The Baseline Vehicle Fleet 

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Table of Contents 

CHAPTER 1: THE BASELINE VEHICLE FLEET

1.1 Why do the agencies establish a baseline and reference vehicle fleet? ............ 1-2

1.2 The 2008 baseline vehicle fleet ......................................................................... 1-3

1.2.1 Why did the agencies choose 2008 as the baseline model year? ............... 1-3

1.2.2 On what data is the baseline vehicle fleet based? ...................................... 1-3

1.3 The MY 2011-2016 Reference Fleet .................................................. 1-131-31-13

1.3.1 On what data is the baseline vehicle fleet based? ....................... 1-131-31-13

1.3.2 How do the agencies develop the reference vehicle fleet? ......... 1-151-31-15

1.3.3 What are the sales volumes and characteristics of the reference fleet? 1-231-

31-23

1.3.4 How is the development of the baseline fleet for this proposal different 

from NHTSA’s historical approach and why is this approach preferable? .. 1-261-31-

26

1.3.5 How does manufacturer product plan data factor into the baseline used in 

this proposal? ............................................................................................ 1-311-31-30

1.3.6 Have the agencies performed any analysis using manufacturer product plan 

data factor? ...................................................................................................... 1-311-31

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CHAPTER 1: The Baseline Vehicle Fleet 

The passenger cars and light trucks sold currently in the United States, and those 

which are anticipated to be sold in the MY 2012-2016 timeframe, are highly varied and 

satisfy a wide range of consumer needs. From two-seater miniature cars to 11-seater 

passenger vans to large extended cab pickup trucks, American consumers have a great 

number of vehicle options to accommodate their utility needs and preferences. Recent 

volatility in oil prices and the state of the economy have demonstrated that consumer 

demand and choice can be sensitive to these factors. Although it is impossible for anyone 

or any organization to precisely predict the future, a characterization and quantification 

are required for the future fleet to assess impacts of rules which would affect that future 

fleet. In order to do this, the various leading publically available sources are examined, 

and a series of models are relied upon that help us to project the composition of a 

reference fleet. This chapter describes the process for accomplishing this. 

1.1 Why do the agencies establish a baseline and reference vehicle fleet? 

In order to calculate the impacts of the EPA and NHTSA proposed regulations, it is 

necessary to estimate the composition of the future vehicle fleet absent these proposed 

regulations in order to conduct comparisons. EPA in consultation with NHTSA has 

developed a comparison fleet in two parts. The first step was to develop a baseline fleet 

based on model year 2008 data. EPA and NHTSA create a baseline fleet in order to track 

the volumes and types of fuel economy-improving and CO2-reducing technologies which 

are already present in today’s fleet. Creating a baseline fleet helps to keep, to some 

extent, the agencies’ models from adding technologies to vehicles that already have these 

technologies, which would result in “double counting” of technologies’ costs and 

benefits. The second step was to project the baseline fleet sales into MYs 2011-2016. 

This is called the reference fleet, and it represents the fleet that would exist in MYs 2011-

2016 absent any change from current regulations. The third step was to add technologies 

to that fleet such that each manufacturer’s average car and truck CO2 levels are in 

compliance with their MY 2011 CAFE standards. This final “reference fleet” is the light 

duty fleet estimated to exist in MYs 2012-2016 without these proposed rules. All of the 

agencies’ estimates of emission reductions/fuel economy improvements, costs, and 

societal impacts are developed in relation to the respective reference fleets. The chapter 

describes the first two steps of the development of the baseline and reference fleets. The 

third step of technology addition is developed separately by each agency as the outputs of 

the OMEGA and Volpe models. The process is described in section II of the preamble 

and in each agency’s respective RIAs. 
The Baseline Vehicle Fleet 

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1.2 The 2008 baseline vehicle fleet 

1.2.1 Why did the agencies choose 2008 as the baseline model year? 

For this proposed rule, the baseline vehicle fleet developed by EPA in 

consultation with NHTSA and is comprised of model year 2008 data. MY 2008 was used 

as the basis for the baseline vehicle fleet, because it is the most recent model year for 

which full data is publicly available. Vehicle manufacturers have 90 days after their last 

vehicle is produced to submit their CAFE data to EPA.1 Most manufacturers interpret 

this to mean 90 days after the end of the calendar year. For example, in calendar year 

2007, model year 2008 vehicles were tested and certified by the EPA. These MY 2008 

vehicles were then sold in the latter part (often fall) of 2007 until the following fall of 

2008. In early 2009 (calendar year), the manufacturers then submit their total sales of 

MY 2008 vehicles. After these sales figures were submitted, EPA and NHTSA 

combined the sales with the previously measured and reported fuel economies to 

calculate the sales-weighted average fleet fuel economy. The analysis for this present 

rulemaking was conducted in early to mid 2009 calendar year, thus the full sales figures 

for MY 2009 vehicles have not yet been submitted. Even though the fuel economies (and 

some other specifications) of the MY 2009 vehicles were known, since they were tested 

earlier, the sales were not yet known for each company exactly. Therefore, the agencies 

chose to use MY 2008 as the baseline since it was the most complete data set available. 

NHTSA and EPA may update the baseline to MY 2009 or MY 2010 between this notice 

and the final rule if the data is complete and if time permits. 

1.2.2 On what data is the baseline vehicle fleet based? 

As part of the CAFE program, EPA measures vehicle CO2 emissions and converts 

them to mpg and generates and maintains the federal fuel economy database. Most of the 

information about the 2008 vehicle fleet was gathered from EPA’s emission certification 

and fuel economy database, most of which is available to the public. The data obtained 

from this source included vehicle production volume, fuel economy, carbon dioxide 

emissions, fuel type, number of engine cylinders, displacement, valves per cylinder, 

engine cycle, transmission type, drive, hybrid type, and aspiration. However, EPA’s 

certification database does not include a detailed description of the types of fuel 

economy-improving/CO2-reducing technologies considered in this proposal, because this 

level of information is not necessary for emission certification or fuel economy testing. 

Thus, the agency augmented this description with publicly-available data which includes 

more complete technology descriptions from Ward’s Automotive GroupWards 

Automotive.

2,a In a few instances when required vehicle information was not available 

from these two sources (such as vehicle footprint), this information was obtained from 

 

a

 Note that WardsAuto.com is a fee-based service, but all information is public to subscribers. 
Draft Joint Technical Support Document 

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publicly-accessible internet sites such as Motortrend.com, Edmunds.com and other 

sources to a lesser extent (such as articles about specific vehicles revealed from internet 

search engine research.3,b  

The baseline vehicle fleet for the analysis in this rule is comprised of publiclyavailable data to the largest extent possible. However, a few relatively low-impact 

technologies were added based on confidential information provided from some 

manufacturers (within their product plan submissions to NHTSA and EPA). This was 

done because the data was not available from any other source. These technologies 

include low friction lubricants, electric power steering, improved accessories, and low 

rolling resistance tires. This confidential information has been excised from the baseline 

data submitted to the docket, though the summary results are still used, so that any 

specific information cannot be traced back to any specific manufacturer. This 

discrepancy between the public baseline and the one used by the agencies is relatively 

minor and should only result in small differences in the outputs of the Volpe and 

OMEGA models for certain manufacturers. 

Creating the 2008 baseline fleet Excel file was an extremely labor intensive 

process. EPA in consultation with NHTSA first considered using EPA’s CAFE 

certification data, which contains most of the required information. However, since the 

deadline for manufacturers to report this data did not allow enough time for early 

modeling review, it was necessary to start this process using an alternative data source. 

The agencies next considered using EPA’s vehicle emissions certification data, 

which contains much of the required information, however it lacked the production 

volumes that are necessary for the OMEGA and Volpe models. The data set also 

contains some vehicle models manufacturers have certified, but not produced. A second 

data source which would supply production volumes and eliminate extraneous vehicles 

was needed. Data from a paid subscription to Ward’s Automotive Group Wards 

Automotive was used as the second source for data, which contains production volumes 

and vehicle specifications. 

 The vehicle emissions certification dataset came in two parts, an engine file and 

a vehicle file. Since there was a common index in the two files, the engine and vehicle 

data were easily combined into one spreadsheet. The agencies had hoped to supplement 

this dataset with production volume data from Ward’s Automotive Group Wards 

Automotive, but the Ward’s data does not have production volumes for individual 

vehicles down to the resolution of the specific engine and transmission level. Although 

production volumes from Ward’s Automotive Group Wards Automotive could not be 

used, the subscription did provide specific details on individual vehicles and engines. 

The Ward’s data used came in two parts (engine file and vehicle file), and also required 

mapping. In this case, mapping was more difficult since there was no common index 

between the two files. A new index was implanted in the engine file and a search 

equation in the vehicle file, which identified most of the vehicle and engine 

 

b

 Motortrend.com and Edmunds.com are free, no-fee internet sites. 
The Baseline Vehicle Fleet 

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combinations. Each vehicle and engine combination was reviewed and corrections were 

made manually when the search routine failed to give the correct engine and vehicle 

combination. The combined Ward’s data was then mapped to the vehicle emissions 

certification data by creating a new index in the combined Ward’s data and using the 

same process that was used to combine the Ward’s engine and vehicle files. In the next 

step, CAFE certification data had to be merged in order to fill out the needed production 

volumes. 

NHTSA and EPA reviewed the CAFE certification data for model year 2008 as it 

became available. The CAFE certification dataset could have been used with the Ward’s 

data without the vehicle emission certification dataset, but was instead appended to the 

combined Ward’s and vehicle certification dataset. The two former datasets were then 

mapped into the CAFE dataset using the same Excel mapping technique described above. 

Finally, EPA and NHTSA obtained the remaining attribute and technology data, such as 

footprint, curb weight, and others (for a complete list of data with sources see Table 1-1 

below) from other sources (such as the internet and the confidential product plan data), 

thus completing the baseline dataset. 

This was the first time a baseline fleet was created using this method. Given the 

long delay before the CAFE certification data became available, EPA explored creating 

the alternative dataset. It is possible to create the same baseline with CAFE certification 

data, the Ward’s engine data, a limited amount of product plan data, and some internet 

searches. 

 

Table 1-1 below shows the baseline data that was compiled, its definition 

(description) and source. The data that is marked “not available” is data NHTSA would 

normally get from product plans. Some of the desired model inputs, such as the presence 

of low rolling resistance tires, reduced engine friction, improved accessories, are not 

available from public sources and the agencies had to rely on manufacturer’s confidential 

product plans. The Technology Effectivenesses Basis and the Cost Effectiveness Basis 

values reflect the percent of a technology package’s effectiveness and cost present in the 

baseline fleet, and they are described in further detail in chapters 3.1 and 3.5, 

respectively. Those technologies that are not accounted for in the baseline—that is, the 

ones marked “not available”—run the risk of getting double counted by the agencies’ 

models, but those effects are expected to be small. 

Table 1-1 Data, Definitions, and Sources

Data Item Definition Where The Data is From

Manufacturer 

Common name of company that manufactured 

vehicle. May include more name plates than Cert 

Manufacturer Name. Certification data 

CERT Manufacturer Name Certification name of company that manufactured 

vehicle Certification data

Name Plate Name of Division Certification data 

Model Name of Vehicle Certification data 

Reg Class EPA Fuel Economy Class Name Certification data 

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Class 

If a car’s Footprint<43 then "SubCmpctAuto" 

If a car’s 43<=Footprint<46 then "CompactAuto" 

If a car’s 46<=Footprint<53 then "MidSizeAuto” 

If a car’s Footprint >=53 then “LargeAuto” 

If a S.U.V.’s Footprint < 43 then “SmallSuv” 

If a S.U.V.’s 43<=Footprint<46 then 

"MidSizeSuv” 

If a S.U.V’s Footprint >=46 then “LargeSuv” 

If a Truck’s Footprint < 50 then “SmallPickup” 

If a Truck’s Footprint>=50 then “LargPickup” 

If a Van’s Structure is Ladder then “CargoVan” 

If a Van’s Structure is Unibody then “Minivan”

Derived From Certification 

data and Footprint

CSM Class CSM Worldwides class for the vehicle. Used to 

weight vehicles based on CSM data. CSM Worldwide 

Traditional Car/Truck C= Car, T=Truck. As defined in the certification 

database. Not used in calculations. Certification data 

EPA Interpretation of New NHTSA 

Car/Truck 

C= Car, T=Truck. EPA Best guess, some incorrect. 

Using NHTSA below. Left in for historical 

reasons. Not used in calculations.

EPA Derived from NHTSA 

Definition 

Total Production Volume Total number of vehicles produced for that model. Certification data 

Fuel Econ. 

(mpg) EPA Unadjusted Fuel Economy Certification data 

Curb 

Weight (lb) 

Vehicles Curb Weight 

Some from Edmonds.com or 

Motortrend.com, Others from 

product plans with a subset 

verified with Edmonds.com or 

Motortrend.com for accuracy. 

Area (sf) Average Track x Wheelbase

Calculated from track width 

and wheel base

Fuel Gas or Diesel Wards 

Disp 

(lit.) Engine Cylinder Displacement Size in Liters Wards/Certification data

Effective Cyl Number of Cylinder + 2 if the engine has a turbo or

super charger. 

Derived From Certification 

data. 

Actual Cylinders Actual Number of Engine Cylinders Certification data 

Valves Per Cylinder Number of Valves Per Actual Cylinder Certification data 

Valve Type Type of valve actuation. 

Wards (Note:Type E is from 

Cert Data) 

Engine Cycle As Defined by EPA Cert. Definition Wards 

Horsepower Max. Horsepower of the Engine Wards

Torque Max. Torque of the Engine Wards 

Trans Type A=Auto AMT=Automated Manual M=Manual 

CVT= Continuously Variable Transmission Certification data

Trans Type Code with number of Gears Certification data 

Num of Gears Number of Gears Certification data

Structure Ladder or Unibody 

General Internet Searches using 

Google.com 

Drive Fwd, Rwd, Awd, 4wd Certification data

Wheelbase 

Length of Wheelbase 

Some from Edmonds.com or 

Motortrend.com, Others from 

product plans with a subset 

verified with Edmonds.com or 

Motortrend.com for accuracy. 

Track Width 

(front) 

Length of Track Width in inches 

Some from Edmonds.com or 

Motortrend.com, Others from 

product plans with a subset 

verified with Edmonds.com or 

Motortrend.com for accuracy. 

Track Width 

(rear) Length of Track Width in inches

Some from Edmonds.com or 

Motortrend.com, Others from 

product plans with a subset 
The Baseline Vehicle Fleet 

1-7 

verified with Edmonds.com or 

Motortrend.com for accuracy. 

Footprint Average Track x Wheelbase

Calculated from track width 

and wheel base

Curb 

Weight 

Curb Weight of the Vehicle 

Some from Edmonds.com or 

Motortrend.com, Others from 

product plans with a subset 

verified with Edmonds.com or 

Motortrend.com for accuracy. 

GVWR 

Gross Vehicle Weight Rating of the Vehicle 

Some from Edmonds.com or 

Motortrend.com, Others from 

product plans with a subset 

verified with Edmonds.com or 

Motortrend.com for accuracy. 

HYBRID Is the Vehicle a Hybrid? Certification data 

HYBRID TYPE Type of Hybrid Certification data 

Turbo Turbo Charged Engine Certification data 

Super Charged Super Charged Certification data 

Turbo and/or Super Charged Either or both Turbo charged / Super Charged Certification data 

SOHC Single Overhead Cam Engine Wards

DOHC Dual Overhead Cam Engine Wards 

OHV Overhead Valve Engine Wards 

1 

LUB Low friction lubricants—incremental to base 

engine 

Obtained from product plans 

from manufacturers that report 

this information.2

2 

EFR Engine friction reduction—incremental to base 

engine 

Obtained from product plans 

from manufacturers that report 

this information.2

3 

CCPS VVT - Coupled Cam Phasing (CCP) on SOHC Wards1

4 

DVVLS Discrete Variable Valve Lift (DVVL) on SOHC Wards1

5 

DEACS Cylinder Deactivation on SOHC Wards1

6 

ICP VVT - Intake Cam Phasing (ICP) Wards1

7 

DCP VVT - Dual Cam Phasing (DCP) (independent) Wards1

8 

DVVLD Discrete Variable Valve Lift (DVVL) on DOHC Wards1

9 

CVVL Continuously Variable Valve Lift (CVVL) Wards1

10 

DEACD Cylinder Deactivation on DOHC Wards1

11 

DEACO Cylinder Deactivation on OHV Wards1

12 

CCPO VVT - Coupled Cam Phasing (CCP) on OHV Wards1

13 

DVVLO Discrete Variable Valve Lift (DVVL) on OHV Wards1

14 

CDOHC Conversion to DOHC with DCP Not available 

15 

SGDI Stoichiometric Gasoline Direct Injection (GDI) Wards

1

16 

CBRST Combustion Restart Not available

17 

TRBDS Turbocharging and Downsizing Not available 

18 

EGRB Exhaust Gas Recirculation (EGR) Boost Not available
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19 

DSLT Conversion to Diesel (from TRBDS) Not available 

20 

DSLC Conversion to Diesel (from CBRST) Not available

21 

6MAN 6-Speed Manual/Improved Internals Certification data 

22 

IATC Improved Auto. Trans. Controls/Externals Not available 

23 

CVT Continuously Variable Transmission Certification data 

24 

NAUTO 6/7/8-Speed Auto. Trans with Improved Internals Certification data 

25 

DCTAM Dual Clutch or Automated Manual Transmission Certification data

26 

EPS Electric Power Steering 

Obtained from product plans 

from manufacturers that report 

this information.2

27 

IACC Improved Accessories 

Obtained from product plans 

from manufacturers that report 

this information.2

28 

MHEV 12V Micro-Hybrid Not available

29 

HVIA Higher Voltage/Improved Alternator Not available

30 

BISG Belt Mounted Integrated Starter Generator Certification data 

31 

CISG Crank Mounted Integrated Starter Generator Certification data

32 

PSHEV Power Split Hybrid Certification data 

33 

2MHEV 2-Mode Hybrid Certification data 

34 

PHEV Plug-in Hybrid Not available 

35 

MS1 Material Substitution (1%) Not available 

36 

MS2 Material Substitution (2%) Not available

37 

MS5 Material Substitution (5%) Not available 

38 

ROLL Low Rolling Resistance Tires 

Obtained from product plans 

from manufacturers that report 

this information.2

39 

LDB Low Drag Brakes Not available 

40 

SAXU Secondary Axle Disconnect-Unibody Not available 

41 

SAXL Secondary Axle Disconnect-Ladder Not available 

Import Car Cars Imported Certification data 

Index Index Used to link EPA and NHTSA baselines Created 

Volume 2011 

Projected Production Volume for 2011

Calculated based on 2008 

volume and AEO and CSM 

adjustment factors.

Volume 2012 

Projected Production Volume for 2012

Calculated based on 2008 

volume and AEO and CSM 

adjustment factors.

Volume 2013 

Projected Production Volume for 2013 

Calculated based on 2008 

volume and AEO and CSM 

adjustment factors. 

Volume 2014 Projected Production Volume for 2014 Calculated based on 2008 
The Baseline Vehicle Fleet 

1-9 

volume and AEO and CSM 

adjustment factors. 

Volume 2015 

Projected Production Volume for 2015

Calculated based on 2008 

volume and AEO and CSM 

adjustment factors.

Volume 2016 

Projected Production Volume for 2016

Calculated based on 2008 

volume and AEO and CSM 

adjustment factors.

Vehicle Type Number 

Vehicle Type Number assigned to a vehicle based 

on its number of cylinders, valves per cylinder, and 

valve actuation technology. Mapping done by Agencies 

Footprint: PU Average 

Car Foot Print is normal. Truck footprint is the 

production weighted average for each vehicle. 

Derived from data from 

Edmunds.com or 

Motortrend.com. Production 

volumes or specific footprints 

from product plans. 

Footprint: PU Cutoff Same as above, but footprint valve for trucks 

limited to 66 before weighting. Meaning valves 

greater than 66 equal 66.

Derived from data from 

Edmunds.com or 

Motortrend.com. Production 

volumes or specific footprints 

from product plans.

NHTSA Defined New NHTSA 

Car/Truck 

New NHTSA Car Truck value as determined by 

NHTSA. Used in calculations. NHTSA 

CO2 CO2 calculated from MPG. CO2 weighted 1.15 

times higher for diesel vehicles. Certification data 

Thesholded FootPrint 

Footprint valve that will be set to 41 for values less 

than 41, Will be set to 56 for car values > 56, and

will be set to 66 for truck values >66 

Used in Summary Calculations 

Derived from data from 

Edmunds.com or 

Motortrend.com. Production 

volumes or specific footprints 

from product plans. 

TEB Tech 1 

Percentage of Tech Package 1

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet.

TEB Tech 2 

Percentage of Tech Package 2

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet.

TEB Tech 3 

Percentage of Tech Package 3

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet.

TEB Tech 4 

Percentage of Tech Package 4

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet.

TEB Tech 5 

Percentage of Tech Package 5

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet.

TEB Tech 6 

Percentage of Tech Package 6

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet.

CEB Tech 1 

Percentage of Cost of Tech Package 1 

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet. 

CEB Tech 2 Percentage of Cost of Tech Package 2 

Calculated using a macro in 

another spread sheet. 
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Calculated based on the 

technology in the "Data" sheet. 

CEB Tech 3 

Percentage of Cost of Tech Package 3 

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet. 

CEB Tech 4 

Percentage of Cost of Tech Package 4 

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet. 

CEB Tech 5 

Percentage of Cost of Tech Package 5 

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet. 

CEB Tech 6 

Percentage of Cost of Tech Package 6 

Calculated using a macro in 

another spread sheet. 

Calculated based on the 

technology in the "Data" sheet. 

Notes: 

1. For engines not available in the Wards WardsAuto.com engine file, an internet search was done to find this information. 

2. These data were obtained from manufacturer’s product plans. They were obtain to block (where possible) the model from 

adding technology that was already on a vehicle. 

3. Ward’s Automotive GroupWards data obtained from "2008 Light Vehicle Engines" . 

The sales volumes for the MY 2008 baseline fleet are included in the section 

below on reference fleet under the MY 2008 columns. Table 1-2 displays the 

technologies present in the baseline fleet. 

Table 1-2 2008 Technology Percentages 

Turbo 

Super Charged 

SOHC 

DOHC 

OHV 

LUB 

CCPS 

DVVLS DEACS 

ICP 

DCP 

DVVLD 

All Trucks 0.0% 0.2% 23.7% 47.6% 28.7% 61.4% 4.1% 5.8% 0.0% 5.3% 36.6% 1.5% 

All Cars 2.5% 0.1% 17.4% 73.3% 9.2% 48.5% 1.4% 7.4% 1.3% 3.2% 47.9% 0.2% 

BMW Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 94.7% 0.0% 

BMW Cars 0.0% 0.0% 13.9% 86.0% 0.0% 0.0% 11.9% 11.9% 0.0% 0.0% 85.8% 1.5% 

Chrysler Trucks 0.0% 0.0% 38.9% 4.1% 56.9% 76.9% 0.0% 0.0% 0.0% 0.0% 3.9% 0.0% 

Chrysler Cars 0.9% 0.0% 20.8% 71.5% 7.7% 28.5% 0.0% 0.0% 0.0% 0.0% 41.7% 0.0% 

Ford Trucks 0.0% 0.1% 62.9% 34.3% 2.8% 3.9% 26.5% 0.0% 0.0% 0.0% 9.3% 0.0% 

Ford Cars 3.1% 0.9% 14.2% 85.8% 0.0% 6.4% 4.0% 0.0% 0.0% 0.0% 5.2% 0.0% 

Subaru Trucks 0.0% 0.0% 70.5% 29.5% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 29.5% 27.4% 

Subaru Cars 0.0% 0.0% 69.2% 30.8% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 30.8% 0.9% 

GM Trucks 0.0% 0.0% 0.0% 30.8% 69.2% 92.7% 0.0% 0.0% 0.0% 14.7% 30.8% 0.0% 

GM Cars 2.6% 0.0% 0.0% 56.2% 43.8% 92.0% 0.0% 0.0% 0.0% 11.5% 28.8% 0.0% 

Honda Trucks 0.0% 0.0% 64.3% 35.7% 0.0% 0.0% 0.0% 64.3% 0.0% 0.0% 31.5% 4.2% 

Honda Cars 0.0% 0.0% 57.2% 42.8% 0.0% 0.0% 0.0% 57.2% 10.7% 0.0% 42.6% 0.3% 

Hyundai Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 29.6% 0.0% 

Hyundai Cars 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 32.2% 0.0% 

Tata Trucks 0.0% 20.3% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 

Tata Cars 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 

Field Code Changed

Formatted Table
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Kia Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 17.2% 0.0% 

Kia Cars 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 10.2% 0.0% 

Mazda Trucks 0.0% 0.0% 0.6% 99.4% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 99.3% 0.0% 

Mazda Cars 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.9% 0.9% 0.9% 0.9% 99.9% 0.9% 

Daimler Trucks 0.0% 0.0% 36.2% 63.8% 0.0% 0.0% 0.0% 0.0% 0.0% 46.7% 0.0% 0.0% 

Daimler Cars 0.0% 0.0% 54.6% 45.4% 0.0% 0.0% 0.0% 0.0% 0.0% 30.3% 0.0% 0.0% 

Mitsubishi Trucks 0.0% 0.0% 100.0% 0.0% 0.0% 100.0% 37.7% 0.0% 0.0% 0.0% 0.0% 0.0% 

Mitsubishi Cars 0.0% 0.0% 100.0% 0.0% 0.0% 100.0% 42.9% 0.0% 0.0% 0.0% 0.0% 0.0% 

Nissan Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 

Nissan Cars 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 

Porsche Trucks 12.4% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 100.0% 100.0% 

Porsche Cars 17.4% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 28.7% 82.6% 0.0% 

Suzuki Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Suzuki Cars 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Toyota Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 89.1% 0.0% 0.0% 0.0% 0.0% 78.3% 0.0% 

Toyota Cars 0.0% 0.0% 0.0% 100.0% 0.0% 69.9% 0.0% 0.0% 0.0% 0.2% 99.4% 0.0% 

VW Trucks 0.6% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 78.9% 99.4% 78.9% 

VW Cars 43.1% 0.0% 85.0% 15.0% 0.1% 0.0% 0.0% 0.0% 0.0% 1.9% 14.1% 0.8% 

Table 1-2 2008 Technology Percentages

CVVL 

DEACD 

DEACO 

CCPO 

DVVLO 

SGDI 

6MAN 

CVT 

NAUTO 

DCTAM 

EPS 

BISG 

CISG 

All Trucks 2.8% 0.0% 10.5% 1.4% 0.0% 2.9% 1.0% 2.6% 19.9% 0.0% 0.9% 0.0% 0.0% 

All Cars 5.2% 0.0% 1.2% 5.7% 0.0% 4.7% 2.3% 11.5% 18.5% 0.8% 12.6% 0.0% 0.4% 

BMW Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 6.3% 0.7% 0.0% 99.3% 0.0% 0.0% 0.0% 0.0% 

BMW Cars 0.0% 0.0% 0.0% 0.0% 0.0% 7.7% 14.6% 0.5% 83.3% 1.1% 0.0% 0.0% 0.0% 

Chrysler Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.2% 4.3% 3.6% 21.4% 0.0% 0.0% 0.0% 0.0% 

Chrysler Cars 0.0% 0.0% 5.2% 0.0% 0.0% 0.0% 0.9% 18.5% 3.9% 0.0% 0.0% 0.0% 0.0% 

Ford Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 1.0% 0.0% 1.8% 18.8% 0.0% 0.0% 0.0% 0.0% 

Ford Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 1.2% 1.9% 36.8% 0.0% 0.0% 0.0% 0.0% 

Subaru Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Subaru Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 4.1% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

GM Trucks 0.0% 0.0% 39.1% 5.0% 0.0% 0.0% 0.0% 0.0% 18.6% 0.0% 0.0% 0.0% 0.0% 

GM Cars 0.0% 0.0% 4.0% 28.8% 0.0% 6.0% 1.1% 0.0% 12.3% 0.0% 0.0% 0.1% 0.0% 

Honda Trucks 31.5% 0.0% 0.0% 0.0% 0.0% 4.2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Honda Cars 42.6% 0.0% 0.0% 0.0% 0.0% 0.0% 3.1% 3.2% 0.0% 0.0% 0.0% 0.0% 3.2% 

Hyundai Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 25.0% 0.0% 0.0% 0.0% 0.0% 

Hyundai Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Tata Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 

Tata Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 91.6% 0.0% 0.0% 0.0% 0.0% 

Kia Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Kia Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Mazda Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 23.5% 0.0% 0.1% 57.2% 0.0% 0.0% 0.0% 0.0% 

Mazda Cars 0.9% 0.9% 0.9% 0.9% 0.9% 11.4% 3.8% 0.1% 19.2% 0.0% 0.0% 0.0% 0.0% 

Daimler Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 15.9% 0.0% 0.0% 99.3% 0.0% 0.0% 0.0% 0.0% 

Daimler Cars 0.0% 0.0% 0.0% 0.0% 0.0% 1.7% 0.3% 0.0% 67.4% 10.4% 0.0% 0.0% 0.0% 

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Mitsubishi Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 14.4% 23.3% 0.0% 0.0% 0.0% 0.0% 

Mitsubishi Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 1.4% 44.2% 7.6% 0.0% 0.0% 0.0% 0.0% 

Nissan Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 1.2% 16.5% 0.0% 0.0% 16.5% 0.0% 0.0% 

Nissan Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 4.5% 69.4% 0.0% 0.0% 32.3% 0.0% 0.0% 

Porsche Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 1.4% 0.0% 98.6% 0.0% 0.0% 0.0% 0.0% 

Porsche Cars 0.0% 0.0% 0.0% 0.0% 0.0% 17.4% 51.9% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Suzuki Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Suzuki Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Toyota Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 5.7% 1.4% 4.7% 19.2% 0.0% 0.0% 0.0% 0.0% 

Toyota Cars 0.0% 0.0% 0.0% 0.0% 0.0% 7.6% 0.1% 16.7% 22.5% 0.0% 64.0% 0.0% 0.0% 

VW Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 

VW Cars 0.0% 0.0% 0.0% 0.0% 0.0% 46.0% 6.4% 5.4% 65.7% 14.3% 0.0% 0.0% 0.0% 

Table 1-2 2008 Technology Percentages

PSHEV 

2MHEV 

PHEV 

Auto 4 Speed Auto 5 Speed Auto 6 Speed Auto 7 Speed Auto 8 Speed 

Manual 5 Speed Manual 6 Speed 

CVT 

Automated Manual

5 Speed 

Automated Manual

6 Speed 

Automated Manual

7 Speed 

All Trucks 0.8% 0.1% 0.0% 37.9% 37.3% 18.6% 1.4% 0.0% 1.1% 1.0% 2.6% 0.0% 0.0% 0.0% 

All Cars 2.7% 0.0% 0.0% 39.1% 22.9% 16.4% 1.7% 0.4% 4.9% 2.3% 11.5% 0.3% 0.5% 0.0% 

BMW Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 99.3% 0.0% 0.0% 0.0% 0.7% 0.0% 0.0% 0.0% 0.0% 

BMW Cars 0.2% 0.0% 0.2% 0.0% 0.0% 82.6% 0.8% 0.0% 0.3% 14.6% 0.5% 0.0% 0.0% 1.1% 

Chrysler Trucks 0.0% 0.0% 0.0% 34.9% 35.5% 21.4% 0.0% 0.0% 0.3% 4.3% 3.6% 0.0% 0.0% 0.0% 

Chrysler Cars 0.0% 0.0% 0.0% 67.0% 8.2% 3.9% 0.0% 0.0% 1.4% 0.9% 18.5% 0.0% 0.0% 0.0% 

Ford Trucks 0.0% 0.0% 0.0% 55.9% 20.9% 18.8% 0.0% 0.0% 2.7% 0.0% 1.8% 0.0% 0.0% 0.0% 

Ford Cars 0.0% 0.0% 0.0% 36.3% 18.2% 36.8% 0.0% 0.0% 5.6% 1.2% 1.9% 0.0% 0.0% 0.0% 

Subaru Trucks 0.0% 0.0% 0.0% 62.1% 29.5% 0.0% 0.0% 0.0% 8.4% 0.0% 0.0% 0.0% 0.0% 0.0% 

Subaru Cars 0.0% 0.0% 0.0% 69.6% 2.4% 0.0% 0.0% 0.0% 23.9% 4.1% 0.0% 0.0% 0.0% 0.0% 

GM Trucks 0.0% 0.5% 0.0% 75.5% 5.0% 19.0% 0.0% 0.0% 0.4% 0.0% 0.0% 0.0% 0.0% 0.0% 

GM Cars 0.0% 0.1% 0.0% 77.9% 5.4% 12.3% 0.0% 0.0% 3.2% 1.1% 0.0% 0.0% 0.0% 0.0% 

Honda Trucks 0.0% 0.0% 0.0% 0.0% 99.7% 0.0% 0.0% 0.0% 0.3% 0.0% 0.0% 0.0% 0.0% 0.0% 

Honda Cars 0.0% 0.0% 0.0% 0.0% 87.3% 0.0% 0.0% 0.0% 6.4% 3.1% 3.2% 0.0% 0.0% 0.0% 

Hyundai Trucks 0.0% 0.0% 0.0% 29.8% 45.0% 25.0% 0.0% 0.0% 0.2% 0.0% 0.0% 0.0% 0.0% 0.0% 

Hyundai Cars 0.0% 0.0% 0.0% 76.4% 16.7% 0.0% 0.0% 0.0% 6.7% 0.2% 0.0% 0.0% 0.0% 0.0% 

Tata Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Tata Cars 0.0% 0.0% 0.0% 0.0% 8.4% 91.6% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Kia Trucks 0.0% 0.0% 0.0% 23.1% 75.7% 0.0% 0.0% 0.0% 1.2% 0.0% 0.0% 0.0% 0.0% 0.0% 

Kia Cars 0.0% 0.0% 0.0% 51.5% 41.0% 0.0% 0.0% 0.0% 7.5% 0.0% 0.0% 0.0% 0.0% 0.0% 

Mazda Trucks 0.0% 0.0% 0.0% 10.1% 29.6% 57.2% 0.0% 0.0% 3.0% 0.0% 0.1% 0.0% 0.0% 0.0% 

Mazda Cars 0.0% 0.0% 0.0% 33.3% 29.7% 19.2% 0.0% 0.0% 13.9% 3.8% 0.1% 0.0% 0.0% 0.0% 

Daimler Trucks 0.0% 0.0% 0.0% 0.0% 0.7% 0.0% 99.3% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Daimler Cars 0.0% 0.0% 0.0% 0.0% 22.0% 0.0% 67.4% 0.0% 0.0% 0.3% 0.0% 10.4% 0.0% 0.0% 

Mitsubishi Trucks 0.0% 0.0% 0.0% 62.3% 0.0% 23.3% 0.0% 0.0% 0.0% 0.0% 14.4% 0.0% 0.0% 0.0% 

Mitsubishi Cars 0.0% 0.0% 0.0% 30.8% 4.5% 7.6% 0.0% 0.0% 11.6% 1.4% 44.2% 0.0% 0.0% 0.0% 

Nissan Trucks 0.0% 0.0% 0.0% 0.0% 81.6% 0.0% 0.0% 0.0% 0.7% 1.2% 16.5% 0.0% 0.0% 0.0% 

Nissan Cars 1.1% 0.0% 0.0% 7.0% 19.1% 0.0% 0.0% 0.0% 0.0% 4.5% 69.4% 0.0% 0.0% 0.0% 

Porsche Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 98.6% 0.0% 0.0% 0.0% 1.4% 0.0% 0.0% 0.0% 0.0% 

Porsche Cars 0.0% 0.0% 0.0% 0.0% 33.7% 0.0% 0.0% 0.0% 14.4% 51.9% 0.0% 0.0% 0.0% 0.0% 

Formatted Table
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Suzuki Trucks 0.0% 0.0% 0.0% 0.0% 99.5% 0.0% 0.0% 0.0% 0.5% 0.0% 0.0% 0.0% 0.0% 0.0% 

Suzuki Cars 0.0% 0.0% 0.0% 76.2% 13.1% 0.0% 0.0% 0.0% 10.7% 0.0% 0.0% 0.0% 0.0% 0.0% 

Toyota Trucks 4.7% 0.0% 0.0% 9.0% 63.9% 19.2% 0.0% 0.0% 1.9% 1.4% 4.7% 0.0% 0.0% 0.0% 

Toyota Cars 16.9% 0.0% 0.0% 35.7% 19.5% 19.8% 0.0% 2.6% 5.5% 0.1% 16.7% 0.0% 0.0% 0.0% 

VW Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

VW Cars 0.0% 0.0% 0.0% 0.0% 0.0% 65.7% 0.0% 0.0% 8.2% 6.4% 5.4% 0.0% 14.3% 0.0% 

These technology tables indicate that some manufacturers are already 

implementing some of these technologies in their 2008 fleet. VW stands out as having a 

significant number of turbocharged direct injection engines, though it is uncertain 

whether their engines are also downsized. Some of the valve and cam technologies are 

quite common today: for example, nearly half the fleet has dual cam phasing, while 

Honda and GM are have considerable levels of engines with cylinder deactivation 

(DEAC). Honda also has already implemented continuously variable valve lift (CVVL) 

on a majority of their engines. Moreover, Toyota has the highest penetration of hybrid 

technologies. Finally, regarding the technologies obtained from the product plans: many 

of the manufacturers who reported the lubricating oil information, indicated that low 

friction (or low viscosity) oil will be used more frequently in the future. Therefore, it is 

likely that this technology is underreported for the fleet as a whole since it was assumed 

that the usage of low viscosity oils was zero for the companies who did not provide 

product plans. The lack of reporting of these types of technologies (if they exist in the 

fleet) will probably lead to a slightly higher cost of compliance for these companies than 

what the agencies show in the Preamble for the MY 2011 costs. However, as described 

in the section II.D of the Preamble, these technologies alone do not necessarily guarantee 

a better fuel economy compared to other vehicles in their footprint class. There are many 

other considerations at play, most notably, weight and power. 

The section below provides further detail on the conversion of the MY 2008 

baseline into the MY 2011-2016 reference fleet. It also described more of the data 

contained in the baseline spreadsheet. 

1.3 The MY 2011-2016 Reference Fleet 

The reference fleet aims to reflect the current market conditions and expectations 

about conditions of the vehicle fleet during the rulemaking time frame. Fundamentally, 

constructing this fleet involved projecting the MY 2008 baseline fleet into the MY 2011-

2016 model years. It also included the assumption that none of the models had changes 

during this period. Projecting what the fleet will look like in the future is a process that is 

inherently full of uncertainty. NHTSA and EPA therefore relied on many sources of 

reputable information to make these projections. 

1.3.1 On what data is the baseline vehicle fleet based? 
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1-14 

EPA and NHTSA have based the projection of total car and light truck sales on 

recent projections made by the Energy Information Administration (EIA). EIA publishes 

a long-term projection of national energy use annually called the Annual Energy Outlook 

(AEO).4

 This projection utilizes a number of technical and econometric models which 

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

future. In support of its projection of fuel use by light-duty vehicles, EIA projects sales 

of new cars and light trucks. Due to the state of flux of both energy prices and the 

economy, EIA published three versions of its 2009 Annual Energy Outlook. The 

Preliminary 2009 report was published early (in November 2008) in order to reflect the 

dramatic increase in fuel prices which occurred during 2008, after the development of the 

2008 AEO. The official 2009 report was published in March of 2009. A third 2009 

report was published a month later which reflected the economic stimulus package passed 

by Congress earlier this year. For the analysis in this rule, NHTSA and EPA use the sales 

projections of this latest report, referred to as the updated 2009 AEO. 

In their updated 2009 report, EIA projects that total light-duty vehicle sales 

gradually recover from their currently depressed levels by roughly 2013. In 2016, car 

and light truck sales are projected to be 9.5 and 7.1 million units, respectively. While the 

total level of sales of 16.6 million units is similar to pre-2008 levels, the fraction of car 

sales is higher than that existing in the 2000-2007 timeframe. This reflects the impact of 

higher fuel prices, as well as the effects of the EISA (which called for a minimum fleet 

average of 35 mpg by 2020). Note that EIA’s definition of cars and trucks follows that 

used by NHTSA prior to the MY 2011 CAFE final rule published earlier this year. The 

MY 2011 CAFE final rule reclassified a number of 2-wheel drive sport utility vehicles 

from the truck fleet to the car fleet. EIA’s sales projections of cars and trucks for the 

2011-2016 model years under both the new and old NHTSA truck definition are shown in 

Table 1-3 and Table 1-4 below, respectively. Actual vehicle sales for MY 2008 are also 

shown under the new NHTSA truck definition. Slight differences exist between the total 

car and truck sales projections. These differences are less than 0.1% and are due to the 

iterative process described further below to shift sales between car and truck market 

segments. 

Table 1-3 AEO Volumes New NHTSA Car Truck Definition After Projections 

2008 

Baseline 

Sales 

2011 

Projected 

Volume 

2012 

Projected 

Volume 

2013 

 Projected 

 Volume 

2014 

Projected 

Volume 

2015 

Projected 

Volume 

2016 

Projected 

Volume 

All Trucks 5,620,847 5,547,326 5,530,583 5,720,280 5,810,895 5,717,300 5,586,953 

All Cars 8,220,517 8,235,204 9,255,624 9,977,341 10,479,350 10,890,967 11,067,608 

Total 13,841,364 13,782,530 14,786,207 15,697,621 16,290,245 16,608,267 16,654,561 

Table 1-4 AEO Volumes Old NHTSA Car Truck Definition Before Projections 

2011 

Projected 

Volume 

2012 

Projected 

Volume 

2013 

 Projected 

 Volume 

2014 

Projected 

Volume 

2015 

Projected 

Volume 

2016 

Projected 

Volume 

Field Code Changed

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The Baseline Vehicle Fleet 

1-15 

All Trucks 7,007,298 7,725,263 8,261,773 8,776,298 9,241,209 9,468,365 

All Cars 6,954,580 7,125,693 7,391,939 7,440,095 7,334,371 7,112,689 

Total 13,961,878 14,850,955 15,653,713 16,216,393 16,575,580 16,581,055 

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

and truck markets have also been changing and are expected to continue to change in the 

future. Manufacturers are introducing more crossover models which offer much of the 

utility of SUVs but using more car-like designs. In order to reflect these changes in fleet 

makeup, EPA and NHTSA considered several available forecasts. After reviewing 

information from a number of forecasting organizations, the agencies decided to purchase 

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

Powers.5 NHTSA and EPA decided to use the forecast from CSM, for several reasons. 

One, CSM agreed to allow us to publish their high level data, on which the forecast is 

based, in the public domain. Two, it covered nearly all the timeframe of greatest 

relevance to this proposed rule (2012-2015 model years). Three, it provided projections 

of vehicle sales both by manufacturer and by market segment. Four, it utilized market 

segments similar to those used in the EPA emission certification program and fuel 

economy guide. As discussed further below, this allowed the CSM forecast to be 

combined with other data obtained by NHTSA and EPA. The breakdown of car and 

truck sales by manufacturer and by market segment for the 2016 model year and beyond 

were assumed to be the same as CSM’s forecast for the 2015 calendar year. 

1.3.2 How do the agencies develop the reference vehicle fleet? 

The process of producing the 2011-2016 reference fleet involved combining the 

baseline fleet with the projection data described above. This was a complex multistep 

procedure, which is described in this section. 

1.3.2.1 How was the 2008 baseline data merged with the CSM data? 

Merging the 2008 baseline data with the 2011-2016 CSM data required a 

thorough mapping of certification vehicles to CSM vehicles by individual make and 

model. One challenge the agencies faced when determining a reference case fleet was 

that the sales data projected by CSM had different market segmentation than the data 

contained in EPA’s internal database. In order to create a common segmentation between 

the two databases, side-by-side comparison of the specific vehicle models in both 

datasets was performed, and additional “CSM segment” modifier in the spreadsheet was 

created, thus mapping the two datasets. The reference fleet sales based on the “CSM 

segmentation” was then projected 

The baseline data and reference fleet volumes are available to the public. The 

baseline Excel spreadsheet in the docket is the result of the merged files.6

It provides 

Formatted Table
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specific details on the sources and definitions for the data. The Excel file contains 

several tabs. They are: “Data”, “Data Tech Definitions”, “SUM”, “SUM Tech 

Definitions”, “Truck Vehicle Type Map”, and “Car Vehicle Type Map”. “Data” is the 

tab with the raw data. “Data Tech Definitions” is the tab where each column is defined 

and its data source named. “SUM” is the tab where the raw data is processed to be used 

in the OMEGA and Volpe models. The “SUM” tab minus columns A-F and minus the 

Generic vehicles is the input file for the models. The “Generic” manufacturer (shown in 

the “SUM” tab) is the sum of all manufacturers and is calculated as a reference, and for 

data verification purposes. It is used to validate the manufacturers’ totals. It also gives 

an overview of the fleet. Table 1-5 shows the sum of the models chosen. The number of 

models is determined by the number of unique segment and vehicle type combinations. 

These combinations of segment and vehicle type (the vehicle type number is the same as 

the technology package number) are determined by the technology packages discussed 

in.the EPA DRIA (chapter 1). “SUM Tech Definitions” is the tab where the columns of 

the “SUM” tab are defined. The “Truck Vehicle Type Map” and “Car Vehicle Type 

Map” map the number of cylinder and valve actuation technology to the “tech package” 

vehicle type number. 

Table 1-5 Models from the SUM Tab Model 

Model 

Car Like LargeSuv >=V8 Vehicle Type: 13

Car Like LargeSuv V6 Vehicle Type: 16 

Car Like LargeSuv V6 Vehicle Type: 12 

Car Like LargeSuv V6 Vehicle Type: 9 

Car Like LargeSuv I4 and I5 Vehicle Type: 7 

Car Like MidSizeSuv V6 Vehicle Type: 8 

Car Like MidSizeSuv V6 Vehicle Type: 5 

Car Like MidSizeSuv I4 Vehicle Type: 7 

Car Like SmallSuv V6 Vehicle Type: 12 

Car Like SmallSuv V6 Vehicle Type: 4 

Car Like SmallSuv I4 Vehicle Type: 3 

LargeAuto >=V8 Vehicle Type: 13 

LargeAuto >=V8 Vehicle Type: 10 

LargeAuto >=V8 Vehicle Type: 6 

LargeAuto V6 Vehicle Type: 12 

LargeAuto V6 Vehicle Type: 5 

MidSizeAuto >=V8 Vehicle Type: 13 

MidSizeAuto >=V8 Vehicle Type: 10 

MidSizeAuto >=V8 (7 or >) Vehicle Type: 6 

MidSizeAuto V6 Vehicle Type: 12 

MidSizeAuto V6 Vehicle Type: 8 

MidSizeAuto V6 Vehicle Type: 5 

MidSizeAuto I4 Vehicle Type: 3 

In the combined EPA certification and CSM database, all of the 2008 vehicle 

models were assumed to continue out to 2016, though their volumes changed in 

proportion to CSM projections. Also, any new models expected to be introduced within 

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the 2009-2016 timeframe are not included in the data. These volumes are reassigned to 

the existing models. All MY 2011-2016 vehicles are mapped to the existing vehicles by 

a process of mapping to manufacturer market share and overall segment distribution. The 

mappings are discussed in the next section. Further discussion of this limitation is 

discussed below in section 1.3.4. The statistics of this fleet will be presented below since 

further modifications were required to the volumes as the next section describes. 

1.3.2.2 How were the CSM forecasts normalized to the AEO forecasts? 

 

The next step in the production of the reference fleet is one of the more 

complicated steps to explain. Here, the projected CSM forecasts for relative sales of cars 

and trucks by manufacturer and by market segment was normalized (set equal) to the 

total sales estimates of the updated 2009 Annual Energy Outlook (AEO). NHTSA and 

EPA used projected car and truck volumes for this period from AEO 2009. However, the 

AEO projects sales only at the car and truck level, not at the manufacturer and modelspecific level, which are needed for the analysis. The CSM data provided year-by-year 

percentages of cars and trucks sold by each manufacturer as well as the percentages of 

each vehicle segment. Using these percentages normalized to the AEO-projected 

volumes then provided the manufacturer-specific market share and model-specific sales 

for model years 2011-2016 (it is worth clarifying that the agencies are not using the 

model-specific sales volumes from CSM, only the volumes by manufacturer and 

segment). This process is described in greater detail in the following paragraphs. 

In order to determine future production volumes, multipliers were developed by 

manufacturer and vehicle segment that could be applied to MY 2008 volumes. The 

process for developing the multipliers is complicated, but is easiest to explain as a threestep process, though the first step is combined with both the second and third step, so 

only one multiplier per manufacturer and vehicle segment is developed. 

The three steps are: 

1. Adjust total car and truck sales to match AEO projections. 

1.2.Adjust Car sales to match CSM market share projections for each manufacturer 

and car segment. 

1.3.Adjust Truck sales to match CSM market share projections for each manufacturer 

and truck segment. 

The first step is the adjustment of total car and truck sales in 2008 to match AEO 

projections of total car and truck sales in 2011-2016. The volumes for all of the trucks in 

2008 were added up (TruckSum2008), and so were the volumes of all the cars 

(CarSum2008). A multiplier was developed to scale the volumes in 2008 to the AEO 

projections. The example equation below shows the general form of how to calculate a 

car or truck multiplier. The AEO projections are shown above in Table 1-3. 

Example Equation :

TruckMultiplier(Year X) = AEOProjectionforTrucks(Year X) / TruckSum2008 

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CarMultiplier(Year X) = AEOProjectionforCars(Year X) / CarSum2008 

Where: Year X is the model year of the multiplier. 

The AEO projection is different for each model year. Therefore, the multipliers 

are different for each model year. The multipliers can be applied to each 2008 vehicle as 

a first adjustment, but multipliers based solely on AEO have limited value since it can 

only give an adjustment that will give the correct total numbers of cars and trucks without 

the correct market share or vehicle mix. A correction factor based on the CSM data, 

which does contain market share and vehicle segment mix, is therefore necessary, so 

combining the AEO multiplier with CSM multipliers (one per manufacturer, segment, 

and model year) will give the best multipliers. 

There were several steps in developing an adjustment for Cars based on the CSM 

data. CSM provided data on the market share and vehicle segment distribution. The first 

step in determining the adjustment for Cars was to total the number of Cars in each 

vehicle segment by manufacturer in MY 2008. A total for all manufacturers in each 

segment was also calculated. The next step was to multiply each segment the volume of 

each segment for each manufacturer by the CSM market share. The AEO multiplier was 

also applied at this time. This gave projected volumes with AEO total volumes and 

market share correction for Cars. This is shown in the “Adjusted for 2011 AEO and 

Manufacturer Market Share” column of Table 1-6. 

The next step is to adjust the sales volumes for CSM vehicle segment distribution. 

The process for adjusting for vehicle segment is more complicated than a simple one step 

multiplication. In order to keep manufacturers’ volumes constant and still have the 

correct vehicle segment distribution, vehicles need to move from segment to segment 

while maintaining constant manufacturers’ totals. Six rules and one assumption were 

applied to accomplish the shift. The assumption (based on the shift in vehicle sales in the 

last year) is that people are moving to smaller vehicles in the rulemaking time frame. A 

higher level (less detailed) example of this procedure is provided in the preamble section 

II. 

1. Vehicles from CSM’s “Luxury Car,” “Specialty Car,” and “Other Car” segments, 

if reduced will be equally distributed to the remaining four categories (“Full-Size 

Car,” “Mid-Size Car,” “Small Car,” “Mini Car”). If these sales increased, they 

were taken from the remaining four categories so that the relative sales in these 

four categories remained constant. 

2. Vehicles from CSM’s “Luxury Car,” “Specialty Car,” and “Other Car” segments, 

if increased will take equally from the remaining categories (“Full-Size Car,” 

“Mid-Size Car,” “Small Car,” “Mini Car”). 

3. All manufacturers have the same multiplier for a given segment shift based on 

moving all vehicles in that segment to achieve the CSM distribution. Table 1-6 

shows how the 2011 vehicles moved and the multipliers that were created for 

each adjustment. This does not mean that new vehicle segments will be added 

(except for Generic Mini Car described in the next step) to manufacturers that do 

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not produce them. Vehicles within each manufacturer will be shifted as close to 

the distribution as possible given the other rules. Table 1-7 has the percentages of 

Cars per CSM segment. These percentages are multiplied by the total number of 

vehicles in a given year to get the total sales in the segment. Table 1-6 shows the 

totals for 2011 in the “2011 AEO-CSM Sales Goal” column. 

4. When “Full-Size Car,” “Mid-Size Car,” “Small Car” are processed, if vehicles 

need to move in or out of the segment, they will move into or out of the next 

smaller segment. So, if Mid-Size Cars are being processed they can only move to 

or be taken from Small Cars. Note: In order to accomplish this, a “Generic Mini 

Car” segment was added to manufacturers who did not have a Mini (type) Car in 

production in 2008, but needed to shift down vehicles from the Small Car 

segment. 

5. The data must be processed in the following order: “Luxury Car,” “Specialty 

Car,” “Other Car,” “Full-Size Car,” “Mid-Size Car,” “Small Car.” The “Mini 

Car” does not need to be processed separately. By using this order, it works out 

that vehicles will always move toward the correct distribution. There are two 

exceptions, BMW and Porsche only have “Luxury Car,” “Specialty Car,” and 

“Other Car” vehicles, so their volumes were not changed or shifted since these 

rules did not apply to them. 

5.6.When an individual manufacturer multiplier is applied for a segment, the vehicles 

move to or from the appropriate segments as specified in the previous rules and as 

shown in Table 1-6. 

Table 1-6 Example: 2011 Model Year Volume Shift 

CSM Segment 

2008 MY 

Sales 

Adjusted for 

2011 AEO 

and 

Manufacturer 

Market Share 

Luxury, Specialty, 

Other Adjustment 

 Full Size 

Adjustment 

 Midsize 

Adjustment 

 Small Car 

Adjustment 

2011 AEOCSM Sales 

Goal 

All Full-Size Car 730,355 501,245 520,885 411,025 411,025 411,025 411,025

All Luxury Car 1,057,875 1,076,470 970,680 970,680 970,680 970,680 970,666 

All Mid-Size Car 1,970,494 1,946,981 2,033,087 2,142,948 1,838,095 1,838,095 1,838,095 

All Mini Car 599,643 686,738 733,339 733,339 733,339 991,309 991,349 

All Small Car 1,850,522 2,007,527 2,099,343 2,099,343 2,404,196 2,146,226 2,146,226

All Specialty Car 754,547 783,982 637,785 637,785 637,785 637,785 637,759

All Others 3,259 4,355 12,178 12,178 12,178 12,178 12,178 

Number Vehicles that shift and Where

All Full-Size Car 19,640 (109,861) - - 

All Luxury Car (105,790) - - -

All Mid-Size Car 86,107 109,861 (304,853) - 

All Mini Car 46,601 - - 257,970 

All Small Car 91,816 - 304,853 (257,970) 

All Specialty Car (146,198) - - -

All Others 7,823 - - - 

Individual Manufacturer Multiplier 

All Full-Size Car 0.789 CHAPTER 2: CHAPTER 3:

All Luxury Car 0.902 CHAPTER 4: CHAPTER 5: CHAPTER 6:

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All Mid-Size Car 0.858 CHAPTER 7:

All Mini Car 1.352

All Small Car 

All Specialty Car 0.814 CHAPTER 8: CHAPTER 9: CHAPTER 10:

All Others 2.796 CHAPTER 11:CHAPTER 12:CHAPTER 13:

Table 1-7 CSM – Percent of Cars per Segment 

 CSM Segment 2011 2012 2013 2014 2015 2016 

Compact Car 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 

Full-Size Car 5.9% 4.3% 4.7% 4.9% 4.9% 4.9% 

Luxury Car 13.9% 13.7% 14.6% 15.0% 15.1% 15.1% 

Mid-Size Car 26.2% 29.0% 27.9% 27.5% 27.9% 27.9% 

Mini Car 14.1% 15.5% 15.5% 15.4% 15.4% 15.4% 

Small Car 30.6% 27.5% 26.5% 26.1% 25.8% 25.8% 

Specialty Car 9.1% 9.8% 10.7% 10.9% 10.6% 10.6%

Others 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 

Mathematically, an individual manufacturer multiplier is calculated by making the 

segment the goal and dividing by the previous total for the segment (shown in Table 1-6). 

If the number is greater than 1, the vehicles are entering the segment, and if the number is 

less than 1, the vehicles are leaving the segment. So, for example, if Luxury Cars have 

an adjustment of 1.5, then for a specific manufacturer who has Luxury Cars, a multiplier 

of 1.5 is applied to its luxury car volume, and the total number of vehicles that shifted 

into the Luxury segment is subtracted from the remaining segments to maintain that 

company’s market share. On the other hand, if Large Cars have an adjustment of 0.7, 

then for a specific manufacturer who has Large Cars, a multiplier of 0.7 is applied to its 

Large Cars, and the total number of vehicles leaving that segment is transferred into that 

manufacturer’s Mid-Size Cars. 

After the vehicle volumes are shifted using the above rules, a total for each 

manufacturer and vehicle segment is maintained. The total for each manufacturer 

segment for a specific model year (e.g., 2011 General Motors Luxury Cars) divided by 

the MY 2008 total for that manufacturer segment (e.g., 2008 General Motors Luxury 

Cars) is the new multiplier used to determine the future vehicle volume for each vehicle 

model. This is done by taking the multiplier (which is for a specific manufacturer and 

segment) times the MY 2008 volume for the specific vehicle model (e.g., 2008 General 

Motors Luxury Car Cadillac CTS). This process is repeated for each model year (2011-

2016). 

The method used to adjust CSM Trucks to the AEO market share was different 

than the method used for Cars. The process for Cars is different than Trucks because it is 

not possible to predict how vehicles would shift between segments based on current 

market trends. This is because of the added utility of some trucks that makes their sales 

more insensitive to factors like fuel price. Again, CSM provided data on the market 

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share and vehicle segment distribution. The process for having the fleet match CSM’s 

market share and vehicle segment distribution was iterative. 

The following totals were determined: 

• The total number of trucks for each manufacturer in 2008 model year. 

• The total number of trucks in each truck segment in 2008 model year. 

• The total number of truck in each segment for each manufacturer in 2008 model 

year. 

• The total number of trucks for each manufacturer in a specific future model year 

based on the AEO and CSM data. This is the goal for market share. 

• The total number of trucks in each truck segment in a specific future model year 

based on the AEO and CSM data. This is the goal for vehicle segment 

distribution. Table 1-8 has the percentages of Trucks per CSM segment 

Table 1-8 CSM – Percent of Trucks per Segment 

 CSM Segment 2011 2012 2013 2014 2015 2016 

Full-Size CUV 4.1% 3.3% 4.0% 4.4% 4.5% 4.5%

Full-Size Pickup 20.0% 17.9% 18.1% 20.1% 20.8% 20.8% 

Full-Size SUV 3.3% 2.8% 1.6% 1.2% 1.3% 1.3% 

Full-Size Van 3.5% 3.3% 4.0% 3.9% 4.0% 4.0% 

Mid-Size CUV 14.5% 15.8% 17.5% 18.1% 18.4% 18.4% 

Mid-Size MAV 3.8% 3.3% 2.6% 2.2% 2.2% 2.2% 

Mid-Size Pickup 3.6% 5.8% 6.4% 6.4% 6.6% 6.6% 

Mid-Size SUV 3.2% 2.3% 1.8% 1.6% 1.6% 1.6% 

Mid-Size Van 11.9% 11.3% 10.7% 10.0% 8.7% 8.7% 

Small CUV 27.3% 28.4% 27.0% 26.1% 26.2% 26.2% 

Small MAV 1.9% 3.4% 4.1% 4.1% 4.1% 4.1% 

Small SUV 2.8% 2.4% 2.2% 2.0% 1.8% 1.8% 

To start, two different types of tables were created. One table had each 

manufacturer with its total sales for 2008 (similar to Table 1-9). This table will have the 

goal for each manufacturer, and a column added for each iteration with the current total. 

The second table has a truck segment total by manufacturer. The second table starts out 

with a “Generic” manufacturer (Table 1-10) which is the table where the goal resides. 

Each manufacturer (BMW is shown in Table 1-11) is then listed below the “Generic” 

manufacturer. With each iteration, a new total is added for each segment that is 

calculated and added to the table. This is not shown in the tables below. A process of 

first adjusting the numbers in the tables to the goal for market share distribution was 

done. This was followed by adjusting to the goal for vehicle segment distribution. Each 

time an adjustment was done a new column was added. An adjustment was done by 

creating a multiplier (either segment distribution based or manufacturer distribution 

based) and applying it to each vehicle segment total in the current iteration. A 

manufacturer-based multiplier is calculated by taking the goal total for a manufacturer 

and dividing by the current total (starting with 2008 model year volumes) for a 

manufacturer. A segment distribution-based multiplier is calculated by taking the goal 

distribution volumes in the Generic manufacturer set and dividing them by the current 

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volume. Table 1-9, Table 1-10, and Table 1-11 below illustrate two iterations using 

BMW. 

Table 1-9 Manufacturer Truck Totals 

 2008 Model Year Sales Manufacturer Distribution 2011Volume Goal Multiplier for Iteration 1 

BMW 61,324 139948 139948/61324=2.28

Table 1-10 Segment Specific Truck Totals for All Manufacturers 

Manufacturer CSM Segment 

2008 Model Year 

Sales 

Segment Distribution 

2011Volume Goal Multipliers 

Generic1 Full-Size Pickup 1,195,073 1,390,343 1.30 

Generic Mid-Size Pickup 598,197 251,433 0.38 

Generic Full-Size Van 33,384 244,393 8.30 

Generic Mid-Size Van 719,529 826,733 1.37

Generic Mid-Size MAV 191,448 263,765 1.26 

Generic Small MAV 235,524 133,309 0.57 

Generic Full-Size SUV 530,748 232,375 0.46 

Generic Mid-Size SUV 347,026 221,607 0.70 

Generic Small SUV 377,262 194,496 0.75 

Generic Full-Size CUV 406,554 287,313 0.69 

Generic Mid-Size CUV 798,335 1,007,583 0.99 

Generic Small CUV 1,441,589 1,901,229 1.16

Note: 1. Generic means all manufacturers. 

Table 1-11 Segment Specific Truck Totals for BMW

Manufacturer CSM Segment 

2008 Model Year 

Sales 

Iteration 1 Adjust for 

Market Share 

Iteration 2 Adjust for 

Segment Distribution 

BMW Full-Size Pickup 

BMW Mid-Size Pickup 

BMW Full-Size Van 

BMW Mid-Size Van 

BMW Mid-Size MAV 3,882 2.28*3,882=8,551 1.26*8,851=11,137 

BMW Small MAV 

BMW Full-Size SUV 

BMW Mid-Size SUV 

BMW Small SUV 

BMW Full-Size CUV 

BMW Mid-Size CUV 36,409 2.28*36,409=83,013 0.99*83,013=82,603

BMW Small CUV 21,033 2.28*21,033=47,955 1.16*47,955=55,592

Total BMW Vehicles 61,324 139,819 149,332

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Using this process, the numbers will get closer to the goal of matching CSM’s market 

share for each manufacturer and distribution for each vehicle segment after each of the 

iterations. The iterative process is carried out until the totals nearly match the goals. 

After 19 iterations, all numbers were within 0.01% of CSM’s distributions. The 

calculation iterations could have been stopped sooner, but they were continued to observe 

how the numbers would converge. 

After the market share and segment distribution were complete, the totals need to be 

used to create multipliers that could be applied to the original individual 2008 model year 

vehicle volumes (each unique manufacture models volume). The total for each 

manufacturer segment divided by the 2008 model year total for each manufacturer 

segment gives a multiplier that can be applied to each vehicle based on its manufacturer 

and segment. 

The above process is done for each model year needed (2011-2016). The multipliers 

are then applied to each vehicle in 2008 model year, which gives a volume for each 

vehicle in 2011 through 2016 model year. The “reference case” (which is the technology 

being applied to 2012-2016 fleet to meet the 2011 cafe standard) is discussed below in 

section 4.1, with the results being presented in section 4.2. 

13.1.11.3.3 What are the sales volumes and characteristics of the reference 

fleet? 

 

Table 1-12 and Table 1-13 below contain the sales volumes and percentages that 

result from the process above for MY 2008 and 2011-2016. The forecast from CSM used 

in this proposal is CSM’s forecast from the 2nd quarter of 2009. CSM also provided to 

EPA an updated forecast in the 3rd quarter of 2009, which we were unable to use for this 

proposal due to time constraints. However, we have placed a copy of the 3rd Quarter 

CSM forecast in the public docket for this rulemaking, and we will consider its use, and 

any further updates from CSM or other data received during the comment period when 

developing the analysis for the final rule.7

Table 1-12 Vehicle Segment Volumes 

 Reference Class 

Segmenta

Actual and Projected Sales Volume 

2008 2011 2012 2013 2014 2015 2016

Large Auto 557,693 390,306 361,186 382,212 390,640 410,847 416,829

Mid-Size Auto 3,097,859 2,649,352 3,153,248 3,470,051 3,722,450 3,929,107 4,022,893 

Compact Auto 1,976,424 1,966,447 2,128,221 2,318,084 2,480,435 2,582,171 2,643,374 

Sub-Compact Auto 1,364,434 1,887,350 2,114,147 2,240,751 2,348,611 2,452,342 2,512,431 

All Cars 6,996,410 6,893,455 7,756,803 8,411,098 8,942,136 9,374,467 9,595,527 

Large Pickup 1,581,880 1,535,300 1,533,514 1,620,983 1,776,746 1,813,145 1,785,188

Small Pickup 177,497 57,694 112,916 140,210 138,240 136,667 145,324 

Large SUV 2,783,949 2,670,474 2,642,285 2,713,398 2,718,252 2,705,080 2,625,901 

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Mid-Size SUV 1,263,360 1,469,957 1,563,424 1,544,252 1,502,608 1,490,577 1,446,932 

Small SUV 285,355 84,525 138,914 180,559 178,377 160,839 156,230 

Mini Van 642,055 749,650 717,454 699,786 657,057 561,199 543,558 

Cargo Van 110,858 321,476 320,898 387,335 376,831 366,294 355,901 

All Trucks 6,844,954 6,889,076 7,029,404 7,286,523 7,348,109 7,233,800 7,059,034 

a This is no longer the CSM segment, but the segment used for the subsequent analysis in this rule.

Table 1-13 Manufacturer Volumes 

2008 

Baseline 

Sales 

2011 

Projected 

Volume 

2012 

Projected 

Volume 

2013 

 Projected 

 Volume 

2014 

Projected 

Volume 

2015 

Projected 

Volume 

2016 

Projected 

Volume 

Total Vehicles 13,841,364 13,782,531 14,786,207 15,697,621 16,290,246 16,608,267 16,654,561 

All Trucks 6,844,954 6,889,076 7,029,404 7,286,523 7,348,109 7,233,800 7,059,034 

All Cars 6,996,410 6,893,455 7,756,803 8,411,098 8,942,136 9,374,467 9,595,527 

BMW Trucks 61,324 139,959 142,861 141,949 144,022 139,034 135,569 

BMW Cars 291,796 272,572 283,471 323,191 352,248 371,668 380,804 

Chrysler Trucks 956,792 402,659 282,472 244,441 222,545 112,381 109,674 

Chrysler Cars 700,413 193,704 178,635 175,072 169,046 136,583 138,602 

Ford Trucks 846,596 943,583 1,025,575 1,107,535 1,202,141 1,230,889 1,202,442 

Ford Cars 1,021,792 1,229,762 1,348,260 1,424,345 1,446,097 1,503,175 1,511,354 

Subaru Trucks 82,546 117,896 88,877 77,593 76,913 73,425 74,135 

Subaru Cars 116,035 153,644 149,192 135,946 135,141 130,588 131,022 

GM Trucks 1,512,047 1,313,927 1,209,642 1,320,438 1,342,856 1,355,820 1,322,512 

GM Cars 1,607,460 1,156,366 1,484,580 1,620,301 1,708,507 1,789,813 1,820,234 

Honda Trucks 505,140 571,178 669,948 724,500 687,208 691,641 675,173 

Honda Cars 1,006,639 996,396 1,155,008 1,352,607 1,493,242 1,562,496 1,593,092 

Hyundai Trucks 53,158 127,199 141,028 135,751 134,274 132,978 129,763 

Hyundai Cars 337,869 570,431 580,538 558,975 562,862 590,579 596,891 

Tata Trucks 55,584 31,344 42,168 46,256 53,335 48,583 47,372 

Tata Cars 9,596 18,572 22,878 32,822 35,534 40,586 41,584 

Kia Trucks 59,472 97,706 78,789 74,596 72,192 69,894 68,310 

Kia Cars 221,980 302,347 304,524 309,667 331,198 347,533 351,081 

Mazda Trucks 55,885 59,782 71,930 71,136 66,919 59,361 57,998 

Mazda Cars 246,661 317,948 313,489 318,669 338,487 340,069 345,489 

Daimler Trucks 79,135 97,926 109,351 115,684 125,189 113,366 110,541 

Daimler Cars 208,052 177,493 172,172 190,133 204,335 229,562 235,205 

Mitsubishi Trucks 15,371 9,268 10,098 11,440 9,124 7,349 7,171 

Mitsubishi Cars 85,358 67,779 64,843 61,169 56,478 52,368 53,459 

Nissan Trucks 305,546 420,666 477,897 478,571 474,558 454,488 444,471 

Nissan Cars 717,869 793,873 958,696 1,031,569 1,073,307 1,104,272 1,123,486 

Porsche Trucks 18,797 21,401 20,767 20,639 19,379 16,822 17,273 

Porsche Cars 18,909 30,909 31,605 35,813 38,470 36,175 37,064 

Suzuki Trucks 35,319 25,194 30,391 29,750 30,545 27,204 26,526 

Suzuki Cars 79,339 91,355 86,537 86,220 81,480 75,965 77,427 

Toyota Trucks 951,136 1,059,161 1,019,375 1,019,048 1,045,671 1,081,323 1,057,837 

Toyota Cars 1,260,364 1,473,999 1,697,762 1,862,201 1,985,033 2,114,273 2,154,115 

VW Trucks 26,999 108,477 109,415 100,952 104,023 102,743 100,186 
The Baseline Vehicle Fleet 

1-25 

VW Cars 290,385 388,054 423,433 458,641 467,885 465,263 476,699 

Table 1-14 also shows how the change in fleet make-up may affect the footprint 

distributions over time. The resulting data indicates that the average footprint level of the 

fleet will shrink by 1.2% (1% for cars and 2% for trucks, and sales weighted). Thus, the 

combination of AEO and CSM projections produces a future vehicle fleet which is only 

slightly smaller in terms of footprint than that which was sold in 2008. At the same time, 

2008 sales volumes were likely significantly lower than sales earlier in the decade due to 

the spike in fuel prices. These projections indicate that the footprint size of the future 

fleet will not rebound in the future. 

Table 1-14 Production Foot Print Mean 

Model Year 

Foot Print Mean 

for 

Car & Truck 

Combined 

Foot Print Mean 

for 

Car 

Foot Print Mean 

for 

Truck 

2008 49 45.4 54.1 

2011 48.9 45 54.8 

2012 48.5 44.9 54.5 

2013 48.5 45 54.7 

2014 48.6 45 55.1 

2015 48.5 45 55.2 

2016 48.4 45 55.2 

Table 1-15 and Table 1-16 below show the changes in engine cylinders over the 

model years. The current assumptions show that engines will be downsized over the 

timing of this rule. The biggest shift occurs between MY 2008 and 2013. This shift is 

caused by the expected changes in class and segment mix as predicted by AEO and CSM, 

and does not represent engine downsizing attributable to the proposed rules. 

Table 1-15 Truck Percentages of 4, 6, 8 Cylinder Engines by Model Year 

Model Percent of Total Sales of 4,6,8 Cylinders Trucks 

2008 2011 2012 2013 2014 2015 2016

All Trucks 8 Cylinders 33.7% 32.3% 30.4% 29.9% 31.7% 32.6% 32.6%

All Trucks 6 Cylinders 55.8% 56.3% 56.8% 57.6% 56.5% 55.4% 55.3%

All Trucks 4 Cylinders 10.5% 11.4% 12.8% 12.4% 11.9% 12.0% 12.1%

Table 1-16 Car Percentages of 4, 6, 8 Cylinder Engines by Model Year 

Model Percent of Total Sales of 4,6,8 Cylinders Cars 

2008 2011 2012 2013 2014 2015 2016

All Cars 8 Cylinders 5.2% 4.1% 3.9% 4.2% 4.3% 4.4% 4.5%

All Cars 6 Cylinders 36.7% 32.8% 32.4% 32.6% 32.6% 32.6% 32.5%

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All Cars 4 Cylinders 58.1% 63.1% 63.7% 63.1% 63.1% 62.9% 63.1%

13.1.21.3.4 How is the development of the baseline fleet for this proposal 

different from NHTSA’s historical approach and why is this approach 

preferable? 

 As described in detail at the opening of this chapter, NHTSA has historically 

based its analysis of potential new CAFE standards on detailed product plans the agency 

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

United States. Although the agency has never compelled manufacturers to submit such 

information, most major manufacturers and some smaller manufacturers have voluntarily 

provided it when requested. 

 As in this and other prior rulemakings, NHTSA has requested extensive and 

detailed information regarding the models that manufacturers plan to offer, as well as 

manufacturers’ estimates of the volume of each model they expect to produce for sale in 

the U.S. NHTSA’s recent requests have sought information regarding a range of 

engineering and planning characteristics for each vehicle model (e.g., fuel economy, 

engine, transmission, physical dimensions, weights and capacities, redesign schedules), 

each engine (e.g., fuel type, fuel delivery, aspiration, valvetrain configuration, valve 

timing, valve lift, power and torque ratings), and each transmission (e.g., type, number of 

gears, logic). 

 The information that manufacturers have provided in response to these requests 

has varied in completeness and detail. Some manufacturers have submitted nearly all of 

the information NHTSA has requested, for most or all of the model years covered by 

NHTSA’s requests, and have closely followed NHTSA’s guidance regarding the 

structure of the information. Other manufacturers have submitted partial information, 

information for only a few model years, and/or information in a structure less amenable 

to analysis. Still other manufacturers have not responded to NHTSA’s requests or have 

responded on occasion, usually with partial information. 

 In recent rulemakings, NHTSA has integrated this information and estimated 

missing information based on a range of public and commercial sources (such as those 

used to develop today’s market forecast). For manufacturers which do not respond, 

NHTSA has estimated fleet composition based on the latest-available CAFE compliance 

data (the same data used as part of the foundation for today’s market forecast). NHTSA 

has then adjusted the size of the fleet based on AEO’s forecast of the light vehicle market 

and normalized manufacturers’ market shares based on the latest-available CAFE 

compliance data. 

 Compared to this approach, the market forecast the agencies have developed for 

this analysis has both advantages and disadvantages. 
The Baseline Vehicle Fleet 

1-27 

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

information sources used to develop today’s market forecast are all either in the public 

domain, available to the public upon request, or available commercially. As a result, 

NHTSA and EPA are able to docket the market inputs actually used in the agencies’ 

respective modeling systems, such that any reviewer may independently repeat and 

review the agencies’ analyses. Previously, although NHTSA provided this type of 

information to manufacturers upon request (e.g., GM requested and received outputs 

specific to GM), NHTSA was otherwise unable to release market inputs and the most 

detailed model outputs (i.e., the outputs containing information regarding specific vehicle 

models) because doing so would violate requirements protecting manufacturers’ 

confidential business information from disclosure.8

 Therefore, this approach provides 

much greater opportunity for the public to replicate and review the agencies’ analyses 

and comment accordingly. 

Another advantage of this market forecast is the agencies’ ability to more fully 

assess the incremental costs and benefits of the proposed standards. In the past two 

years, NHTSA has requested and received three sets of future product plan submissions 

from the automotive companies, most recently this past spring. These submissions are 

intended to be the actual future product plans for the companies. In the most recent 

submission it is clear that many of the firms have been and are clearly planning for future 

CAFE standard increases for model years 2012 and later. This is not surprising, as 

NHTSA’s proposed standards for MY 2011-2015 and the 2007 passage of EISA have 

prompted the companies to expect that there will be increases in the CAFE standards for 

MY 2012 and later, as well as the likelihood of future GHG standards. The results for the 

product plans for many firms show a significant increase in their projected application of 

fuel-saving (and CO2-reducing) technologies by MY 2016. However, for the purposes of 

assessing the costs of the model year 2012-2016 standards, the use of the product plans 

present a difficulty – specifically, how to assess the increased costs of the proposed future 

standards if the companies have already anticipated the future standards, such that the 

costs are now part of the agencies’ baseline. The approach used for this proposal does 

not raise this concern, as the underlying data comes from model year 2008 production. 

On the other hand, manufacturers’ plans for MY 2010 and MY 2011 are less subject to 

this concern, because manufacturers’ expectations regarding these model years were 

informed by knowledge of the MY 2010 and MY 2011 standards. The agencies are 

hopeful that manufacturers will agree to make public their plans for one or both of these 

model years, potentially facilitating the development of a baseline fleet that better 

balances multiple concerns. 

In addition, by developing a baseline fleet from common sources, the agencies 

have been able to avoid some errors—perhaps related to interpretation of requests—that 

have been observed in past responses to NHTSA’s requests. For example, while 

reviewing information submitted to support the March 2009 CAFE final rule, NHTSA 

staff discovered that one manufacturer had misinterpreted instructions regarding the 

specification of vehicle track width, leading to important errors in estimates of vehicle 

footprints. Although the manufacturer resubmitted the information with corrections after 
Draft Joint Technical Support Document 

1-28 

being alerted by the agency, this new approach helps the agencies reduce the potential for 

such errors and inconsistencies by utilizing common data sources and procedures. 

An additional advantage of the approach used for this proposal is a consistent 

projection of the change in fuel economy and CO2 emissions across the various vehicles 

from the application of new technology. In the past, manufacturer product plans would 

include the application of new fuel economy improvement technology for a new or 

improved vehicle model with the resultant estimate from the manufacturer of the fuel 

economy levels for the vehicle. However, manufacturers did not always provide to 

NHTSA detailed analysis which showed how they forecasted what the fuel economy 

performance of the new vehicle was – that is, whether it came from actual test data, from 

vehicle simulation modeling, from best engineering judgment or some other 

methodology. Thus, it was not always possible for NHTSA to review the methodology 

used by the manufacturer, nor was it always possible to review what approach the 

different manufacturers utilized from a consistency perspective. With the approach used 

for this proposal, the baseline market data comes from actual vehicles which have actual 

fuel economy test data, so there is no question what is the basis for the fuel economy or 

CO2 performance of the baseline market data, as it is actual measured data. 

Another advantage of today’s approach is that future market shares are based on a 

forecast of what will occur in the future, rather than on a static value. In the past, 

NHTSA has utilized a constant market share for each model year, based on the most 

recent year available for example from the CAFE compliance data, that is, a forecast of 

the 2011-2015 time frame where company market shares do not change. In the approach 

used today, the forecasts from CSM have been utilized to determine how future market 

shares among the companies may change over time.c

The approach that NHTSA and EPA have taken in developing the market forecast 

does, however, have some disadvantages. Most importantly, it produces a market 

forecast that does not represent some important changes likely to occur in the future. 

Some of the changes not captured by this approach are specific. For example, the 

current market forecast includes some vehicles for which manufacturers have announced 

plans for elimination or drastic production cuts such as the Chevrolet Trailblazer, the 

Chrysler PT Cruiser, the Chrysler Pacifica, the Dodge Magnum, the Ford Crown 

Victoria, the Hummer H2, the Mercury Sable, the Pontiac Grand Prix, and the Pontiac 

G5. These vehicle models appear explicitly in market inputs to NHTSA’s analysis, and 

are among those vehicle models included in the aggregated vehicle types (representative 

vehicles) appearing in market inputs to EPA’s analysis. 

Conversely, the agencies’ market forecast does not include some forthcoming 

vehicle models, such as the Chevrolet Volt, the Chevrolet Camaro, the Ford Fiesta and 

several publicly announced electric vehicles, including the announcements from Nissan. 

Nor does it include several MY 2009 and 2010 vehicles, such as the Honda Insight, the 

 

c The agencies note, however, that CSM or other data could also be applied to product plan data in order to 

adjust market share over time. 
The Baseline Vehicle Fleet 

1-29 

Hyundai Genesis and the Toyota Venza, as the starting point for vehicle definitions was 

MY 2008. Additionally, the market forecast does not account for publicly-announced 

technology introductions, such as Ford’s EcoBoost system, whose product plans specify 

which vehicles and how many are planned to have this technology. Were the agencies to 

rely on manufacturers’ product plans, today’s market forecast would account for not only 

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

publicly. 

The agencies believe that including specific new vehicle models such as the Volt 

or Insight after MY 2008 would most likely have a small impact on the estimates of the 

final technology required to comply with the proposed standards. However, including 

them would make the standards appear to cost less relative to the reference case. First, 

the projections of sales by vehicle segment and manufacturer include these expected new 

vehicle models. Thus, to the extent that these new vehicles are expected to change 

consumer demand, they should be reflected in the reference case. While projecting the 

characteristics of the new vehicles with MY 2008 vehicles, the primary difference 

between the new vehicles and 2008 vehicles in the same vehicle segment is the use of 

additional CO2-reducing/fuel-saving technology. Both the NHTSA and EPA models add 

such technology to facilitate compliance with the proposed standards. Thus, the future 

projections of the vehicle fleet generally shift vehicle designs towards those of these 

newer vehicles. The advantage of the agencies approach is that it helps clarify the costs 

of this proposal, as the cost of all fuel economy improvements beyond those required by 

the MY 2011 CAFE standards are being assigned to the proposal. In some cases, the new 

vehicles being introduced by manufacturers are actually in response to their anticipation 

of this rulemaking. The agencies approach prevents some of these technological 

improvements and their associated cost from being assumed in the baseline. Thus, the 

added technology will not be considered to be free for the purposes of this rule. 

We note that, as a result of these issues, the market file may show sales volumes 

for certain vehicles during MYs 2012-2016 even though they will be discontinued before 

that time frame. Although the agencies recognize that these specific vehicles will be 

discontinued, they are included in the market forecast because they are useful for 

representing successor vehicles that may appear in the rulemaking time frame to replace 

the discontinued vehicles in that market segment. 

Other market changes not captured by today’s approach are broader. For 

example, Chrysler Group LLC has announced plans to offer small- and medium-sized 

cars using Fiat powertrains. The product plan submitted by Chrysler includes vehicles 

that appear to reflect these plans. However, none of these specific vehicle models are 

included in the market forecast the agencies have developed starting with MY 2008 

CAFE compliance data. The product plan submitted by Chrysler is also more optimistic 

with regard to Chrysler’s market share during MYs 2012-2016 than the market forecast 

projected by CSM and used by the agencies today. 

Additionally, some technical information manufacturers that have provided in 

product plans regarding specific vehicle models is, at least as far as NHTSA and EPA 
Draft Joint Technical Support Document 

1-30 

have been able to determine, not available from public or commercial sources. While 

such gaps do not bear significantly on the agencies’ analysis, the diversity of pickup 

configurations necessitated utilizing a sales-weighted average footprint valued for many 

manufacturers’ pickups. Since the modeling only utilizes footprint in order to estimate 

each manufacturer’s CO2 or fuel economy standard and all the other vehicle

characteristics are available for each pickup configuration, this approximation has no 

practical impact on the projected technology or cost associated with compliance with the 

various standards evaluated. The only impact which could arise would be if the relative 

sales of the various pickup configurations changed, or if the agencies were to explore 

standards with a different shape or attribute. This would necessitate recalculating the 

average footprint value in order to maintain accuracy. 

The agencies have carefully considered these advantages and disadvantages of 

using a market forecast derived from public and commercial sources rather than from 

manufacturers’ product plans, and the agencies believe that the advantages outweigh the 

disadvantages for the purpose of proposing standards for model years 2012-2016. 

NHTSA’s inability to release confidential market inputs and corresponding detailed 

outputs from the CAFE model has raised serious concerns among many observers 

regarding the transparency of NHTSA’s analysis, as well as related concerns that the lack 

of transparency might enable manufacturers to provide unrealistic information to try to 

influence NHTSA’s determination of the maximum feasible CAFE levels. While 

NHTSA does not agree with some observers’ assertions that some manufacturers have 

deliberately provided inaccurate or otherwise misleading information, today’s market 

forecast is fully open and transparent, and is therefore not subject to such concerns. 

With respect to the disadvantages, the agencies are hopeful that manufacturers 

will, in the future, agree to make public their plans regarding model years that are very 

near, such as MY 2010 or perhaps MY 2011, so that this information can be incorporated 

into an analysis that is available for public review and comment. In any event, because 

NHTSA and EPA are releasing market inputs used in the agencies’ respective analyses, 

manufacturers, suppliers, and other automobile industry observers and participant can 

submit comments on how these inputs should be improved, as can all other reviewers 

 

d

 A full-size pickup might be offered with various combinations of cab style (e.g., regular, extended, crew) 

and box length (e.g., 51⁄2’, 61⁄2’, 8’) and, therefore, multiple footprint sizes. CAFE compliance data for 

MY2008 data does not contain footprint information, and does not contain information that can be used to 

reliably identify which pickup entries correspond to footprint values estimable from public or commercial 

sources. Therefore, the agencies have used the known production levels of average values to represent all 

variants of a given pickup line (e.g., all variants of the F-150 and the Sierra/Silverado) in order to calculate 

the sales-weighted average footprint value for each pickup family. Again, this has little impact on the 

results of the modeling effort. In the extreme, one single footprint value could be used for every vehicle 

sold by a single manufacturer as long as the fuel economy standard associated with this footprint value 

represented the sales-weighted, harmonic average of the fuel economy standards associated with each 

vehicle’s footprint values. 
The Baseline Vehicle Fleet 

1-31 

13.1.31.3.5 How does manufacturer product plan data factor into the 

baseline used in this proposal? 

In the spring of 2009, many manufacturers submitted product plans in response to 

NHTSA’s recent request that they do so. NHTSA and EPA both have access to these 

plans, and both agencies have reviewed them in detail. A small amount of product plan 

data was used in the development of the baseline. The specific pieces of data are: 

• Wheelbase 

• Track Width Front 

• Track Width Rear 

• EPS (Electric Power Steering) 

• ROLL (Reduced Rolling Resistance) 

• LUB (Advance Lubrication i.e. low weight oil) 

• IACC (Improved Electrical Accessories) 

• Curb Weight 

• GVWR (Gross Vehicle Weight Rating) 

The track widths, wheelbase, curb weight, and GVWR could have been looked up 

on the internet (159 were), but were taken from the product plans when available for 

convenience. To ensure accuracy, a sample from each product plan was used as a check 

against the numbers available from Motortrend.com. These numbers will be published in 

the baseline file since they can be easily looked up on the internet. On the other hand, 

EPS, ROLL, LUB, and IACC are difficult to determine without using manufacturer’s 

product plans. These items will not be published in the baseline file, but the data has 

been aggregated into the agencies’ baseline in the technology effectiveness and cost 

effectiveness for each vehicle in a way that allows the baseline for the model to be 

published without revealing the manufacturers data. 

13.1.4Have the agencies performed any analysis using manufacturer product 

plan data factor?

In addition to performing analysis using the baseline common to both agencies, 

NHTSA has conducted a separate analysis that does make use of these product plans. 

The analysis is documented in the Preliminary Regulatory Impact Analysis (PRIA) 

accompanying NHTSA’s Notice of Proposed Rulemaking (PRIA). However, NHTSA 

performed this separate analysis for purposes of comparison only. NHTSA used the 

publicly available baseline for all analysis related to the development and evaluation of 

the proposed new CAFE standards

Formatted: Bullets and Numbering
Draft Joint Technical Support Document 

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References 

 

1

 CFEIS (Certification Fuel Emissions Information System) Database: CFEIS is an EPA database system. 

2 WardsAuto.com: Used as a source for engine specifications. 

3

 Motortrend.com and Edmunds.com: Used as a source for foot print and vehicle weight data. 

4

Energy Information Administration’s 2009 Annual Energy Outlook.

 

5

CSM World Wide, CSM World Wide is a paid service provider; J.D. Power Automotive Forecasting, J.D. Power 

Automotive Forecasting is a paid service provider.

6

 The baseline Excel file (“2008-2016 Production Summary Data _Definitions Docket 08_27_2009”) is 

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

7

 “CSM North America Sales Forecast Comparison 2Q09 3Q09 For Docket.” 2nd and 3rd quarter 

forecasting results from CSM World Wide (Docket EPA-HQ-OAR-2009-0472). 

8

See 49 CFR Part 512.