires 224 n.a. 

Fuel, Exhaust System, etc. 224 n.a. 

Body Closures 192 n.a. n.a. 42 42 

Fluids 160 n.a. 

Electrical 128 n.a. 

Steering and Brakes 96 n.a. 

TOTAL 3,200 256 176 458 298 

Total With Compounding 320 176 573 298 

Percent Reduction 10.0% 5.5% 17.9% 9.3% 

Reduced Parasitics – Two separate combinations of design changes for the reduction of 

parasitic losses on the engine were considered. The first involves minor changes in 

lubricants and/or minor engine design to reduce friction sufficiently to reduce fuel 

consumption by 0.5% relative to the baseline fleet. The other involves more complex 

changes to other subsystems that impose parasitic loads on the engines. The 2.0% 

reduction in fuel consumption associated with the second set of changes was based on a 

specific set of design changes under development by a particular manufacturer, the 

details of which are confidential. Other manufacturers are known to be pursuing similar 

design changes. 

Variable Valve Lift And Timing – For technologies providing variable valve lift and 

timing, our analysis indicates that fuel consumption reductions in midsize sedans of 6.3% 

to 11.4% can be achieved depending on the sophistication of the system. The 6.3% 

reduction is for a “two-step” system. The 11.4% reduction assumes the use of systems 

that are continuously variable and control engine output without using a throttle. (This 

requires either “camless” technology, such as electro-hydraulic valve actuation, or a 

relatively complex mechanical system similar to the “Valvetronic” system developed by 

BMW.) The specific benefits are based on technical literature showing the effects of 

variable valve timing and lift on engine efficiency across the full range of engine load.*

 

 

*

 See, for example, SAE paper number 2001-01-0667. 

-43- 
It should be noted that our vehicle simulation modeling indicates that variable valve lift 

and timing technology will not provide benefits in actual driving conditions as large as 

the benefits calculated using the CAFE test procedures. (This is the result of the higher 

engine loads and reduced idle time in customer service, which reduces the benefit of any 

technology that improves fuel economy by reducing throttling losses.) 

Cylinder Deactivation – For cylinder deactivation systems, our vehicle simulation 

modeling indicates that a 7.5% reduction in fuel consumption can be achieved on the 

CAFE test procedures and a 4.3% reduction can be achieved in customer service for the 

average midsize sedan. Slightly greater benefits are estimated for the average pickup 

truck. It should be noted that these estimates are for vehicles that have a relatively high 

power-to-weight ratio. The benefits of cylinder deactivation are reduced in vehicles with 

a lower power-to-weight ratio. Because of NVH problems, the technology is not applied 

to 4 cylinder engines. It also should be noted that the benefits are calculated using an 

engine map that reflects appropriately reduced throttling losses over the full range of 

speeds and loads where the cylinder deactivation system can be activated. (Our cylinder 

deactivation maps have been validated by comparing them to actual cylinder deactivation 

maps provided by a large volume manufacturer.) The modeling therefore assumes that 

no compromises are being made to deal the NVH issues. (As described below, there are 

significant costs for NVH mitigation that have to be included to utilize cylinder 

deactivation to the maximum extent.) 

Gasoline Direct Injection – Gasoline Direct Injection (GDI) can improve fuel economy 

by allowing an increase in compression ratio due to the charge cooling effect of injecting 

the fuel directly into the cylinder, where the cooling effect occurs as the fuel vaporizes. 

Numerous researchers have reported the ability to increase compression ratio by 1.0 to 

1.5 over baseline. The amount of increase depends on how well the non-GDI version of 

the engine was optimized for high compression ratio. Assuming a base compression ratio 

of 10:1, the theoretical benefits of a 1.25 number increase in compression ratio would be 

3.8%. A benefit this large would not be realized in practice because some of the work 

done to compress the fuel air mixture to a higher pressure is not recoverable (it is lost in 

increased heat transfer to the cooling system). A more reasonable estimate of the 

efficiency increase would be 3%. 

In addition to the efficiency change associated with higher compression ratio, numerous 

SAE papers indicate that the charge cooling effect of direct injection increases the 

volumetric efficiency of an engine by approximately 3 - 4%.*

 Combined with an 

efficiency increase of 3%, the increase in volumetric efficiency is estimated to increase 

peak torque and power levels by approximately 7%. When the engine is resized for 

constant performance, VEHSIM indicates that a reduction in fuel consumption of 5.9% 

should be achievable in a typical midsize sedan. It should be noted that the improvement 

for GDI assumes all new cylinder heads and no attempt to salvage exiting cylinder head 

tooling. GDI implementations that attempt to utilize existing tooling may result in the 

need for reduced valve sizes or other compromises that would reduce volumetric 

efficiency and reduce or eliminate the benefits associated with engine resizing. 

 

*

 See, for example, SAE paper numbers 962018 and 1999-01-0171. 

-44- 
Turbocharging With Engine Downsizing – In theory, the use of turbocharging to achieve 

equivalent engine power with a smaller engine would improve fuel economy by reducing 

throttling losses. However, it is also necessary to account for the effect of turbocharging 

on octane requirement. To avoid an increase in octane requirement, it is necessary to 

reduce compression ratio, which adversely affects fuel economy. The simultaneous 

application of turbocharging and direct injection can reduce or eliminate the need for a 

compression ratio reduction, but turbocharging and downsizing without the use of GDI 

does not yield benefits on a constant performance basis, based on a statistical analysis of 

available CAFE data done in 2004.8

 A more recent analysis using 2007 model year 

CAFE data produces similar results, as shown in Figure 5-6. 

Using a Two-Parameter Model 

Figure 5-6 

Predicted vs. Actual Fuel Economy for 2007 Model Year Gasoline Cars 

(Test Weight and HP/lb, r2

=0.83, Excludes Hybrids) 

The small dots in Figure 5-6 show, for naturally-aspirated vehicles, the relationship 

between measured fuel economy and fuel economy predicted with a simple two 

parameter model based on test weight and power-to-weight ratio. The coefficient of 

determination (r2

) is 0.83. The triangles represent the turbocharged vehicles in the data 

set that do not use gasoline direct injection (GDI). The “predicted” fuel economy was 

-45- 
calculated with the same equation used for the naturally-aspirated vehicles. As the figure 

shows, the turbocharged vehicles, on average, fall along the same line, which indicates 

that turbocharging has no effect on fuel economy when weight and power-to-weight ratio 

are held constant. The three larger squares represent turbocharged vehicles that are also 

equipped with GDI. Each of these vehicles also uses premium grade fuel. The actual 

fuel economy of these vehicles is about 10% higher than the fuel economy predicted by 

the same equation, but it is apparent that all of the benefit are associated with GDI and 

premium fuel, not turbocharging. Without GDI and premium fuel, turbocharged vehicles 

have the same fuel economy as non-turbo vehicles of the same weight and HP/lb. 

The effect of turbocharging and engine downsizing on fuel economy also depends on the 

metric used to determine constant performance. The amount of downsizing that is 

possible depends on whether “launch” performance is being maintained in addition to 

other performance metrics, such as 0-60 mph acceleration time. Maintenance of launch 

feel limits the downsizing that is possible with turbocharging. Automotive journalists 

frequently note that degraded low speed acceleration and throttle linearity (due to turbo 

lag) is typical of turbocharged vehicles relative to non-turbocharged vehicles of similar 

horsepower.9

Overhead Cam Engines – As shown in Table 5-2, our simulation modeling indicates an 

8.6% reduction in fuel consumption associated with replacing 2-valve, OHV engines with 

4-valve, OHC engines. As noted in the footnote to the table, these benefits are not 

available for truck engines requiring relatively high “torque rise” (i.e., increasing torque 

as engine speed decreases). 

Transmission Changes – In the case of transmissions, our simulation modeling indicates 

that 5-speed automatic transmissions with aggressive shift logic (ASL) will provide a 

6.2% reduction in fuel consumption in a typical midsize car relative to a 4-speed 

automatic with non-aggressive shift logic on the CAFE test procedure and a 3.6% 

reduction in actual customer service. (About half of the benefit is associated with the 

reduced throttling loss associated with earlier upshifts and about half is associated with 

the reduced throttling loss associated with being able to maintain constant acceleration 

performance with a slightly downsized engine.) Automated Manual Transmissions were 

estimated to provide an additional 4% reduction in fuel consumption on the CAFE test 

procedures. 

Engine Accessories – Our analysis indicates that the fuel consumption reductions 

associated with electric power steering (EPS) and higher efficiency alternators are about 

1% in customer service and 1-1.8% on the CAFE test procedures. The EPS benefit was 

developed using simulation modeling. The increase in alternator efficiency is based on 

our review of test results reported by individual manufacturers. 

Hybrids – A wide range of hybrid system designs have been developed. At one end of 

the spectrum are systems with just enough electric motor power to facilitate an “engineoff-at-idle” strategy with rapid restart when the accelerator is depressed. We have 

modeled a “mild” hybrid system that has a slightly larger motor (10 kW) that can provide 

-46- 
a minor amount of launch assist and can qualify as a “Type D” hybrid under the ZEV 

regulations adopted by the California Air Resources Board. Our modeling of a mild 

hybrid system produced a fuel consumption reduction using the CAFE test procedures of 

7.3%. In customer service, the estimated benefit drops to 3.6%. The benefits come from 

being able to turn the engine off at idle and reducing throttling loss by being able to 

slightly downsize the engine while maintaining constant acceleration performance. (This 

technology is most effective in reducing fuel consumption at idle, an operating condition 

that is overrepresented in the CAFE test procedures.) 

Much larger reductions in fuel consumption are possible with a hybrid system capable of 

maximizing the capture of regenerative braking energy. When the model is used to 

estimate the effect of applying a hybrid system designed to maximize the use of 

regenerative braking on the CAFE test procedure, the result is a predicted reduction in 

fuel consumption of 28.7%, which is equivalent to a fuel economy improvement of 

40.3%. This is the hybrid system benefit associated with being able to turn the engine off 

at idle, recapture 80% of the braking energy associated with the CAFE test procedures, 

and downsize the combustion engine to account for the amount of electric motor assist 

available. With this type of system, the vehicle would have equivalent acceleration 

performance; however, towing capacity would be reduced because battery energy would 

be depleted quickly. For trucks that need to maintain towing capacity, the engine could 

not be downsized. This would reduce the benefits to a reduction in fuel consumption of 

22.1%, which is equivalent to a fuel economy improvement of 28.4%. 

The hybrid system benefits we have calculated are representative of what can be 

accomplished with what is sometimes referred to as a “strong” hybrid system. Although 

there are not yet any industry standard definitions, we have used the term “strong hybrid 

system” to refer to a system that has a large enough battery and motor to maximize the 

amount of energy that can be captured through the use of regenerative braking. (Our 

detailed vehicle simulation modeling indicates that the size of the battery in the Prius is 

adequate to recover 95% of the braking energy on the CAFE test procedures, although 

inefficiencies in the system prevent all of that energy from being used to replace energy 

provided by the combustion engine. A larger battery would not be able to further 

improve fuel economy without compromising vehicle performance.*

) The Civic hybrid 

does not have a battery and motor large enough to maximize the effect of regenerative 

braking. It might therefore be considered a “moderate” hybrid; however, we have not 

included such a system in our detailed analysis of what technologies might be used to 

comply with the EISA standards. 

(It should be noted that the Toyota Prius, the 2008 GM Tahoe Hybrid, and other some 

other hybrids use larger motor/generators that assumed in our “strong” hybrid system. 

Larger motor/generators facilitate slightly greater fuel economy improvements, but at a 

 

*

 In theory, a larger battery could allow the combustion engine to be further downsized while maintaining 

acceleration performance; however, the amount of energy required for hard accelerations would exceed the 

amount of energy being recovered through regenerative braking. As a result, the acceleration performance 

of the vehicle would decrease when it was being driven hard, which might create consumer acceptance and 

safety concerns. 

-47- 
cost premium. We have modeled what we consider the most cost-effective hybrid system 

rather than the most fuel efficient.) 

Diesel Engines – Table 5-2 shows that the fuel consumption reduction achievable with a 

diesel engine in a midsize car is 21.3%. This corresponds to a 27.1% improvement in 

fuel economy expressed in miles per gallon. Our estimate is based on the use of 

VEHSIM with an engine map based on an actual turbocharged, direct injection diesel 

engine. We made an adjustment to the map to reflect an estimated 5% increase in fuel 

consumption due to the use of the additional emission controls that would be required to 

comply with LEV II emissions standards. We used this diesel engine map, sized to 

provide the same 0-60 mph acceleration performance of the industry average midsize 

passenger car, and compared the results to the simulation model estimates for a 200-

pound lighter car using an industry average gasoline engine. (The 200-pound weight 

difference was based on difference in curb weights reported for the gasoline and diesel 

versions of the Mercedes E320.) 

To check the reasonableness of our estimates, we also configured the simulation model to 

represent the Mercedes-Benz E320 turbocharged diesel using the same engine map 

resized to match the power of the Mercedes engine. The model calculates the 

“combined” city/highway fuel economy to be 34.5 mpg. The actual test results for the 

vehicle show that it achieves 35.5 mpg, which is just 2.9% higher. If the fuel 

consumption rate of the Mercedes E320 is increased by 5% to account for additional 

emission controls required for future NOx standards, its fuel economy would be reduced 

to 33.8 mpg, which is 2.0% lower than our estimate. Thus our analysis is consistent with 

the level of fuel economy demonstrated by the Mercedes E320 diesel. 

Reductions In Aerodynamic Drag And Rolling Resistance – It should be noted that our 

analysis assumes that significant reductions in aerodynamic drag and rolling resistance 

are not feasible. Styling limitations would be imposed by further reductions in 

aerodynamic drag and there is evidence that many consumers favor styling that is less 

aerodynamic than the styling of many current models. 

The current version of the Chrysler 300 sedan is a case in point. Its 0.35 drag coefficient 

is significantly higher than the 0.31 drag coefficient of the vehicle it replaced. As 

reported in the June 2004 edition of Car & Driver, “The 300 also represents a return to 

chiseled three-box proportions after a long run of smooth, cab-forward designs.” Similar 

trends toward more classic, chiseled styling are apparent at other companies and the 

similar effects on drag coefficient are expected. The obvious tradeoff between drag 

coefficient and styling flexibility limits the extent to which the reductions in aerodynamic 

drag can be relied on. 

In the case of reduced rolling resistance, our detailed analysis indicates that (1) the rate of 

progress in reducing rolling resistance has slowed; and (2) new federal safety standards 

may limit the extent to which future reductions occur.10

-48- 
### 

-49- 
6. TECHNOLOGY COST ESTIMATES 

In conjunction with a rigorous assessment of available fuel economy improvement 

technologies, a detailed update of the costs of these technologies was also performed. 

These technology cost estimates are discussed below. 

6.1 Overview

Technology cost estimates are derived primarily from information obtained from Harbour 

Consulting and The Martec Group. Harbour is an internationally recognized 

manufacturing and management consulting firm that has studied the manufacturing 

processes used by most major manufacturers and that annually produces “The Harbour 

Report,” which compares manufacturing productivity throughout the industry. The 

Martec Group is a partnership of consultants specializing in business-to-business 

markets, including Tier 1 and Tier 2 suppliers to the automotive industry. 

Variable cost estimates were adjusted to Retail Price Equivalent (RPE) using markup 

factors recommended by researchers at Argonne National Laboratory (ANL)11 and Dr. 

Wynn Van Bussman,12 former Chief Economist for Chrysler Corporation. 

Harbour provided detailed estimates of fixed (e.g., tooling) and variable costs for a wide 

range of engine, transmission, and body designs. Information obtained from Harbour 

was supplemented with research and development (R&D) cost information obtained from 

individual manufacturers. The sum of “overhead” costs, manufacturer profit, and dealer 

margin was estimated from the work by ANL.*

 This approach was used for the 

following technologies: 

• OHV gasoline engines; 

• OHC gasoline engines; 

 

*

 Based on the ANL report, an overall markup factor of 2.0 to 2.05 should generally be applied to variable 

costs for components developed by OEMs. The ANL report also indicates that a factor of 1.61 applied to 

the sum of amortized fixed costs and variable costs is equivalent to a markup factor of 2.0 applied to 

variable costs only. We have therefore used a 1.61 factor and added amortized fixed costs in cases where 

detailed fixed cost estimates were available from Harbour or individual manufacturers. In the case of 

components for hybrid vehicles developed by vendors (e.g., batteries), ANL estimated a 1.50 cost 

multiplier assuming the supplier covers 100% of the warranty costs. In the more likely case that warranty 

costs are primarily borne by the vehicle manufacturer, the ANL formula translates to a cost multiplier of 

1.61 applied to variable costs (which assumes that R&D and tooling are covered by vendor prices for 

supplied components). 

-50- 
• OHC diesel engines; 

• Continuously variable valve lift and timing systems (CVVLT); 

• 4-speed automatic transmissions; 

• 5-speed automatic transmissions; 

• 6-speed automatic transmissions; 

• 6-speed automated manual transmissions; 

• Conventional steel bodies and closures; 

• Ultralight steel bodies and closures; and 

• Aluminum bodies and closures. 

Whenever possible, cost estimates obtained from Harbour were compared to cost 

estimates independently obtained by The Martec Group from individual manufacturers 

and vendors. We also relied on The Martec Group to obtain subsystem cost estimates in 

cases where Harbour did not have detailed cost studies available from which reliable 

information could be provided regarding the cost of hybrid vehicle components or 

various technologies that have never been mass produced (e.g., diesel aftertreatment 

systems capable of meeting LEVII standards). 

Weight Scaling – For certain technologies, such as the batteries used in hybrid electric 

vehicles, the capacity of the batteries required for heavier vehicles increases with weight 

in a linear fashion and the cost is a nearly linear function of capacity. For most other 

power train technologies, we have estimated that the cost increases approximately in 

proportion to 50% of the change in weight. This estimate is based on data obtained from 

Harbour Consulting. Using Harbour’s data for engine costs, we calculated the Retail 

Price Equivalent for a DOHC V6 engine used in a 3,300-pound curb weight passenger 

car. For comparison, Harbour’s cost estimates for a DOHC V8 translate to a retail price 

that is 19% higher. Since the V8 would be the baseline engine for a vehicle that weighs 

40% more than a 3,300-pound passenger car, it is apparent that power train costs scale 

with approximately 50% of the change in weight. 

Table 6-1 summarizes our estimates of the price increases required to cover the costs 

associated with various technology changes. The estimates shown in the table assume 12 

years lead time is available to ensure that new technologies can be phased in without the 

need for stranding any investment in other technologies that have not yet been fully 

amortized. Estimates are provided for the average mid-size sedan and the fleet average 

pickup truck. 

-51- 
Table 6-1 

Long-Term Estimates of Retail Price Increase for 

Various Technologies 

Technology 

Mid-Size 

Car 

Pickup 

Truck 

Ultralight Steel Body and Suspension $209a $171a,b 

Aluminum Intensive Vehicle (over UL Steel) $1,596 $1,240b 

5-Speed Automatic vs. 4-Speed Automatic $238 $291 

Reduced Parasitics-I $14 $17 

Reduced Parasitics-II $122 $149 

Replace OHV Engine with OHC Engine $593 $725 

Discrete Variable Valve Lift (w/ Cam Phasers) $518 $634 

Continuously Variable Valve Lift & Timing $899 $1,100 

Turbocharging w/ engine resize $407-874 $498-1,069 

Cylinder Deactivation $360 $440 

6-Speed Automated Manual vs. 4-Speed Auto $483 $591 

Electric / Electro-Hydraulic Power Steering $82 $150 

Higher Efficiency Alternator $73 $89 

Gasoline Direct Injection-Stoichiometric $553 $676 

Mild Hybrid (42-volt, 10 kW) $1,886 $2,728 

Strong Hybrid (7kW/1000 lbs battery power) $5,968 $8,632 

Diesel Engine (turbocharged, direct injection) $6,198 $7,581 a Ultralight steel costs assume 50% of the technology is already in the baseline.

b Cost for materials substitution is lower for pickups because of body on frame construction.

6.2 Sources of Individual Estimates

The sources of each of the individual cost estimates listed in Table 6-1 are described 

below. The basic cost estimates for each technology have been developed for mid-size 

sedans using V-6 engines. The costs must be scaled, as described above, when the 

technologies are applied to smaller and larger vehicles. 

Ultralight Steel Body and Suspension – Cost estimates for the expanded use of ultralight 

steel are based on estimates provided by Harbour Consulting. Some existing tooling 

must be retired prematurely in order to fully implement this technology by 2020 because 

the high risk associated with conversion to maximum use of ultralight steel necessitates a 

relatively slow ramp up. The estimated increase in retail price of $209 for midsize cars 

applies only to vehicles that are currently using minimal amounts of ultralight steel. On 

average, about 50% penetration of ultralight steel is estimated to be included in the 

baseline by model year 2020. 

-52- 
Aluminum Intensive Vehicle Incremental to UL Steel – Cost estimates for aluminumintensive vehicles are based on estimates provided by Harbour Consulting. 

Reduced Parasitics-I – The cost estimate for a miscellaneous design changes to provide a 

minor reduction is parasitic losses is based on a large-volume manufacturer’s estimate for 

the cost of next-generation lubricants. 

Reduced Parasitics-II – Sierra’s estimates for this combination of technologies is based 

on variable cost and R&D cost estimates provided by a large volume manufacturer that 

has developed the technologies. The proprietary technologies on which the estimate is 

based cover three different sources of parasitic losses that are unrelated to improved 

alternators and power steering (which are addressed separately). 

Replace OHV Engine with OHC Engine – The cost estimate for replacing overhead valve 

engines with overhead cam engines is based on the variable cost and tooling cost data 

obtained from Harbour Consulting combined with research, development, and 

engineering cost estimates obtained from several high volume manufacturers. 

Discrete Variable Valve Lift – The cost estimate for discrete variable valve lift and 

timing is based on Martec’s variable cost estimates prepared for the previously referenced 

NESCCAF report of $115 for electro-mechanic variable valve lift plus $140 for dual cam 

phasers. A markup factor of 2.05 produces an RPE value of $553 for midsize car with a 

V6 engine. 

Continuously Variable Valve Lift and Timing – Based on cost estimates obtained from 

Harbour Consulting, we estimated the net change in retail price associated with 

Continuously Variable Valve Lift and Timing at $899 RPE for a midsize passenger car. 

This was for an electro-mechanical type system similar to the Valvetronic/Vanos system 

used by BMW. Martec independently estimated the net change in variable cost for a 

similar system at $285 for an inline 4-cylinder engine, $450 for a V6 engine, and $550 

for a V8 engine. The 22% increase in cost for the V8 system compared to V6 is 

consistent with the weight-scaling assumptions used in our own analysis. Using a 

markup factor of 2.0 to 2.05, Martec’s estimate for a V6 almost exactly matches are 

estimate for a midsize car. 

Turbocharging w/ Engine Resize – Based on cost estimates obtained from Harbour 

Consulting, we estimated the net change in retail price associated with converting a 

naturally aspirated V6 engine to a turbocharged inline 4-cylinder engine at +$407.*

 It 

should be noted, however, that this estimate did not account for the loss in consumer 

value associated with the replacement of a V6 with an inline 4-cylinder, nor did it 

account for NVH mitigation measures. It also was based on a relatively simple 

turbocharger system that would not be able to match the launch performance of the 

larger, naturally aspirated engine. Martec independently estimated the net change in 

variable cost at $437, assuming the use of a twin scroll turbo with an air-to-air intercooler 

 

*

 Based on the change in RPE for a V6 DOHC vs. I4 DOHC not including the catalyst plus $650 in 

additional variable cost for a turbo system marked up to RPE using a factor of 1.61. 

-53- 
and $111 in NVH mitigation costs. On an RPE basis, Martec’s estimate would be 

approximately $874. Although there is a 2:1 variation in the cost estimates, it does not 

affect our analysis because turbocharging w/downsizing is not cost effective relative to 

other technologies under either estimate. 

Cylinder Deactivation – In its work for NESCCAF, Martec estimated the variable cost 

increase for cylinder deactivation applied to a V6 engine at $115, which translates to an 

increase in retail price of approximately $230. Based on the cost of NVH mitigation 

measures provided by Martec, we estimate the total retail price increase to be $360 for a 

midsize car. 

Transmissions – Based on fixed and variable cost estimates from Harbour Consulting, we 

have estimated the price premium for a 5-speed automatic at $172 over a 4-speed 

automatic when the transmission is sized for a midsize car. An additional $66 is added to 

account for the mitigation of NVH issues related to the use of aggressive shift logic 

(bringing the total increase in RPE to $238). The price premium for a 6-speed automatic 

over a 5-speed automatic is estimated at $153. Martec independently estimated the 

variable cost increase for a 6-speed automatic over a 4-speed automatic at $215. On an 

RPE basis, this would be $322-$346, depending on the assumptions made about warranty 

cost. This independent estimate is in line with the $325 estimate ($172+$153) based on 

estimates provided by Harbour Consulting. 

Although early estimates of the cost for automated manual transmissions were lower than 

for conventional automatics, experience has shown that the achievement of comparable 

driveability requires features that significantly increase cost. Updated estimates 

developed by Martec put the increase in variable costs for a 6-speed, dual-clutch AMT at 

$300 to $400 over a conventional 4-speed automatic, which translates to a retail price 

increase of $483 to $644. The difference in the estimates is related to the extent to which 

measures are required to address NVH issues. We have used the lower estimate in our 

analysis. Since automated manuals are produced with completely different tooling, and 

since there has recently been substantial capital investment in new 6-speed automatic 

transmissions, analyses based on the assumed use of less expensive, automatic manual 

transmissions apply only in the 2020 and later time frame. 

Electric Power Steering and Electro-Hydraulic Power Steering – Retail price estimates of 

$82 for electric power steering and $123 for electro-hydraulic power steering (required 

for heavier vehicles) are based on variable cost estimates by The Martec Group presented 

in Appendix C of the previously referenced NESCCAF report. Martec’s variable cost 

estimates were marked up by a factor of 2.05. 

Higher Efficiency Alternator – The retail price increase for a higher efficiency alternator 

was based on a $40 variable cost increase estimate by The Martec Group in Appendix C 

of the previously referenced NESCCAF report. Martec’s variable cost estimate was 

marked up by 1.83, a factor midway between the 1.61 factor used for parts developed 

entirely by vendors and a more generally applicable 2.05 markup factor. 

-54- 
Gasoline Direct Injection-Stoichiometric – Based on detailed variable cost data obtained 

from a large-volume manufacturer using GDI, we previously estimated the RPE for GDI 

systems at $553 for a midsize car. Martec independently estimated the net change in 

variable cost at $293, $372, and $497 for “wall guided” GDI system applied to a I4, V6, 

and V8 engines, respectively. In the case of the V6, Martec estimated the cost of GDI 

itself at $256 and the cost of NVH mitigation measures at $116. Based on our 

independent analysis, 1.74 is the appropriate markup factor a GDI system. Applying that 

markup factor to Martec’s estimate of variable cost, the RPE for the V6 system would be 

$647, 17% higher than Sierra’s estimate. To be conservative, we have used our $553 

estimate for midsize cars. 

Mild Hybrid – A retail price increase of $1,886 for a mild hybrid system is based on 

Martec’s variable cost estimates prepared for the NESCCAF study for a 42-volt, 10 kW 

Flywheel-Alternator-Starter (FAS) hybrid system. Variable cost for the system was $800 

for the FAS system and $120 for a 42-volt lead-acid battery to which was applied a 

markup factor of 2.05. The markup factor would arguably be less for individual 

components; however, the integration costs associated with a system that includes 

regenerative braking would be substantial as would be the warranty costs for a relatively 

expensive lead-acid battery. This system was not given a detailed evaluation because the 

cost-effectiveness ratio was not attractive. 

Strong Hybrid – We have used the term “strong hybrid system” to refer to a system that 

has a large enough battery and motor to maximize the amount of energy that can be 

captured through the use of regenerative braking on the CAFE test procedure. (Our 

detailed vehicle simulation modeling indicates that the size of the battery in the Prius is 

adequate to recover 95% of the braking energy on the CAFE test procedures, although 

inefficiencies in the system prevent all of that energy from being used to replace energy 

provided by the combustion engine. A larger battery would not be able to further 

improve fuel economy without compromising vehicle performance.*

) Approximately 7 

kW of battery power per 1,000 pounds of vehicle test weight is necessary to maximize 

regeneration energy capture on the CAFE test procedures. (That level of power is 

associated with approximately 0.43 kWh of battery capacity per 1,000 pounds.) We 

assumed that motor/generators would be sized at 25% above peak battery power to 

account for the efficiency loss in transferring braking energy through the generator and 

inverter/converters into the battery. Based on cost estimates obtained from Martec, the 

variable cost equations provided for the flywheel/alternator/starter (FAS) style hybrids 

were $96+$502/kWh (or $96+$31/kW) for NiMH batteries; $100+$22.5/kW for 144v 

motor generators; and $70+$16.8/kW for power electronics. We used these equations in 

combination with our own estimates of the cost of brake-by-wire, electric power steering, 

electric accessory drive, and a shielded, high voltage wiring system totaling $910 variable 

cost. We then added a variable cost of $1/lb to account for offsetting half of a 64 

 

*

 In theory, a larger battery could allow the combustion engine to be further downsized while maintaining 

acceleration performance; however, the amount of energy required for hard accelerations would exceed the 

amount of energy being recovered through regenerative braking. As a result, the acceleration performance 

of the vehicle would decrease when it was being driven hard, which would create consumer acceptance and 

safety concerns. 

-55- 
lb/1,000 pounds test weight increase in vehicle weight associated with the hybrid system. 

After applying appropriate markup factors (1.61 for battery, motor/generator, and power 

electronics; 2.0 for other components), our estimated increase in RPE for a 3,300 pound 

midsize car was $5,370. 

Martec has recently completed an updated and more comprehensive analysis of hybrid 

system costs. A variable cost of $1,040 was estimated for the combination of brake-bywire, electric power steering, electric accessory drive, a shielded, high voltage wiring 

system, and an electric heater/liquid cooling loop for cabin heating when the engine is 

off. This can be compared to our $910 estimate for the same subsystems without electric 

cabin heating. Since electric cabin heating is not required, and since there is no CAFE 

credit for preserving engine-off modes during cold weather, we do not believe the 

additional cost for electric cabin heating should be included. 

Martec’s latest battery cost estimate for a midsize car is $1,150 (variable) using Li-Ion 

technology. This is based on the assumption that the cost of Li-Ion batteries will 

eventually drop to $50 per kW. Although some have estimated even lower prices at high 

production volumes, those estimates assume significant reductions in lithium prices as 

volume increases. Martec reports that sources involved in mining expect prices to 

increase at high levels of lithium demand. Martec therefore considers the $50 per kW 

estimate to be optimistic. Given the uncertainty associated with Li-Ion battery cost, we 

have continued to base our hybrid system cost estimates on NiMH technology. Based on 

estimates provided by Martec, we have increased our cost estimate for the NiMH battery 

in a midsize hybrid by $320 to account for the increase in nickel prices since our earlier 

estimate was prepared. This increases the variable cost estimate for the battery from 

$873 to $1,193. With a 1.61 markup factor applied to the variable cost, this increases the 

RPE of a midsize hybrid by $515. Our updated estimates for the average 3,226 pound 

mid-size car and 4,666 pound full-size pickup are now $5,968 and $8,632, respectively 

Martec’s latest estimate of the cost for the motor/generator and power electronics for a 

midsize hybrid is $2,388 (variable). In contrast, our previous variable estimate for these 

components was only $1,305. However, our estimate is for a system with the 

motor/generator and power electronics sized for a maximum of 29 kW. Martec’s 

estimate is for a more aggressive hybrid system with 50 kW capacity. The percent 

increase in cost for the system assumed by Martec is roughly proportional to the percent 

increase in power. We have therefore continued to use our earlier estimates for the cost 

of the lower powered system. However, as noted previously, higher capacity 

motor/generators are used on several hybrid vehicles that are already on the market. Our 

estimated increases in price for these higher powered hybrid systems would be 

approximately $7,000 for mid-size cars and $10,000 for full-size pickup trucks. 

Diesel Engine – Based on cost estimates obtained from Harbour Consulting, we 

estimated the net change in retail price associated with replacing a naturally aspirated V6 

engine to a turbocharged V6 Diesel engine. Table 6-2 summarizes the information 

provided by Harbour for V6 engines and translates it to RPE. 

-56- 
Table 6-2 

Harbour and Associates Engine Cost Estimates a

Cost Element 

OHV V6 

Gasoline 

DOHC V6 

Gasoline 

SOHC V6

Diesel Increment 

Major Component Parts $791 $1,142 $2,674 

Labor (Burdened) $208 $208 $338 

Fuel System $90 $90 $910 

Aftertreatment $195 $195 $896b

Total Variable Costs $1,284 $1,635 $4,818 

Amortized Fixed Cost $256 $273 $321 

Retail Price Equivalentc $2,480 $3,073 $8,274 $5,201-$5,794

a Excludes ECM, alternator, power steering pump 

b Based on Martec Group estimate of $1,000 incremental cost for V8. 

c Variable cost plus engineering, facilities, and tooling marked up by 61%.

As noted in a footnote to the table, The Martec Group has estimated the incremental 

variable cost of a vendor-supplied Diesel aftertreatment system at $1,000 for V8 

engines.*

 (We reduced the incremental cost for aftertreatment systems by 25% to 

represent V6 engines.) Using this estimate in conjunction with Harbour’s estimates of 

other costs leads to an estimated RPE for a V6 Diesel engine of $8,274. Depending on 

whether the gasoline engine being replaced is of an overhead valve or overhead cam 

design, the incremental variable cost is $3,183-$3,534. After accounting for fixed cost 

and the application of markup factors, the RPE increase for the Diesel is $5,201-$5,794. 

Martec has recently prepared an independent estimate of the cost difference between 

Diesel and gasoline engines. Using a DOHC gasoline engine as the baseline, the variable 

cost increase for the Diesel was estimated to be $3,497, $314 higher than our estimate. 

Examining the detail provided by Martec, the difference is explained by Martec’s most 

recent estimate for Diesel aftertreatment being $424 higher than the $896 estimate we 

used. This increase is related to higher platinum group metal prices since Martec’s 

earlier aftertreatment cost estimate on which we relied. On an RPE basis, the higher 

aftertreatment costs translate to an increase in RPE of $683. We have increased our 

original Diesel cost estimate of $5,515 by this amount, bringing it to $6,198. 

6.3 Cost-Effectiveness

Table 6-3 shows the cost-effectiveness ratio (dollars per percent reduction in fuel 

consumption) calculated by dividing the price increase in Table 6-1 by the reduction in 

 

*

 See Appendix C, “Reducing Greenhouse Gas Emissions from Light-Duty Motor Vehicles,” Northeast 

States Center for a Clean Air Future, September 2004 

-57- 
fuel consumption in Table 5-2. Generally, technologies would be deployed in order of 

increasing cost-effectiveness ratio. However, certain technologies are either mutually 

exclusive or much less effective when employed in combination. For example, the fuel 

economy benefits associated with Diesel engines and gasoline engines with variable 

valve lift and timing are not available simultaneously. One technology must be removed 

before the other is added. Note that Diesel engines end up not being assumed in our 

analysis because hybrid systems applied to gasoline vehicles provide slightly higher fuel 

economy improvement at slightly lower cost. There are other reasons why a 

manufacturer may opt for Diesels instead of hybrids, particularly in trucks; the net price 

increase associated with that approach, however, would not be fundamentally different 

than our estimates based on hybrids. 

Table 6-3 

Long-Term Estimates of Cost-Effectiveness for 

Various Technologies Applied to a Mid-Size Car and Pickup Truck 

$/% Reduction 

Mid-Size Car Pickup Truck 

5-Speed Automatic w/ASL vs. 4-Speed $28 $37 

Reduced Parasitics I $28 $34 

Electric/Electro-Hydraulic Power Steering $47 $136 

6-Speed AMT vs. 4-Speed/5-speed $48 / $61 $57 / $68 

Cylinder Deactivation $48 $50 

Reduced Parasitics II $61 $75 

Ultra-Light Steel Body and Suspension $63 $137 

Dual Overhead Cams vs. Overhead Valves $69 n/a 

Higher Efficiency Alternator $77 $155 

Continuously Variable Valve Lift & Timing $79 $89 

Discrete Variable Valve Lift & Timing $82 $94 

Gasoline Direct Injection-Stoichiometric $94 $110 

Strong Hybrid (7 kW battery power/1000 lbs.) $208 $391 

Mild Hybrid (42-volt, 10 kW) $259 $608 

Diesel Engine (turbocharged, direct injection) $291 $407 

Aluminum Body vs. Ultralight Steel $299 $665 

Turbocharging (with engine resize) - $1,676 

### 

-58- 
7. VEHICLE SIMULATION MODELING 

Starting with the baseline fleet characteristics for model year 2006, vehicle simulation 

modeling was performed to evaluate the improvement in fuel economy associated with 

various combinations of design changes applied to 25 different vehicle categories for 11 

different manufacturers. The modeling approach and key elements of the simulation 

modeling runs are described in this section. 

7.1 Modeling Approach

Table 7-1 lists the technology combinations that were modeled based on those deemed to 

be cost-effective under nationwide federal CAFE compliance. As shown in the table, the 

deployment sequence was slightly different for pickup trucks and SUVs than for other 

vehicles because 2-valve/OHVengines are retained when the vehicle category has a 

relatively high towing capacity. The order in which the technologies were applied is 

consistent with the order presented in Table 7-1 (i.e., top to bottom = first to last). After 

each technology, the notation in italicized parentheses indicates whether the fuel 

economy benefits of the technology were modeled using the VEHSIM vehicle simulation 

model (V) or by a simple off-model multiplicative adjustment (O). 

Table 7-1 

Technology Combinations Modeled by Vehicle Type for 

Compliance with Federal EISA CAFE Standards 

Passenger Cars / Vans Pickup Trucks / SUVs 

5-Speed Automatic Replaces 4-Speed (V) 5-Speed Automatic Replaces 4-Speed (V)

Lower Friction/Parasitics (O) Lower Friction/Parasitics (O)

6-Speed AMT Replaces 5-Speed Automatic (V) 6-Speed AMT Replaces 5-Speed Automatic (V)

Electric Power Steering (V) Cyl. Deactivation on 2V engines with >4 cyl. (V)

Lower Friction/Parasitics-2 (O) Lower Friction/Parasitics-2 (O)

Major Weight Reduction with Ultralight Steel (V) Major Weight Reduction with Ultralight Steel (V)

Improved Alternator/Charging (V) Improved Alternator/Charging (V)

2V engines replaced with 4V engines (V) Electro-Hydraulic Power Steering (V)

All engines get CVVLT (V) 4V engines get CVVLT (V)

Gasoline Direct Injection on CVVLT engines (V) Gasoline Direct Injection on CVVLT engines (V)

Strong Hybrid (V) Strong Hybrid (V)

Additional Weight Reduction using Aluminum (V) Additional Weight Reduction using Aluminum (V)

Notes: (V) = applied using the VEHSIM vehicle simulation model 

 (O) = applied using an off-model multiplicative adjustment 

-59- 
As indicated in Table 7-1, most of the technologies were modeled using the VEHSIM 

vehicle simulation model. Use of the model ensured that interaction between 

technologies would be properly accounted for and the benefits of reduced throttling 

losses would not be double-counted. (Throttling losses are the work done to draw air into 

the engine across the throttle. Because many of the technologies considered reduce 

throttling losses, the benefits of an individual technology are reduced when it is applied 

in combination with other technologies that also reduce throttling loss.) In the case of 

parasitic loss reductions, where throttling losses were not significantly affected and where 

the impact was small, fuel economy benefits could be correctly accounted for with an offmodel adjustment. 

A basic description of the VEHSIM model and its operation was presented earlier in 

Section 5. As explained there, specific vehicle, engine, and drivetrain characteristics are 

input to the model along with a second-by-second driving cycle over which vehicle 

operation is simulated and fuel economy/consumption is calculated. 

VEHSIM runs were set up and executed for each of 11 manufacturers and for each of the 

25 vehicle categories used to classify the vehicle fleet that were described earlier in 

Section 3. A total of 139 sets of manufacturer/vehicle category runs were conducted. 

(Not all 25 categories are represented in an individual manufacturer’s fleet.) 

Internal Model Corrections – VEHSIM’s engine maps and drivetrain inputs are based on 

a 2WD vehicle and produce fuel economy estimates assuming a fully warmed-up vehicle. 

Thus, multiplicative correction factors were programmed into the model to account for 

4WD vehicle simulations and to correct simulated urban fuel economy to reflect the 

hot/cold start weighting (43% and 57%, respectively) in the Federal Test Procedure 

(FTP). Each of these adjustments is discussed below. 

4WD Adjustment – For all 4WD vehicle category simulations, a correction factor was 

applied within the model to represent 4WD fuel consumption based on reported CAFE 

differences between similar 2WD and 4WD models. Relative differences in CAFE fuel 

consumption between 2WD and 4WD versions were found to be very similar across 

manufacturers and vehicle types. On average, 4WD CAFE fuel consumption was 2.8% 

higher than 2WD, based on a comparison of 223-paired vehicle model, engine, and 

transmission combinations after accounting for only the weight difference. 

Hot-to-FTP Adjustment – FTP bag-specific fuel economy data from EPA’s Mobile 

Source Observation Database (MSOD) were queried to calculate an adjustment factor to 

translate hot start urban fuel economy simulated by VEHSIM to FTP weighted 

conditions. This adjustment factor was determined to be 1.025 for recent model year 

vehicles and was applied internally within VEHSIM to produce FTP urban, rather than 

hot urban fuel economy. (The same adjustment factor was also applied to the Cal-Urban 

cycle fuel economy simulated within the model.) 

-60- 
7.2 VEHSIM Modeling

The VEHSIM model was programmed to simulate operation and calculate fuel 

economy/consumption over the official EPA City and Highway driving cycles as well as 

more representative (“real world”) California Urban and Rural driving cycles that better 

represent current in-use driving patterns. (Speed traces for each of these cycles were 

presented and discussed earlier in Section 5.) Manufacturer and vehicle category-specific 

VEHSIM modeling runs were performed in two separate stages, as summarized below. 

1. 2006 Baseline Runs – These simulations were based on MY2006 U.S. salesweighted characteristics (weight, engine size/power, transmission mix, drag 

coefficient, frontal area, rolling resistance, etc.) of the baseline fleet. (These 

detailed characteristics are listed by manufacturer and vehicle category in 

Appendix A.) 

2. Future Technology Runs – This series of simulations contains incrementally 

added technologies listed earlier in Table 7-1 to the 2006 Baseline vehicle 

characteristics. 

The VEHSIM modeling done for the 2006 Baseline cases used “blended” engine maps, 

which were constructed by averaging engine maps provided to Sierra by several largevolume manufacturers. Separate maps were created to represent OHC and OHV engines. 

None of the engines represented in the baseline engine maps used cylinder deactivation, 

cam phasers, or variable valve lift and timing. (Penetration of these engine technologies 

in the 2006 Baseline is described later in this sub-section under “Baseline Technology 

Penetration Adjustments.”) 

All of the maps were for regular fuel (87 R+M/2 octane rating) engines. All maps were 

adjusted to reflect an assumed 2% reduction in engine friction from the 1998 time period 

when the maps were developed. (This adjustment reflects lubricant changes and other 

minor modifications.) The maps were adjusted to match the displacement of the vehicles 

being simulated using an engine “resize” routine built into the VEHSIM model. 

Transmission gear ratios were set to represent the actual gearing of high-volume models. 

Four-speed automatic transmission shift logic was configured to represent typical current 

shift logic provided to Sierra by high-volume automobile manufacturers. The shift logic 

used for 5- and 6-speed automatics was relatively aggressive (i.e., early upshifts). 

Each of the up to 25 vehicle categories for each manufacturer was modeled with two 

different types of engines (OHC and OHV). Up to five different types of transmissions 

were simulated: 

1. 5-speed manual (6-speed manuals were treated as 5-speeds); 

2. 4-speed automatic, 

3. 5-speed automatic, 

4. 6-speed automatic (7-speed automatics were treated as 6-speeds), and 

5. 6-speed AMTs (continuously variable transmissions were treated as AMTs). 

-61- 
Inputs to the model that identify the fleet fractions by engine and transmission type for 

each manufacturer/vehicle category combination are then used within VEHSIM to 

compute sales-weighted average fuel economy estimates composited across engines and 

transmissions. 

Baseline Technology Penetration Adjustments – As noted earlier, baseline simulations 

were based on the basic blended OHC and OHV gasoline engine maps. (VEHSIM’s 

internal logic expects baseline engines to be based on standard OHC or OHC blended 

maps.) Thus, the baseline simulations by manufacturer and vehicle category had to be 

adjusted to account for the fact that the current fleet now contains sufficient fractions of 

cylinder deactivation, variable valve lift and timing and strong hybrid technologies to 

significantly affect average fuel economy. These technology penetrations across all 

manufacturers were summarized and listed earlier in Table 3-4. 

To account for their effects on simulated baseline fuel economy, the individual 

technology benefits shown earlier in Table 5-2 were used to generate adjustment factors 

for each manufacturer and vehicle category that represented the combined effects of these 

technologies given their penetration. The individual technology benefits shown in Table 

5-2 were listed on a fuel consumption basis. They were converted to fuel economy

adjustment factors and combined with penetration rates of each of the three individual 

technologies by manufacturer and vehicle category. (Note that the penetration 

percentages shown earlier in Table 3-4 were compiled for all manufacturers. These 

adjustment calculations were performed using penetration rates by individual 

manufacturer and vehicle category that are contained in Appendix A.) 

In performing these adjustments, variable valve lift and timing technology contained in 

the baseline was assumed to be discrete, not continuously variable type systems. The 

penetration adjustments are thus based on the discrete variable valve benefit of 6.7% (on 

a fuel consumption basis). 

Although not shown in Table 3-4, Diesel-fueled baseline vehicle fractions were also 

compiled and applied to the turbocharged, direct-injection Diesel engine fuel 

consumption reduction of 21.5% shown in Table 5-2 to incorporate a similar adjustment 

for baseline Diesel use. 

Finally, although Table 3-4 also listed penetrations of AMT/CVT transmission in the 

baseline, their effects were directly modeled in VEHSIM. Thus, no multiplicative 

adjustments to the baseline simulations were required for these technologies. 

Baseline Comparisons to Reported CAFE – To ensure VEHSIM modeling results were 

consistent with reported fuel economy, the combined City/Highway fuel economy for the 

2006 Baseline fleet was compared to reported CAFE results. These comparisons were 

performed using sales-weighted composites of each of the 25 modeling categories across 

all manufacturers and are presented below in Table 7-2. Table 7-2 also shows the 

advanced technology penetration adjustment factors applied to each vehicle category. 

-62- 
(Note that the uncorrected VEHSIM fuel economy is not shown in the table. The values 

in the “Modeled” column include the adjustment for advanced technology penetrations.) 

Table 7-2 

Comparison of Reported and Simulated MY2006 Baseline Fuel Economy by 

Individual Vehicle Category Across All Manufacturers 

CAFE Fuel Economy (mpg)

Vehicle Category Code 

Adv. Tech 

Penetration Reported Modeled 

Relative

Error (%)

Mini Cars MINI 1.0795 33.62 43.22 +28.6%

Subcompact Sedans/Wagons SCSW 1.0160 33.33 35.80 +7.4%

Compact Sedans/Wagons CSW 1.0341 34.21 35.51 +3.8%

Mid-size Sedans/Wagons MSW 1.0108 29.63 30.69 +3.6%

Large Sedans/Wagons LSW 1.0021 27.48 25.92 -5.7%

Small Coupes/Convertibles SCC 1.0293 27.35 32.52 +18.9%

Mid-size Coupes/Convertibles MCC 1.0097 27.15 28.29 +4.2%

Large Coupes/Convertibles LCC 1.0206 27.52 24.47 -11.1%

Small Sports/Luxury Sedan/Wagon SSL 1.0324 26.11 28.60 +9.5%

Mid-size Sports/Luxury Sedan/Wagon MSL 1.0213 25.88 27.27 +5.4%

Large Sports/Luxury Sedan/Wagon LSL 1.0164 23.64 23.07 -2.4%

Sports/GT Cars SC 1.0110 26.62 30.13 +13.2%

Hi-Performance Sports/GT Cars HPSC 1.0158 23.68 23.53 -0.6%

Small Vans SVAN 1.0248 24.57 24.35 -0.9%

Large Vans LVAN 1.0047 19.24 17.00 -11.7%

Small 2WD Pickups S2P 1.0000 25.05 26.40 +5.4%

Small 4WD Pickups S4P 1.0000 21.84 23.07 +5.6%

Large 2WD Pickups L2P 1.0040 20.14 19.47 -3.3%

Large 4WD Pickups L4P 1.0126 19.37 18.21 -6.0%

Small 2WD SUVs S2SU 1.0000 28.95 31.17 +7.7%

Small 4WD SUVs S4SU 1.0332 22.47 24.24 +7.9%

Mid-Size 2WD SUVs M2SU 1.0174 24.73 25.21 +1.9%

Mid-Size 4WD SUVs M4SU 1.0356 22.75 23.17 +1.8%

Large 2WD SUVs L2SU 1.0042 19.68 19.36 -1.6%

Large 4WD SUVs L4SU 1.0042 18.83 17.97 -4.6%

Sales-Weighted Averages 25.09 25.21 +0.5%

As shown in Table 7-2, modeled fuel economy averaged across all manufacturers agrees 

within 6% of reported CAFE levels for most of the individual categories, and essentially 

all of the categories with high sales volumes (e.g., mid-size sedans, small vans, large 

pickups, mid-size SUVs, etc.). Given the use of blended engine maps that were used to 

model categories with low- and high-performance engines, the modeled results are in 

very good agreement with reported values. The overall relative error sales-weighted 

across all categories was 0.5% as highlighted at the bottom of Table 7-2. 

-63- 
Maintaining Constant Performance – The VEHSIM modeling was conducted in a manner 

that preserved the acceleration performance of the baseline fleet (represented using 

simulated 0-30 mph and 0-60 mph times). Benchmark performance times were 

established by manufacturer, vehicle category, engine type (OHV vs. OHC) and 

transmission from the baseline runs and are internally stored within VEHSIM during a 

future technology build-up simulation. 

Only under certain conditions was performance not maintained at the individual 

transmission level. For example, if a manufacturer/vehicle category included only 5-

speed manuals and 5-speed automatics in the baseline, in the future technology step for 

adding 6-speed automatics the resized engine for the manual was assumed to be that of 

the automatic. (This logic was intended to represent instances where manuals and 

automatics were likely to exist on the same engine and when a resize would be done to 

maintain equal performance with a new automatic. In that case, the resized engine would 

be used with the manual also.) 

To maintain towing performance, acceleration performance for pickup trucks and SUVs 

was maintained with added towing weight of 7,900 lb and 5,500 lb, respectively. This 

was accomplished in the VEHSIM modeling by executing “parallel” model runs for these 

vehicle categories that included the added towing loads and maintaining acceleration 

performance (by engine resizing) using these added load runs. 

In modeling advanced hybrid technology, further downward resizing of the internal 

combustion engine to maintain acceleration performance was applied for passenger cars 

and minivans to account for the increase in acceleration provided by the electric motor. 

For pickups, no resizing was performed because of the need to maintain towing capacity 

(towing depletes the battery and makes it impossible to rely on the electric motor). For 

SUVs, resizing was simulated for half of the fleet to reflect the mixed towing use of this 

category of vehicles. 

Future Technology Spreadsheets – All the manufacturer-specific VEHSIM modeling runs 

for a given vehicle category were assembled into an Excel workbook with the following 

naming convention: 

FutureRuns_ V_S.xls

where V is the vehicle category (e.g.., MSW, SV, L2P, M4SU, etc.) and S is a simulation 

set that includes or excludes certain weight reduction technologies. (Due to the 

uncertainty in where each weight reduction measure “fit” in a cost-effective technology 

deployment sequence, multiple sets of model simulations were executed with and without 

these technologies so their proper order could be determined at a later point in the 

workflow.) These “Future Runs” workbooks had separate tabs (spreadsheets) for each 

manufacturer producing vehicles within the vehicle category. These spreadsheets contain 

the “composited” results of multiple simulations by engine and transmission type for a 

-64- 
given manufacturer and vehicle category that show simulated fuel economy on both a 

CAFE and real-world cycle basis for each step in the technology build-up. 

Table 7-3 shows an example of one of the summary spreadsheets for Chrysler’s Compact 

Sedan/Wagon (CSW) simulations. Each technology step is identified in the “Case” and 

“Description” columns. (Case-00 is the baseline step.) Fuel economy (both CAFE and 

real) values are shown in the tan shaded “EPA-Wtd” and “Cal-Wtd” columns. Changes 

in fuel economy and fuel consumption relative to the baseline are shown in the “%FE” 

and “%FC” columns to the right of these. Selected vehicle specifications (test weight and 

engine size) and performance measures (gradeability,*

 0-30 and 0-60 times) are shown in 

the rightmost columns. 

4

5

6

7

8

9

10

11

12

13

14

15

16

AB C D E F G H N O P Q R S T U VW

Test Displ

Line # Case Description Urban Highway EPAWtd %FE %FC Cal-Urb Cal-Rur CalWtd %FE %FC Wt (lb) (cid) Gradab 0-30 0-60

6 CSW-00 Base 27.943 37.786 31.654 - - 25.360 28.014 25.820 - - 3,419 125.6 1.312 3.646 10.121

11 CSW-01 ASLA5 27.955 37.759 31.653 0.0% 0.0% 25.372 28.010 25.829 0.0% 0.0% 3,419 126.0 1.385 3.599 10.026

16 CSW-02 AMT6 28.912 38.016 32.404 2.4% 2.3% 26.083 28.334 26.479 2.6% 2.5% 3,419 125.1 1.212 3.510 10.032

21 CSW-03 EPS 29.517 38.696 33.044 4.4% 4.2% 26.478 28.733 26.875 4.1% 3.9% 3,419 124.1 1.231 3.510 10.032

26 CSW-04 ULS 30.562 39.627 34.069 7.6% 7.1% 27.287 29.365 27.655 7.1% 6.6% 3,268 119.4 1.160 3.510 10.031

31 CSW-05 IALT 30.962 39.880 34.426 8.8% 8.1% 27.466 29.501 27.827 7.8% 7.2% 3,268 119.2 1.182 3.508 10.032

36 CSW-06 2V>4V 30.961 39.879 34.425 8.8% 8.0% 27.466 29.501 27.827 7.8% 7.2% 3,268 119.2 1.183 3.508 10.031

41 CSW-07 CVVLT 34.401 42.396 37.591 18.8% 15.8% 28.464 29.941 28.730 11.3% 10.1% 3,268 105.4 1.211 3.508 10.031

46 CSW-08 GDI 36.111 43.968 39.269 24.1% 19.4% 29.464 30.823 29.710 15.1% 13.1% 3,268 98.5 1.220 3.510 10.032

51 CSW-09 AHYB 48.641 44.789 46.829 47.9% 32.4% 33.923 31.235 33.383 29.3% 22.7% 3,372 75.9 3.634 4.662 13.872

56 CSW-10 ALM 50.941 46.219 48.702 53.9% 35.0% 35.182 31.997 34.535 33.8% 25.2% 3,133 71.4 1.105 4.650 13.871

FTP Cycle Fuel Economy New California Cycle Fuel Economy

Table 7-3 

Sample Technology Combination Simulation Summary for Chrysler CSWs 

The simulation modeling results in these “Future Runs” spreadsheets were then combined 

with cost data for each technology and used to calculate the technology requirements and 

costs to comply with EISA as discussed in the next section. 

### 

 

*

 Gradeability as defined in these VEHSIM outputs represents the percentage upgrade for which a vehicle 

can maintain the top speed of the EPA Highway cycle (about 57 mph) without downshifting from top gear. 

-65- 
8. COMPLIANCE ANALYSIS 

The final step in the analysis consisted of combining the future technology simulation 

results described in the preceding section with retail price-equivalent technology costs 

and calculated 2020 fuel economy targets by manufacturer under new EISA-based CAFE 

standards to determine the amount of technology required and the costs to comply with 

those standards. This compliance analysis is documented in this section of the report. In 

addition to calculation of costs and technology needed, a “payback” analysis of the net 

costs given certain assumptions such as fuel price and payback period is discussed in this 

section. 

8.1 Technology Deployment

The first element in the compliance analysis consisted of the development of separate 

spreadsheets for each manufacturer that contained the technology deployment or “supply 

curve” calculations for each vehicle category in that manufacturer’s fleet. These supply 

curves calculate the fuel economy and incremental cost-effectiveness (in dollars per 

percent change in fuel consumption) at each step in the build-up of modeled technologies. 

The technologies were generally*

 ordered by increasing incremental cost-effectiveness. 

These cost-effectiveness (CE) spreadsheets were named using the following convention: 

CE_HR6_A_M.xls 

Where: A is the specific set of attribute-based standards (FP for footprint, etc.) 

and 

M is the manufacturer code (B=BMW, C=Chrysler, etc.). 

The cost-effectiveness spreadsheets were loaded with simulation modeling results from 

the “Future Runs” spreadsheet described in the preceding section. Within the CE 

spreadsheets, several other sets of data were loaded into a sheet called “LOOKUPS” and 

 

*

 It quickly became apparent during the analysis that most, if not all, manufacturers would need to get near 

the end of the technology supply curve to comply with the EISA-based targets. Since the cost-effectiveness 

for several technologies were bunched within a fairly narrow range near the start of the supply sequence, 

we were less concerned with perfectly ordering each supply curve sequence by manufacturer and vehicle 

category (representing well over 100 unique sequences). The sequences were checked to ensure they 

followed increasing incremental cost-effectiveness near the end of the curves (where compliance would be 

met). 

-66- 
were used in calculating incremental cost-effectiveness. These data included the 

following: 

• Sales Fractions, Weights and Other Specifications – Baseline sales mixes, curb 

weights, 2V and 4V engine fractions, transmission type fractions, fleet fractions 

of vehicles with more than 4 cylinders and advanced technology penetration 

fractions by manufacturer for each vehicle category; 

• EISA-Based New CAFE Targets – Calculated 2020 fuel economy targets by 

manufacturer and sub-fleet (cars and trucks) based on EISA implementation; and

• Base Technology Costs – Individual technology costs based on a “reference” midsize sedan and factors for each technology that indicate how strongly their costs 

are estimated to vary by weight. 

The sales and fleet fractions are used to calculate the fraction of a modeled vehicle 

category for a given manufacturer that is affected by each technology. For example, Ford 

mid-size sedans/wagons (MSWs) are 39.5% 2V engines and 65.2% engines with over 4 

cylinders. Since cylinder deactivation is applied only on 2V engines with over 4 

cylinders, the Ford MSW fleet fraction “eligible” for cylinder deactivation is 25.7% 

(0.395 × 0.652). 

The advanced technology penetration fractions are used to account for the amounts of 

advanced technology already in the baseline. For example, assume the fuel economy 

benefit of a particular technology is 10%, but the baseline fleet (for a given manufacturer 

and vehicle category) already contained 20% of that technology on a sales basis. This 

20% technology penetration fraction is used within the CE spreadsheet to adjust the 

simulation modeling outputs (which reflect the full 10% fuel economy improvement) to a 

discounted value of 8% improvement [10% × (1-20%)]. 

The EISA CAFE targets are used later to determine the point on the technology supply 

curves where compliance with the new EISA standards would occur. Finally, the base 

technology costs and scaling factors are used to calculate individual technology costs for 

each manufacturer and vehicle category based on the relative difference between the 

reference vehicle weight (3,226 lb) and that of each individual manufacturer and vehicle 

category. 

These base costs and weight scaling factors are shown in Table 8-1. As shown, all 

technologies except PARA2 are assumed to vary with weight. (Note that the advanced 

hybrid cost is in dollars per 1,000 lb curb weight.) The costs used in this analysis are 

long-term costs and do not include any stranded costs. 

-67- 
Table 8-1 

Base Long-Term Technology Costs 

(Based on Midsize Sedan/Wagon with 3,226 lb Reference Weight) 

Tech Description 

Base 

Cost 

Wt Scale 

Tech Code Factor 

ASLA5 A5 w/Aggressive Shift Logic over A4 w/o ASL $238 50% 

PARA Lower Eng. Fric./Parasitics $14 50% 

PARA2 Lower Eng. Fric./Parasitics-2 $122 0% 

CD2V(Deac) Cylinder Deactivation on 2V Engines $360 50% 

CVVLT CVVL&T on 4V After 2V to 4V $899 50% 

CVVLT4 CVVL&T on 4V $899 50% 

EPS Electric Power Steering $82 50% 

EHPS Electro-Hydraulic Power Steering $123 50% 

ULS UL Steel vs. closures only, 50% Penetration $417 100% 

DOHC DOHC V6 vs OHV V6 $593 50% 

IMPALT Imp. Alternator/Charging $73 50% 

AMT6 6-Speed AMT vs. 5-Speed Automatic $311 50% 

DVGDI Gasoline Direct Injection on 4V DVVLT $553 50% 

CVGDI Gasoline Direct Injection on 4V CVVLT $553 50% 

ALM Aluminum Incremental to ULSteel $1,596 100% 

$1,850 a AHYB Advanced Hybrid w/Regen Braking 100% 

 a Advanced hybrid cost shown is in dollars per 1,000 lb curb weight 

The weight scaling factor represents the amount of variation in cost for a given change in 

weight. For example, assume a technology is applied to a 4,000 lb vehicle with a base 

cost of $100 and a 50% weight scale factor. The weight-scaled technology cost is then 

calculated as follows: 

Scaled Cost = Base Cost × [1 + ((TechWt/RefWt) – 1) × ScaleFactor] 

= $100 × [1 + ((4000/3200) – 1)×50%] 

= $112.50 

Below the base costs in the LOOKUPS sheet, a supplemental set of factors is used to 

discount costs of the major weight reduction measures (ultralight steel and aluminum) 

when applied to vehicle categories other than passenger cars. The “% of MSW Wt Red” 

row shows the relative reduction of each weight measure available on other vehicle 

types (vans, pickups, and SUVs). (For example, pickup trucks get a lower percentage 

weight reduction for aluminum because they retain body-on-frame construction and 

therefore do not achieve as great a reduction in weight as can be achieved with a unibody 

passenger car.) The next row—“Discount Factor”—is used to account for the fact that 

-68- 
-69- 

roughly half of the benefits of ultralight steel are already being achieved in the baseline 

fleet. Thus, the available benefits (and costs) beyond the baseline are discounted by 50%. 

(The LOOKUPS sheet also contains annual mileage accumulation rates and assumed fuel 

prices, tax and discount rates, and “rebound effect” factors used to calculate net 

technology costs and payback periods as discussed later in Section 8.3.) 

The data tabulation in the LOOKUPS sheet was then used in conjunction with the vehicle 

simulation modeling data (loaded from the “Future Runs” spreadsheets) to generate 

technology deployment sequences for each vehicle category for a given manufacturer. 

(There are 25 individual deployment sheets within each spreadsheet file, one for each 

vehicle category.) 

Table 8-2 shows the layout of the deployment sequence for Chrysler midsize 

sedans/wagons (MSW) under a footprint-based new CAFE standard. (This sheet is 

named “MSW” in the spreadsheet file.) Manufacturer- and vehicle category-specific 

costs are shown in the upper portion of Table 8-2 (in Rows 11 through 33 of the 

spreadsheet). These costs (shown in Column F of the spreadsheet) have been weight 

scaled based on the relative difference in curb weight between Chrysler MSWs and the 

reference weight. Column J contains the calculated fraction of the vehicle category for 

which each technology is applicable. 

The bottom portion of Table 8-2 (Rows 40-52) shows the technology deployment 

sequence beginning from the baseline. Columns A and B list each technology. Columns 

D through F contain logic that determines whether the technology benefit is being 

supplied from VEHSIM modeling or a simple off-model adjustment. (The logic accounts 

for the fact that off-model adjustment effects can accumulate as additional off modelbased technologies are deployed along the sequence.) 

Where the technology benefit has been modeled using VEHSIM, Column G contains the 

CAFE (combined City/Highway) fuel economy from the earlier modeling run 

spreadsheets. Column H shows the technology benefit modeled by VEHSIM. Column I 

is used to represent the technology benefit accounting for off-model adjustments. 

Column J adjusts the fuel economy to account for advanced technology penetrations 

already reflected in the baseline as described earlier. (In this example for Chrysler 

MSWs no advanced penetrations have occurred, so the results in Column J are identical 

to those in Column I.) Column K is used to “fill” either actual or specially coded missing 

values that enable composite calculations across multiple vehicle categories (and 

accounts for instances where not all 25 vehicle categories are populated for a given 

manufacturer). Finally, Column L contains sales-weighted composite fuel economy for 

either all passenger car or light-duty truck categories for comparison to federal CAFE 

standards in calculating compliance. The composite fuel economy calculated in Column 

L spans multiple sheets in the workbook. For example, the passenger car composite is 

calculated from the MINI, SCSW, CSW, MSW, LSW, SCC, MCC, SCC, SSL, MSL, 

LSL, SC, and HPSC sheets. 
1

23456789

10111213141516171819202122232425262728293031323334353637383940414243444546474849505152

AB C D E F G H I J K L M N O P Q 

Code: C

Category: MSW

SubFleet: CarsCat Index: 4

SubFleet Index: 26

Manufacturer: Chrysler

Affected Vehicle

Sub Fleet Category Baseline

Tech Code Technology Description Source CAFE Real Cost CAFE Real Fraction Fraction AdvTech? SubFleet Category

WT1 Minimal Weight Reduction -0.84% -0.83% $13 $15 $15 1.000 1.000

ASLA5 A5 with ASL vs. A4 w/o ASL V -1.79% -1.99% $236 $132 $119 0.254 1.000

PARA Lower Eng. Fric./Parasitics O -0.50% -0.50% $14 $28 $28 1.000 1.000

PARA2 Lower Eng. Fric./Parasitics-2 O -2.00% -2.00% $121 $61 $61 1.000 1.000

CD2V Cylinder Deactivation on 2V V -8.61% -4.98% $358 $42 $72 0.056 0.000 CDCT 0.894 1.000 

CVVLT4 CVVL&T on 4V only V -12.70% -7.40% $893 $70 $121 0.879 1.000 Full Relative Benefit of 

CVVLT CVVL&T on 4V after 2V to 4V V -12.70% -7.40% $893 $70 $121 1.000 1.000 VVLT 0.000 0.000 Benefit Adjusted for DVVLT in B

EPS Electric Power Steering V -1.50% -1.10% $81 $54 $74 1.000 1.000

EHPS Electro-Hydraulic Power Steering V -1.50% -1.10% $122 $81 $111 1.000 1.000

ULS UL Steel vs. closures only, 50% penetration V -4.99% -4.73% $206 $41 $43 1.000 1.000

DVVLT4 DVVL&T on 4V -6.70% -4.60% $515 $77 $112 0.879 1.000

DOHC DOHC V6 vs OHV V6 V -8.70% -7.37% $589 $68 $80 0.121 0.000

IMPALT Imp. Alternator/Charging V -1.00% -1.00% $73 $73 $73 1.000 1.000

SCDSL Supercharged Diesel -11.30% -8.50% $5,480 $485 $645 1.000 1.000

AMT6 6-Speed Automated Manual w/ASL, EL V -3.74% -3.08% $309 $83 $100 0.647 1.000 AMT 0.668 1.000

ASLA6 6-Speed Auto w/ASL -0.92% -1.99% $152 $165 $76 0.647 1.000

ALM Aluminum Incremental to ULSteel V -5.87% -5.70% $1,576 $268 $276 1.000 1.000

MHYB 42-volt Hybrid Motor Assist -5.98% -2.40% $1,862 $311 $776 1.000 1.000

CVGDI Gasoline Direct Injection on 4V CVVLT V -5.14% -3.71% $549 $107 $148 1.000 1.000

TURB87 Turbocharging, 87 octane -0.27% -2.11% $815 $3,018 $386 1.000 1.000

AHYB Advanced Hybrid w/Regen Braking V -26.50% -24.70% $5,893 $222 $239 1.000 1.000 HYB 1.000 1.000

A5 A5 vs. A4 w/o ASL $171 - - 0.254 1.000

Chrysler MSW 2006 Baseline Actual: 28.785 Existing Federal CAFE Target -- Chrysler Cars: 27.500

Chrysler MSW Adv Tech Penetration Factor: 1.0000 New Federal CAFE Target -- Chrysler Cars: 37.901

Chrysler MSW Sales Percentage: 3.12% Filled Filled Sales-Wtd Filled

Tech VEHSIM VEHSIM Modeled MSW MSW Car VEHSIM VEHSIM Modeled MSW Sequence F

Code Technology Description %PhaseIn Source Increment Accum CAFE FE CAFE FE CAFE Adj CAFE Adj CAFE Adj CAFE Real FE Real FE Real Adj Real Number Ba

BASE MSW 2006 Baseline - - 1.000 1.000 30.846 30.846 30.846 30.846 30.846 27.326 25.987 25.987 25.987 25.987 0 

ASLA5 A5 with ASL vs. A4 w/o ASL 100.0% V 1.000 1.000 32.304 32.304 32.304 32.304 32.304 27.632 26.782 26.782 26.782 26.782 1 

PARA Lower Eng. Fric./Parasitics 100.0% O 1.005 1.005 32.304 32.304 32.466 32.466 32.466 27.771 26.782 26.782 26.917 26.917 2 

AMT6 6-Speed Automated Manual w/ASL, EL 100.0% V 1.005 1.005 33.635 33.635 33.804 33.804 33.804 28.454 27.870 27.870 28.010 28.010 3 

EPS Electric Power Steering 100.0% V 1.005 1.005 34.244 34.244 34.416 34.416 34.416 28.909 28.293 28.293 28.435 28.435 4 

PARA2 Lower Eng. Fric./Parasitics-2 100.0% O 1.020 1.026 34.244 34.244 35.118 35.118 35.118 29.499 28.293 28.293 29.015 29.015 5 

ULS UL Steel vs. closures only, 50% penetration 100.0% V 1.020 1.026 35.396 35.396 36.300 36.300 36.300 30.488 29.185 29.185 29.930 29.930 6 

IMPALT Imp. Alternator/Charging 100.0% V 1.020 1.026 35.708 35.708 36.620 36.620 36.620 30.742 29.385 29.385 30.135 30.135 7 $1

DOHC DOHC V6 vs OHV V6 100.0% V 1.020 1.026 35.708 35.708 36.620 36.620 36.620 31.360 29.385 29.385 30.135 30.135 8 $1

CVVLT CVVL&T on 4V after 2V to 4V 100.0% V 1.020 1.026 39.730 39.730 40.745 40.745 40.745 35.205 30.821 30.821 31.608 31.608 9 $1

CVGDI Gasoline Direct Injection on 4V CVVLT 100.0% V 1.020 1.026 41.662 41.662 42.726 42.726 42.726 37.015 31.947 31.947 32.763 32.763 10 $2

AHYB Advanced Hybrid w/Regen Braking 100.0% V 1.020 1.026 53.090 53.090 54.446 54.446 54.446 46.178 38.267 38.267 39.244 39.244 11 $8

ALM Aluminum Incremental to ULSteel 100.0% V 1.020 1.026 55.286 55.286 56.698 56.698 56.698 48.204 39.737 39.737 40.752 40.752 12 $9

Adv Tech Available

Cost-Effectiveness of Individual Technologies -- Chrysler MSWs

FC Change $ / %FC

Off-Model Multipliers

Table 8-2 

Technology Deployment Sequence for Chrysler MSWs 

-70- 
Columns M through P contain logic using real world fuel economy similar to that in 

Columns G through J based on CAFE fuel economy. Column Q shows the technology 

deployment sequence number. 

As shown in Table 8-2, cumulative cost and incremental cost effectiveness are calculated 

in Columns R through U. The spreadsheet had been structured to show values calculated 

from two different baselines: (1) the 2006 Baseline; and (2) a second baseline labeled 

“Exist CAFE” in the spreadsheet. The latter was used in earlier work that examined 

GHG compliance incremental to future year CAFE standards and was not used for this 

analysis. (Due to the complexity of the spreadsheet formulas, it was easier to leave these 

columns in place.) For this analysis, the compliance costs are thus calculated as 

incremental to the existing 2006 baseline. 

The deployment sequence calculations shown in Table 8-2 and described above are 

repeated in separate sheets for each of the 25 vehicle categories. The results from these 

sheets are then utilized in other sheets within the CE workbook files to calculate 

compliance costs and technology requirements as described in the next subsection. 

8.2 Compliance Calculations

The next element in the analysis consisted of calculating costs and determining the level 

of technology needed by each manufacturer to comply with the new EISA-based CAFE 

regulations in 2020. These compliance calculations were performed in sheets labeled 

“Results” and “Compliance” in the CE workbook files (one for each manufacturer and set 

of attribute-based CAFE targets). The key compliance calculations contained in each of 

these sheets are described separately below. 

Fleet Compilations (Results) – Table 8-3 provides an example of the Results sheet for 

Chrysler. Calculations in this sheet are focused on compiling sales-weighted composite 

fuel economies for the passenger car and light truck sub-fleets from their individual 

vehicle categories (13 for cars and 12 for trucks). 

The Results sheet also includes logic that can be invoked to simulate the effect of 

different sales distributions that result in cases where a manufacturer would stop selling 

specific vehicle models in order to achieve compliance instead of adding further 

technology. These “mix-shift” adjustments are contained in Column G and applied in 

Columns H and I, but were not used under this current analysis. (In Table 8-3, they are 

set to unity to reflect no mix shifting.) 

-71- 
Table 8-3 

Results Sheet Layout for Chrysler Fleet Compilation 

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

A B CD E F G H I J K L M N O P Q R S T U VW X

Note: All fuel economy values shown are unadjusted. To convert to label values, multiply combined mpg by 0.853

Note: Price increases shown are for average of vehicle categories listed above price. Convert price to % increase and then apply to individual categories.

Hypothetical

Model Shift 2006 Modeled Proj Base ASLA5 PARA AMT6 EPS PARA2 ULS IMPALT DOHC CVVLT CVGDI AHYB ALM

# Category Abbrev Auto LDV Factor Auto LDV Actual Baseline 0 1 2 3 4 5 6 7 8 9 10 11 12 13

1 Minicars MINI 0.00% 0.00% 1.00 0.00% 0.00% - - - - - - - - - - - - - - - -

2 Subcomp Sedans/Wgns SCSW 0.00% 0.00% 1.00 0.00% 0.00% - - - - - - - - - - - - - - - -

3 Compact Sedans/Wgns CSW 36.72% 9.46% 1.00 36.72% 9.46% 31.716 31.654 31.654 31.653 31.812 31.882 32.512 33.175 34.204 34.563 34.562 37.740 39.425 47.015 48.895 0.000

4 Mid-Size Sedans/Wgns MSW 12.10% 3.12% 1.00 12.10% 3.12% 28.785 30.846 30.846 32.304 32.466 33.804 34.416 35.118 36.300 36.620 36.620 40.745 42.726 54.446 56.698 0.000

5 Large Sedans/Wgns LSW 8.36% 2.16% 1.00 8.36% 2.16% 27.514 27.351 27.351 29.084 29.230 30.158 30.673 31.299 32.372 32.644 32.636 36.037 37.740 46.850 48.837 0.000

6 Small Coupes/Conv SCC 0.73% 0.19% 1.00 0.73% 0.19% 24.757 28.496 28.496 28.496 28.639 29.182 29.642 30.247 31.299 31.581 31.581 36.481 38.630 50.309 52.540 0.000

7 Mid Coupes/Conv MCC 3.10% 0.80% 1.00 3.10% 0.80% 28.756 30.555 30.555 31.989 32.150 33.510 34.111 34.807 35.974 36.324 36.324 40.338 42.293 54.189 56.467 0.000

8 Large Coupes/Conv LCC 0.00% 0.00% 1.00 0.00% 0.00% - - - - - - - - - - - - - - - -

9 Sm. Sports/Lux Sedans SSL 0.00% 0.00% 1.00 0.00% 0.00% - - - - - - - - - - - - - - - -

10 Mid Sports/Lux Sedans MSL 0.00% 0.00% 1.00 0.00% 0.00% - - --------------

11 Lg. Sports/Lux Sedans LSL 38.99% 10.05% 1.00 38.99% 10.05% 24.296 23.285 23.285 23.285 23.402 24.217 24.522 25.022 25.900 26.071 27.241 31.399 33.230 42.748 44.809 0.000

12 Sports Cars SC 0.00% 0.00% 1.00 0.00% 0.00% - - - - - - - - - - - - - - - -

13 Hi-Perf Sports Cars HPSC 0.00% 0.00% 1.00 0.00% 0.00% - - - - - - - - - - - - - - - -

All Cars 100.00% 25.77% 100.00% 25.77% 27.593 27.326 27.326 27.632 27.771 28.454 28.909 29.499 30.488 30.742 31.360 35.205 37.015 46.178 48.204 #DIV/0!

PC Baseline Price Increase: $0 $0 $62 $76 $292 $377 $503 $721 $797 $876 $1,737 $2,309 $8,695 $10,354 $0

All PCs 25.77% 25.77% 27.593 27.326

Hypothetical

Model Shift 2006 Modeled Proj Base ASLA5 PARA AMT6 EPS PARA2 ULS IMPALT DOHC CVVLT CVGDI AHYB ALM

# Category Abbrev LT LDV Factor LT LDV Actual Baseline 0 1 2 3 4 5 6 7 8 9 10 11 12 13

14 Small Vans SVAN 27.86% 20.68% 1.00 27.86% 20.68% 24.510 23.371 23.371 24.969 25.094 25.903 26.307 26.843 27.744 27.945 30.682 33.849 35.436 45.047 46.833 0.000

15 Large Vans LVAN 0.11% 0.08% 1.00 0.11% 0.08% 27.560 28.298 28.298 28.298 28.440 29.823 30.250 30.867 31.388 31.630 31.630 33.875 35.262 42.129 42.906 0.000

27.96% 20.76% 27.96% 20.76% 24.521 23.387 23.387 24.980 25.106 25.916 26.320 26.857 27.756 27.957 30.685 33.849 35.436 45.035 46.817 #DIV/0!

SVAN Baseline Price Increase: $0 $0 $271 $287 $644 $738 $877 $1,146 $1,229 $1,877 $2,341 $2,974 $10,677 $12,731 $0

Hypothetical

Model Shift 2006 Modeled Proj Base ASLA5 PARA AMT6 CD2V PARA2 ULS IMPALT EHPS CVVLT4 CVGDI AHYB ALM

# Category Abbrev LT LDV Factor LT LDV Actual Baseline 0 1 2 3 4 5 6 7 8 9 10 11 12 13

16 Small 2WD Pickups S2P 0.00% 0.00% 1.00 0.00% 0.00% - - - - - - - - - - - - - - - -

17 Small 4WD Pickups S4P 0.00% 0.00% 1.00 0.00% 0.00% - - - - - - - - - - - - - - - -

18 Large 2WD Pickups L2P 9.62% 7.14% 1.00 9.62% 7.14% 19.651 20.203 20.203 20.509 20.612 21.173 22.973 23.442 23.718 23.895 24.188 24.190 24.188 31.766 33.741 0.000

19 Large 4WD Pickups L4P 7.15% 5.30% 1.00 7.15% 5.30% 19.080 18.560 18.560 18.720 18.815 19.215 20.233 20.646 20.923 21.049 21.290 21.290 21.290 27.662 30.384 0.000

16.76% 12.44% 16.76% 12.44% 19.403 19.468 19.468 19.706 19.805 20.291 21.719 22.162 22.440 22.593 22.861 22.862 22.861 29.876 32.223 #DIV/0!

PU Baseline Price Increase: $0 $0 $52 $69 $434 $725 $877 $1,050 $1,140 $1,294 $1,768 $1,768 $10,656 $11,648 $0

Hypothetical

Model Shift 2006 Modeled Proj Base ASLA5 PARA AMT6 CD2V PARA2 ULS IMPALT EHPS CVVLT4 CVGDI AHYB ALM

# Category Abbrev LT LDV Factor LT LDV Actual Baseline 0 1 2 3 4 5 6 7 8 9 10 11 12 13

20 Small 2WD SUVs S2SU 8.93% 6.63% 1.00 8.93% 6.63% 27.587 30.489 30.489 31.617 31.776 33.339 33.339 34.019 34.953 35.285 35.998 39.720 41.576 51.389 53.154 0.000

21 Small 4WD SUVs S4SU 4.29% 3.19% 1.00 4.29% 3.19% 18.996 20.325 20.325 21.414 21.522 21.957 23.548 24.028 24.434 24.614 24.986 25.132 25.209 30.606 31.068 0.000

22 Midsize 2WD SUVs M2SU 8.85% 6.57% 1.00 8.85% 6.57% 22.463 22.227 22.227 22.734 22.848 23.560 25.331 25.848 26.469 26.663 27.066 27.702 27.980 35.867 37.159 0.000

23 Midsize 4WD SUVs M4SU 21.97% 16.30% 1.00 21.97% 16.30% 20.828 20.035 20.035 20.451 20.554 21.175 22.891 23.358 23.887 24.064 24.418 24.467 24.490 31.205 32.473 0.000

24 Large 2WD SUVs L2SU 6.26% 4.65% 1.00 6.26% 4.65% 21.043 21.349 21.349 22.182 22.293 23.194 24.126 24.619 25.034 25.208 25.553 27.252 28.053 36.049 36.816 0.000

25 Large 4WD SUVs L4SU 4.98% 3.69% 1.00 4.98% 3.69% 19.236 18.886 18.886 19.272 19.368 20.101 21.313 21.748 22.115 22.253 22.512 23.129 23.408 30.284 30.901 0.000

55.27% 41.03% 55.27% 41.03% 21.638 21.631 21.631 22.228 22.340 23.090 24.544 25.045 25.588 25.779 26.166 26.862 27.175 34.489 35.618 #DIV/0!

SUV Baseline Price Increase: $0 $0 $133 $149 $485 $735 $874 $1,101 $1,184 $1,325 $1,941 $2,133 $9,840 $11,468 $0

All LDTs 100.00% 74.23% 74.23% 21.936 21.682

All LDVs 100.00% 100.00% 23.160 22.901

Cars

Sales Fractions

U.S. Sales Fractions

Shift-Adjusted

U.S. Sales Fractions

Vans

Sales Fractions

Actual U.S.

Chrysler Fuel Economy and Cost Forecasts

Shift-Adjusted

U.S. Sales Fractions

Sales Fractions

Actual U.S. CAFE Fuel Econ (mpg)

Actual U.S.

Sales Fractions

Actual U.S. Shift-Adjusted

Shift-Adjusted

U.S. Sales Fractions

CAFE Fuel Econ (mpg)

CAFE Fuel Econ (mpg)

CAFE Fuel Econ (mpg)

"Combined" Fuel Economy for Technology Combinations (mpg)

"Combined" Fuel Economy for Technology Combinations (mpg)

Pickups

SUVs

"Combined" Fuel Economy for Technology Combinations (mpg)

"Combined" Fuel Economy for Technology Combinations (mpg)

Note: Cells with values of “#REF!”, “#DIV/0!” or negative costs do not indicate faulty logic in the 

spreadsheet calculations, but merely reflect instances or effects of missing vehicle categories or unused 

technology array elements. 

Sales-weighted composite fuel economy and incremental cost calculations are performed 

in Columns K through W for the baseline and each successive technology step. The sales 

fractions contained in Column H are combined with the fuel economy values for each 

vehicle category to compute harmonically averaged passenger car and light-duty truck 

sub-fleet composite fuel economy by technology step in Rows 23, 33, 43 and 55.*

 Note 

that the light-truck compilations are performed at the individual sub-fleet level in this 

sheet (i.e., separately for vans, pickups, and SUVs). These light-truck sub-fleet values 

are kept separate in this sheet to account for instances where the technology steps must be 

aligned across the sub-fleets, which is performed later. (Technology alignment was not 

an issue under this analysis because of the decision to calculated compliance costs 

incremental to the current baseline fleet. This alignment element is preserved in the 

compliance workflow from earlier analyses.) 

 

*

 These calculations are not shown in Figure 8-2 but are performed in columns to the right of those shown. 

-72- 
Sales-weighted composite technology costs for each sub-fleet are shown in Rows 24, 34, 

44, and 56, just below the composite fuel economy values. 

Compliance Technology and Costs (Compliance) – Calculation of long-term 2020 

compliance costs and technology requirements was performed in the Compliance sheet. 

Table 8-4 shows the layout of the Compliance sheet, again using Chrysler. This example 

shows compliance calculations for a footprint-based Reformed CAFE standard. 

Table 8-4 

Compliance Sheet Layout for Chrysler Using a Footprint-Based Standard 

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

A B C D E F G H I J K L M N O PQR S T U VW X

Tech Code

Manufacturer: Base

As shown in Table 8-4, compliance calculations are performed for passenger car and 

light-duty truck fleets, and composite values are computed for the combined light-duty 

vehicle fleet. However, compliance with the EISA-based standards is evaluated 

separately for cars and trucks (although credit transfer is allowed between these fleets and 

is discussed later). 

Sales fractions in Column A are carried forward from the Results sheet and are used to 

calculate sales-weighted composite fuel economy and compliance costs separately for the 

passenger car and light-truck fleets. Columns D through Q in Table 8-4 contain the 

Supply PCs Vans Pickups SUVs All Trucks

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP CDCT CD2V 10.56% 0.00% 34.76% 9.32% 10.98%

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP VVLT CVVLT 0.00% 0.00% 0.00% 0.00% 0.00%

Rulemaking Version: HR6 HYB AHYB 0.00% 0.00% 0.00% 0.00% 0.00%

Optimum Combinations MfrCode: C

Combo # 0 1 2 3 4 5 6 7 8 9 10 11 12 13

Passenger Cars Tech Name: Proj Base ASLA5 PARA AMT6 EPS PARA2 ULS IMPALT DOHC CVVLT CVGDI AHYB ALM 0 CAFE Std: 37.901 Tech Fleet% ATFleet%

U.S. Sales CAFE 27.33 27.63 27.77 28.45 28.91 29.50 30.49 30.74 31.36 35.20 37.01 46.18 48.20 #DIV/0! Point Reached: 11 AHYB 11.78% 11.78%

Fraction Tech Cost $0 $62 $76 $292 $377 $503 $721 $797 $876 $1,737 $2,309 $8,695 $10,354 $0 Prior Point: 10 CVGDI 88.22%

25.77% $/MPG $202 $104 $316 $186 $214 $221 $298 $127 $224 $316 $697 $819 #DIV/0! Model Mix Shift: No Diff

Blended MPG: 37.901 0.000

Blended Cost: $3,062

Combo # 0 1 2 3 4 5 6 7 8 9 10 11 12 13

Vans Tech Name: Proj Base ASLA5 PARA AMT6 EPS PARA2 ULS IMPALT DOHC CVVLT CVGDI AHYB ALM 0

U.S. Sales CAFE 23.39 24.98 25.11 25.92 26.32 26.86 27.76 27.96 30.69 33.85 35.44 45.03 46.82 #DIV/0!

Fraction Tech Cost $0 $271 $287 $644 $738 $877 $1,146 $1,229 $1,877 $2,341 $2,974 $10,677 $12,731 $0

20.76% $/MPG $170 $128 $440 $232 $260 $299 $416 $237 $147 $399 $802 $1,153 #DIV/0!

Combo # 0 1 2 3 4 5 6 7 8 9 10 11 12 13

Pickups Tech Name: Proj Base ASLA5 PARA AMT6 CD2V PARA2 ULS IMPALT EHPS CVVLT4 CVGDI AHYB ALM 0

U.S. Sales CAFE 19.47 19.71 19.81 20.29 21.72 22.16 22.44 22.59 22.86 22.86 22.86 29.88 32.22 #DIV/0!

Fraction Tech Cost $0 $52 $69 $434 $725 $877 $1,050 $1,140 $1,294 $1,768 $1,768 $10,656 $11,648 $0

12.44% $/MPG $217 $176 $751 $204 $343 $622 $592 $571 $452,904 $0 $1,267 $423 #DIV/0!

Combo # 0 1 2 3 4 5 6 7 8 9 10 11 12 13

SUVs Tech Name: Proj Base ASLA5 PARA AMT6 CD2V PARA2 ULS IMPALT EHPS CVVLT4 CVGDI AHYB ALM 0

U.S. Sales CAFE 21.63 22.23 22.34 23.09 24.54 25.04 25.59 25.78 26.17 26.86 27.17 34.49 35.62 #DIV/0!

Fraction Tech Cost $0 $133 $149 $485 $735 $874 $1,101 $1,184 $1,325 $1,941 $2,133 $9,840 $11,468 $0

41.03% $/MPG $223 $144 $448 $172 $279 $416 $439 $364 $885 $613 $1,054 $1,441 #DIV/0!

Combo # 0 1 2 3 4 5 6 7 8 9 10 11 12 13

Light-Duty Trucks Tech Name: Proj Base ASLA5 PARA AMT6 CD2V PARA2 ULS IMPALT EHPS CVVLT4 CVGDI AHYB ALM 0 CAFE Std: 31.349 Tech Fleet% ATFleet%

U.S. Sales SWCAFE 21.68 22.44 22.55 23.26 24.47 24.97 25.55 25.73 26.62 27.65 28.12 35.91 37.46 #DIV/0! Point Reached: 11 AHYB 47.49% 47.49%

Fraction SWCost $0 $158 $174 $521 $734 $876 $1,105 $1,189 $1,474 $2,024 $2,307 $10,211 $11,852 $0 Prior Point: 10 CVGDI 52.51%

74.23% Model Mix Shift: No Diff

Blended MPG: 31.349 0.000

Blended Cost: $6,061

Sales Combo # 0 1 2 3 4 5 6 7 8 9 10 11 12 13

Check Tech Name: Proj Base ASLA5 PARA AMT6 EPS PARA2 ULS IMPALT DOHC CVVLT CVGDI AHYB ALM 0 Sales-Wtd CAFE Std: 32.811 Tech ATFleet%

100.00% SWCAFE 22.90 23.58 23.70 24.41 25.48 26.00 26.66 26.86 27.70 29.27 29.98 38.09 39.74 #DIV/0! Point Reached: 11 AHYB 38.29%

SWCost $0 $133 $149 $462 $642 $780 $1,006 $1,088 $1,320 $1,950 $2,308 $9,820 $11,466 $0 Prior Point: 10 CVGDI

Model Mix Shift: No Diff

Blended MPG: 32.811 0.000

Blended Cost: $5,288

Adv Tech Penetration in Chrysler Baseline

LDT Compliance

NEW FEDERAL CAFE COMPLIANCE ANALYSIS

PC Compliance

PASSENGER CARS

LIGHT-DUTY TRUCKS (and MDPVs)

SALES-WEIGHTED LDV & MDPV FLEET

Chrysler

LDV Composite

-73- 
deployed technology sequences for each sub-fleet, starting with the Baseline. Sub-fleet 

CAFE fuel economy values and costs at every point along each sequence are brought 

forward from the Results sheet. (When deployment sequence alignment is required, it is 

performed in the Compliance sheet.) 

Finally, the amount of technology and cost needed to comply with the long-term CAFE 

standards is calculated in Columns T through X in Table 8-4. These calculations are 

performed separately for both cars and light trucks. Logic in these cells automatically 

calculates composite fuel economy and costs based upon the percentages entered in the 

green shaded cells (Cell W14 for passenger cars and Cell W45 for light trucks). This 

logic basically performs linear interpolation of technology cost and CAFE fuel economy 

along each sales-weighted composite deployment sequence (Rows 15 and 16 for cars and 

45 and 46 for light trucks). 

An Excel “solver” utility macro was used to iteratively calculate the percentage of the 

“last” or final needed technology in these green “input” cells to meet the compliance 

targets. These long-term compliance cost and technology calculations performed in the 

Compliance sheet were performed in a manner that assumed full phase-in for all but the 

final needed technology combination. 

8.3 Cost-Effectiveness Analysis

From the perspective of the theoretical “rational consumer,” the acceptability of the 

design changes to reduce fuel consumption depends on how the price the consumer must 

pay for the technology compares to the value of the fuel savings. Based on a simplistic 

analysis, the cost effectiveness of a particular technology can be estimated by calculating 

the fuel saved over the life of the vehicle and comparing the cost of the technology to the 

value of the fuel saved. Assuming, for example, a baseline fuel economy of 30 mpg and 

a vehicle life of 150,000 miles, the lifetime gasoline cost is $12,500 at a fuel price of 

$2.50 per gallon. A 1% reduction in fuel consumption would reduce the lifetime fuel 

cost by $125. But this does not mean that a rational consumer would be willing to spend 

$125 per percent reduction in fuel consumption. 

The simplistic analysis described above fails to account for several important factors, 

including (1) the time value of money, (2) the difference between fuel economy in 

customer service and on the CAFE test procedures, (3) differences in the fuel economy 

improvement that individual technologies provide in customer service compared to the 

CAFE test procedures, and (4) the “rebound effect” (i.e., the extra driving induced by 

vehicles with higher fuel economy). Higher sales taxes associated with higher priced 

technology must also be considered. 

Accounting for the time value of money is necessary to address the fact that no rational 

consumer would borrow $1,000 today to pay for more sophisticated technology that 

would provide a fuel savings of $1,000 over a period of ten years. A discount rate has to 

-74- 
be applied to future fuel savings to address this factor. Based on an analysis by NERA,13

we have used an 12.4% discount rate in our calculations. 

Calculations using the fuel economy measured by the CAFE test procedures will not 

reflect actual fuel economy in customer service. It has long been recognized that fuel 

economy in customer service is lower than the fuel economy reported using the CAFE 

test procedures. One obvious factor contributing to the shortfall in customer service is 

that the EPA Highway cycle was intentionally developed to represent vigorous 

enforcement of a nationwide 55 mph speed limit.14

The difference between driving patterns in customer service and on the CAFE test 

procedures also affects the reduction in fuel consumption associated with individual 

technologies. For example, a technology that reduces fuel consumption at idle will 

provide a different average benefit if the fraction of idle operation in customer service is 

different from the fraction of idle operation on the CAFE test procedures. 

A 1999 paper by Greene, et al, from Oak Ridge National Laboratory15 describes the body 

of research that supports the existence of a “rebound effect” when automotive fuel 

economy increases. The rebound effect is basically an extension of the “Law of 

Demand”—when the cost of something decreases (in this case vehicle travel), there is a 

natural tendency for consumers to demand more of it. As Greene explains, numerous 

researchers have documented that a rebound effect exists for increasing automotive fuel 

economy and Greene concludes that the long-term effect is 20%. In other words, a 100% 

improvement in fuel economy induces a 20% increase in vehicle travel. In its recent 

rulemaking regarding light-duty truck fuel economy standards, NHTSA also addressed 

the rebound effect and concluded that the magnitude of the effect was the same as Greene 

had estimated.16 To be conservative, we have assumed a 17% rebound effect in our 

analysis. 

Accounting for all of the above-described factors, the following equation shows the 

calculation of the net present value (NPV) of the increased cost to a consumer of design 

changes that reduce fuel consumption: 

])1/())*))*)

1

[(()1(* 1((1(*()* i DR

mpg

FP REB

ni

i mpg

mpgbase VMTi VMTi

mpgbase

FP NPV RPE tax ∑ + =

=

++−= − −+

where: 

RPE = increase in retail price equivalent (dollars), 

Tax = sales tax applied to the increase in RPE, 

N = number of years over which the fuel price savings is considered, 

FP = fuel price in dollars per gallon, 

mpgbase = real baseline fuel economy in miles per gallon (85% of CAFE), 

VMTi = annual vehicle miles travelled in year i, adjusted for scrappage, 

mpg = real fuel economy after the design change, 

-75- 
REB = rebound effect (% increase in VMT per % reduction in fuel cost), 

 and 

DR = discount rate. 

The first term in the equation is the increase in price the consumer pays for the design 

change multiplied by 1.0 plus the applicable sales tax (e.g., 1.08 for 8% sales tax). The 

remainder of the equation calculates present value fuel cost savings for each year, while 

accounting for the rebound effect and a discount rate. 

For an example of how the equation is applied, we consider the case of a hybrid system 

applied to a passenger car with a baseline CAFE rating of 29.6 mpg (the actual 2006 

model year baseline). As discussed earlier in Section 6.2, we estimate the increase in 

retail price for a strong hybrid system applied to a mid-size passenger car at $5,968. 

When an 8% sales tax is considered, the cost to the consumer is $6,445 ($5,968 * 1.08). 

The savings in the first year are calculated by subtracting the actual fuel cost from the 

baseline fuel cost and then applying the discount rate. 

The baseline fuel cost is the fuel price, assumed in this example to be $2.50 per gallon, 

divided by the baseline fuel economy and then multiplied by the annual miles of travel, 

calculated as follows: 

482,1$910,14*)6.29*85.0(

50.2$ * i = = base

VMT

mpg

FP

where: 

 14,910 = average annual VMT for passenger cars during their first year of 

operation, and 

 0.85 = standard factor used to translate CAFE to customer service fuel 

economy. 

The first year annual mileage of 16,071 in the above equation is extracted from EPA’s 

MOBILE6 vehicle emission factor model. The 0.85 factor adjusts the “composite” 

CAFE value to what consumers are expected to achieve in customer service when the 

“city” mpg is discounted by 10% and the “highway” mpg is discounted by 22%. 

The actual fuel cost with the hybrid system is calculated from the following portion of the 

equation that accounts for the rebound effect: 

-76- 
143,1$0735.0$*571,150735.0$*)0443.1(*14,910

0735.0$*)17.0*)7393.01((1(*14,910

)5.41*82.0(

50.2$ *)17.0*))5.41*82.0(

)6.29*85.0( 1((1(*910,14

**)1((1(*

= = =

= −+

= −+

−+

mpg

FP REB

mpg

mpg VMT base

i

As shown above, the annual miles of travel increase by 4.1% due to the rebound effect 

and the actual fuel cost drops to $1,143. (The 41.5 mpg CAFE value for the hybrid 

reflects a 28.7% reduction in fuel consumption from the 29.6 mpg baseline. The 0.82 

adjustment factor applied to the fuel economy of the vehicle equipped with a hybrid 

system is based on simulation modeling showing that the benefits of hybrids in customer 

service are somewhat less than on the CAFE test procedures.) 

Subtracting the revised fuel cost from the baseline fuel cost and accounting for the 

discount rate involves the following calculation: 

($1,482−$1,143) / (1+0.124)1

 = $338/1.124 = $301 

Based on the above calculations, the $6,445 cost to the consumer of the hybrid system 

has been offset by a fuel cost savings with a discounted present value of $301 at the end 

of the first year of ownership. When performing the above calculations for additional 

years, it is necessary to account for the fact that annual VMT is decreasing as the vehicle 

ages, and some vehicles are being retired from customer service due to accidents. We 

have used mileage accumulation rates and scrappage rates from EPA’s MOBILE6 model 

in performing those calculations. 

Using a 12.4% discount rate, a 17% rebound effect, an 8% sales tax, and vehicle 

simulation modeling to account for fuel economy in customer service, a costeffectiveness analysis was conducted for three assumed retail fuel price levels of 

$2.50/gal, $3.00/gal, and $3.50/gal to represent Low, Reference, and High cases. We 

considered fuel cost savings over “payback” periods of 5 and 20 years. (It is more likely 

that average consumers would consider the savings during the period of time they expect 

to own the vehicle, likely closer to the five-year period.). Thus, the net present 

compliance costs (accounting for fuel savings) were computed for a total of six 

combinations of retail fuel price and payback period for each manufacturer. These 

calculations were performed separately for cars and light trucks as well as for a light-duty 

fleet composite. 

Finally, an analysis of the “break-even” retail fuel price was conducted for each 

manufacturer and payback period. (The break-even price represents that at which the 

compliance technology package has a net present cost of zero.) 

-77- 
8.4 Summary of Results

Calculated technology requirements, compliance costs, and break-even fuel prices in 

model year 2020 by manufacturer are presented in Table 8-5 for footprint-based reformed 

CAFE standards assuming no credit transfer of up to 2 mpg between passenger car and 

light truck fleets as allowed under provisions in EISA. Table 8-6 presents a similar 

compliance summary with credit transfer. 

In each table, separate summaries are shown for both passenger car and light-duty truck 

compliance. Sales-weighted composite results for the light-duty fleet are shown at the 

bottom of each table. After the leftmost column, the next two columns show actual 2006 

CAFE fuel economy and the CAFE levels required under the new standard in 2020, 

respectively. The next three columns list the type and amount of the last, most expensive 

technology required for compliance (including explicit identification of the fraction of 

advanced hybrids needed). The next column presents the retail per-vehicle compliance 

costs (incremental to the existing 2006 baseline). Finally, break-even retail fuel prices at 

each of the evaluated payback periods are listed in the two rightmost columns. 

As shown in Table 8-5, the increase in retail price equivalent (RPE) for a footprint-base 

standard (with no credit transfer) for the entire light-duty fleet range across manufacturers 

from $1,324 to $7,646, with a sales-weighted average over the entire fleet of $3,646 per 

vehicle. 

In Table 8-6, compliance costs after accounting for allowed credit transfer between cars 

and trucks generally drop between $100 and $200 for most manufacturers. The salesweighted average price increase is $3,505 per vehicle. Under both of the scenarios 

examined, break-even fuel prices for the entire light-duty U.S. vehicle fleet are generally 

slightly below $5.00 per gallon over a 20-year payback period. When payback is 

evaluated over a shorter five-year period (more in line with the typical vehicle lifetime 

for an individual owner/purchaser), the break-even fuel price exceeds $7.00 per gallon. 

Appendix B contains a series of summary tables that provide detailed results of the costeffectiveness analysis, showing net present costs (that account for fuel savings) for each 

of the six fuel price and payback period scenarios that were analyzed. (The tables in 

Appendix B are paginated by manufacturer. For each manufacturer, a table of results is 

shown without credit transfer, followed by results with credit transfer.)

-78- 
Table 8-5 

Compliance Analysis for Footprint-Based Standards 

No Credit Transfer Between Cars and Trucks to Reduce Compliance Cost

Hybrid Retail Price

Manufacturer 2006 Actual New Standard Type Amount Fraction Equiv Cost 5-Year 20-Year

BMW 26.89 40.78 AHYB 9.02% 9.02% $2,323 $8.93 $5.73

Chrysler 27.59 37.90 AHYB 11.78% 11.78% $3,062 $8.74 $5.61

Daimler 24.43 39.77 AHYB 46.31% 46.31% $5,470 $10.73 $6.89

Ford 27.69 39.89 CVGDI 88.71% 0.00% $2,296 $6.71 $4.30

GM 28.50 40.31 CVGDI 48.70% 0.00% $2,251 $5.65 $3.62

Honda 31.64 41.21 CVGDI 26.17% 0.00% $1,383 $5.89 $3.78

Hyundai 30.47 42.63 CVGDI 81.65% 0.00% $2,209 $7.84 $5.03

Nissan 28.82 40.59 CVGDI 30.18% 0.00% $1,955 $6.78 $4.35

Porsche 25.21 47.26 AHYB 81.84% 81.84% $6,108 $11.66 $7.48

Toyota 34.50 42.98 CVVLT 86.16% 0.00% $1,561 $7.43 $4.77

VW 29.79 42.80 CVGDI 61.18% 0.00% $1,976 $8.70 $5.58

Composite: 29.39 40.99 2.85% $2,189 $7.08 $4.54

Hybrid Retail Price

Manufacturer 2006 Actual New Standard Type Amount Fraction Equiv Cost 5-Year 20-Year

BMW 21.22 32.97 CVGDI 19.60% 0.00% $1,602 $4.49 $3.16

Chrysler 21.94 31.35 AHYB 47.49% 47.49% $6,061 $8.92 $6.28

Daimler 20.27 29.64 AHYB 37.14% 37.14% $5,834 $8.82 $6.21

Ford 20.36 29.94 AHYB 40.74% 40.74% $6,107 $8.18 $5.76

GM 21.68 29.96 AHYB 44.68% 44.68% $6,181 $8.08 $5.69

Honda 24.76 31.28 CVVLT4 69.03% 0.00% $1,273 $3.97 $2.80

Hyundai 23.42 33.34 AHYB 10.78% 10.78% $3,403 $6.81 $4.80

Nissan 20.90 30.04 AHYB 36.54% 36.54% $5,663 $8.26 $5.82

Porsche 18.56 30.34 AHYB 77.53% 77.53% $10,004 $11.68 $8.22

Toyota 23.58 30.83 AHYB 0.89% 0.89% $2,596 $5.61 $3.95

VW 20.05 30.26 AHYB 64.39% 64.39% $9,085 $12.08 $8.50

Composite: 22.04 30.74 28.66% $5,025 $7.50 $5.28

Hybrid Retail Price

Manufacturer 2006 Actual New Standard Fraction Equiv Cost 5-Year 20-Year

BMW 25.76 39.26 7.54% $2,205 $8.20 $5.31

Chrysler 23.16 32.81 38.29% $5,288 $8.88 $6.11

Daimler 23.18 36.49 43.90% $5,566 $10.23 $6.71

Ford 22.97 33.54 23.24% $4,470 $7.55 $5.13

GM 24.38 34.01 23.96% $4,359 $6.95 $4.73

Honda 27.57 35.27 0.00% $1,324 $4.87 $3.26

Hyundai 27.68 39.00 3.60% $2,608 $7.49 $4.95

Nissan 24.90 35.43 15.17% $3,495 $7.40 $4.96

Porsche 22.09 38.73 80.14% $7,646 $11.67 $7.78

Toyota 28.32 36.25 0.42% $2,048 $6.57 $4.38

VW 29.27 42.17 2.33% $2,233 $8.82 $5.69

Composite: 25.09 35.00 15.60% $3,646 $7.29 $4.92

Break-Even Retail Fuel Price

Passenger Car Compliance

Break-Even Retail Fuel Price

CAFE Fuel Economy (mpg) Technology Needed

CAFE Fuel Economy (mpg) Break-Even Retail Fuel Price

Light-Duty Truck (and MDPV) Compliance

Light-Duty Vehicle (and MDPV) Sales-Weighted Averages

CAFE Fuel Economy (mpg) Technology Needed

-79- 
Table 8-6 

Compliance Analysis for Footprint-Based Standards 

With Credit Transfer Between Cars and Trucks to Reduce Compliance Cost

Hybrid Retail Price

Manufacturer 2006 Actual New Standard Type Amount Fraction Equiv Cost 5-Year 20-Year

BMW 26.89 40.39 AHYB 5.23% 5.23% $2,081 $8.31 $5.33

Chrysler 27.59 37.01 CVGDI 100.00% 0.00% $2,309 $7.13 $4.57

Daimler 24.43 41.19 AHYB 58.66% 58.66% $6,335 $11.55 $7.42

Ford 27.69 40.13 AHYB 0.00% 0.00% $2,359 $6.78 $4.35

GM 28.50 41.41 AHYB 0.00% 0.00% $2,541 $5.99 $3.84

Honda 31.64 39.47 CVVLT 56.16% 0.00% $1,036 $5.11 $3.28

Hyundai 30.47 43.22 AHYB 2.08% 2.08% $2,427 $8.24 $5.29

Nissan 28.82 42.12 AHYB 0.00% 0.00% $2,337 $7.24 $4.65

Porsche 25.21 49.26 AHYB 94.53% 94.53% $6,830 $12.16 $7.80

Toyota 34.50 43.67 CVVLT 100.00% 0.00% $1,681 $7.68 $4.93

VW 29.79 42.97 CVGDI 68.93% 0.00% $2,020 $8.76 $5.62

Composite: 29.39 41.27 2.35% $2,270 $7.10 $4.55

Hybrid Retail Price

Manufacturer 2006 Actual New Standard Type Amount Fraction Equiv Cost 5-Year 20-Year

BMW 21.22 34.33 AHYB 0.00% 0.00% $2,131 $5.12 $3.60

Chrysler 21.94 31.56 AHYB 50.21% 50.21% $6,276 $9.09 $6.40

Daimler 20.27 27.64 AHYB 4.54% 4.54% $2,918 $5.62 $3.95

Ford 20.36 29.84 AHYB 39.36% 39.36% $5,989 $8.09 $5.69

GM 21.68 29.46 AHYB 37.69% 37.69% $5,314 $7.25 $5.11

Honda 24.76 32.24 CVVLT4 100.00% 0.00% $1,408 $4.04 $2.84

Hyundai 23.42 32.64 AHYB 0.00% 0.00% $2,632 $5.66 $3.99

Nissan 20.90 28.95 AHYB 20.94% 20.94% $4,374 $7.12 $5.01

Porsche 18.56 29.17 AHYB 60.03% 60.03% $8,408 $10.76 $7.58

Toyota 23.58 30.44 CVGDI 79.63% 0.00% $2,407 $5.44 $3.83

VW 20.05 28.26 AHYB 33.53% 33.53% $6,206 $10.03 $7.06

Composite: 22.04 30.40 22.28% $4,674 $7.15 $5.03

Hybrid Retail Price

Manufacturer 2006 Actual New Standard Fraction Equiv Cost 5-Year 20-Year

BMW 25.76 39.26 4.37% $2,089 $7.79 $5.05

Chrysler 23.16 32.80 37.27% $5,254 $8.58 $5.93

Daimler 23.18 36.49 44.45% $5,438 $10.00 $6.51

Ford 22.97 33.54 22.46% $4,430 $7.52 $5.12

GM 24.38 34.01 20.21% $4,028 $6.67 $4.52

Honda 27.57 35.27 0.00% $1,233 $4.54 $3.05

Hyundai 27.68 39.00 1.38% $2,496 $7.38 $4.85

Nissan 24.90 35.43 8.70% $3,183 $7.19 $4.80

Porsche 22.09 38.73 80.91% $7,453 $11.61 $7.71

Toyota 28.32 36.25 0.00% $2,023 $6.63 $4.41

VW 29.27 42.17 1.21% $2,172 $8.81 $5.67

Composite: 25.09 35.00 13.54% $3,505 $7.12 $4.80

CAFE Fuel Economy (mpg) Break-Even Retail Fuel Price

Passenger Car Compliance

Light-Duty Truck (and MDPV) Compliance

Light-Duty Vehicle (and MDPV) Sales-Weighted Averages

Break-Even Retail Fuel Price

Technology Needed

Technology Needed

CAFE Fuel Economy (mpg)

CAFE Fuel Economy (mpg)

Break-Even Retail Fuel Price

### 

-80- 
9. REFERENCES 

1. Expert Report of Thomas C. Austin, Central Valley Chrysler-Jeep, Inc., et al. vs. 

Catherine E. Witherspoon, in her official capacity as Executive Officer of the 

California Air Resources Board, United States District Court, Eastern District of 

California – Fresno, Case No. CIV-F-04-06663-REC-LJO, May 2, 2006. 

2. http://www.fueleconomy.gov/feg/download.shtml 

3. http://www.automotive.com/used-cars/specifications/ 

4. http://www.carsdirect.com/research/ 

5. http://autos.msn.com/home/used_research.aspx 

6. http://www.cars.com/go/crp/index.jsp?aff=national 

7. “Light-Duty Automotive Technology and Fuel Economy Trends: 1975-2007,” U.S. 

Environmental Protection Agency, EPA420-R-07-008, September 2007. 

8. T.C. Austin, et al., “Review of the August 2004 Proposed CARB Regulations to 

Control Greenhouse Gas Emissions from Motor Vehicles: Cost Effectiveness for the 

Vehicle Owner or Operator,” Attachment C-5, “Problems with CARB’s 

Turbocharging Analysis,” Sierra Research Report No. SR2004-09-04, September 22, 

2004. 

9. Personal communication with Larry Weitzman, automotive columnist, Mountain 

Democrat, November 2007. 

10. T.C. Austin, et al., “Review of the August 2004 Proposed CARB Regulations to 

Control Greenhouse Gas Emissions from Motor Vehicles: Cost Effectiveness for the 

Vehicle Owner or Operator,” Attachment C-7, “Rolling Resistance,” Sierra Research 

Report No. SR2004-09-04, September 22, 2004. 

11. A. Vyas, et al., “Comparison of Indirect Cost Multipliers for Vehicle Manufacturing, 

Technical Memorandum in Support of Electric and Hybrid Vehicle Cost Estimation,” 

Argonne National Laboratory, April 2000. 

12. “Estimating Changes in Retail Price Equivalent (RPE) from Changes in Direct 

Manufacturing Cost of Passenger Cars and Light-Duty Trucks,” Sierra Research, 

November 12, 2007. 

13. Memoranda from NERA to Sierra Research on the subject of discount rates for 

private costs, November 20, 2007. 

14. T.C. Austin, et al., “Passenger Car Fuel Economy During Non-Urban Driving,” SAE 

Paper No. 740592, 1974. 

-81- 
-82- 

15. David L. Greene, et al., “Fuel Economy Rebound Effect for U.S. Household 

Vehicles,” The Energy Journal, Vol. 20, No. 3, 1999. 

16. Light Truck Average Fuel Economy Standards, Model Years 2005-2007, Docket No.: 

NHTSA-2002-11419 or 68 FR 16867; April 7, 2003. 
APPENDIX A

Detailed Baseline Fleet Tabulations 
A-1 
A-2 
A-3 
A-4 
A-5 
A-6 
A-7 
A-8 
A-9 
A-10 
A-11 
A-12 
APPENDIX B

Detailed Cost-Effectiveness Analysis Results 
Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $562 -$1,947 

-$1,807 -$1,526 -$1,634 -$1,415 

-$977 

>24 $770 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $702 >24 $963 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $983 >24 $1,348 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $876 >24 $1,094 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,095 >24 $1,368 

High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,532 >24 $1,915 

Note: Tech Cost column includes assumed sales tax.

AHYB 9.02% 9.02% $2,509 CVGDI 19.60% 0.00% $1,730

Summary of Compliance Technology Cost Effectiveness

BMW

Passenger Cars Light-Duty Trucks (and MDPVs

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $541 -$1,707 

-$1,571 -$1,301 -$1,405 -$1,194 

-$772 

>24 $899 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $676 >24 $1,124 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $947 >24 $1,573 Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $843 >24 $1,277 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,054 >24 $1,596 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,475 >24 $2,235 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

BMW

Passenger Cars Light-Duty Trucks (and MDPVs

AHYB 5.23% 5.23% $2,248 AHYB 0.00% 0.00% $2,301

B-1 
Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $757 -$2,550 

-$2,361 -$1,982 -$2,128 -$1,833 -$1,243 

>24 $1,467 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $946 >24 $1,834 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,324 >24 $2,567 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,179 >24 $2,084 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,474 >24 $2,605 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $2,063 >24 $3,647 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

Chrysler

Passenger Cars Light-Duty Trucks (and MDPVs

AHYB 11.78% 11.78% $3,307 AHYB 47.49% 47.49% $6,546

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $700 -$1,794 

-$1,619 -$1,269 -$1,403 -$1,131 

-$585 

>24 $1,491 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $875 >24 $1,864 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,225 >24 $2,610 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,091 >24 $2,118 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,363 >24 $2,648 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,909 >24 $3,707 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

Chrysler

Passenger Cars Light-Duty Trucks (and MDPVs

CVGDI 100.00% 0.00% $2,494 AHYB 50.21% 50.21% $6,778

B-2 
Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $1,101 -$4,806 

-$4,531 -$3,981 -$4,192 -$3,763 -$2,905 

>24 $1,430 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $1,376 >24 $1,787 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,927 >24 $2,502 Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,716 >24 $2,030 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $2,144 >24 $2,538 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $3,002 >24 $3,553 

Note: Tech Cost column includes assumed sales tax.

AHYB 46.31% 46.31% $5,907 AHYB 37.14% 37.14% $6,301

Summary of Compliance Technology Cost Effectiveness

Daimler

Passenger Cars Light-Duty Trucks (and MDPVs

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $1,184 -$5,657 

-$5,361 -$4,769 -$4,996 -$4,535 -$3,612 

>24 $1,122 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $1,480 >24 $1,403 

High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $2,072 >24 $1,964 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,845 >24 $1,594 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $2,307 >24 $1,992 

High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $3,229 >24 $2,789 

Note: Tech Cost column includes assumed sales tax.

AHYB 58.66% 58.66% $6,842 AHYB 4.54% 4.54% $3,151

Summary of Compliance Technology Cost Effectiveness

Daimler

Passenger Cars Light-Duty Trucks (and MDPVs

B-3 
Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $740 -$1,740 

-$1,555 -$1,185 -$1,327 -$1,039 

-$463 

>24 $1,613 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $924 >24 $2,016 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,294 >24 $2,823 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,152 >24 $2,291 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,441 >24 $2,864 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $2,017 >24 $4,010 

Note: Tech Cost column includes assumed sales tax.

CVGDI 88.71% 0.00% $2,480 AHYB 40.74% 40.74% $6,596

Summary of Compliance Technology Cost Effectiveness

Ford

Passenger Cars Light-Duty Trucks (and MDPVs

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $752 -$1,796 

-$1,608 -$1,232 -$1,376 -$1,083 

-$497 

>24 $1,599 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $940 >24 $1,999 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,316 >24 $2,799 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,172 >24 $2,272 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,465 >24 $2,840 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $2,051 >24 $3,976 

Note: Tech Cost column includes assumed sales tax.

AHYB 0.00% 0.00% $2,548 AHYB 39.36% 39.36% $6,468

Summary of Compliance Technology Cost Effectiveness

Ford

Passenger Cars Light-Duty Trucks (and MDPVs

B-4 
Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $861 -$1,570 

-$1,355 

-$924 

-$1,089 

-$754 

-$83 

>24 $1,652 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $1,076 >24 $2,065 

High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,506 >24 $2,891 Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,341 >24 $2,346 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,677 >24 $2,933 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $2,347 >24 $4,106 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

GM

Passenger Cars Light-Duty Trucks (and MDPVs

CVGDI 48.70% 0.00% $2,431 AHYB 44.68% 44.68% $6,675

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $916 -$1,828 

-$1,599 -$1,140 -$1,316 

-$959 -$245 

>24 $1,583 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $1,145 >24 $1,979 

High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,604 >24 $2,770 Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,428 >24 $2,248 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,785 >24 $2,810 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $2,499 >24 $3,935 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

GM

Passenger Cars Light-Duty Trucks (and MDPVs

AHYB 0.00% 0.00% $2,744 AHYB 37.69% 37.69% $5,739

B-5 
Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $507 -$987 

-$860 -$607 -$704 -$506 -$112 

>24 $692 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $633 >24 $865 

High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $887 >24 $1,211 Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $790 >24 $983 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $987 >24 $1,229 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,382 >24 $1,721 

Note: Tech Cost column includes assumed sales tax.

CVGDI 26.17% 0.00% $1,493 CVVLT4 69.03% 0.00% $1,375

Summary of Compliance Technology Cost Effectiveness

Honda

Passenger Cars Light-Duty Trucks (and MDPVs

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $438 -$681 

-$572 -$353 -$437 -$266 

$75 

>24 $753 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $547 >24 $941 

High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $766 >24 $1,318 Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $682 >24 $1,069 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $853 >24 $1,337 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,194 >24 $1,872 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

Honda

Passenger Cars Light-Duty Trucks (and MDPVs

CVVLT 56.16% 0.00% $1,119 CVVLT4 100.00% 0.00% $1,520

B-6 
Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $609 -$1,777 

-$1,625 -$1,321 -$1,437 -$1,200 

-$726 

>24 $1,079 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $761 >24 $1,349 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,066 >24 $1,888 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $949 >24 $1,533 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,186 >24 $1,916 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,660 >24 $2,682 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

Hyundai

Passenger Cars Light-Duty Trucks (and MDPVs

CVGDI 81.65% 0.00% $2,386 AHYB 10.78% 10.78% $3,675

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $636 -$1,985 

-$1,826 -$1,508 -$1,630 -$1,382 

-$886 

>24 $1,004 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $795 >24 $1,255 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,113 >24 $1,757 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $991 >24 $1,426 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,239 >24 $1,782 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,735 >24 $2,495 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

Hyundai

Passenger Cars Light-Duty Trucks (and MDPVs

AHYB 2.08% 2.08% $2,621 AHYB 0.00% 0.00% $2,842

B-7 
Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $623 -$1,489 

-$1,333 -$1,022 -$1,141 

-$899 -$413 

>24 $1,481 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $778 >24 $1,851 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,090 >24 $2,591 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $970 >24 $2,103 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,213 >24 $2,629 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,698 >24 $3,680 

Note: Tech Cost column includes assumed sales tax.

CVGDI 30.18% 0.00% $2,111 AHYB 36.54% 36.54% $6,116

Summary of Compliance Technology Cost Effectiveness

Nissan

Passenger Cars Light-Duty Trucks (and MDPVs

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $697 -$1,827 

-$1,653 -$1,304 -$1,438 -$1,166 

-$623 

>24 $1,327 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $872 >24 $1,658 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,220 >24 $2,322 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,087 >24 $1,884 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $1,358 >24 $2,355 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,901 >24 $3,298 

Note: Tech Cost column includes assumed sales tax.

AHYB 0.00% 0.00% $2,524 AHYB 20.94% 20.94% $4,724

Summary of Compliance Technology Cost Effectiveness

Nissan

Passenger Cars Light-Duty Trucks (and MDPVs

B-8 
Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $1,131 -$5,465 

-$5,183 -$4,617 -$4,834 -$4,393 -$3,512 

>24 $1,851 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $1,414 >24 $2,313 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $1,980 >24 $3,239 Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,763 >24 $2,629 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $2,203 >24 $3,286 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $3,085 >24 $4,600 

Note: Tech Cost column includes assumed sales tax.

AHYB 81.84% 81.84% $6,597 AHYB 77.53% 77.53% $10,805

Summary of Compliance Technology Cost Effectiveness

Porsche

Passenger Cars Light-Duty Trucks (and MDPVs

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $1,213 -$6,163 

-$5,860 -$5,253 -$5,486 -$5,013 -$4,068 

>24 $1,687 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $1,517 >24 $2,109 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $2,123 >24 $2,953 Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $1,891 >24 $2,397 

Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $2,363 >24 $2,996 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $3,309 >24 $4,194 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

Porsche

Passenger Cars Light-Duty Trucks (and MDPVs

AHYB 94.53% 94.53% $7,377 AHYB 60.03% 60.03% $9,081

B-9 
Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $454 -$1,232 

-$1,118 

-$891 -$978 -$802 -$448 

>24 $1,000 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $568 >24 $1,250 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $795 >24 $1,751 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $708 >24 $1,421 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $885 >24 $1,776 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,238 >24 $2,486 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

Toyota

Passenger Cars Light-Duty Trucks (and MDPVs

CVVLT 86.16% 0.00% $1,686 AHYB 0.89% 0.89% $2,804

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $472 -$1,343 

-$1,225 

-$988 

-$1,079 

-$895 -$527 

>24 $956 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $590 >24 $1,195 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $827 >24 $1,673 Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $736 >24 $1,358 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $920 >24 $1,697 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,288 >24 $2,376 

Note: Tech Cost column includes assumed sales tax.

CVVLT 100.00% 0.00% $1,815 CVGDI 79.63% 0.00% $2,600

Summary of Compliance Technology Cost Effectiveness

Toyota

Passenger Cars Light-Duty Trucks (and MDPVs

B-10 
B-11 

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 No Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $491 -$1,643 

-$1,520 -$1,275 -$1,369 -$1,178 

-$796 

>24 $1,625 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $613 >24 $2,031 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $859 >24 $2,843 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $765 >24 $2,308 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $956 >24 $2,885 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,338 >24 $4,038 

Note: Tech Cost column includes assumed sales tax.

Summary of Compliance Technology Cost Effectiveness

VW

Passenger Cars Light-Duty Trucks (and MDPVs

CVGDI 61.18% 0.00% $2,134 AHYB 64.39% 64.39% $9,812

Manufacturer: 

PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

LDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FP

Rulemaking Version: HR6 With Credit Transfer Between Cars and Trucks

Vehicle Payback Driving

Retail Rebound Discount Sales Period Cycle Tech Hybrid Tech Saved Net Payback Tech Hybrid Tech Saved 

Scenario Fuel Price Effect Rate (%) Tax (%) (years) Type Needed Amount Fraction Cost Fuel Cost Savings Year Needed Amount Fraction Cost Fuel Cost 

Low Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real $498 -$1,684 

-$1,559 -$1,310 -$1,406 -$1,211 

-$823 

>24 $1,337 

Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real $623 >24 $1,671 High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real $872 >24 $2,339 

Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real $776 >24 $1,899 Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real $970 >24 $2,373 High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real $1,358 >24 $3,323 

Note: Tech Cost column includes assumed sales tax.

CVGDI 68.93% 0.00% $2,182 AHYB 33.53% 33.53% $6,702

Summary of Compliance Technology Cost Effectiveness

VW

Passenger Cars Light-Duty Trucks (and MDPVs