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 • P hone 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 5 th 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 th e 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 mode l 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 st andards required by EI SA 2007 on individual

manufacturers and on a fleet average basis. Given the ti ming, this analysis does not specifically address the NPRM released on April 22, 2008. We intend to provide NHTSA with a supplemental analysis sp ecifically addressing the propo sed 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 st andards that might be adopted by the Department of Transportation.

3. Determining the incremental increase in vehicl e 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 ac curately 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) 444-6666Report No. SR2008-04-01



### BASIC ANALYSIS OF THE COST AND LONG-TERM IMPACT OF

THE ENERGY INDEPENDEN CE 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 INDEPENDEN CE 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-Base d 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 Fu el Consumption vs. Footprint ...................................... 28

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

Figure 5-2 Cal-Urban Dr iving 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 Dr iving 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 Analys is for Footprint-Based Standards with Transfer Between Cars and Trucks to Reduce Compliance Cost ..................................................................... 2

Table 3-1 Frontal Ar ea Regression Statistics .................................................................. 11

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

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

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

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

Table 3-5 Characteristics of the MY2006 U.S. Light-Duty a Vehicle Fleet .................... 21

Table 4-1 Vehicle Attr ibute Models Evaluated .............................................................. 26

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

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

Table 4-4 Baseline Fleet Fuel Econ omy 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 Vehicl es With VVLT and Cylinder Deactivation ........... 38

Table 5-2 Estimates of Achievable Fu el Consumption Reductions Assuming Engine Size Adjustments for Constant Acceleration Performance ............................................... 39

Table 5-3 Typical Midsize Ve hicle Weight Reduction Potentia l with Ultralight Steel and

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

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

Table 6-2 Harbour and Associ ates 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 Modele d by Vehicle Type for Compliance with

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

-iv--vTable 7-2 Comparison of Reported a nd Simulated MY2006 Baseline Fuel Economy by Individual Vehicle Catego ry Across All Manufacturers .................................................. 63

Table 7-3 Sample Technology Combinati on 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 Deploymen t Sequence for Chrysler MSWs ............................... 70

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

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

Table 8-5 Compliance Analys is for Footprint-Based Standards No Credit Transfer Between Cars and Trucks to Reduce Compliance Cost .................................................... 79

Table 8-6 Compliance Analys is 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 sale s mix of cars and light trucks, the fleet average standard would be 25 mpg. In D ecember of 2007, the President signed House of Representatives Bill 6 (HR6), The Ener gy 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 util ity vehicles above 8,500 pounds to be subject to CAFE standards for the first time.)

Currently, the same mpg standards apply to ea ch manufacturer. Under EISA that will not be the case. The mpg values that each manuf acturer 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 thos e standards, manufacturers who produce vehicles with sm aller 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 fo r trucks and adopts si milar footprint-based standards for passenger cars.

On April 22, 2008, NHTSA announced a Noti ce of Proposed Rulemaking (NPRM) proposing footprint-based sta ndards for passenger cars and lig ht trucks for model years 2011 through 2015. However, this report was pr epared 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 containe d in the NPRM.

Detailed vehicle simulation modeling of th e footprint-based standards necessary to achieve a fleet average of 35 mpg by 2020 indi cates 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 le vel of design changes required may exceed the availability of engineering and cap ital 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 foot print-based standards e quivalent to a 35 mpg fleet average will be approximately $3,500. This estimate assumes individual

manufacturers will transfer cr edits between their car and tr uck 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 manuf acturer is expected to be able to comply with a price increase of $1,233 per vehicl e while several other manufacturers are expected to require price in creases above $5,000 per vehicle. The difference in price increase is directly related to the percenta ge 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

Manufacture r 2006 Actual New Standard Fraction Equiv Cost 5-Yea r 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 fu el 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 discountrate, 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 w ould 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 as sociated 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 Averag e 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 Autom obile Manufacturers, Sierra Research has analyzed the vehicle design changes that may be required to comply with the new Corporate Average Fuel Economy (CAFE) st andards 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 approxima tely 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 “t he 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-passeng er automobiles” are vehicles that have previously been called “light-duty trucks” pl us Sport Utility Vehicl es (SUVs) that are up to 10,000 pounds gross vehicle weight. Under th e 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 fi rst time. As under th e current regulations, there may still be separate standards for passenger cars and “trucks” (now called nonpassenger automobiles), but the statutory fu el economy minimum applies to the salesweighted average of cars and trucks together.

A significant change in the CAFE standards th at 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 fu el economy and express each standard in the

-3-form of a mathematical function.” In othe r words, manufacturer s 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 de fined, but based on previous National Highway Traffic Safety Administration (NHTSA) experience in settin g 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 la rger passenger cars. Every manufacturer is require d to achieve at least “92 pe rcent of the average fuel economy projected by the Secretary for the combined domestic and nondomestic passenger automobile fleets manufactured fo r sale in the United States by all manufacturers.” In other words, when th e 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 y ear old EPA “Highway” test based on the assumptions that only 55% of all driving occurs in urban ar eas (which was true about 30 years ago) and that non-urban fuel economy can be characterized using a driving cycle that was intentionally designe d to reflect vigorous enfor cement of a nationwide 55 mph speed limit. As a result, actual fuel economy in customer service will be somewhat lower than fuel economy measured us ing 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 Trans portation is obligated to adop t a more stringent standard

if feasible. There is no minimum or maximu m 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 cr edits between manufacturer s (which is allowed under the law) will actually occur. *



### 2. 2 Project Objectives

Th e overall objective of the project was to determine the expected changes in vehicle design and price associated with meeting th e new CAFE standards required by EISA on

both an individual manufacturer and fleet av erage basis. To accomplish this overall objective, the following tasks were performed:

* The maximum increase in a ny compliance category attribut able 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 ma nufacturers against which the design changes necessary to meet more string ent CAFE standards would be compared.

2. Developing attribute-based st andards that might be adopted by the Department of Transportation.

3. D etermining the incremental increase in vehicle prices associated with the deployment of design changes inte nded to increase CAFE levels.

4. Determining the optimum sequence of desi gn 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 ma nufacturer to comply with the new

standards.

6. Determining the net increase in vehicle pr ice 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 describe s the work that was done to develop a “baseline” against which the effect of mo re stringent CAFE standards would be

evaluated. Section 4 describe s how the potential footprint-ba sed 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 desc ribes 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. S ection 8 contains the manufacturer-specific compliance analysis results, showing the incr ease in vehicle price for each manufacturer and for the fleet as a whole for a variety of attribute-based standard s. Finally, Section 9

contains a list of references cited throughout the report.

Appendix A provides detailed specificati ons for the model year 2006 baseline. Appendix B contains detailed re sults 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 character ized the specifications, technol ogy implementation, and fuel economy performance of light-duty vehicles and medium-duty passenger vehicles subject

to CAFE standards under EISA.

In earlier work 1 for the Alliance, baseline fleet char acterizations 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 specificat ions for which baseline data were assembled was broader

than in the 2003 baseline fleet deve loped earlier to s upport analysis of attribute-based reformed fuel economy/CO 2 standards. In addition to th e “basic” parameters in the 2003 baseline (e.g., sales, fuel economy, curb wei ght, frontal area, drag, displacement, power, etc.), data for additional vehicl e attributes such as footprin t, 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 ot her attributes that could be used in the development of ot her forms of attribute-based standards.

The effort consisted of identifying and asse mbling supporting datasets, classification of vehicle types, accounting for existing pe netration of “advanced” fuel economy technologies (as defined under this effort), a nd 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 sale s data were compiled by vehicle model, body style, engine size, and transm ission. (For some models, further breakdowns by trim level were also possible.)

As noted above, MY2006 was identified as that fo r which complete data were available. Although vehicle specification and fuel ec onomy 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-t erm mix of sales. Based on input from Chrysler , a decision was made to use MY2007 sales (provided by Chrysler) to represent all Ch rysler group passenger cars.

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

described below.

A utoSite Pro * – The subscription-based AutoSite Pro data developed by the Automotive Information Center provides a detailed database of vehicle specificati ons and attributes at the individual vehicle model, body style, engine size, and transmission level. (These data were supplied to Sierra under the study e ffort 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, midsi ze, 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, tu rbocharged, supercharged) ;

• Fuel type (gasoline, Dies el or hybrid electric) ;

• Passenger and cargo volumes;

• Rear axle ratio; and

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

N

HSTA 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” sale s version for MY2006. These sale s 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. *

P olk 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 peri od 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.

T he 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, Di esel , 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 EP A’s official fuel economy web site. 2 These data are available at the vehicle make, model/namepla te, body and drive train type, engine size, number of cylinders, fuel type, and transmission level. For flexible-fueled (E85) vehicles, separate fuel economy results fo r 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 a nd unadjusted City, Highway, and Combined (with 55/45 City/Highway weighting) fuel economy.

EPA Test Car List – The MY2006 Test Car List data base compiled by EPA contains vehicle specification, fuel economy, and dynamometer setting data from official

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

identical. For flexible fuel vehicl es (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 ve hicle 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 measur ements for a number of late model vehicles from all major manufacturers were provided by General Motors in a confidential

database. Measured frontal areas and aer odynamic drag coefficients for nearly 150 vehicles between model years 2003 and 2008 were available from this database. They were used to develop regression-based estim ates of frontal area fr om vehicle width and height as described in greater detail later in th is sub-section and to fill in drag coefficients

when these data were not available from auto motive Internet sites (which are described below).

Automotive Internet Sites – A series of Internet sites 3

, 4

, 5

, 6 that provide free automotive content were also used to supply additional ve hicle 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 prov ided 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 si tes 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 th e 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 re presenting the MY2006 baseline fleet began with the AutoSite data. A master spreadshee t was initially populated with the detailed specifications and attributes by vehicle manuf acturer, model, body style, engine size, and

transmission from the AutoSite database. Th e 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 shee t. Aerodynamic data, gear ratios, and truck body type classifications were manually ente red into the master sheet from the ATA

database and various web sites. The master sheet contained a to tal of 1,167 individual vehicle records (617 car reco rds and 550 truck records).

V ehicle sales at the individual model, engi ne, and transmission le vel were generally loaded directly from the CAFE Sales sheet. However, the CAFE Sales database did not separate sales of the some model (and engi ne size/transmission) by body style (e.g. sedan

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

were used to ratio the total sales for a model/engine/transmission combination from the CAFE Sales database by body style.

T he 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:

• F ootprint (ft 2 ) = Wheelbase × (Track front + Track

rear ) / 2

• Interior Volume (ft 3 ) = Passenger Volume + Cargo Volume

• “Box” Volume (ft 3 ) = 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 fr om 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 sometim es 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 inc onsistencies, “best” es timates of Interior Volume were made by summing passenger and ca rgo volumes. (The auto web sites were also used to corroborate the passenger a nd cargo volume values from the AutoSite database, where available.)

Bo x Volume and Power/Weight Ratio (P/W) we re calculated to s upport classification of each vehicle into one of 13 different passenge r 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 si mulation 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 ra rely included vehicle frontal areas. As a result, frontal area was estimated for th e 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 mo dels for which actual data available. The regression-based frontal ar ea was developed using the following form:

))(())(( 2 10 WCHCCA

F ++=

where the estimated frontal area A F (in ft 2 ) is based on a multiple-linear fit of vehicle height H (in inches) and width W (in inches) and C 0 , C 1 and C 2 are the least-squares fitted

coefficients.

Table 3-1 shows the resulting re gression and correlation coeffi cients. 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 C 0 C 1 C 2 Sample Size (N) Correlation (R 2 )

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 co rrelated to vehicle he ight 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 aforementi oned databases was the rolling friction (or rolling resistance) coefficient, C f . Vehicle model-specific rolling resistance was backcalculated in the baseline fleet using track ro ad load horsepower at 50 mph (TRLHP) data that Sierra has compiled in a detailed l ookup table for use in setting dynamometers in IM240-based Inspection and Maintenance prog rams. This “I/M Lookup Table” database contains TRLHP data by model year, vehicl e model, engine size, and transmission.

Under a steady speed on level terrain and assuming no wind, road load power P ROAD is given by:

-11-vFFP AERO ROLL ROAD ) ( +=

v vCA gmCP DF f ROAD )] 2 ()[( 2 ρ + =

where F ROLL and F AERO are the rolling resistance and aerodynamic drag forces, respectively, C f is the rolling resistance coefficient, m is the mass (in kg), g is the gravitational constant, ρ is the density of air (in kg/m 3 ), A F is the frontal area (in m 2 ), C D 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 )4667.150( 0765.0

550 4667.150 3

×× ×××× + ×××

= g CA WCf 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/ft 3 , the frontal area A F is expressed in ft 2 units, and the gravitational constant g is 32.174 ft/s 2

.

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

increase in mass due to driveline rotational in ertia. 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 rolli ng resistance power loss).

Given these assumptions and vehicle test wei ght, frontal area, and dr ag coefficient, the equation above was solved for th e rolling resistance coefficient ( C f ) of each individual vehicle. (Drag coefficients were not availa ble for 99 of the nearly 1,200 vehicles in the baseline fleet. In these instances, rolli ng resistance coefficients could not be backcalculated and were se t 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 distincti ons and accounting for penetrations of advanced t echnologies 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 f undamentally different characteristics. For example, the “small car” category contains hi gh-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 passe nger cars into 13 different categories and light trucks in to 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 gover nment, 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 di fference is that we distinguish between sports cars and other small cars, spor ts/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 Mi d-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

I n contrast, the federal scheme categorizes vehicles based primar ily 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 ar e 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 inconsis tent 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 ve hicles had fuel economy ratings equivalent to what could be achieved by a “typical” ve hicle using an optimum combination of technologies. Assuming that a high-performa nce 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 crea ted to account for characterist ics 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 EP A, our classification sc heme moves most of these models into other categories (e.g., spor ts/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 ve hicles, like the Honda Insight, that do not

meet our definition of “s ports 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 ar ea surrounded by windows). Station wagons are sedans with a greenhouse extended to the re ar of the vehicle to facilitate larger cargo volume or a third row of seating. Subcomp act 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/l uxury sedans, that have interior

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

of such vehicles.

Mid-Size Sedans/Wagons are sedans, other than sports/l uxury 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 t hose in the EPA “mid-size” category.

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

volumes the same as those in the EPA “lar ge” category and stati on wagons that have

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

-14-Small Coupes/Convertibles - Coupes are two-door, fixed ro of 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 s ports/GT cars, with fold-away or completely stowable tops. Small Coupes/Convertibles are c oupes 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-siz e” 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 se dans and wagons, other than sports sedans and wagons, that incorporat e numerous luxury features (such as powerassisted seats, steering, windows, and door lo cks; standard leather upholstery; automated climate control; and numerous decorative items [e.g., meta llic paint, wood-trimmed interiors, aluminum wheels, etc.]) as standa rd equipment and that have no more than 19 pounds curb weight per horsepower. Luxur y sedans/wagons usually incorporate suspension systems designed to maximize ride quality when driven sedately. Small Sports/Luxury Sedans/Wagons are sports seda ns/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 performa nce 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 th e EPA size class for two-s eaters, 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 la ck of distinction betw een 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, widt h, 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 driv e and 4-wheel drive minivans. We classify all vans as either small or large based on th e product of length, wi dth, and height because there are relatively few 4-wheel drive vans a nd 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. Ta ble 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 tr ucks 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 tr ucks 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 tr ucks 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 tr ucks 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 enclos ed 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 encl osed 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, he ight, and width is >680 cubic feet.

Small 2WD Sport/Utility Vehicles are light-duty trucks, othe r than pickup trucks and vans, incorporating relatively high ground clea rance 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, othe r than pickup trucks and vans, incorporating relatively high ground clea rance 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, othe r than pickup trucks and vans, incorporating relatively high ground clea rance and 2-wheel drive, and for which the product of length, height, and wi dth is >450 cubic feet and ≤ 600 cubic feet.

Mid-Size 4WD Sport/Utility Vehicles are light-duty trucks, othe r than pickup trucks and vans, incorporating relatively high ground clea rance and 4-wheel drive, and for which the product of length, height, and wi dth is >450 cubic feet and ≤ 600 cubic feet.

Large 2WD Sport/Utility Vehicles are light-duty trucks, othe r than pickup trucks and vans, incorporating relatively high ground clea rance 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, othe r than pickup trucks and vans, incorporating relatively high ground clea rance and 4-wheel drive, and for which the product of length, height, and width is >600 cubic feet.



### 3 .3 Determination of Advan ced Technology Penetrations

D uring the update of the baseline fleet, se veral technologies affec ting 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-varia ble transmissions (AMT/CVT).

(As discussed later, technology benefits of AMTs and CVTs were roughly similar. Thus, their penetrations were comb ined and treated together.)

Even in cases where penetration of these tec hnologies 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 desi gn changes needed by each manufacturer to comply with new reformed CAFE standards, it was necessary to properly account for advanced technology fractions in the base line fleet. By exhaustively querying manufacturer and third-party automotive web sites, the presence oR absence of each of these four advanced technologi es in the MY2006 fleet at th e individual vehicle model level was determined. In the master baseline fleet spreadsheet, a column for each technology was established and va lues 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 sa les-based technology pene trations by vehicle category across all manufacturers. Subtotals are also shown for al l 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 contai ns roughly 3% cylinde r deactivation, 13%

variable valve lift and timi ng, 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

Deac. Vehicle Category Code 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 A ll 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 data base 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, Mazd a, Mercury, and Volvo. Manufacturer groupings were also applied at the nameplate le vel, consistent with current practice (e.g. the Mitsubishi Raider pickup built for Chrysler was included in Chrysler’s fleet).

Mean values for each vehicle characteris tic were sales-weighted, based on the disaggregated fleet data assembled at the vehicle model, body styl e, engine size, and transmission level. (All fuel economy-re lated metrics were properly harmonically weighted.)

Table 3-5 contains a summary of sales-wei ghted average characteristics of the MY2006 U.S. light-duty * vehicle baseline fleet by vehicl e category obtained from the abovedescribed approach. As show n, “unadjusted” combined C ity/Highway passenger car and light truck fuel economy is 29.38 mpg and 22.04 mpg, respectively.

Th e sales-weighted fuel economy estimates fo r the passenger car and light truck fleets shown in Table 3-5 match the values published by EPA 7 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 da ta in our baseline fleet were

based on MY2007 rather than MY2006 sales da ta. (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., labo ratory) fuel economy values published by EPA include credits for alternativ e fuel vehicles that NHTSA applies when calculating official CAFE results. (As st ated earlier, our baseline fleet fuel economy

excludes the alternative fuel ad justment applied under CAFE.)

Mo re detailed tabulations similar to that pres ented 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 complian ce 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 R over, Lincoln, Mazda, Mercury, Volvo);

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

6. H onda (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 th e MY2006 U.S. Light-Duty a 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

Unadj. Fuel Econ. (mpg) Test

Vehs. Wtd Curb Wt (lb) Power (hp) Disp (cid) %2V City Hwy %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 manufactur er-specific fuel economy targets in MY2020 based on assumptions regarding how the disc retion provided under EISA might be used by the Secretary of Transportation.



### 4.1 Key Assumptions

EISA contains several open-ended provision s 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 r easonable 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 fo rces may result in higher fuel economy in the future, especially if fuel prices remain at cu rrent (April 2008) levels. Forecasting the design changes re sulting from such market forces was beyond the scope of our analysis. We have therefore estimated the necessary design changes and associat ed 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 st andards. 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 ba seline 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 change s 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 ad justed 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 analysis 1 sponsored by the Alliance, Sierra had projected hist orical increases in vehicle weight, power/weight ratio and use of dual overh ead cam [DOHC] engines to continue between MY2003 and MY2009. These trends were projected to match assumptions made by the California Air Resource s Board [CARB] in its analysis

of California’s GHG vehicle emission standa rds. For this analysis of federal CAFE standards, there was no n eed 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 li ght truck standards that, when salesweighted together, yield 35 mpg. The le gislation leaves th e decision on setting the specific car and truck standards that equate to 35 mpg fleet-wide to the Secretary of Transportation. In the ab sence of draft rulemaking from NHTSA, it was assumed that these separate standa rds would be set by requiring the same percentage increase in car and truck fu el economy between the 2006 baseline and 2020. (As shown later in this section, this increase wa s calculated to be just below 40%.)

• Reformed Standards Patterned Afte r Earlier Light Truck Standards – In its March 2006 rulemaking, NHTSA introduced the concept of “Reformed” CAFE standards in setting fuel economy re quirements for MY2008-2011 light trucks. Under Reformed CAFE, fuel economy standa rds were determined on the basis of

a measure of individual vehicle size calle d “footprint,” defined as the product of wheelbase and average track width. (By contrast, earlier unreformed CAFE was simply a single fuel economy standard a pplied to all manufacturers.) Reformed standards were developed unde r this effort using a con ceptually 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 assumpti ons, 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 eco nomy targets for cars and light trucks in 2020. Each of these steps is descri bed in the following sub-sections.



### 4.2 Development of Footprint- Based Reformed Standard Models

The first step in determining EISA-based fu el economy targets consisted of generating footprint-based models for cars and trucks. Th e approach used was consistent with that employed by NHTSA in setting reformed standards for MY2008-2011 light-duty trucks.

-23-Un der that rulemaking, NHTSA selected vehicle footprint (the product of wheelbase and average track width) as the at tribute the agency felt should be used to define vehicle-tovehicle differences in fuel economy standa rds. Although NHTSA considered several

other attributes such as wei ght and power/weight ra tio, these were rejected due to safety and political concerns.

The MY2006 baseline fleet databa se contains a detailed seri es 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 establ ishment 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 s ub-fleet datasets (initially in spreadsheet form) into SAS ® datasets. (Statistical Analysis So ftware, developed by the SAS Institute,Inc. is a multi-platform software package that contains an exhaustive library of preprogrammed statistical analysis and data tabul ation 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 ba sis. (In its earlier light truck rulemaking, NHTSA developed attribute models on the basis of fuel consumption instead of fuel economy. This wa s done to more simply translate the results to estimates of fuel savings.) The SAS “N LIN” 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 i AttCCFC ×+=

where FC i is the fuel consumption (in gallons/100 mile s) of vehicle i

, Att i is the value of a given attribute (e.g., footprint) for vehicle i and C 0 , C 1 , and C 2 are least squares-fitted

coefficients for that attr ibute 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 attr ibute 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 C 2 . A constrained logistic function was also evaluated for footprint-based car and truck m odels in order to replicate the exact form used earlier by NHTSA for light trucks. This constrained lo gistic 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, FP i is the footprint for vehicle i and C 0 through C 4 are the fitted coefficients.

This constrained version of the logistic function flatte ns out at both ends of the range of vehicle footprint (coefficients C 3 and C 4 establish the portion of the footprint spectrum where the curve flattens) and was specif ically chosen by NHTSA to provide a disincentive to designing vehicles wi th very small or large footprints.

Vehicle Weighting – In addition to the f unctional forms, another key issue in attribute modeling involved whether to weight the indi vidual 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 f its by sales-weighting ea ch 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 sale s mix in existence at the time the models are developed. Any real unde rlying relationship between fu el consumption and a given

attribute is less evident when individual vehi cle data points are wei ghted 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 de veloped 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 at tribute 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 co lumn identifies whether the model was fitted using a zero intercept, i.e., with C 0 set equal to zero. (Som e models were tested both ways, with or without setting the intercept co efficient to zero, to assess the importance of allowing the best fitted curve to intersect the y- axis at a point other th an 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 (C 0 ) Model Name Functional

Form Attribute(s)

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 coeffi cients determined for each model and presents sum-of-squared e rror (SSE) and correlation (R 2 ) 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 C 0 C 1 C 2 C 3 C 4 SSE R 2

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

Fi gure 4-1 presents the scatter plot of footprint against actua l passenger car fuel consumption. Each point in Figure 4-1 re presents an individual vehicle (i.e., the combination of make, model, body style, engi ne size, and transmission) in the baseline fleet. As the figure indicates, the correlation between footpr int and fuel consumption is poor. An example of this problem is illustrate d by the dashed vertical line, arbitrarily

drawn at the 44 ft 2 point on the footprint axis. As not ed 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 reform ed standard, both would have to meet the same fuel economy level, even though the lower-powered Civic ha s over twice the fuel economy of the GT/Gransport (39.0 mpg vs. 17.1 mpg CAFE).

As illustrated by the above example, if refo rmed standards are based on an underlying attribute model that is as poorly correlate d 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 nece ssary to comply with fuel economy standards; and

2. Reformed standards for model year 2020 calculated from an attribute model developed either from current baseline da ta 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

R 2 = 0.215

0 1 2 3 4 5 6 7 8 9 10

0 1 0 2 0 3 0 4 0 5 0 6 0 7 0

Footprint (ft2)Fuel Consumption (gal / 100 miles)

8 0 Honda Civic 1.8L, M5 Maserati GT/Gransport 4.2L, MTA6

Light-Duty Truck Models – Table 4-3 below presents a co mparison 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 C 0 C 1 C 2 C 3 C 4 SSE R 2

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 consump tion against footprint is shown for the lightduty truck baseline fleet in Fi gure 4-2. By comparing Figure 4-2 with Figure 4-1 it is apparent that fuel consumption is better corr elated with footprint for light-duty trucks.

Model Year 2006 Light-Duty Truck Fuel Consumption vs. Footprint

R 2 = 0.362

0 1 2 3 4 5 6 7 8 9 10

0 1 0 2 0 3 0 4 0 5 0 6 0 7 0

Footprint (ft2)Fuel Consumption (gal / 100 miles) Figure 4-2 Light-Duty Truck Fuel Consumption vs. Footprint

8 0



### 4.4 Calculation of Fuel Economy Targets

The final step of this study element consiste d of applying each of the selected attribute model equations to each manu facturer’s baseline passenger ca r and light truck fleet data to calculate the expected fuel economy target s 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 calc ulations were performed in a manner in which the separate fuel economy targets fo r each manufacturer (and sub-fleet) yielded this composite standard when comb ined on a sales-weighted basis.

As reported earlier in Table 3-5, the MY 2006 baseline light-duty vehicle fleet fuel economy was 25.09 mpg. Since the standard in 2020 is 35 mpg fleet-wid e, 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 passe nger car and light-duty truck sub-fleets.

-28-A lso from Table 3-5, the baseline fuel ec onomy for passenger cars a nd 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 manuf acturers listed in Table represent over 99.9% of all U.S. light-duty ve hicles 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 vehi cle 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 Veh icles

Parent

Manufacturer U.S

Sales % ( U

Sales % ( U

Sales % ( . PC FE

Sales mpg) .S. LT FE

Sales .S. LDV FE

Sales mpg) mpg)

BMW 309,425 8 4.30% 26.886 60,643 0.80% 21.219 370,06 2.50% 25.759

CHRYS LER 1,4 1 2 1 513,185 7.13% 27.593 87, 885 9.60% 21.927 ,001,070 3.53% 23.146

DAIMLER 195,064 2.71% 24.433 69, 436 0.91% 20.270 264,500 1.79% 23.183

FORD 1 1 1,4 1 2 1 ,067,739 4.83% 27.693 18, 473 8.69% 20.355 ,486,212 6.81% 22.969

GM 1,610,801 22.37% 28.497 1,863,203 24.55% 21.676 3,474,004 23.49% 24.382

HON DA 585,226 8.13% 31.644 662,394 8. 73% 24.758 1,247,620 8.43% 27.573

HYUNDA I 488,393 6.78% 30.468 245,214 3.23% 23.416 733,607 4.96% 27.681

MITSUBISH I 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 4 1 51,130 5.94% 20.901 ,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 1 2 53, 159 2.02% 27.097 17,814 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 1,0 1 2 1 04,012 6.72% 34.499 71, 479 4.12% 23.577 ,275,491 5.38% 28.321

VW 324,832 4.51% 29.787 12,213 0.16% 20.049 337,045 2.28% 29.272

All M frs 7 10 7, 5 10 14 10 ,201,578 0.00% 29.388 90,840 0.00% 22.036 ,792,418 0.00% 25.092

anufacturer-specific reformed fuel ec onomy targets in 2020 were computed by

ble 4-4.

r and light

l M applying the footprint-based mode l 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 mode l-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 applie d 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 attr ibute 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 pa ssenger car fleet fuel economy calculated from the attribute actual fuel economy on an un-weighted vehi cle basis. To the extent that highperformance vehicles in the fleet have rela tively low fuel economy per unit of f and relatively low sales, the equations will pr oduce 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 re lative improvement percentage of 39.49

translate the results from the baseline to mode l year 2020. These steps are best illustrated

with actual data.

T performed. Table 4-5 shows th ese calculations using the co nstrained logistic footprint attribute model (FP-L). In the table, the rows and columns are labeled as in the spreadsheet. Passenger car calculations ar e shown in Columns B through H. Sim computations for light-duty trucks are cont ained in Columns J through P. Light-duty fleet composite calculations are gi ven in Columns R through V.

F

model is shown under the heading “Attrib ute 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 th is 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 fu el economy calculated from the equation is higher than the actual fuel economy for manufacturers like Porsche who produce primarily high performance vehicles. (As s hown in Column D of Table 4-5, Porsc actual baseline passenger car fu el economy is 25.2 mpg, but th e 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 th e 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 botto m of Column F now matches the actu baseline passenger car fleet fuel econo my shown at the bo ttom 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 Colu mn F. These are the manufact urer-specific passenger car economy targets required in 2020 under EISA us ing a footprint-based reformed model.Table 4-5MY2020 Reformed Fuel Economy Requirementsby Manufacturer – Footprint-Based Approach31323335373839404142434445464849505152535456A B C D E FGH J K L MNOP R S T UVForm: FP-LEquation: FC = C0 + [1/C1 + (1/C2 - 1/C1) x EXP((FP-C3)/C4) / (1 + EXP((FP-C3)/C4)]Multiplier:1.142Multiplier:1.018ParentManufacturerU.S. MY06PC Sales% of MfrLDV SalesBaseline FE(mpg)AttributeEquationBaselineTargetTarget(mpg)% FEChangeU.S. MY06LDT Sales% of MfrLDV SalesBaseline FE(mpg)AttributeEquationBaselineTargetTarget(mpg)% FEChangeU.S. MY06LDV Sales% of U.S.LDV SalesBaseline FE(mpg)Standard(mpg)% FEChangeBMW309,425 83.61% 26.886 25.610 29.23740.78251.68% 60,643 16.39% 21.219 23.229 23.63632.96955.38% 370,068 2.50% 25.75939.25752.40%CHRYSLER 513,185 25.65% 27.593 23.800 27.17137.90137.35% 1,487,885 74.35% 21.927 22.087 22.47531.34942.97% 2,001,070 13.53% 23.14632.80341.73%DAIMLER195,064 73.75% 24.433 24.973 28.51139.76962.77% 69,436 26.25% 20.270 20.882 21.24829.63846.22% 264,500 1.79% 23.18336.49457.42%FORD1,067,739 42.95% 27.693 25.051 28.60039.89344.06% 1,418,473 57.05% 20.355 21.097 21.46729.94347.10% 2,486,212 16.81% 22.96933.53546.00%GM1,610,801 46.37% 28.497 25.315 28.90040.31241.46% 1,863,203 53.63% 21.676 21.109 21.47929.96138.22% 3,474,004 23.49% 24.38234.01039.49%HONDA585,226 46.91% 31.644 25.880 29.54641.21330.24% 662,394 53.09% 24.758 22.038 22.42531.27926.34% 1,247,620 8.43% 27.57335.26727.90%HYUNDAI488,393 66.57% 30.468 26.770 30.56242.63039.92% 245,214 33.43% 23.416 23.488 23.90033.33742.37% 733,607 4.96% 27.68138.99740.88%MITSUBISHI 101,433 75.35% 29.311 26.977 30.79842.96046.57% 33,176 24.65% 23.926 24.138 24.56134.25943.19% 134,609 0.91% 27.77040.42945.58%NISSAN635,417 58.48% 28.822 25.492 29.10340.59440.85% 451,130 41.52% 20.901 21.165 21.53730.04143.73% 1,086,547 7.35% 24.90435.42742.26%PORSCHE24,081 60.52% 25.212 29.675 33.87847.25687.43% 15,706 39.48% 18.564 21.377 21.75230.34163.44% 39,787 0.27% 22.09038.73275.34%SUBARU64,655 29.68% 27.770 28.574 32.62145.50263.86% 153,159 70.32% 27.097 25.512 25.95936.21033.63% 217,814 1.47% 27.29338.54741.23%SUZUKI69,867 59.92% 29.497 28.662 32.72245.64254.74% 46,728 40.08% 24.058 24.733 25.16735.10545.92% 116,595 0.79% 27.04640.74150.64%TOYOTA 1,204,012 52.91% 34.499 26.991 30.81442.98224.59% 1,071,479 47.09% 23.577 21.720 22.10130.82830.76% 2,275,491 15.38% 28.32136.25228.00%VW324,832 96.38% 29.787 26.879 30.68742.80443.70% 12,213 3.62% 20.049 21.320 21.69430.26050.92% 337,045 2.28% 29.27242.17044.06%All Mfrs7,201,578 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% 14,792,418 100.00% 25.092 35.000 39.49%LDV FUEL ECONOMY STANDARDS UNDER NEW CAFE ALTERNATIVES - HOUSE ENERGY BILL (H.R. 6)LDV Fleet Sales-Weighted CompositeLight-Duty Trucks (& MDPVs)Passenger Cars-31-Finally, Column H shows the relative change in fuel economy resulting from these targets for each manufacturer compared to the ma nufacturer’s actual (MY2006) baseline passenger car fuel economy contained in Colu mn D. As shown in Column H, required improvements between 2006 and 2020 range fr om 24.6% (Toyota) to 87.4% (Porsche) and are dictated by the distribution of footpr int within each manuf acturer’s passenger car fleet. (Note the sales-weighted average com puted 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 li ght-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 exampl e, BMW’s composite fleet standard of 39.257 mpg shown in cell U40 was calcu lated from sales fractions in cells C40 and K40 and fuel economy targets in cells G40 and O40 as follows:

mpg dardS
BMW 257.39 )]969.32/%39.16()782.40/%61.83[( 1 tan = + =

As stated earlier, these compliance calc ulations 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 ve hicle 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 combus tion engines has to consider the fact that maximum fuel economy is achieved by mini mizing propulsion energy requirements and maximizing the efficiency with which fuel is converted to mechanical energy. Propulsion energy requirements are primarily de termined 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 engi ne 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 vehi cles. For a typical midsized passenger car, a 10% reduction in its weight will im prove fuel economy by about 3.9% while simultaneously increasing the performance of the vehicle. A 10% weight reduction combined with resizing the engine for cons tant performance will improve fuel economy by about 7.6%.

By reducing frontal area and streamlining the sh ape of the vehicle, less power is required to maintain any given speed, which improve s 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 co mbined with resizi ng 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 re sistance is reduced. For a typical midsized passenger ca r, a 10% reduction in rolling resistance will improve fuel

-33-economy by about 1.8%. A 10% rolling resist ance reduction combined with resizing the engine for constant performance will improve fuel economy by about 1.9%.

Increasing Engine Efficiency –The most significant fact or in overall power train efficiency is engine efficiency. Both gasolin e and Diesel engines are most efficient when they are run at relatively hi gh load, producing close to the maximum available power at a particular engine speed. Engi nes 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 signi ficant in Diesel engines but are a major source of inefficiency in gasoline engines, in which re striction of intake airf low is the method used to control power output. Smaller, less pow erful 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 de sired level of maximum vehicle performance (e.g., acceleration rate, towing capacity).

Af ter the engine power level needed to ach ieve the desired performance level has been established, fuel economy can be improve d by a number of different techniques, including the following:

1. Using design features that minimize th e engine size required to achieve the desired power level (e.g., 4-valve cylinde r 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 losse s associated with low power levels;

3. Using variable valve lift and timing to minimize the throttling loss associated with part-load operation;

4. D eactivating cylinders to minimize the th rottling loss associated with producing low power levels;

5. Using gasoline direct in jection (GDI) to achieve higher efficiency through increased compression ratio (as noted a bove, GDI also enables some engine downsizing);

6. Reducing engine friction and parasitic losses;

7. Turning the engine off during period s 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 th e 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 conti nuously 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 upshift s under part load operation, can be used to reduce throttling losses (at the e xpense 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 o ccur in the torque converter. The torque converter is the hydraulic coupling that can be used to increase to rque at low engine speeds and provide for a smooth launch and smoo th shifts. However, the efficiency loss associated with the fluid coup ling reduces overall transmission efficiency. Efficiency can be improved by mechanically “locking up” th e torque converter earlier or replacing the torque converter with a fric tion clutch of the type used on a manual transmission. A transmission with an automatically controll ed friction clutch is referred to as an automated manual transmission (AMT).



### 5.2 Benefits of Individual Technologies

Based on the available tec hniques for improving fuel ec onomy 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 th at 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 in crease performance (e.g., replacing a 5- speed transmission with a 6-speed), our analys is assumes engine downsizing to maintain constant 0-30 and 0-60 mph acceleration perf ormance for passenger cars, minivans, and unibody sport utility vehicles. For pickup tr ucks 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 or iginally 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 shap es, using a variety of different engines and transmissions. A schematic showing the ba sic 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 th e specified speed-time profile. Based on the tire size, axle ratio, and axle efficiency, th e 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 l ogic, torque converter speed ra tio, 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 dete rmined from the engine map. * The fuel consumption is computed 20 times a second by interpola tion between the individual data points contained on the map. Fuel economy is calculated by integrati ng 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 lo ad. 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 expe rienced under deceleration to full load).

-36-consumption over a specified driving cycle. To compute city/highway combined fuel economy, approximately 45,000 indivi dual calculations are combined.

The baseline engine maps used in VEHS IM 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. Transm ission modules have been configured to represent different numbers of gears, gear ratios, torque converter characteristics, and shift logic. Hybrid vehicles are simulate d by continuously accounti ng 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 co mbustion 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 bei ng 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 estim ates 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 m odel 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 duri ng 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 al so used to evaluate the effect of fuel efficiency improvement technologies on the ab ility of vehicles to maintain freeway cruising speeds on grades (i.e., “gradeability”).

In cases where a technology was already in pr oduction, the accuracy of the model in representing the technology changes was check ed by comparing model results to CAFE data. Table 5-1 presents the results for simulations of con tinuously variable valve lift and timing and cylinder deactivation compared to the actual performance of vehicles using those technologies. As shown, the VEHS IM predictions matched actual CAFE test results within 2%, which is less than the variab ility in test results that would be expected from two different drivers testing the sa me car in two different laboratories.

The use of a vehicle simulation model to evaluate the individual technologies was important because it allowed for all technol ogies to be evaluated using a consistent, representative baseline. The fuel economy benefit of a pa rticular technology cannot be accurately evaluated just by comparing test re sults 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 representativ e 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 reducti ons 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 combin ations of technology were modeled.) The table shows the reduction in fuel consump tion 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 Calif ornia driving patterns. This distinction is significant for certain technologi es that provide greater bene fits on the 30-year old CAFE test procedures than in actual driving. As our research has demons trated, the CAFE test procedures are no longer represen tative in terms of speeds, time at idle, and acceleration rates. (Although the referen ced study was focused on Califor nia driving patterns, data collected in other states more closely matc h California driving patterns than the CAFE test procedures.)

-38-Table 5-2

Estimates of Achievable Fu el 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 Suspension a,b -3.3% -3.2% -1.2% -1.5%
Aluminum Body vs. Ultralight Steel b -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-Stoichio metric -5.9% -4 .8% -6.2% -5.1%
Turbocharging (with engine resize) 0.3% 2.7% -0.3% 2.8%
OHC Engine Replaces OHV Engine c -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 Tran smission -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 ar e 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 seve ral acceleration-deceler ation “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, resp ectively. Like the urban comparison, the Cal-Rural cycle has more high speed travel than its counterpart, the EPA Highway cycle, and dramatically so. The ma ximum 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 anal ysis indicates that a 3.3% reduction in fuel consumption could be achieved thr ough the use of ultrali ght steel in midsize

sedans. This reduction is relative to a baseli ne fleet that already uses lightweight steel closures and has 50% penetration of ultra light steel bodies and suspensions. Lesser reductions are available in trucks using body on frame construction. Greater reductions

are available with the use of aluminum. Th e 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% reducti on in the weight of components designed and produced using ultralight steel, which incl udes 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 su spension. 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 re duction potential for unibody construction. Since most vehicles with body-on-frame constr uction are designed to carry or tow heavy loads the theoretical benefits of compoundi ng 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 ultrali ght steel in the baseli ne 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 approxima tely 50% lighter than unibody vehicles constructed from conventional, mild steel. When aluminum closures are accounted for, the incremental reduction in weight over ultra light steel is an additional 7.9% over a mild steel baseline vehicle (an additional 8.8% reduction over ultralight st eel). As shown in Table 5-2, the corresponding reducti on in fuel consumption is 5.3%.

For body-on-frame construction, we estimat e the use of aluminum can achieve an additional 3.8% reduction in weight can be achieved over a mild st eel baseline vehicle using lightweight closures, bringing the tota l 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 Unibody Category 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 consider ed. The first involves minor changes in lubricants and/or minor engi ne 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 pa rasitic 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 devel opment by a particular manufacturer, the

details of which are confidential. Other ma nufacturers are known to be pursuing similar design changes.

Variable Valve Lift And Timing – For technologies providin g variable valve lift and timing, our analysis indicates that fuel cons umption 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 e ngine output without usi ng a throttle. (This requires either “camless” technology, such as electro-hydraulic valve actuation, or a relatively complex mechanical system simila r to the “Valvetronic” system developed by BMW.) The specific benefits are based on t echnical literature showing the effects of variable valve timing and lift on engine effici ency across the full range of engine load. *

* See, for example, SAE paper number 2001-01-0667.

-43-It should be noted that our ve hicle simulation modeling indica tes 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 proc edures. (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 econo my by reducing throttling losses.)

Cylinder Deactivation – For cylinder deactivation systems, our vehicle simulation modeling indicates that a 7.5% reduction in fuel consum ption 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 be nefits 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 cylinde r 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 bene fits are calculated using an engine map that reflects appr opriately reduced throttling lo sses over the full range of speeds and loads where the cylinder deactivatio n system can be activated. (Our cylinder deactivation maps have been validated by comp aring 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 descri bed 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 abil ity to increase comp ression 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 compressi on ratio. Assuming a ba se compression ratio of 10:1, the theoretical benefits of a 1.25 nu mber increase in compression ratio would be 3.8%. A benefit this large would not be real ized 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 syst em). A more reasonable estimate of the efficiency increase would be 3%.

In addition to the efficiency change associ ated with higher compression ratio, numerous SAE papers indicate that the charge cooli ng effect of direct in jection increases the volumetric efficiency of an engine by approximately 3 - 4%. * Combined with an efficiency increase of 3%, the increase in vo lumetric efficiency is estimated to increase peak torque and power levels by approximate ly 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 seda n. 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 co mpromises that would reduce volumetric efficiency and reduce or eliminate the bene fits 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 en gine would improve fuel economy by reducing throttling losses. However, it is also necessa ry to account for the effect of turbocharging on octane requirement. To avoi d an increase in octane requirement, it is necessary to reduce compression ratio, which adversely a ffects fuel economy. The simultaneous application of turbocharging a nd direct injection can reduce or eliminate the need for a compression ratio reduction, but turbochargi ng and downsizing without the use of GDI does not yield benefits on a constant performa nce basis, based on a st atistical analysis of

available CAFE data done in 2004. 8 A more recent analys is 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, r 2 =0.83, Excludes Hybrids)

The small dots in Figure 5-6 show, for natu rally-aspirated vehicl es, 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 (r 2 ) is 0.83. The triangles represent the turbocharged vehicles in the data set that do not use gasoline direct injection (GDI). Th e “predicted” fuel economy was

-45-calculated with the same equation used for the naturally-aspirated vehicles. As the figure shows, the turbocharged vehicl es, on average, fall along the same line, which indicates that turbocharging has no effect on fuel ec onomy when weight and power-to-weight ratio are held constant. The three larger squares re present 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 a ll of the benefit are associated with GDI and premium fuel, not turbochargi ng. 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 dow nsizing on fuel economy also depends on the metric used to determine constant perform ance. The amount of downsizing that is possible depends on whether “launch” performa nce is being maintained in addition to other performance metrics, such as 0-60 m ph acceleration time. Ma intenance of launch feel limits the downsizing that is possible with turbocharging. Automotive journalists frequently note that degraded low speed acce leration and throttle lin earity (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 associat ed with replacing 2-valve, OHV engines with 4-valve, OHC engines. As noted in the f ootnote to the table, these benefits are not available for truck engines re quiring relatively high “torque ri se” (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 a ggressive 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 te st procedure and a 3.6% reduction in actual customer service. (About ha lf 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 be ing able to maintain constant acceleration performance with a slightly downsized engi ne.) Automated Manual Transmissions were estimated to provide an additional 4% reduc tion 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 proc edures. The EPS benefit was developed using simulation modeling. The incr ease in alternator efficiency is based on

our review of test results reported by indi vidual manufacturers.

Hybrids – A wide range of hybrid system designs have been developed. At one end of the spectrum are systems with just enough elec tric motor power to facilitate an “engineoff-at-idle” strategy with ra pid restart when the accelerator is depressed. We have modeled a “mild” hybrid system that has a slig htly larger motor (10 kW) that can provide

-46-a minor amount of launch assist and can qua lify as a “Type D” hybrid under the ZEV regulations adopted by the California Air Re sources Board. Our modeling of a mild hybrid system produced a fuel consumption redu ction using the CAFE test procedures of 7.3%. In customer service, the estimated bene fit 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 maintaini ng 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 rege nerative 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 proced ure, the result is a predicted reduction in fuel consumption of 28.7%, which is equiva lent to a fuel economy improvement of 40.3%. This is the hybrid system benefit associ ated 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 accoun t for the amount of electric motor assist available. With this type of system, th e vehicle would have e quivalent acceleration performance; however, towing capacity would be reduced because battery energy would be depleted quickly. For truc ks that need to maintain towing capacity, the engine could

not be downsized. This would reduce the benef its 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 calcula ted are representative of what can be accomplished with what is sometimes referre d to as a “strong” hybrid system. Although there are not yet any industry standard defini tions, we have used the term “strong hybrid system” to refer to a system that has a la rge 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 th at 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 consider ed a “moderate” hybrid; however, we have not included such a system in our detailed analysis of what tec hnologies 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 ener gy required for hard accelerations would exceed the amount of energy being recovered th rough 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 c onsider the most cost-effective hybrid system rather than the most fuel efficient.)

Diesel Engines – Table 5-2 shows that the fuel c onsumption 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 act ual turbocharged, dire ct 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 accel eration performance of the industry average midsize passenger car, and compared the results to the simulati on 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 we ights 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 Merced es 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, wh ich 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 st andards, its fuel economy would be reduced to 33.8 mpg, which is 2.0% lower than our esti mate. Thus our analysis is consistent with the level of fuel economy demonstr ated by the Mercedes E320 diesel.

Reductions In Aerodynamic Dr ag And Rolling Resistance – It should be noted that our analysis assumes that signifi cant reductions in aerodynamic drag and rolling resistance are not feasible. Styling limitations w ould be imposed by further reductions in aerodynamic drag and there is evidence that ma ny consumers favor st yling 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 & Dr iver, “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 sty ling are apparent at other companies and the similar effects on drag coefficient are e xpected. 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 de tailed analysis indicates that (1) the rate of progress in reducing rolling re sistance 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 thes e technologies was also performed. These technology cost estimat es 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 annu ally produces “The Harbour Report,” which compares manufacturing pr oductivity throughout the industry. The Martec Group is a partnership of consu ltants specializing in business-to-business markets, including Tier 1 and Tier 2 suppliers to the automotive industry.

V ariable 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.

H arbour provided detailed estimates of fixed (e.g., tooling) and variable costs for a wide range of engine, transmission, and body de signs. Information obt ained from Harbour was supplemented with research and developm ent (R&D) cost information obtained from

individual manufacturers. The sum of “overh ead” 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 Ha rbour 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 warra nty 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 li ft 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 Ma rtec Group from indivi dual manufacturers

and vendors. We also relied on The Martec Group to obtain subsystem cost estimates in

cases where Harbour did not ha ve detailed cost studies av ailable from which reliable information could be provided regarding th e 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 th e batteries used in hybrid electric vehicles, the capacity of the batteries required for heavier vehicles in creases 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 us ed in a 3,300-pound curb weight passenger car. For comparison, Harbour’s cost estimate s 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 pr ice 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 t echnologies that have not yet been fully amortized. Estimates are provided for the av erage 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 $209 a $171 a,b

Aluminum Intensive Vehicle (over UL Steel) $1,596 $1,240 b

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 Li ft (w/ Cam Phasers) $518 $634 Continuously Variable Va lve 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-Hydrau lic Power Steering $82 $150 Higher Efficiency Alternator $73 $89 Gasoline Direct Injectio n-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 Ul tralight steel costs assume 50% of the technology is already in the baseline.

b Cost for materials substitution is lower for pick ups 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 sm aller and larger vehicles.

Ultralight Steel Body and Suspension – Cost estimates for the expanded use of ultralight steel are based on estimates provided by Ha rbour 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 ma ximum use of ultralight steel necessitates a relatively slow ramp up. The estimated incr ease in retail price of $209 for midsize cars applies only to vehicles that are currently usin g minimal amounts of ultralight steel. On average, about 50% penetration of ultralight steel is estima ted to be included in the baseline by model year 2020.

-52-Aluminum Intensive Vehicl e Incremental to UL Steel – Cost estimates for aluminumintensive vehicles are based on estimate s provided by Harbour Consulting.

Reduced Parasitics-I – The cost estimate for a misce llaneous 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 co mbination of technologies is based on variable cost and R&D cost estimates pr ovided by a large volum e manufacturer that has developed the technologies. The proprie tary technologies on which the estimate is based cover three different sources of parasi tic losses that are unrelated to improved alternators and power steering (whi ch 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 combin ed with research, development, and engineering cost estimates obtained fr om 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 estim ates prepared for the previously referenced NESCCAF report of $115 for electro-mechanic va riable valve lift pl us $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 ch ange in retail price associated with Continuously Variable Valve Lift and Timi ng at $899 RPE for a midsize passenger car. This was for an electro-mechanical type syst em 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-cy linder 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 assumpti ons used in our own analysis. Using a markup factor of 2.0 to 2.05, Martec’s esti mate 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 associat ed 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 re placement 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 ab le to match the launc h 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 va riation in the cost estimates, it does not affect our analysis because turbocharging w/ downsizing is not cost effective relative to other technologies und er either estimate.

Cylinder Deactivation – In its work for NESCCAF, Martec estimated the variable cost increase for cylinder deactivati on 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 in crease 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 rela ted 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 automa tic 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 sh own that the achievement of comparable driveability requires features that signif icantly increase cost. Updated estimates developed by Martec put the increase in vari able costs for a 6-speed, dual-clutch AMT at $300 to $400 over a conventional 4-speed automa tic, 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 produce d with completely different tooling, and since there has recently been substantial capital investment in new 6-speed automatic transmissions, analyses based on the assume d use of less expensive, automatic manual transmissions apply only in th e 2020 and later time frame.

Electric Power Steering and El ectro-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 repor t. 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 genera lly 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 mitig ation 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 syst em. Variable cost for the system was $800 for the FAS system and $120 for a 42-volt l ead-acid battery to which was applied a markup factor of 2.05. The markup fact or 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 wa s 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 ma ximize the amount of energy that can be captured through the use of regenerative brak ing on the CAFE test procedure. (Our detailed vehicle simulation modeling indicates th at 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 vehicl e 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 si zed at 25% above peak battery power to account for the efficiency loss in transferri ng braking energy through the generator and

inverter/converters into the ba ttery. Based on cost estima tes obtained from Martec, the variable cost equations provided for the flyw heel/alternator/starter (FAS) style hybrids were $96+$502/kWh (or $96+$31/kW) for Ni MH 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 co st of brake-by-wire, electric power steering, electric accessory drive, a nd 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 ener gy required for hard accelerations would exceed the amount of energy being recovered th rough 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 a nd more comprehensive analysis of hybrid system costs. A variable cost of $1,040 wa s estimated for the combination of brake-bywire, electric power steering, electric accesso ry 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 estim ate 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 duri ng 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 (v ariable) 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 si gnificant reductions in lithium prices as volume increases. Martec reports that sour ces 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 uncertain ty associated with Li-Ion battery cost, we have continued to base our hybrid system co st 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 in crease in nickel prices since our earlier estimate was prepared. This increases the va riable cost estimate for the battery from $873 to $1,193. With a 1.61 markup factor applie d to the variable cost, this increases the RPE of a midsize hybrid by $515. Our upda ted 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 th e motor/generator and power electronics for a midsize hybrid is $2,388 (variable). In contra st, our previous variab le estimate for these components was only $1,305. However, our estimate is for a system with the motor/generator and power electronics si zed 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 contin ued to use our earlier estimates for the cost of the lower powered system. However, as noted previous ly, higher capacity motor/generators are used on several hybrid vehicles that are al ready 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 engi ne. 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 $896 b

Total Variable Costs $1,284 $1,635 $4,818

Amortized Fixed Cost $256 $273 $321 Retail Price Equivalent c $2,480 $3,073 $8,274 $5,201-$5,794

a Excludes ECM, alternat or, 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, Th e 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 estim ated 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 ga soline 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 rela ted to higher platinum group metal prices since Martec’s

earlier aftertreatment cost estimate on whic h we relied. On an RPE basis, the higher

aftertreatment costs translat e 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 rati o (dollars per percent reduction in fuel consumption) calculated by dividing the pri ce 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 employe d in combination. For example, the fuel economy benefits associated with Diesel en gines and gasoline e ngines with variable valve lift and timing are not available simu ltaneously. One technology must be removed

before the other is added. Note that Di esel engines end up not being assumed in our analysis because hybrid systems applied to gaso line vehicles provide slightly higher fuel economy improvement at slightly lower cost. There are other reasons why a manufacturer may opt for Diesel s instead of hybrids, particularly in trucks; the net price increase associated with that approach, how ever, 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 Va lve Lift & Timing $79 $89
Discrete Variable Valve Lift & Timing $82 $94
Gasoline Direct Injectio n-Stoichiometric $94 $110
Strong Hybrid (7 kW battery power/1000 lbs.) $208 $391
Mild Hybrid (42-volt, 10 kW) $259 $608
Diesel Engine (turbocharge d, direct injection) $291 $407
Aluminum Body vs. Ultralight Steel $299 $665
Turbocharging (with engine resize)

- $1,676

###

-58-

### 7. V EHICLE SIMULATION MODELING

Starting with the baseline fleet characterist ics for model year 2006, vehicle simulation modeling was performed to evaluate the improvement in fuel economy associated with various combinations of design changes appl ied to 25 different vehicle categories for 11 different manufacturers. The modeling appr oach and key elements of the simulation modeling runs are descri bed in this section.



### 7.1 Modeling Approach

Table 7-1 lists the technology combinations th at were modeled based on those deemed to

be cost-effective under nationwid e federal CAFE compliance. As shown in the table, the deployment sequence was slightly different fo r pickup trucks and SUVs than for other vehicles because 2-valve/OHVengines are re tained 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 mode led 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 t echnologies were modeled using the VEHSIM

vehicle simulation model. Use of the model ensured that interaction between technologies would be properly accounted fo r 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 indivi dual 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 co uld 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 w ith a second-by-second drivi ng cycle over which vehicle operation is simulated and fuel ec onomy/consumption is calculated.

VEHSIM runs were set up and executed for each of 11 manufacturer s and for each of the 25 vehicle categories used to classify the ve hicle fleet that were described earlier in

Section 3. A total of 139 sets of manufact urer/vehicle category r uns 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 si mulated urban fuel economy to reflect the hot/cold start weighting (43% and 57%, resp ectively) in the Federal Test Procedure (FTP). Each of these adjustments is discussed below.

4WD Adjustment – For all 4WD vehicle category si mulations, a correction factor was applied within the model to represent 4WD fuel consumption based on reported CAFE

differences between similar 2WD and 4WD mode ls. Relative differences in CAFE fuel consumption between 2WD and 4WD versions were found to be very similar across manufacturers and vehicle types. On aver age, 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 econom y data from EPA’s Mobile Source Observation Database (MSOD) were queri ed to calculate an adjustment factor to translate hot start urban fuel economy simulated by VEHSIM to FTP weighted conditions. This adjustment factor was dete rmined 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 adjustme nt factor was also applied to the Cal-Urban cycle fuel economy simulated within the model.)

-60-

### 7.2 VEHSIM Modeling

Th e VEHSIM model was programmed to si mulate 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 drivi ng patterns. (Speed traces fo r each of these cycles were presented and discussed earlier in Section 5.) Manufacturer and vehicle category-specific VEHSIM modeling runs were pe rformed in two separate stages, as summarized below.

1. 2006 Baseline Runs – These simulations were based on MY2006 U.S. salesweighted characteristics (weight, engi ne 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 Baseli ne cases used “blended” engine maps, which were constructed by aver aging 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 baseli ne 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 unde r “Baseline Technology Penetration Adjustments.”)

Al l of the maps were for regular fuel (87 R+ M/2 octane rating) engi nes. All maps were adjusted to reflect an assumed 2% reducti on in engine friction from the 1998 time period when the maps were developed. (This adju stment 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 represen t the actual gearing of high-volume models. Four-speed automatic transmission shift logic was configured to repr esent typical current shift logic provided to Sierra by high-volume automobile manufacturers. The shift logic used for 5- and 6-speed automatics was rela tively aggressive (i .e., early upshifts).

Ea ch of the up to 25 vehicle categories fo r 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 tr ansmissions were treated as AMTs).

-61-Inputs to the model that identify the fleet fr actions by engine and transmission type for each manufacturer/vehicle category combina tion are then used within VEHSIM to compute sales-weighted average fuel econom y estimates composite d across engines and

transmissions.

Baseline Technology Penetration Adjustments – As noted earlier, baseline simulations

were based on the basic blended OHC a nd OHV gasoline engine maps. (VEHSIM’s internal logic expect s baseline engines to be based on standard OHC or OHC blended maps.) Thus, the baseline simulations by ma nufacturer and vehicl e category had to be adjusted to account for the fact that the current fleet now c ontains sufficient fractions of cylinder deactivation, variable valve lift and timing and st rong 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 penetra tion. The individual technol ogy benefits shown in Table

5-2 were listed on a fuel consumption basis. They were converted to fuel economy adjustment factors and combined with penetr ation rates of each of the three individual technologies by manufacturer and vehicle category. (N ote that the penetration percentages shown earlier in Table 3-4 were compiled for all manufacturers. These adjustment calculations were performe d 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 di screte variable valve benefit of 6.7% (on a fuel consumption basis).

Although not shown in Table 3-4, Diesel-fuele d baseline vehicle fr actions were also compiled and applied to the turbocharged , direct-injection Diesel engine fuel consumption reduction of 21.5% shown in Tabl e 5-2 to incorporate a similar adjustment

for baseline Diesel use.

Finally, although Table 3-4 also listed penetratio ns 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 reporte d CAFE results. These comparisons were performed using sales-weighted composites of each of the 25 mode ling categories across all manufacturers and are presented below in Table 7-2. Table 7-2 also shows the advanced technology penetration adjustment f actors applied to each vehicle category.

-62-(Note that the uncorrected VEHSIM fuel econom y is not shown in the table. The values

in the “Modeled” column incl ude the adjustment for advanc ed technology penetrations.)

Table 7-2 Comparison of Reported and Simulated MY2006 Baseline Fuel Economy by Individual Vehicle Category Across All Manufacturers

CAFE Fuel Econom y ( m pg) 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 18.83 17.97 -4.6% 1.0042

Sales-Weighted Averages 25.09 25.21 +0.5%

As shown in Table 7-2, modeled fuel econom y averaged across all manufacturers agrees within 6% of reported CAFE levels for most of the individual categor ies, 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- a nd high-performance engines, the modeled results are in very good agreement with reported values. Th e overall relative error sales-weighted across all categories was 0.5% as high lighted 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 categ ory, 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 ma nufacturer/vehicle cat egory included only 5- speed manuals and 5-speed automatics in the ba seline, 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 exis t on the same engine and whena 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, accelerati on 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 ex ecuting “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, fu rther 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 impo ssible to rely on the electric motor). For SUVs, resizing was simulated for half of the fl eet 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 wei ght reduction technol ogies. (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 coul d be determined at a later point in the workflow.) These “Future Runs” workbooks ha d 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 techno logy step is identified in the “Case” and “Description” columns. (Case-00 is the base line 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 rela tive to the baseline are shown in the “%FE” and “%FC” columns to the right of these. Se lected vehicle specifications (test weight and engine size) and performance measures (gradeability, * 0-30 and 0-60 times) are shown in the rightmost columns.

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16 AB C D E F G H N O P Q R S T U VW Test Displ Line # Case Description Urban Highwa y 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 Simula tion Summary for Chrysler CSWs

The simulation modeling results in these “Fut ure Runs” spreadsheets were then combined with cost data for each technology and used to calculate the tec hnology requirements and costs to comply with EISA as discussed in the next section.

###

* Gradeability as defined in these VEHSIM outputs represents the perc entage 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 w ith retail price-equivalent technology costs and calculated 2020 fuel economy targets by ma nufacturer under new EISA-based CAFE

standards to determine the am ount 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 technol ogy 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 cont ained the technology deployment or “supply curve” calculations for each vehicle category in that manufacturer’s fleet. These supply curves calculate the fuel economy and incr emental cost-effectiveness (in dollars per percent change in fuel consumption) at each st ep 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.).

T he cost-effectiveness spreadsheets were lo aded 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 star t 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-e ffectiveness. These data included the following:

• Sa les Fractions, Weights and Other Specifications – Baseline sales mixes, curb weights, 2V and 4V engine fractions, tran smission type fractions, fleet fractions of vehicles with more than 4 cylinde rs and advanced t echnology 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 tr ucks) based on EISA implementation; and

• Base Technology Costs – Individual technology cost s 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 th e baseline fleet (for a given manufacturer and vehicle category) already contained 20% of that technology on a sales basis. This 20% technology penetration fract ion is used within the CE spreadsheet to adjust the simulation modeling outputs (w hich 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 fact ors 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 wei ght.) The costs used in this analysis are long-term costs and do not in clude 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

Factor Tech Code

A5 w/Aggressive Shift Logic over A4 w/o ASL $238 50% ASLA5

PARA Lower Eng. Fric./Parasitics $14 50%

PARA2 Lower Eng. Fric./Parasitics-2 $122 0%
Cylinder Deactivation on 2V Engines $360 50% CD2V(Deac)

CVVL&T on 4V After 2V to 4V $899 50% CVVLT

CVVL&T on 4V $899 50% CVVLT4
Electric Power Steering $82 50% EPS
Electro-Hydraulic Power Steering $123 50% EHPS
UL Steel vs. closures only, 50% Penetration $417 100% ULS

DOHC V6 vs OHV V6 $593 50% DOHC

IMPALT Imp. Alternator/Charging $73 50%
6-Speed AMT vs. 5-Speed Automatic $311 50% AMT6
Gasoline Direct Injection on 4V DVVLT $553 50% DVGDI
Gasoline Direct Injection on 4V CVVLT $553 50% CVGDI

Aluminum Incremental to ULSteel $1,596 100% ALM $1,850 a 100% AHYB Advanced Hybrid w/Regen Braking

a Advanced hybrid cost shown is in dollars per 1,000 lb curb weight

The weight scaling factor repres ents 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-sca led 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 wei ght measure available on other vehicle types (vans, pickups, and SUVs). (For exam ple, pickup trucks get a lower percentage weight reduction for aluminum because they retain body-on-frame construction and therefore do not achieve as gr eat a reduction in weight as can be achieved with a unibody passenger car.) The next row—“Discount Fact or”—is used to account for the fact that

-68--69- roughly half of the benefits of ultralight st eel are already being ach ieved in the baseline fleet. Thus, the available benefits (and co sts) beyond the baseline are discounted by 50%.

(The LOOKUPS sheet also contains annual mileage accumulation rates and assumed fuel prices, tax and discount rate s, and “rebound effect” factor s 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 “F uture Runs” spreadsheets) to generate technology deployment sequences for each vehi cle category for a gi ven 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-base d new CAFE standard. (This sheet is named “MSW” in the spreadsheet file.) Ma nufacturer- and vehicl e 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 cu rb weight between Chrysler MSWs and the reference weight. Column J contains the ca lculated 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. Colu mns 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 adjust ment. (The logic accounts for the fact that off-model adjustment e ffects can accumulate as additional off modelbased technologies are depl oyed along the sequence.)

Where the technology benefit has been modele d 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 bene fit accounting for off-model adjustments. Column J adjusts the fuel economy to acc ount for advanced technology penetrations already reflected in the baseline as descri bed 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 vehi cle categories are populated for a given manufacturer). Finally, Colu mn L contains sales-weighted composite fuel economy for either all passenger car or light-duty truc k categories for comparison to federal CAFE standards in calculating compliance. The co mposite 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, MS W, LSW, SCC, MCC, SCC, SSL, MSL, LSL, SC, and HPSC sheets.12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152AB CDEFGHIJKLMNOPQRSTUCode: CCategory: MSWSubFleet: CarsCat Index: 4SubFleet Index: 26Manufacturer: ChryslerAffected VehicleSub Fleet Category BaselineTech Code Technology DescriptionSource CAFE Real Cost CAFE Real Fraction FractionAdvTech? SubFleet CategoryWT1Minimal Weight Reduction-0.84% -0.83%$13$15 $15 1.000 1.000ASLA5A5 with ASL vs. A4 w/o ASLV -1.79% -1.99%$236$132 $119 0.254 1.000PARALower Eng. Fric./ParasiticsO -0.50% -0.50%$14$28 $28 1.000 1.000PARA2Lower Eng. Fric./Parasitics-2O -2.00% -2.00%$121$61 $61 1.000 1.000CD2VCylinder Deactivation on 2VV -8.61% -4.98%$358$42 $72 0.056 0.000 CDCT 0.894 1.000CAFERealCVVLT4CVVL&T on 4V onlyV -12.70% -7.40%$893$70 $121 0.879 1.000Full Relative Benefit of CVVLT: 1.1126 1.0489CVVLTCVVL&T on 4V after 2V to 4VV -12.70% -7.40%$893$70 $1211.000 1.000VVLT 0.000 0.000Benefit Adjusted for DVVLT in Baseline: 1.1126 1.0489EPSElectric Power SteeringV -1.50% -1.10%$81$54 $74 1.000 1.000EHPSElectro-Hydraulic Power SteeringV -1.50% -1.10%$122$81 $111 1.000 1.000ULSUL Steel vs. closures only, 50% penetrationV -4.99% -4.73%$206$41 $43 1.000 1.000DVVLT4DVVL&T on 4V-6.70% -4.60%$515$77 $112 0.879 1.000DOHCDOHC V6 vs OHV V6V -8.70% -7.37%$589$68 $80 0.121 0.000IMPALTImp. Alternator/ChargingV -1.00% -1.00%$73$73 $73 1.000 1.000SCDSLSupercharged Diesel-11.30% -8.50%$5,480$485 $645 1.000 1.000AMT66-Speed Automated Manual w/ASL, ELV -3.74% -3.08%$309$83 $100 0.647 1.000 AMT 0.668 1.000ASLA66-Speed Auto w/ASL-0.92% -1.99%$152$165 $76 0.647 1.000ALMAluminum Incremental to ULSteelV -5.87% -5.70%$1,576$268 $276 1.000 1.000MHYB42-volt Hybrid Motor Assist-5.98% -2.40%$1,862$311 $776 1.000 1.000CVGDIGasoline Direct Injection on 4V CVVLTV -5.14% -3.71%$549$107 $1481.000 1.000TURB87Turbocharging, 87 octane-0.27% -2.11%$815$3,018 $386 1.000 1.000AHYBAdvanced Hybrid w/Regen BrakingV -26.50% -24.70%$5,893$222 $239 1.000 1.000 HYB 1.000 1.000A5A5 vs. A4 w/o ASL$171- - 0.254 1.000Chrysler MSW 2006 Baseline Actual: 28.785Existing Federal CAFE Target -- Chrysler Cars: 27.500Chrysler MSW Adv Tech Penetration Factor: 1.0000New Federal CAFE Target -- Chrysler Cars: 37.901Chrysler MSW Sales Percentage: 3.12%FilledFilled Sales-WtdFilledTechVEHSIM VEHSIM Modeled MSW MSW Car VEHSIM VEHSIM Modeled MSW Sequence From From ProjBase CAFE BECode Technology Description%PhaseIn Source IncrementAccum CAFE FE CAFE FE CAFEAdj CAFEAdj CAFEAdj CAFE Real FE Real FE RealAdj Real Number Baseline Exist CAFE ($ / %FC) ($ / mpg)BASE MSW 2006 Baseline-- 1.000 1.000 30.846 30.846 30.846 30.846 30.84627.32625.987 25.987 25.98725.9870$0.00---ASLA5 A5 with ASL vs. A4 w/o ASL100.0% V 1.000 1.000 32.304 32.304 32.304 32.304 32.30427.63226.782 26.782 26.78226.7821 $236.49 $236.49$52.40 $162.20PARA Lower Eng. Fric./Parasitics100.0% O 1.005 1.005 32.304 32.304 32.466 32.466 32.46627.77126.782 26.782 26.91726.9172 $250.40 $250.40$27.82 $85.69AMT6 6-Speed Automated Manual w/ASL, EL100.0% V 1.005 1.005 33.635 33.635 33.804 33.804 33.80428.45427.870 27.870 28.01028.0103 $559.42 $559.42$78.09 $231.01EPS Electric Power Steering100.0% V 1.005 1.005 34.244 34.244 34.416 34.416 34.41628.90928.293 28.293 28.43528.4354 $640.90 $640.90$45.82 $133.12PARA2 Lower Eng. Fric./Parasitics-2100.0% O 1.020 1.026 34.244 34.244 35.118 35.118 35.11829.49928.293 28.293 29.01529.0155 $762.12 $762.12$60.61 $172.59ULS UL Steel vs. closures only, 50% penetration 100.0% V 1.020 1.026 35.396 35.396 36.300 36.300 36.30030.48829.185 29.185 29.93029.9306 $967.97 $967.97$63.25 $174.24IMPALT Imp. Alternator/Charging100.0% V 1.020 1.026 35.708 35.708 36.620 36.620 36.62030.74229.385 29.385 30.13530.1357 $1,040.50 $1,040.50$83.02 $226.70DOHC DOHC V6 vs OHV V6100.0% V 1.020 1.026 35.708 35.708 36.620 36.620 36.62031.36029.385 29.385 30.13530.1358 $1,040.50 $1,040.50$83.02 $226.70CVVLT CVVL&T on 4V after 2V to 4V100.0% V 1.020 1.026 39.730 39.730 40.745 40.745 40.74535.20530.821 30.821 31.60831.6089 $1,933.78 $1,933.78$88.24 $216.57CVGDI Gasoline Direct Injection on 4V CVVLT100.0% V 1.020 1.026 41.662 41.662 42.726 42.726 42.72637.01531.947 31.947 32.76332.76310 $2,483.26 $2,483.26$118.49 $277.33AHYB Advanced Hybrid w/Regen Braking100.0% V 1.020 1.026 53.090 53.090 54.446 54.446 54.44646.17838.267 38.267 39.24439.24411 $8,376.15 $8,376.15$273.76 $502.81ALM Aluminum Incremental to ULSteel100.0% V 1.020 1.026 55.286 55.286 56.698 56.698 56.69848.20439.737 39.737 40.75240.75212 $9,951.84 $9,951.84$396.69 $699.66Adv Tech AvailableCost-Effectiveness of Individual Technologies -- Chrysler MSWs$ / %FCFC ChangeCumulative Costs Inc Cost EffectivenessOff-Model MultipliersTable 8-2Technology Deployment Sequence for Chrysler MSWs-70-Columns M through P contain logi c using real world fuel economy similar to that in Columns G through J based on CAFE fuel ec onomy. Column Q shows the technology deployment sequence number.

As shown in Table 8-2, cumulative cost and in cremental cost effectiveness are calculated in Columns R through U. The spreadsheet had b een 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 CA FE standards and was not used for this analysis. (Due to the complexity of the sp readsheet 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 show n 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 calcu lations 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 achi eve compliance instead of adding further technology. These “mix-shift” adjustments ar e 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

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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 # Categor y A bbrev A uto LDV Factor A uto LDV A ctual 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 50.3 09 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 3 3.230 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 # Categor y A bbrev LT LDV Factor LT LDV A ctual 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 45.04 7 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 # Categor y A bbrev LT LDV Factor LT LDV A ctual 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 51.38 9 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 30.60 6 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 24.49 0 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 e ach successive technolo gy step. The sales

fractions contained in Column H are combin ed with the fuel economy values for each vehicle category to compute harmonically av eraged passenger car and light-duty truck sub-fleet composite fuel economy by tec hnology 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 sh eet to account for instances where the technology steps must be aligned across the sub-fleets, which is perf ormed 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 foot print-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 be tween these fleets and is discussed later).

Sales fractions in Column A are carried forw ard from the Results sheet and are used to calculate sales-weighted composite fuel ec onomy and compliance costs separately for the passenger car and light-truck fleets. Colu mns 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 A SLA5 PAR A A MT6 EPS PARA2 ULS IMPALT DOHC CVVLT CVGDI A HYB A LM 0 CAFE Std: 37.901 Tech Fleet% A TFleet%

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

V ans Tech Name: Proj Base A SLA5 PAR A A MT6 EPS PARA2 ULS IMPALT DOHC CVVLT CVGDI A HYB A LM 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 A SLA5 PAR A A MT6 CD2V PARA2 ULS IMPALT EHPS CVVLT4 CVGDI A HYB A LM 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 A SLA5 PAR A A MT6 CD2V PARA2 ULS IMPALT EHPS CVVLT4 CVGDI A HYB A LM 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 A SLA5 PAR A A MT6 CD2V PARA2 ULS IMPALT EHPS CVVLT4 CVGDI A HYB A LM 0 CAFE Std: 31.349 Tech Fleet% A TFleet%

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 A SLA5 PAR A A MT6 EPS PARA2 ULS IMPALT DOHC CVVLT CVGDI A HYB A LM 0 Sales-Wtd CAFE Std: 32.811 Tech A TFleet%

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-flee t, 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 deploy ment sequence alignment is required, it is performed in the Compliance sheet.)

Finally, the amount of technology and cost need ed to comply with the long-term CAFE

standards is calculate d in Columns T through X in Tabl e 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 ca rs and Cell W45 for light trucks). This logic basically performs linea r interpolation of technology cost and CAFE fuel economy along each sales-weighted composite deploym ent sequence (Rows 15 and 16 for cars and 45 and 46 for light trucks).

An Excel “solver” utility macro was used to iteratively calculate th e 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 “r ational 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 ex ample, a baseline fuel economy of 30 mpg and a vehicle life of 150,000 miles, the lifetime ga soline 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 severa l important factors, including (1) the time value of money, (2) the difference between fuel economy in customer service and on the CAFE test pro cedures, (3) differences in the fuel economy improvement that individual technologies prov ide in customer service compared to the CAFE test procedures, and (4) the “rebound e ffect” (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 nece ssary 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 pe riod of ten years. A discount rate has to

-74-be applied to future fuel savings to addre ss 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 l ong 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 intenti onally 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 fu el consumption associ ated with individual technologies. For example, a technology that reduces fuel consumption at idle will provide a different average bene fit if the fraction of idle ope ration 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 Laboratory 15 describes the body of research that supports the existence of a “rebound effect” when automotive fuel economy increases. The rebound effect is ba sically 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 mo re of it. As Greene explains, numerous

researchers have documented that a rebound eff ect 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 magnit ude 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 va lue (NPV) of the increased co st 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 tax RPE NPV + ∑ =

= −+

− ++−=

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,

mpg base = real baseline fuel economy in m iles per gallon (85% of CAFE),

VMT i = annual vehicle miles travelled in year i, adjusted for scrappage,

mpg = real fuel economy after the design change,

-75-REB = rebound effect (% increase in VM T 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 calcula tes present value fuel cost savings for each year, while accounting for the rebound eff ect 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 w ith a baseline CAFE rating of 29.6 mpg (the actual 2006 model year baseline). As di scussed earlier in Section 6.2, we estimate the increase in retail price for a strong hybrid system app lied to a mid-size passenger car at $5,968. When an 8% sales tax is considered, the co st 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, a ssumed 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 passenge r cars during thei r first year of operation, and

0.85 = standard factor used to tran slate CAFE to customer service fuel

economy.

The first year annual mileage of 16,071 in th e 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 th e “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 consump tion from the 29.6 mpg baseline. The 0.82 adjustment factor applied to the fuel ec onomy 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 th e baseline fuel cost and accounting for the

discount rate involves th e 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 va lue of $301 at the end of the first year of ownership. When pe rforming 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 fr om 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 e ffect, an 8% sales tax, and vehicle simulation modeling to account for fuel economy in customer service, a costeffectiveness analysis was conducted for thr ee assumed retail fuel price levels of $2.50/gal, $3.00/gal, and $3.50/gal to repres ent Low, Reference, and High cases. We considered fuel cost savings over “payback” pe riods of 5 and 20 years. (It is more likely that average consumers would consider the sa vings 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 savi ngs) 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, complian ce costs, and break-even fuel prices in model year 2020 by manufacturer ar e presented in Table 8-5 fo r footprint-based reformed CAFE standards assuming no credit transfer of up to 2 mpg betw een passenger car and light truck fleets as allowed under provisions in EISA. Ta ble 8-6 presents a similar compliance summary with credit transfer

.

In each table, separate summaries are show n for both passenger car and light-duty truck compliance. Sales-weighted composite result s 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 ex plicit identification of the fraction of advanced hybrids needed). Th e 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 transfe r) for the entire light-duty flee t 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 accounti ng for allowed credit tr ansfer between cars and trucks generally drop between $100 a nd $200 for most manufacturers. The salesweighted average price increase is $3,505 pe r vehicle. Under both of the scenarios examined, break-even fuel prices for the entire light-duty U.S. vehicl e 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 br eak-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 co sts (that account for fuel savings) for each of the six fuel price and payback period scenar ios that were analyzed. (The tables in Appendix B are paginated by manufacturer. Fo r each manufacturer, a table of results is shown without credit transfer, followe d 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-Yea r 20-Yea r

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-Yea r 20-Yea r

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-Yea r 20-Yea r

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 Technology Needed CAFE Fuel Economy (mpg)

Break-Even Retail Fuel Price CAFE Fuel Economy (mpg) Light-Duty Truck (and MDPV) Compliance

Light-Duty Vehicle (and MDPV) Sales-Weighted Averages Technology Needed CAFE Fuel Economy (mpg)

-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-Yea r 20-Yea r

BMW 26.89 40.39 AHYB 5.23% 5.23% $2,081 $8.31 $5.33 Chrysler 27.59 37.01 CVGDI 10 0.00% 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-Yea r 20-Yea r

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-Yea r 20-Yea r

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, Ce ntral Valley Chrysler-Jeep, Inc., et al. vs. Catherine E. Witherspoon, in her offici al capacity as Executive Officer of the California Air Resources Board, United Stat es District Court, Eastern District of California – Fresno, Case No. CI V-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 th e August 2004 Proposed CA RB Regulations to

Control Greenhouse Gas Emissions from Motor Vehicles: Cost Effectiveness for the Vehicle Owner or Operator,” Attach ment C-5, “Problems with CARB’s Turbocharging Analysis,” Sierra Resear ch Report No. SR2004-09-04, September 22,

2004.

9. Personal communication w ith Larry Weitzman, automotive columnist, Mountain Democrat, November 2007.

10. T.C. Austin, et al., “Review of th e August 2004 Proposed CA RB 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 Electri c and Hybrid Vehicle Cost Estimation,” Argonne National Laboratory, April 2000.

12. “Estimating Changes in Retail Price E quivalent (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 Res earch on the subject of discount rates for private costs, November 20, 2007.

14. T.C. Austin, et al., “Passenger Car Fu el Economy During Non-Urban Driving,” SAE Paper No. 740592, 1974.

-81--82- 15. David L. Greene, et al., “Fuel Ec onomy Rebound Effect for U.S. Household Vehicles,” The Energy Journal, Vol. 20, No. 3, 1999.

16. Light Truck Average Fuel Economy Sta ndards, Model Years 2005-2007, Docket No.: NHTSA-2002-11419 or 68 FR 16867; April 7, 2003.

### APPENDIX A

Detailed Baseline Fleet TabulationsA-1A-2A-3A-4A-5A-6A-7A-8A-9A-10A-11A-12

### APPENDIX B Detailed Cost-Effectiveness Analysis ResultsManufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$562-$1,947-$960-$1,807-$767-$1,526-$382-$1,634-$636-$1,415-$362-$977$185>24$770>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$702>24$963>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$983>24$1,348>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$876>24$1,094>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,095>24$1,368>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,532>24$1,915>24Note:Tech Cost column includes assumed sales tax.CVGDI 19.60% 0.00% $1,730AHYB 9.02% 9.02% $2,509$8.93$8.20$5.73$5.31$4.49$3.16Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesBMWPassenger CarsLight-Duty Trucks (and MDPVs)Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$541-$1,707-$1,402-$1,571-$1,177-$1,301-$728-$1,405-$1,024-$1,194-$705-$772-$66>24$899>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$676>24$1,124>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$947>24$1,573>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$843>24$1,277>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,054>24$1,596>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,475>24$2,235>24Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesBMWPassenger CarsLight-Duty Trucks (and MDPVs)$8.31$7.79$5.33$5.05$5.12$3.60AHYB 5.23% 5.23% $2,248AHYB 0.00% 0.00% $2,301B-1Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$757-$2,550-$5,079-$2,361-$4,712-$1,982-$3,978-$2,128-$4,462-$1,833-$3,941-$1,243-$2,899>24$1,467>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$946>24$1,834>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,324>24$2,567>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,179>24$2,084>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,474>24$2,605>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$2,063>24$3,647>24Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesChryslerPassenger CarsLight-Duty Trucks (and MDPVs)$8.74$8.88$5.61$6.11$8.92$6.28AHYB 11.78% 11.78% $3,307AHYB 47.49% 47.49% $6,546Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$700-$1,794-$5,287-$1,619-$4,914-$1,269-$4,168-$1,403-$4,660-$1,131-$4,130-$585-$3,071>24$1,491>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$875>24$1,864>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,225>24$2,610>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,091>24$2,118>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,363>24$2,648>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,909>24$3,707>24Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesChryslerPassenger CarsLight-Duty Trucks (and MDPVs)$7.13$8.58$4.57$5.93$9.09$6.40CVGDI 100.00% 0.00% $2,494AHYB 50.21% 50.21% $6,778B-2Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$1,101-$4,806-$4,872-$4,531-$4,514-$3,981-$3,799-$4,192-$4,271-$3,763-$3,763-$2,905-$2,748>24$1,430>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$1,376>24$1,787>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,927>24$2,502>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,716>24$2,030>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$2,144>24$2,538>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$3,002>24$3,553>24Note:Tech Cost column includes assumed sales tax.AHYB 37.14% 37.14% $6,301AHYB 46.31% 46.31% $5,907$10.73$10.23$6.89$6.71$8.82$6.21Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesDaimlerPassenger CarsLight-Duty Trucks (and MDPVs)Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$1,184-$5,657-$2,029-$5,361-$1,748-$4,769-$1,187-$4,996-$1,557-$4,535-$1,159-$3,612-$362>24$1,122>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$1,480>24$1,403>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$2,072>24$1,964>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,845>24$1,594>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$2,307>24$1,992>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$3,229>24$2,789>24Note:Tech Cost column includes assumed sales tax.AHYB 4.54% 4.54% $3,151AHYB 58.66% 58.66% $6,842$11.55$10.00$7.42$6.51$5.62$3.95Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesDaimlerPassenger CarsLight-Duty Trucks (and MDPVs)B-3Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$740-$1,740-$4,982-$1,555-$4,579-$1,185-$3,773-$1,327-$4,304-$1,039-$3,732-$463-$2,586>24$1,613>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$924>24$2,016>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,294>24$2,823>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,152>24$2,291>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,441>24$2,864>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$2,017>24$4,010>24Note:Tech Cost column includes assumed sales tax.AHYB 40.74% 40.74% $6,596CVGDI 88.71% 0.00% $2,480$6.71$7.55$4.30$5.13$8.18$5.76Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesFordPassenger CarsLight-Duty Trucks (and MDPVs)Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$752-$1,796-$4,869-$1,608-$4,469-$1,232-$3,669-$1,376-$4,197-$1,083-$3,629-$497-$2,493>24$1,599>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$940>24$1,999>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,316>24$2,799>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,172>24$2,272>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,465>24$2,840>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$2,051>24$3,976>24Note:Tech Cost column includes assumed sales tax.AHYB 39.36% 39.36% $6,468AHYB 0.00% 0.00% $2,548$6.78$7.52$4.35$5.12$8.09$5.69Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesFordPassenger CarsLight-Duty Trucks (and MDPVs)B-4Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$861-$1,570-$5,023-$1,355-$4,611-$924-$3,785-$1,089-$4,329-$754-$3,743-$83-$2,570>24$1,652>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$1,076>24$2,065>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,506>24$2,891>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,341>24$2,346>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,677>24$2,933>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$2,347>24$4,106>24Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesGMPassenger CarsLight-Duty Trucks (and MDPVs)$5.65$6.95$3.62$4.73$8.08$5.69CVGDI 48.70% 0.00% $2,431AHYB 44.68% 44.68% $6,675Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$916-$1,828-$4,156-$1,599-$3,760-$1,140-$2,969-$1,316-$3,491-$959-$2,929-$245-$1,804>24$1,583>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$1,145>24$1,979>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,604>24$2,770>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,428>24$2,248>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,785>24$2,810>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$2,499>24$3,935>24Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesGMPassenger CarsLight-Duty Trucks (and MDPVs)$5.99$6.67$3.84$4.52$7.25$5.11AHYB 0.00% 0.00% $2,744AHYB 37.69% 37.69% $5,739B-5Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$507-$987-$682-$860-$509-$607-$163-$704-$391-$506-$145-$112$346>24$692>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$633>24$865>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$887>24$1,2116Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$790>24$983>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$987>24$1,229>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,382>24$1,7216Note:Tech Cost column includes assumed sales tax.CVVLT4 69.03% 0.00% $1,375CVGDI 26.17% 0.00% $1,493$5.89$4.87$3.78$3.26$3.97$2.80Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesHondaPassenger CarsLight-Duty Trucks (and MDPVs)Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$438-$681-$767-$572-$579-$353-$203-$437-$451-$266-$183$75$351>24$753>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$547>24$941>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$766>24$1,3187Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$682>24$1,069>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$853>24$1,337>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,194>24$1,8727Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesHondaPassenger CarsLight-Duty Trucks (and MDPVs)$5.11$4.54$3.28$3.05$4.04$2.84CVVLT 56.16% 0.00% $1,119CVVLT4 100.00% 0.00% $1,520B-6Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$609-$1,777-$2,596-$1,625-$2,326-$1,321-$1,786-$1,437-$2,142-$1,200-$1,759-$726-$993>24$1,079>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$761>24$1,349>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,066>24$1,888>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$949>24$1,533>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,186>24$1,916>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,660>24$2,682>24Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesHyundaiPassenger CarsLight-Duty Trucks (and MDPVs)$7.84$7.49$5.03$4.95$6.81$4.80CVGDI 81.65% 0.00% $2,386AHYB 10.78% 10.78% $3,675Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$636-$1,985-$1,839-$1,826-$1,588-$1,508-$1,086-$1,630-$1,417-$1,382-$1,060-$886-$347>24$1,004>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$795>24$1,255>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,113>24$1,757>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$991>24$1,426>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,239>24$1,782>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,735>24$2,495>24Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesHyundaiPassenger CarsLight-Duty Trucks (and MDPVs)$8.24$7.38$5.29$4.85$5.66$3.99AHYB 2.08% 2.08% $2,621AHYB 0.00% 0.00% $2,842B-7Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$623-$1,489-$4,636-$1,333-$4,266-$1,022-$3,525-$1,141-$4,013-$899-$3,488-$413-$2,436>24$1,481>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$778>24$1,851>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,090>24$2,591>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$970>24$2,103>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,213>24$2,629>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,698>24$3,680>24Note:Tech Cost column includes assumed sales tax.AHYB 36.54% 36.54% $6,116CVGDI 30.18% 0.00% $2,111$6.78$7.40$4.35$4.96$8.26$5.82Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesNissanPassenger CarsLight-Duty Trucks (and MDPVs)Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$697-$1,827-$3,397-$1,653-$3,065-$1,304-$2,402-$1,438-$2,839-$1,166-$2,368-$623-$1,426>24$1,327>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$872>24$1,658>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,220>24$2,322>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,087>24$1,884>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$1,358>24$2,355>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,901>24$3,298>24Note:Tech Cost column includes assumed sales tax.AHYB 20.94% 20.94% $4,724AHYB 0.00% 0.00% $2,524$7.24$7.19$4.65$4.80$7.12$5.01Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesNissanPassenger CarsLight-Duty Trucks (and MDPVs)B-8Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$1,131-$5,465-$8,954-$5,183-$8,491-$4,617-$7,566-$4,834-$8,176-$4,393-$7,519-$3,512-$6,205>24$1,851>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$1,414>24$2,313>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$1,980>24$3,239>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,763>24$2,629>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$2,203>24$3,286>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$3,085>24$4,600>24Note:Tech Cost column includes assumed sales tax.AHYB 77.53% 77.53% $10,805AHYB 81.84% 81.84% $6,597$11.66$11.67$7.48$7.78$11.68$8.22Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesPorschePassenger CarsLight-Duty Trucks (and MDPVs)Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$1,213-$6,163-$7,394-$5,860-$6,972-$5,253-$6,128-$5,486-$6,684-$5,013-$6,085-$4,068-$4,887>24$1,687>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$1,517>24$2,109>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$2,123>24$2,953>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$1,891>24$2,397>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$2,363>24$2,996>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$3,309>24$4,194>24Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesPorschePassenger CarsLight-Duty Trucks (and MDPVs)$12.16$11.61$7.80$7.71$10.76$7.58AHYB 94.53% 94.53% $7,377AHYB 60.03% 60.03% $9,081B-9Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$454-$1,232-$1,803-$1,118-$1,553-$891-$1,053-$978-$1,383-$802-$1,028-$448-$317>24$1,000>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$568>24$1,250>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$795>24$1,751>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$708>24$1,421>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$885>24$1,776>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,238>24$2,486>24Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesToyotaPassenger CarsLight-Duty Trucks (and MDPVs)$7.43$6.57$4.77$4.38$5.61$3.95CVVLT 86.16% 0.00% $1,686AHYB 0.89% 0.89% $2,804Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$472-$1,343-$1,644-$1,225-$1,405-$988-$927-$1,079-$1,242-$895-$902-$527-$223>24$956>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$590>24$1,195>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$827>24$1,673>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$736>24$1,358>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$920>24$1,697>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,288>24$2,376>24Note:Tech Cost column includes assumed sales tax.CVGDI 79.63% 0.00% $2,600CVVLT 100.00% 0.00% $1,815$7.68$6.63$4.93$4.41$5.44$3.83Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesToyotaPassenger CarsLight-Duty Trucks (and MDPVs)B-10B-11Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 No Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$491-$1,643-$8,187-$1,520-$7,781-$1,275-$6,969-$1,369-$7,504-$1,178-$6,927-$796-$5,773>24$1,625>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$613>24$2,031>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$859>24$2,843>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$765>24$2,308>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$956>24$2,885>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,338>24$4,038>24Note:Tech Cost column includes assumed sales tax.Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesVWPassenger CarsLight-Duty Trucks (and MDPVs)$8.70$8.82$5.58$5.69$12.08$8.50CVGDI 61.18% 0.00% $2,134AHYB 64.39% 64.39% $9,812Manufacturer:PC Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPLDT Standard Form: FP-L NHSTA-Equivalent Logistic Curve - FPRulemaking Version: HR6 With Credit Transfer Between Cars and TrucksVehicle Payback DrivingRetail Rebound Discount Sales Period Cycle TechHybrid Tech Saved Net Payback TechHybrid Tech Saved Net PaybackScenarioFuel Price Effect Rate (%) Tax (%) (years) Type Needed AmountFraction Cost Fuel Cost Savings YearNeeded Amount Fraction Cost Fuel CostSavings YearCars Trucks CompositeLow Fuel, 5-Yr Payback $2.00 0.17 12.4% 8% 5 Real$498-$1,684-$5,366-$1,559-$5,032-$1,310-$4,363-$1,406-$4,804-$1,211-$4,329-$823-$3,380>24$1,337>24Ref Fuel, 5-Yr Payback $2.50 0.17 12.4% 8% 5 Real$623>24$1,671>24High Fuel, 5-Yr Payback $3.50 0.17 12.4% 8% 5 Real$872>24$2,339>24Low Fuel, 20-Yr Payback $2.00 0.17 12.4% 8% 20 Real$776>24$1,899>24Ref Fuel, 20-Yr Payback $2.50 0.17 12.4% 8% 20 Real$970>24$2,373>24High Fuel, 20-Yr Payback $3.50 0.17 12.4% 8% 20 Real$1,358>24$3,323>24Note:Tech Cost column includes assumed sales tax.AHYB 33.53% 33.53% $6,702CVGDI 68.93% 0.00% $2,182$8.76$8.81$5.62$5.67$10.03$7.06Summary of Compliance Technology Cost EffectivenessBreak-Even RetailFuel PricesVWPassenger CarsLight-Duty Trucks (and MDPVs)