Computer Simulation of Light-Duty 

Vehicle Technologies for Greenhouse 

Gas Emission Reduction in the 

2020-2025 Timeframe 
NOTICE

This technical report does not necessarily represent final EPA decisions or 

positions. It is intended to present technical analysis of issues using data 

that are currently available. The purpose in the release of such reports is to 

facilitate the exchange of technical information and to inform the public of 

technical developments.

Assessment and Standards Division

Office of Transportation and Air Quality

U.S. Environmental Protection Agency

Prepared for EPA by

Ricardo, Inc.

and

Systems Research and Applications Corporation (SRA)

EPA Contract No. EP-C-11-007

Work Assignment No. 0-12

Computer Simulation of Light-Duty 

Vehicle Technologies for Greenhouse 

Gas Emission Reduction in the 

2020-2025 Timeframe

EPA-420-R-11-020

December 2011
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COMPUTER SIMULATION OF LIGHT-DUTY VEHICLE TECHNOLOGIES FOR 

GREENHOUSE GAS EMISSION REDUCTION IN THE 2020–2025 TIMEFRAME 

EXECUTIVE SUMMARY

Ricardo, Inc. was subcontracted by Systems Research and Applications Corporation (SRA), a 

wholly owned subsidiary of SRA International, Inc., under contract to the United States 

Environmental Protection Agency (EPA) to assess the effectiveness of future light duty vehicle 

(LDV) technologies on future vehicle performance and greenhouse gas (GHG) emissions in the 

2020–2025 timeframe. GHG emissions are a globally important issue, and the EPA's Office of 

Transportation and Air Quality (OTAQ) has been chartered with examining the GHG emissions 

reduction potential of LDVs, including passenger cars and light-duty trucks. This program was 

performed between October 2009 and November 2011. 

The scope of this project was to execute an independent and objective analytical study of LDV 

technologies likely to be available within the 2020–2025 timeframe, and to develop a data 

visualization tool to allow users to evaluate the effectiveness of LDV technology packages for 

their potential to reduce GHG emissions and their effect on vehicle performance. This study 

assessed the effectiveness of a broad range of technologies including powertrain architecture 

(conventional and hybrid), engine, transmission, and other vehicle attributes such as engine 

displacement, final drive ratio, vehicle weight, and rolling resistance on seven light-duty vehicle 

classes. The methodology used in this program surveyed the broad design space using robust 

physics-based modeling tools and then generated a computationally efficient response surface 

to enable extremely fast surveying of the design space within a data visualization tool. During 

this effort, quality assurance checks were employed to ensure that the simulation results were a 

valid representation of the performance of the vehicle. Through the use of the data visualization 

tool, the users can query the design space on a real time basis while capturing interactions 

between technologies that may not be identified from individual simulations. 

This report documents the work done on the program “Computer Simulation of Light Duty 

Vehicle Technologies for Greenhouse Gas Emission Reduction in the 2020–2025 Timeframe”. 

This work has included identifying and selecting technologies for inclusion in the study, 

developing and validating baseline models, and developing the data visualization tool. 

 
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TABLE OF CONTENTS

1. INTRODUCTION ................................................................................................................... 8 

2. OBJECTIVES ........................................................................................................................ 9 

3. BACKGROUND .................................................................................................................... 9 

3.1 Study Background .......................................................................................................... 9 

3.2 Ground Rules for Study ................................................................................................ 10 

3.3 Technology Package Selection Process ...................................................................... 11 

3.4 Complex Systems Modeling Approach ......................................................................... 12 

3.5 Data Visualization Tool ................................................................................................. 13 

4. TECHNOLOGY REVIEW .................................................................................................... 13 

4.1 Advanced Engine Technologies ................................................................................... 13 

4.1.1 Advanced Valvetrains ............................................................................................ 14 

4.1.1.1 Cam-Profile Switching Valvetrain .......................................................................... 14 

4.1.1.2 Digital Valve Actuation Valvetrain ......................................................................... 14 

4.1.2 Direct Injection Fuel Systems ................................................................................ 17 

4.1.3 Boosting System ................................................................................................... 17 

4.1.4 Other Engine Technologies ................................................................................... 18 

4.2 Engine Configurations .................................................................................................. 19

4.2.1 Stoichiometric DI Turbo ......................................................................................... 19 

4.2.2 Lean-Stoichiometric Switching .............................................................................. 21 

4.2.3 EGR DI Turbo ........................................................................................................ 22 

4.2.4 Atkinson Cycle ....................................................................................................... 23

4.2.5 Advanced Diesel ................................................................................................... 23 

4.2.6 Fueling Map Development Examples .................................................................... 24 

4.2.6.1 EBDI® to EGR DI Turbo ......................................................................................... 24 

4.2.6.2 Contemporary to Future Atkinson ......................................................................... 25 

4.3 Hybrid Technologies ..................................................................................................... 26 

4.3.1 Micro Hybrid: Stop-Start ........................................................................................ 26 

4.3.2 P2 Parallel Hybrid .................................................................................................. 26 

4.3.3 Input Powersplit ..................................................................................................... 27

4.4 Transmission Technologies .......................................................................................... 27 

4.4.1 Automatic Transmission ........................................................................................ 28 

4.4.2 Dual Clutch Transmission (DCT) ........................................................................... 28 

4.4.3 Launch Device: Wet Clutch ................................................................................... 29 

4.4.4 Launch Device: Dry Clutch Advancements ........................................................... 29 

4.4.5 Launch Device: Multi-Damper Torque Converter .................................................. 30 

4.4.6 Shifting Clutch Technology .................................................................................... 30 

4.4.7 Improved Kinematic Design .................................................................................. 30 

4.4.8 Dry Sump .............................................................................................................. 31 

4.4.9 Efficient Components ............................................................................................ 31 

4.4.10 Super Finishing ..................................................................................................... 31

4.4.11 Lubrication ............................................................................................................. 31 

4.5 Vehicle Technologies ................................................................................................... 31
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4.5.1 Intelligent Cooling Systems ................................................................................... 31 

4.5.2 Electric Power Assisted Steering .......................................................................... 32 

5. TECHNOLOGY BUNDLES AND SIMULATION MATRICES ............................................. 32 

5.1 Technology Options Considered ............................................................................... 32 

5.2 Vehicle configurations and technology combinations ............................................... 32 

6. VEHICLE MODEL ............................................................................................................... 35 

6.1 Baseline Conventional Vehicle Models ..................................................................... 35 

6.2 Baseline Hybrid Vehicle Models ............................................................................... 36 

6.3 Engine Models .......................................................................................................... 36

6.3.1 Warm-up Methodology .......................................................................................... 38 

6.3.2 Accessories Models .............................................................................................. 38 

6.4 Transmission Models ................................................................................................ 40 

6.5 Torque Converter Models ......................................................................................... 42 

6.6 Final Drive Differential Model .................................................................................... 42 

6.7 Driver Model .............................................................................................................. 43 

6.8 Hybrid Models ........................................................................................................... 43 

7. MODEL VALIDATION RESULTS ....................................................................................... 47 

7.1 Validation Cases and 2010 Baseline Vehicle Models ............................................... 47 

7.2 Nominal Runs ........................................................................................................... 48

8. COMPLEX SYSTEMS MODEL VALIDATION .................................................................... 48 

8.1 Evaluation of Design Space ...................................................................................... 48 

8.2 Response Surface Modeling ..................................................................................... 50 

9. RESULTS ............................................................................................................................ 50 

9.1 Basic Results of Simulation ...................................................................................... 50 

9.2 Design Space Query ................................................................................................. 50 

9.3 Exploration of the Design Space ............................................................................... 51 

9.4 Identification and Use of the Efficient Frontier .......................................................... 51 

10. RECOMMENDATIONS FOR FURTHER WORK ................................................................ 56 

11. CONCLUSIONS .................................................................................................................. 56 

12. ACKNOWLEDGEMENTS ................................................................................................... 57 

13. REFERENCES .................................................................................................................... 58 

APPENDICES............................................................................................................................. 60 

Appendix 1, Abbreviations .......................................................................................................... 60 

Appendix 2, Assessment of Technology Options ....................................................................... 61 

Appendix 3, Baseline Vehicle Parameters and Runs Results .................................................... 63 

Appendix 4, Output Factors for Study ......................................................................................... 64 

Appendix 5, Nominal Runs Results ............................................................................................ 65 

ATTACHMENT A ....................................................................................................................... 69

 
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LIST OF FIGURES

Figure 3.1: Technology package selection process. ................................................................... 11

Figure 4.1: Honda's VTEC cam profile switching system ........................................................... 15

Figure 4.2: Expected BSFC benefit from CPS system over typical engine operating map. ........ 15

Figure 4.3: INA UniAir digital valve actuation system ................................................................. 16

Figure 4.4: Expected BSFC benefit from DVA system over typical engine operating map. ........ 16

Figure 4.5: General Motors two-stage turbo transient performance ........................................... 18

Figure 4.6: Typical region of fuel enrichment in stoichiometric DI engines, eliminated through 

use of a water-cooled exhaust manifold. .................................................................................... 20

Figure 4.7: 2.0-l General Motors SIDI two-stage boosted engine BSFC map ............................ 21

Figure 4.8: Zone of lean operation for Lean-Stoichiometric DI Turbo engine. ............................ 22

Figure 4.9: BSFC map (in g/kW•h) for EBDI® engine with EGR ................................................. 24

Figure 4.10: BSFC map (in g/kW•h) for Toyota Prius engine ..................................................... 25

Figure 4.11: Comparison of Automatic and DCT Transmission Efficiencies............................... 29

Figure 4.12: Typical transverse wet clutch DCT arrangement .................................................... 30

Figure 6.1: MSC.Easy5 conventional vehicle model. .................................................................. 36

Figure 6.2: Change in BSFC resulting from cylinder heat loss. .................................................. 38

Figure 6.4: Comparison of CVT and optimized DCT gear ratios over drive cycle....................... 41

Figure 6.5: Comparison of shift activity for traditional and optimized shifting strategies. ............ 42

Figure 6.6: 2007 Camry motor-inverter efficiency contour map .................................................. 44

Figure 6.7: High level state flow diagram for the hybrid control strategy. ................................... 44

Figure 6.8: Best BSFC curve superimposed on fueling map. ..................................................... 46

Figure 6.9: Hybrid powertrain energy supervisory strategy. ....................................................... 46

Figure 9.1: Design Space Query screen in Data Visualization Tool. .......................................... 52

Figure 9.2: Design Space Analysis screen in Data Visualization Tool. ....................................... 52

Figure 9.3: Full Size Car Design Space Analysis example ......................................................... 53

Figure 9.4: Full Size Car Design Space Analysis example ......................................................... 53

Figure 9.5: Full Size Car Design Space Analysis example ......................................................... 54

Figure 9.6: Standard Car design space analysis example comparing powertrains with EGR DI 

Turbo engine ............................................................................................................................... 54

Figure 9.7: Full design space example showing all seven vehicle classes using Stoichiometric 

DI Turbo engine and advanced automatic transmission with varying vehicle mass and engine 

displacement. .............................................................................................................................. 55

Figure 9.8: Efficient Frontier screen of Data Visualization Tool with example plot. .................... 55

 
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LIST OF TABLES

Table 5.1: Engine technology package definition. ...................................................................... 33

Table 5.2: Hybrid technology package definition. ....................................................................... 33

Table 5.3: Transmission technology package definition. ............................................................ 33

Table 5.4: Baseline and Conventional Stop-Start vehicle simulation matrix. .............................. 34

Table 5.5: P2 and Input Powersplit hybrid simulation matrix. ..................................................... 34

Table 6.1: Vehicle classes and baseline exemplar vehicles. ...................................................... 36

Table 6.3: Accessory loads for conventional stop-start and P2 hybrids. .................................... 39

Table 6.4: Mechanical cooling fan loads for LDT and LHDT. ..................................................... 39

Table 6.5: Transmission gear ratios for six-speed and eight-speed transmissions. ................... 40

Table 7.1: Validation vehicle fuel economy performance. .......................................................... 47

Table 8.1: Continuous input parameter sweep ranges with conventional powertrain. ................ 49

Table 8.2: Continuous input variable ranges for P2 and Powersplit hybrid powertrains. ............ 49

Table A3.1: Baseline Vehicle Parameters and Runs Results. .................................................... 63

Table A5.1: Nominal Runs Results. ............................................................................................ 66

 
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1. INTRODUCTION 

Ricardo was subcontracted by Systems Research and Applications Corporation (SRA), a wholly 

owned subsidiary of SRA International, Inc., under contract to the United States Environmental 

Protection Agency (EPA) to assess the effectiveness of future light duty vehicle (LDV) 

technologies on future vehicle performance and greenhouse gas (GHG) emissions in the 2020–

2025 timeframe. GHG emissions are a globally important issue, and the EPA's Office of 

Transportation and Air Quality (OTAQ) has been chartered with examining the GHG emissions 

reduction potential of LDVs, including passenger cars and light-duty trucks. 

SRA is a company of over 7,000 staff dedicated to solving complex problems of global 

significance for government organizations serving the civil government, global health, and 

national security markets. SRA’s Air Programs and Climate Change Account works extensively 

with OTAQ and other EPA offices on regulatory and voluntary programs to reduce air pollution 

and address climate change. 

SRA and Ricardo worked closely with the EPA team on nearly every technical and contractual 

issue. 

The team at EPA OTAQ included the following staff members: 

 Matt Brusstar, Director, Advanced Powertrain Center, Testing and Advanced 

Technology Division 

 Jeff Cherry, Staff Engineer, Light Duty Vehicles and Small Engine Center, Assessment 

and Standards Division 

 Ann Chiu, Contract Project Officer, Data Analysis and Information Center, Compliance 

Division 

 Ben Ellies, Staff Engineer, Climate Analysis and Strategies Center, Transportation and 

Climate Division 

 Joe McDonald, Senior Engineer, Fuels Center, Assessment and Standards Division 

In addition to the SRA–Ricardo team working for EPA, other stakeholders for the program 

included the International Council on Clean Transportation (ICCT) and the California Air 

Resources Board (ARB). ICCT contributed funding for the early portion of the study in 

collaboration with ARB. The Advisory Committee provided advice to EPA, and included the 

following representatives from ICCT and ARB: 

 Steven Albu, Assistant Division Chief, ARB 

 Anup Bandivedakar, Senior Researcher, ICCT 

 John German, Senior Fellow and Program Director, ICCT 

 Paul Hughes, Manager, ARB 

Ricardo, Inc., is the US division of Ricardo plc., a global engineering consultancy with nearly 

100 years of specialized engineering expertise and technical experience in engines, 

transmissions, and automotive vehicle research and development. This program was performed 

between October 2009 and November 2011. 

The scope of the program was to execute an independent and objective analytical study of LDV 

technologies likely to be available for volume production in the 2020–2025 timeframe, and to 

develop a data visualization tool to allow users to evaluate the effectiveness of LDV technology 

packages for their potential to reduce GHG emissions. An assessment of the effect of these 

technologies on LDV cost was beyond the scope of this study. 
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This work was done in collaboration with EPA, and the approach included the following: 

 Activities funded by ICCT 

o Identify a large set of future technologies that could improve LDV GHG 

emissions. 

o Assess these technologies for potential benefit and ability to be commercialized 

by the 2020–2025 timeframe. 

o Reduce this large set to the technologies selected for further study in this 

program. 

 Activities funded by EPA: 

o Extrapolate selected technologies to their expected performance and efficiency 

levels in the 2020–2025 timeframe. 

o Conduct detailed simulation of the technologies over a large design space, 

including a range of vehicle classes, powertrain architectures, engine designs, 

and transmission designs, as well as parameters describing these configurations, 

such as engine displacement, final drive ratio, and vehicle rolling resistance. 

o Interpolate the results over the design space using a functional representation of 

the responses to the varied model input factors. 

o Develop a Data Visualization Tool to facilitate interrogation of the simulation 

results over the design space. 

2. OBJECTIVES 

The goal of this technical program has been to objectively evaluate the effectiveness and 

performance of a large LDV design space with powertrain technologies likely to be available in 

the 2020–2025 timeframe, and thereby assess the potential for GHG emissions reduction in 

these future vehicles while also understanding the effects of these technologies on vehicle 

performance. 

3. BACKGROUND 

3.1 Study Background 

The EPA has an interest in improving the environmental performance and efficiency of cars, 

trucks, buses, and transportation systems to protect and improve public health, the 

environment, and quality of life. Additionally, reduction of GHG emissions—emphasizing carbon 

dioxide (CO2)—is an increasing priority of national governments and other policymakers 

worldwide. 

This program builds on the work done earlier by Perrin Quarles Associates (PQA, now part of 

SRA) and Ricardo in 2007–2008 to assess the potential effectiveness of GHG-reducing 

technologies in LDVs in the 2010–2017 timeframe (Ricardo and PQA, 2008). The earlier 

program was also funded by EPA and looked at a series of specific LDV configurations and 

from these assessed the benefits. 

The purpose of this study is to define and evaluate potential technologies that may improve 

GHG emissions in LDVs in the 2020–2025 timeframe. These technologies represent a mixture 

of future mainstream technologies and some emerging technologies for the study timeframe. 

For this program, however, a large design space was comprehensively examined so that 
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broader conclusions could be drawn about these technologies that could lead to benefits to 

GHG emissions reduction. 

3.2 Ground Rules for Study 

Several ground rules for the study were agreed at the beginning of the program to bound the 

design space considered in the study. These ground rules identified content that should be 

included in the study as well as content that should be excluded. 

Some examples of the ground rules include the following items for the technology assessment: 

 Seven vehicle classes will be included, as described below. 

 LDV technologies must have the potential to be commercially deployed in 2020–2025. . 

 Vehicle sizes, particularly footprint and interior space, for each class will be largely 

unchanged from 2010 to 2020–2025. 

 Hybrid vehicles will use an advanced hybrid control strategy, focusing on battery state of 

charge (SOC) management, but not at the expense of drivability. 

 Vehicles will use fuels that are equivalent to either 87 octane pump gasoline or 40 

cetane pump diesel. 

 2020–2025 vehicles will meet future California LEV III requirements for criteria 

pollutants, which are assumed to be equivalent to current SULEV II (or EPA Tier 2 Bin 2) 

levels. 

 Ricardo would be allowed to use Ricardo proprietary data and expertise to assess 

technologies and develop the models, as this allowed the technologies to be assessed 

more comprehensively than if only publicly available data were used. Ricardo 

confidential business information relevant to the execution of the program was shared 

with EPA for the purposes of allowing an external audit of the model inputs developed 

for the program. 

 Due to the multiple designs that manufacturers may realize for any given advanced 

technology, the effect of technologies on overall vehicle mass is not incorporated directly 

in the Easy5 models. Instead, the model makes the overt simplifying assumption that all 

technologies are mass-neutral. The end-user has the flexibility to incorporate their own 

assumptions about mass reduction from advanced technologies when exploring the 

design space with the Data Visualization Tool. 

 Similarly, other road load reductions such as aerodynamic drag and rolling resistance 

reduction were addressed as input variables within the complex systems modeling 

approach. 

Likewise, EPA, along with input from the Advisory Committee agreed for this program that the 

technology assessment should exclude the following: 

 Charge-depleting powertrains, such as plug-in hybrid electric vehicles (PHEV) or battery 

electric vehicles (BEV)1

. 

 Fuel cell power plants for fuel cell-electric vehicles (FCEV). 

 Non-reciprocating internal combustion engines (ICE) or external combustion engines. 

 Manual transmissions and automated manual transmissions (AMT) with a single clutch. 

 Kinetic energy recovery systems (KERS) other than battery systems. 

 

1

 While modeling of vehicles with increased electrification would be beneficial, the highest priority was 

given to vehicle architectures determined most likely to be present in higher volumes during the 2020–

2025 time frame. Due to resource limitations, PHEVs and BEVs were considered outside the scope of 

this study and left as candidates for follow-up modeling work. 
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 Intelligent vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) optimization 

technology. 

 Bottoming cycles, such as organic Rankine cycles, for energy recovery. 

 Vehicle safety systems or structures will not be explicitly modeled for vehicles. A full 

safety analysis of the technologies presented in this report is beyond the scope of this 

study. 

The seven vehicle classes considered in this study are the following, with a currently available 

example vehicle given for each class: 

1. Small (B-class) Car, such as the Toyota Yaris 

2. Standard (D-class) Car, such as the Toyota Camry 

3. Small Multi-Purpose Vehicle (MPV), such as the Saturn Vue 

4. Full Sized Car, such as the Chrysler 300 

5. Large MPV, such as the Dodge Grand Caravan 

6. Light-Duty Truck (LDT), such as the Ford F150 

7. Light Heavy-Duty Truck (LHDT), such as the General Motors HD3500 

3.3 Technology Package Selection Process 

The program team used the process shown in Figure 3.1 to identify the technology options 

listed in Appendix 2, Assessment of Technology Options, to the set described in Chapter 4, 

Technology Review, and integrated into the technology bundles described in Chapter 5, 

Technology Bundles and Simulation Matrices. 

F1Figure 3.1: Technology package selection process.

The program team first developed a comprehensive list of potential technologies shown in 

Appendix 2 that could be in use on vehicles in the study timeframe, 2020–2025. These 

technologies were grouped by subject area, such as transmissions, engines, or vehicle, and 

given to Ricardo subject matter experts (SMEs) for assessment and evaluation. These SME 

assessments were then reviewed with EPA, who also sought input from the Advisory 

Committee. Together, the program team determined which technologies would be included 

once they were evaluated qualitatively against the following criteria for further consideration: 

 Potential of the technology to improve GHG emissions on a tank to wheels basis 

 State of development and commercialization of the technology in the 2020–2025 

timeframe 

 Current (2010) maturity of the technology 

The technology options selected were then put together into technology packages for use in the 

vehicle performance simulations. An additional consideration was how the inclusion of the 

Technology 

Identification

Ricardo 

Subject 

Matter 

Expert 

Assessment

EPA Review 

& 

Technology 

Discussion

Technology 

Package 

Selection
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technology would affect simulation matrices presented in Section 5.2, particularly the effect on 

the overall number of simulations needed. 

3.4 Complex Systems Modeling Approach 

Complex systems modeling (CSM) is an objective, scientific approach that supports high-level 

decision making when there are a large number of factors to consider that influence the 

outcome, as with LDV development for vehicle performance and GHG emissions reduction. 

A vehicle is made up of interrelated components and subsystems, which combined make up a 

system that by definition provides functionality greater than the sum of its parts. An automotive 

system like a vehicle may be defined as a "complex system" based upon the number of 

interrelated, interconnected, and interwoven elements and interfaces requiring a great deal of 

information to specify (Kinnunen, 2006). An important concept associated with complex systems 

is the property of "emergence". In this context it means that there may be collective behavior of 

the components and subsystems along with the system’s response to its environment that are 

not predictable or linear in response to changes to the individual behavior of each part. 

A number of interdisciplinary scientific efforts have led to the development of "complex systems 

theory", which seeks to overcome the limitations of reductionist approaches through the 

development of tools and models that are able to capture emergence and other behavior of 

complex systems (McCarthy, et al., 2000). Supplementing the use of complex systems theory is 

the application of the system engineering process model, which dictates proceeding from the 

general to the detailed—a top down approach—and observes the principle of creation and 

selection of alternatives. These theories and principles have been developed into a 

methodology that utilizes physics-based modeling and simulation in order to enable quantitative 

analysis over a multidimensional design space along with advanced visualization techniques in 

order to understand the results (Biltgen, et al., 2006). Ricardo has incorporated this 

methodology, now referred to as “complex system modeling (CSM) into its consulting practice 

on previous projects (Luskin, 2010). 

In this program, many combinations of technologies were used to generate detailed results that 

were abstracted and made accessible through a Data Visualization Tool described in 

Section 3.5. To be objective, performance metrics were identified by EPA and the Advisory 

Committee; these metrics were outputs of the vehicle performance simulation effort and 

characterize key vehicle attributes. To be scientific, the performance simulations use a physicsbased modeling approach for detailed simulation of the vehicle. 

 

The design of experiments (DoE) approach surveys the design space in a way that extracts the 

maximum information using a limited budget of simulation runs. The purpose of the DoE 

simulation matrix was to efficiently explore a comprehensive potential design space for LDVs in 

the 2020–2025 timeframe. The simulation matrix was designed to generate selected 

performance results over the selected drive cycles, such as fuel consumption or acceleration 

times. 

A statistical analysis was used to correlate variations in the input factors to variations in the 

output factors. Because of the complex nature of the LDV configurations and constituent 

technology packages, a neural network approach was used to quantify the relationships 

between input and output factors over the design space explored in the simulations. The result 

of this analysis was a set of response surface models (RSM) that represent in simplified form 

the complex relationships between the input and output factors in the design space. 
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3.5 Data Visualization Tool 

The Data Visualization Tool allows the user to efficiently assess the effects of various 

combinations of future technologies on GHG emissions and other vehicle performance metrics. 

The tool allows the user to query the RSM and investigate options leading to equivalent GHG 

emissions levels. A separate User Guide for the Data Visualization Tool will be released with the 

tool and will provide more information on how to use the tool to access the results. 

The Data Visualization Tool uses the RSM set generated by the Complex Systems approach to 

represent the vehicle performance simulation results over the design space. These simulations 

cover multiple variations of vehicle configuration, including several combinations of advanced 

powertrain and vehicle technologies in the seven LDV classes. Vehicle configurations with 

unacceptable performance, such as combined fuel economy below a certain threshold or 

acceleration times longer than some benchmark value, can be excluded from further study. 

The tool samples vehicle configurations from a selected subset of the design space by using 

Monte Carlo type capabilities to pick input parameter values from a uniform distribution. Defining 

selected portions of the design space and plotting the results visualizes the effect of these 

parameters on vehicle fuel economy and performance, allowing trade off analysis via 

constraints setting to be performed over a wide design space representing the 2020–2025 

technologies as applied. 

4. TECHNOLOGY REVIEW 

Following the process outlined above in Section 3.3, Technology Package Selection Process, a 

broad list of potential technologies was identified for consideration in the study and then 

narrowed to a subset for inclusion in the study. The technologies in this subset are described in 

this chapter. 

In the study timeframe of 2020–2025, spark-ignited (SI) engines are projected to continue to be 

the dominant powertrain in the U.S. LDV market, especially since the efficiency of SI engines is 

expected to approach the efficiency of compression ignition (CI, or diesel) engines at the 

required 2020–2025 emissions levels. Diesel engines are also included as they are still 

expected to be present in the study timeframe, especially in the heavier vehicle classes. 

The first two sections of this chapter therefore describe the technologies expected to appear in 

future engines generally and in the specific engine configurations considered in the study, 

respectively. The other sections in this chapter describe the transmission and driveline, vehicle, 

and hybrid system technologies that were included in the overall design space of the study. The 

implementation of these technologies in the vehicle performance models is described in 

Chapter 6, Vehicle Model. 

4.1 Advanced Engine Technologies 

The primary challenge for advanced engines in the 2020–2025 timeframe is to reduce GHG 

emissions and maintain performance while meeting increasingly stringent criteria pollutant 

standards. This challenge is expected to be met through a range of improvements, from the 

application of highly-efficient downsized engines through to detailed optimization of components 

and systems. This section describes specific technologies or systems that are expected to be 
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included in future engines, each of which supports the overall goal of reduced GHG emissions 

in future vehicles. Section 4.2, Engine Configurations, describes the complete engine 

technology packages that synthesize the effects of the technologies described here to develop 

the model inputs used. 

4.1.1 Advanced Valvetrains 

Several advances in valvetrain technology are expected to be available in the study timeframe. 

These technologies are expected to apply to engines across the whole set of vehicle classes 

examined in the study. 

Advanced valvetrain systems improve fuel consumption and GHG emissions mainly by reducing 

pumping losses in the engine. The pumping loss mitigation provides larger benefits at part-load 

operation, such as during urban driving. Advanced valvetrains also support engine downsizing, 

which provides fuel consumption benefits across the complete engine operating map. Lastly, 

they can be used to support faster aftertreatment warm-up through varied timing, leading to 

additional, synergistic gains if the faster aftertreatment warm-up creates a benefit to tailpipe-out 

NOx emissions that can be traded off to improve GHG emissions. 

Two advanced valvetrain options, cam-profile switching and digital valve actuation, were 

included in the study and are discussed below. The effects of these valvetrains were integrated 

into the model inputs developed for the complete engine technology packages described in 

Section 4.2. 

4.1.1.1 Cam-Profile Switching Valvetrain 

Cam-profile switching (CPS) systems use a hydraulically-actuated mechanical system to select 

between two or three cam profiles. CPS systems, such as the Honda VTEC, Mitsubishi MIVEC, 

Porsche VarioCam, and Audi Valvelift, have been developed by a number of Japanese and 

European manufacturers. Figure 4.1 shows a diagram of Honda's VTEC CPS system (Honda, 

2011). CPS systems can be designed to improve low-speed torque or to improve fuel economy 

by reducing pumping losses at light load. CPS systems are applicable in all LDV classes. The 

benefit to fuel consumption is expected to range up to 7% at specific part-load operating points, 

as shown in Figure 4.2, and will therefore provide a larger benefit in city driving than in highway 

driving. 

4.1.1.2 Digital Valve Actuation Valvetrain 

Digital valve actuation (DVA) uses a mechanical, hydraulic, or electrical system to actuate the 

valves independently of a camshaft. The full realization of DVA in the study timeframe will be a 

camless DVA system, where there is no mechanical linkage between the engine crank and the 

valves. The engine fueling maps with DVA were assumed to use camless DVA systems, such 

as electrohydraulic or electromagnetic systems. Electropneumatic systems are less mature 

currently, but may yet be available late in the timeframe. An example DVA system in current 

production is the Fiat MultiAir system, which is an electro-hydraulic system (Fiat, 2009), 

although it still uses a camshaft to provide the primary timing for the valve open and valve close 

events. The Schaeffler Group's INA UniAir DVA system is shown in Figure 4.3. The DVA system 

could be implemented to provide flexibility with valve event timing, valve lift profiles, or both. As 

with the CPS systems, the main benefit in GHG emissions is a result of reducing pumping 

losses at part-load operation and lower engine speeds, although the benefits at specific 

operating points can range up to 12% as shown in Figure 4.4. 
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F2Figure 4.1: Honda's VTEC cam profile switching system. (Honda, 2011) 

F3Figure 4.2: Expected BSFC benefit from CPS system over typical engine operating 

map. 

BMEP [bar]

0

2

4

6

8

10

Engine speed [rev/min]

1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000

5

4

3

2

1

0

6

CPS benefit [%]
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F4Figure 4.3: INA UniAir digital valve actuation system. (Schaeffler Group, 2010)

F5Figure 4.4: Expected BSFC benefit from DVA system over typical engine operating 

map. 

BMEP [bar]

0

2

4

6

8

10

Engine speed [rev/min]

1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000

0

2

4

6

8

10

Variable valve-lift (DVA) benefit [%]
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4.1.2 Direct Injection Fuel Systems 

Direct injection (DI) fuel systems are the standard fuel injection system in use on current diesel 

engines. One of the significant changes expected by the 2020–2025 timeframe is a continued 

transition from port fuel injection (PFI) to DI in SI engines as well. For SI engines with DI, the 

fuel is injected directly into the combustion cylinder before being ignited. DI fuel systems inject 

the fuel at a higher pressure than PFI injectors do, and allow the use of multiple injection events 

to support advanced combustion control. SI engines with DI were first introduced in Japan in 

1996, and an increasing number of new SI engines now feature DI. 

 

Using DI improves fuel consumption across the full range of engine operation, including at partload and high-load conditions, with an expected benefit of 2–4%. DI improves fuel economy by 

facilitating a higher compression ratio in the engine, which improves the engine's volumetric and 

thermal efficiency. Although detailed injection control strategies were not specifically modeled, 

the effects of DI fuel systems were integrated into the model inputs developed for the complete 

engine technology packages described in Section 4.2. The program team used their experience 

with research engines and with developing and benchmarking production engines to project that 

spray-guided DI will be the mainstream DI technology in use in the 2020–2025 timeframe, 

supplanting wall guided DI. Spray-guided DI offers the capability to deliver a stratified charge—

where the fuel concentration decreases away from the spark plug—that will facilitate lower GHG 

emissions through unthrottled lean-burn operation. 

For diesel engines, emissions requirements will cause the injection pressures to continue to 

increase to the 2000–2400 bar injection pressure range. These very high injection pressures 

support better combustion and reduced engine-out emissions. In addition, multiple injection 

events will be used to better control the onset and progress of the combustion event in the 

cylinder. 

4.1.3 Boosting System 

Using devices to boost the engine's intake air pressure will increase the torque and power 

available from a given engine displacement. By increasing the boost pressure while decreasing 

engine displacement, the power level is maintained while reducing pumping work in the engine 

by shifting engine operation to higher-load operating points. 

The advanced engines in the 2020–2025 timeframe are expected to have advanced boosting 

systems to increase the pressure of the intake charge up to 3 bar. Various boosting approaches 

are possible, such as superchargers, turbochargers, and electric motor-driven compressors and 

turbines. The appropriate technology for 2020–2025 will need to provide cost-effective 

improvement in performance and efficiency while mitigating turbo lag. Matching a boosting 

system to a particular engine is very important to realize the maximum benefits of this 

technology. For this study, the effects of the boosting system are already incorporated in the 

engine map to produce a reasonably optimized system performance over a wide range of input 

variables. 

Turbocharged engines in the 2020–2025 timeframe are expected to have an advanced boost 

strategy that provides a smooth acceleration feel. The advanced engines with boost systems 

were assumed to have two-stage series sequential turbocharger systems. Turbocharging 

means that there is some risk of the vehicle performance being affected by turbo lag, a delay in 

the torque rise that results from the dynamics of the gas flow through the engine. This effect is 

illustrated in Figure 4.5, which shows the benefits of the two-stage turbo system described by 
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Schmuck-Soldan, et al. (2011), that General Motors had tested against twin-scroll 

turbochargers. Figure 4.5 shows the torque response using net mean effective pressure 

(NMEP), which equals both the difference between the indicated and pumping mean effective 

pressures (IMEP and PMEP, respectively), and the sum of the brake and friction mean effective 

pressures (BMEP and FMEP, respectively). Turbo lag is most significant during hard 

acceleration events, especially when the engine starts at or near its idle speed and load. 

Mitigating turbo lag means carefully choosing the capacities of the high pressure and low 

pressure compressors and turbines and connecting pipes to provide acceptable steady-state 

torque across the engine speed range and an acceptable transient rate of torque rise, often 

expressed as the time required to reach 85% of maximum torque at a given engine speed. 

Modeling turbo lag effects is described later in Section 6.3, Engine Models. 

F6Figure 4.5: General Motors two-stage turbo transient performance. 

(Schmuck-Soldan, et al., 2011)

4.1.4 Other Engine Technologies 

Other engine technologies incorporated into the future engines were further improvements in 

engine friction leading to a global reduction in engine fuel consumption. This friction reduction is 

expected to result from a combination of technology advances, including piston ringpack, bore 

finish, lower-viscosity crankcase lubricants, low-friction coatings, valvetrain components, and 

bearing technology. The details of these improvements in engine friction were not explicitly 

itemized in this study, and were instead treated as a global engine friction reduction. 

Another approach is to optimize the overall engine design, for example, by combining engine 

components to reduce mass and thermal inertia, giving an improved package and faster warmup. Ancillary systems may also be electrified to remove the front engine accessory drive (FEAD) 
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and allow variable accessory performance independent of engine speed. (See, for example, 

Section 4.5.2, Electric Power Assisted Steering.) The combination of components, such as the 

exhaust manifold and cylinder head design, will improve the response time for turbocharging 

and aftertreatment warm-up. Electrification of FEAD components, such as the electrical coolant 

pump, oil pump, or AC compressor, reduces parasitic losses on the engine and allows 

accessory operation to be optimized for the operating point independently of the engine. 

4.2 Engine Configurations 

Several engine configurations were defined using combinations of the advanced engine 

technologies described in Section 4.1 based on an assessment of what would be in mainstream 

use in the 2020–2025 timeframe. Five main types of engines were used in the study, and are 

described in this section. 

The engines considered for the 2020–2025 timeframe were developed using two main methods. 

The first method, used with the boosted SI engines, was to review the reported performance of 

current research engines, and assume that these current research engines would closely 

resemble the production engines of the 2020–2025 timeframe. This method takes current 

research engines and refines them to meet production standards, including manufacturability, 

cost, and durability. The second method, used with the Atkinson cycle SI and the diesel 

engines, was to start from current production engines and then determine a pathway of 

technology improvements over the next 10–15 years that would lead to an appropriate engine 

configuration for the 2020–2025 timeframe. With both methods, current trends in engine design 

and development were extrapolated to obtain an advanced concept performance for the 2020–

2025 timeframe that should be achievable in production volumes. All of the engine fueling maps 

developed accounted for the effects of future criteria pollutant standards, assumed to be 

equivalent to California ARB's SULEV II or to EPA Tier 2 Bin 2. These fueling maps were 

reviewed by EPA and the Advisory Committee to ensure that they were suitable for the study. 

The combinations of technologies encompassed in each advanced engine concept provide 

benefits to the fueling map, or values of brake-specific fuel consumption (BSFC) over the 

operating speed and load ranges of each engine. For these future engines, the BSFC is 

improved by up to 10% from current levels. Many of the future engine concepts have low BSFC 

values over large zones of the engine operating map, with the best BSFC point often at lower 

speeds and part-load conditions. The implementation of these technology packages into the 

vehicle performance models is described in Section 6.3. 

4.2.1 Stoichiometric DI Turbo 

The basic advanced engine configuration is the Stoichiometric DI Turbo SI engine. This 

advanced engine assumes continued use of a stoichiometric air-fuel ratio for simplified 

aftertreatment using a three-way catalyst. The engine modeled has a peak brake mean effective 

pressure (BMEP) of 25–30 bar, which supports significant downsizing compared to current 2010 

engines. This high BMEP level is reached through a combination of engine technologies, 

including advanced valve actuation, such as CPS; spray-guided DI; and advanced boost 

systems, such as series-sequential turbochargers (see Sections 4.1.1, 4.1.2, and 4.1.3, 

respectively). The compression ratio of the engines was set at 10.5:1, which provides a balance 

between fuel consumption and performance. 

Current research engines of this configuration have been developed by several groups. One 

example is the Sabre engine described by Coltman, et al. (2008) and by Turner, et al. (2009). 
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The Sabre engine uses CPS to reduce pumping losses at part-load operation (Turner, et al., 

2009), but only uses single-stage turbocharging with DI in a 1.5 l three-cylinder engine to reach 

20 bar peak BMEP. Lumsden, et al. (2009) at MAHLE Powertrain have also developed a 1.2 l, 

three-cylinder research engine similar to the Stoichiometric DI Turbo SI engine with a peak 

BMEP of 28 bar to support up to 50% downsizing. 

The Stoichiometric DI Turbo engine was assumed to operate with a stoichiometric air-fuel ratio, 

without enrichment, over the complete operating map, even at high-speed, high-load operating 

conditions, which significantly improves the fuel consumption in this part of the operating map 

as shown in Figure 4.6. This change in operation requires design changes to support the higher 

exhaust gas temperatures to ensure protecting the valves, pistons, and exhaust system 

components. For example, the future engine configuration uses a cooled exhaust manifold to 

keep the turbine inlet temperatures below 950°C over the full operating range of the engine to 

mitigate the need for upgraded materials in the exhaust manifold and turbine. This change also 

provides benefits to criteria pollutant emissions, especially over the US06 cycle. 

F7Figure 4.6: Typical region of fuel enrichment in stoichiometric DI engines (shown in 

blue), eliminated through use of a water-cooled exhaust manifold. 

Since the initial conception of the 2020 Stoichiometric DI Turbo, several companies have 

engineered new versions of direct injected turbo engines with fueling maps that closely 

resemble the maps that were synthesized and used in this study. One example is the research 

engine executed by General Motors described by Schmuck-Soldan, et al. (2011), that uses a 

two-stage series sequential boosting system like that envisioned for the Stoichiometric DI Turbo 

engine in a 2.0-l variant of the Ecotec SIDI engine. Presented at the Internationales Wiener 

Motorensymposium, General Motors' engine achieves a maximum BMEP of 26.4 bar. The best 

BSFC island shown in Figure 4.7 is rather large and the zone of best BSFC (up to 105% of the 

minimum BSFC) marked on the map encompasses almost half of the useable engine operating 

range. All of the features described by General Motors are similar to those integrated into the 

Stoichiometric DI Turbo engine concept modeled for this program, and consequently the two 

engines have very comparable fueling maps. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 1000 2000 3000 4000 5000 6000

Normalized Load

Engine Speed (rpm)
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F8Figure 4.7: 2.0-l General Motors SIDI two-stage boosted engine BSFC map. 

(Schmuck-Soldan, et al., 2011) 

4.2.2 Lean-Stoichiometric Switching 

The Lean-Stoichiometric DI Turbo SI engine configuration is similar in all respects to the 

Stoichiometric DI Turbo engine described above in Section 4.2.1, except that it uses a fuel-lean 

air-fuel ratio with λ ≈ 1.5 at moderate speeds and loads, such as those seen on the FTP75 

cycle. Elsewhere, such as on the US06 cycle, the engine switches to stoichiometric operation 

with a three-way catalyst, to avoid exceeding the expected temperature and space velocity 

limits of the lean aftertreatment system. This mixed-mode operation allows the engine to take 

advantage of the efficiency benefits of lean operation while mitigating the technical challenges 

associated with lean-burn emissions control. Figure 4.8 illustrates the zones of lean and 

stoichiometric operation over the engine operating map. 

Fuel lean operation improves fuel consumption by increasing the relative charge volume per unit 

of fuel burned, enabling a higher compression ratio, improved charge mixing and less intake 

throttling. Nevertheless, while lean operation leads to efficient oxidation of unburned 

hydrocarbon and carbon monoxide pollutants in the engine exhaust stream, the presence of 

excess oxygen makes reduction of nitrogen oxides (NOx) more challenging. Therefore, an 

additional emissions control device, such as a lean NOx trap (LNT) or a urea-based selective 

catalytic reduction (SCR) system, would be required to remove NOx from the net oxidizing 

exhaust gas. The program team raised concerns about the effectiveness of these NOx removal 

systems at the high temperatures and exhaust gas flow rates, or space velocities, easily 

reached by SI engines at high engine speed or load, and also about catalyst durability under hot 
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and oxidizing conditions over the vehicle life. These concerns suggest that meeting criteria 

pollutant levels over a drive cycle such as the US06 could be challenging to the expected end of 

life, but advances would be made over the intervening years to make such systems production 

feasible. 

Therefore, the engine switches to stoichiometric operation when the exhaust temperature 

crosses a threshold above which the NOx removal system catalysts would suffer accelerated 

degradation. This transition zone between lean and stoichiometric operation is shown in 

Figure 4.8. At high load conditions, then, the exhaust emissions are treated using typical threeway catalysts. The engine therefore performs exactly like the Stoichiometric DI Turbo engine at 

higher load, but has improved BSFC at lower load because it switches to lean operation. A 

modest fuel consumption penalty is applied over each drive cycle to account for the use of fuel 

or other reducing agent to remove NOx during lean operation. 

F9Figure 4.8: Zone of lean operation for Lean-Stoichiometric DI Turbo engine. 

4.2.3 EGR DI Turbo 

The EGR DI Turbo engine is also similar to the Stoichiometric DI Turbo Engine described in 

Section 4.2.1, except that it uses cooled external exhaust gas recirculation (EGR) to reduce 

intake throttling and to manage combustion knock and exhaust temperatures. The recirculated 

exhaust gas dilutes the air and fuel charge in the cylinder, thereby moderating the temperature 

during combustion and allowing operation without enrichment over a higher range of load and 

speed. Additionally, the EGR mitigates the tendency for engine knock, potentially enabling a 

higher compression ratio, and reduces the need for throttling at low-load operation, thereby 

reducing engine pumping losses. 
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Dual high-pressure and low-pressure EGR loops were assumed for this engine configuration, 

which will require additional components such as EGR valves and a heat exchanger (EGR 

cooler) to manage the EGR flow and temperature. EGR rates of up to 20–25% are feasible with 

this air system (Cruff, et al., 2010; Beazley, 2010). EGR use allows a modest overall 

improvement in fuel consumption across the complete operating map compared to the 

Stoichiometric DI Turbo engine. 

4.2.4 Atkinson Cycle 

The Atkinson cycle is characterized by leaving the intake valves open during the start of the 

compression stroke, which lowers the effective compression ratio of the engine back to that of 

the normal SI engine, but allows for a larger effective expansion ratio. This change in engine 

operation improves fuel consumption, but penalizes torque availability at lower engine speeds. 

For this reason, Atkinson cycle engines are typically used only in hybrid vehicle applications, 

where the electric machine can be used to provide extra torque during launch or other hard 

acceleration events. 

Separate Atkinson cycle engine fueling maps were developed for the 2020–2025 timeframe with 

both CPS and DVA valvetrains. These fueling maps reflect the differing net benefits of the 

valvetrains, including actuation losses. These engines are only used with the P2 parallel and 

Input Powersplit hybrid powertrains described in Section 4.3, Hybrid Technologies. The torque 

curve and fueling map thus generated also reflect the benefits of so-called downspeeding, or a 

lower overall operating speed range, which yields further fuel consumption benefits by reducing 

frictional losses in the engine (Hohenner, 2010). 

4.2.5 Advanced Diesel 

The advanced diesel engines for the 2020–2025 timeframe were developed by starting with 

existing production engines and identifying technology advances that would lead to further 

improvements in fuel consumption. Several of the technologies discussed in Section 4.1, 

Advanced Engine Technologies, are applicable to advanced diesels, including seriessequential, two-stage turbocharging, enhanced EGR and charge air cooling, and CPS. The 

composite effects of these technologies were reflected in the improvements made to existing 

engine fueling maps to derive the advanced diesel engine fueling maps. 

This approach led to different maps being developed for each of the vehicle classes that had 

diesel engines available: the Small Car, Full Size Car, Large MPV, LDT, and LHDT. For 

example, the LHDT engine torque curve and fueling maps were generated by starting with a 

6.6 l diesel engine typical for this class and applying the benefits of improvements in pumping 

losses or friction to the fueling map. Engine displacements for the advanced diesels were 

chosen based on the current torque and power levels available from these engines, the 

expected future requirements, and the effects of applying advanced technologies to support 

further downsizing. Current diesel engines for LDVs already use advanced variable-geometry 

boost systems and high-pressure common-rail direct injection for better torque response and 

specific power. Improvements in these areas are therefore expected to be incremental, by 

contrast with the more extensive changes to SI engine architectures described above. For 

example, the peak BMEP of the advanced diesels is in the 17–23 bar range, which is noticeably 

lower than that expected for the advanced SI engines. 

This difference is, however, consistent with Ricardo's expectation of the pace and direction of 

technology development for diesel engines that comply with the expected emissions 
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requirements defined in the study's ground rules defined in Section 3.2, that is, emissions 

standards consistent with today's California SULEV II or EPA Tier 2 Bin 2 standards. A modest 

fuel consumption penalty was applied to account for the additional fuel required for particulate 

filter regeneration and lean NOx aftertreatment. 

4.2.6 Fueling Map Development Examples 

Examples of each method of developing the advanced engine fueling maps are presented 

below. The first example shows how the EGR DI Turbo engine described in Section 4.2.3 was 

developed, and the second, how the Atkinson engine described in Section 4.2.4 was developed. 

4.2.6.1 EBDI® to EGR DI Turbo 

The EBDI® engine (Cruff, et al., 2010; Beazley, 2010) is a recently-developed research engine 

that incorporates many of the technologies expected in the EGR DI Turbo engine and was 

therefore the starting point for the advanced engine. Adjustments were then made to the EBDI®

engine fueling map to make it representative of a production engine expected in the 2020–2025 

timeframe. 

The current research engine has the fueling map shown in Figure 4.9, where the contours show 

BSFC (in g/kW·h) as a function of engine speed and BMEP and the best BSFC point marked is 

230 g/kW·h at 2000 rpm and 12 bar BMEP. This engine is designed to reach 30 bar BMEP 

running on gasoline and up to 35 bar BMEP on E85. To this end, the EBDI® engine uses a 10:1 

compression ratio and the single-stage turbocharger is sized to reach 2.88 bar boost pressure. 

EGR rates vary from 0% up to 23% during operation. The research engine uses direct injection 

and has variable intake and exhaust cam phasing. 

F10Figure 4.9: BSFC map (in g/kW•h) for EBDI® engine with EGR. (Beazley, 2010) 

BMEP - Observed [kPa]

0

500

1000

1500

2000

2500

3000

Engine Speed [rev/min]

1000 1500 2000 2500 3000 3500 4000 4500 5000

25

283

63 230

450

400

350

300

260

250

245

240

230

220
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To translate this to the 2020–2025 timeframe's EGR DI Turbo engine, the compression ratio 

was increased to 10.5:1, which improves the fuel consumption by approximately 1% across the 

map. The EGR DI Turbo engine also assumes use of an advanced boost system as described 

in Section 4.1.3 instead of a single-stage system. Switching from the current valvetrain to the 

CPS system described in Section 4.1.1.1 will provide up to 7% improvements in the steadystate fueling map, with the best benefits coming at moderate load and low speed as shown in 

Figure 4.2. Lastly, a fuel consumption improvement of 3.5% was applied to account for 

continued application of friction reduction technologies. The final fueling map used in the study 

for the EGR DI Turbo engine is the result of synthesizing these technology improvements into a 

cohesive whole. 

4.2.6.2 Contemporary to Future Atkinson 

In the case of the Atkinson cycle engines, the program team started with a contemporary 

example of the class of engine and translated it into the future by applying technology 

improvements to an existing fueling map. These technology improvements include those 

described in Section 4.1.1, Advanced Valvetrains, and Section 4.1.4, Other Engine 

Technologies. 

F11Figure 4.10: BSFC map (in g/kW•h) for Toyota Prius engine. (Muta, et al., 2004) 

An example of a contemporary Atkinson cycle engine is the Toyota Prius engine as presented 

by Muta, et al. (2004), which uses the fueling map shown in Figure 4.10. To translate the current 

map to the study timeframe, several adjustments were made to the fueling map. First, the 

engine speed range was modified so that the engine would tend to operate at lower speeds, 

which reduces frictional losses in the engine. Additional friction reduction improvements, such 

as those described in Section 4.1.4, Other Engine Technologies, were also applied to the map. 

Furthermore, the Atkinson engines in the design space can use either of the advanced 
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valvetrains, the CPS or DVA, which provides additional benefits to fuel consumption at part-load 

conditions, especially at lower engine speeds as described in Section 4.1.1 and shown in 

Figures 4.2 and 4.4. 

These technologies together have the net effect of improving the best BSFC by about 5%, but 

more importantly, of substantially improving fuel consumption across the map, especially at 

lower-speed and moderate load operating conditions. 

4.3 Hybrid Technologies 

The selection of hybrid technology for a vehicle is complex, comprising a series of engineering 

trade-offs between fuel consumption benefit and system complexity and cost. As the market 

share of hybrid vehicles continues to grow, consumers will have a range of choices. 

A wide range of hybrid configurations were considered in the initial part of the program, with the 

program studying three main approaches: micro hybrid (stop-start), P2 parallel, and Input 

Powersplit. For this study, it was assumed that the hybrid powertrain configurations will be 

studied in all but the LHDT vehicle class as shown in Table 5.2. The implementation of these 

hybrid systems into the vehicle models is described in Section 6.8. 

4.3.1 Micro Hybrid: Stop-Start 

The most basic hybridization method shuts off the engine during idle periods, and typically uses 

an enhanced starter motor and limited use of driver comfort features during engine off, such as 

the radio and some heat but not air conditioning. This approach reduces fuel use over city drive 

cycles by minimizing idling, but provides no benefit for highway driving or when air conditioning 

is requested. 

The stop-start, micro hybrid approach is the lowest-cost hybrid system, and can be implemented 

relatively quickly on most vehicles on the market today. Stop-start systems are already in 

production and the technology is maturing. Further development will lead to increased user 

acceptance, for example, through transparent integration with low impact on vehicle 

performance or noise, vibration, and harshness (NVH) and by implementing new technologies 

to mitigate the effects on cabin cooling (Weissier, 2011). 

The program team has assumed that by the 2020–2025 timeframe, all vehicles with an 

otherwise conventional powertrain will have stop-start functionality implemented. For the vehicle 

models in this study, the starter motor does not provide motive power, but is capable of 

recovering enough energy to offset accessory loads. 

4.3.2 P2 Parallel Hybrid 

The P2 Parallel Hybrid powertrain places an electric machine on the transmission input, 

downstream of the engine clutch. This system allows stop-start, electrical launch, launch assist, 

and regenerative braking functionality. The clutch also allows the engine to be decoupled from 

the rear of the driveline, allowing pure electric propulsion, or electric vehicle (EV) mode 

operation. This wide application of electrical power in a variety of vehicle operating conditions 

facilitates downsizing the engine from that in the comparable conventional vehicle. 

This hybrid powertrain is expected to significantly reduce GHG emissions, especially during city 

driving. Highway driving fuel consumption is expected to improve because the electric machine 
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in the P2 hybrid allows a smaller, more efficient internal combustion engine to be used. This 

smaller engine, however, may limit vehicle performance in situations requiring continuous 

engine power, such as a sustained hill climb. 

 

P2 Parallel hybrids are in limited production currently, including such vehicles as the Hyundai 

Sonata, the Porsche Cayenne, and the Volkswagen Touareg. Prototypes have also been built 

by various companies using existing off-the-shelf components. 

A P2 Parallel Hybrid system can be used with an automatic transmission, automated manual 

transmission (AMT), continuously variable transmission (CVT), or dual clutch transmission 

(DCT). Hellenbroich and Rosenburg (2009) describe a P2 variant with AMT, for example. For 

this program, the P2 Parallel Hybrid powertrain was modeled using the DCT, which has fixed 

gear ratios and no torque converter, as described in Section 4.4.2. 

4.3.3 Input Powersplit 

The simplest Powersplit hybrid configuration replaces the vehicle’s transmission with a single 

planetary gearset and two electrical machines connected to the planetary gearset. The 

planetary gearset splits engine power between the mechanical path and the electrical path to 

achieve a continuously variable transmission. In some Input Powersplit configurations, a second 

planetary gearset is used to speed up one of the electrical machines while retaining the CVT 

functionality. The Toyota Prius and the Ford Hybrid Escape are two examples of Input 

Powersplit hybrid vehicles currently sold in the US. 

With the appropriate electric accessories, the Input Powersplit system allows for EV mode 

operation, as well as stop-start operation, electric launch, launch assist, and regenerative 

braking. In addition, the system allows for engine downsizing to help reduce fuel consumption, 

although the smaller engine may limit vehicle performance in situations requiring continuous 

engine power, such as a sustained hill climb. The Powersplit system provides significant 

improvements in fuel consumption in city driving. During highway cycles, the benefits of 

regenerative braking and engine start-stop are reduced, although the CVT feature of the engine 

helps during the highway cycle as the engine is kept at an efficient operating point. 

4.4 Transmission Technologies 

The U.S. vehicle market is currently dominated by automatic transmissions, with a development 

emphasis on increasing the launch-assist device efficiency and on increasing the number of 

gear ratios to keep the engine operating in regions of high efficiency. Nevertheless, dual clutch 

transmissions (DCT) are expected to be adopted over the next 10 to 15 years because of their 

potential to further improve fuel economy and maintain drivability. CVTs tend to have higher 

friction than DCTs and provide a different driving experience than stepped transmissions. 

Although CVTs are a current production technology, CVTs were not included in the scope of this 

study. The baseline 6-speed transmissions used the same gear ratios as the previous fuel 

economy study by Ricardo and PQA, (2008) to maintain continuity between improvement 

projections. The 6-speed ratios have a total ratio span of 6.05 which is typical of current 6-speed 

transmissions that were designed for fuel economy and performance improvements over their 4-

speed or 5-speed predecessors. The 8-speed ratios offer a first gear ratio that has improved 

launch torque multiplication over the 6-speed and two overdrive ratios that provide lower engine 

rpm than the 6-speed ratios. The gear step progression of the 8-speed transmission is similar to 

current production and provides acceptable drivability, and is shown in Table 6.3. 
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The development of DCT technology is expected to be implemented in the U.S. based on 

experience with European and Japanese applications. Some vehicles with DCTs are entering 

volume production, such as the Ford Fiesta, Ford Focus, and VW Passat. Automatic 

transmissions too are still being developed and refined, with new technologies being 

implemented in luxury vehicles, and then cascaded down to other vehicle classes. Given that 

94% of current U.S. transmissions are automatics, efficiency improvements that mitigate GHG 

emissions are expected to come from the following: 

 Increased gear count from 4–6 currently to 7 or 8 by 2020–2025 

 Improved kinematic design 

 Component efficiency improvement or alternative technologies 

 Launch devices 

 Dry sump technology 

The various base transmission technologies are described, followed by launch device options, 

and, finally, other technologies expected to improve transmission efficiency. The effects of these 

various technologies on transmission efficiency were incorporated into the models as described 

in Section 6.4, Transmission Models. 

4.4.1 Automatic Transmission 

The automatic transmission is hydraulically operated, and uses a fluid coupling or torque 

converter and a set of gearsets to provide a range of gear ratios. Viscous losses in the torque 

converter decrease the efficiency of the automatic transmission. For the study timeframe, it was 

assumed that eight-speed automatic transmissions will be in common use, as this supports 

more efficient operation. The Small Car is an exception, and was assumed to only have enough 

package space to support a six-speed transmission. For the 2020–2025 timeframe, losses in 

advanced automatic transmissions are expected to be about 20–33% lower than the losses in 

current automatic transmissions from the application of the specific technologies described in 

Section 4.4. The overall benefits are compiled from Ricardo's confidential business information 

on transmission systems. Additional benefits will be realized by having more gear ratios 

available to help maintain the engine near its best operating condition. 

4.4.2 Dual Clutch Transmission (DCT) 

The DCT has two separate gearsets operating in tandem, one with even gears and the other, 

odd. As the gear changes, one clutch engages as the other disengages, thereby reducing 

torque interrupt and improving shift quality, making it more like an automatic transmission. The 

DCT, however, does not require a torque converter which improves its efficiency compared to 

an automatic transmission, and may use either wet or dry type launch clutches. For the study 

timeframe, energy losses in both wet clutch and dry clutch DCTs are expected to be 40–50% 

lower than in current automatic transmissions. Additional benefits will be realized by having 

more gear ratios available to help keep the engine near its best operating condition. As with the 

automatic transmission, the Small Car was assumed to only have package space for a sixspeed transmission. An overall comparison of the efficiency of the stepped-gear transmissions 

is shown in Figure 4.11. 
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F12Figure 4.11: Comparison of Automatic and DCT Transmission Efficiencies 

4.4.3 Launch Device: Wet Clutch 

A wet clutch provides torque transmission during operation by means of friction action between 

surfaces wetted by a lubricant. The lubricant is required for cooling during gear shifts when the 

clutch is slipping in larger LDV classes. Wet clutch DCTs provide added durability for the higher 

torque requirements of larger LDVs, although a secondary lubrication system is needed for the 

actuation requirements. As a result, wet clutch systems are expected to be heavier, cost more, 

and be less efficient than dry clutch systems. An example of a wet clutch DCT system is shown 

in Figure 4.12. 

By the 2020–2025 timeframe, wet clutch DCTs are expected to develop into so-called damp 

clutch DCTs, which approach the efficiency of a dry clutch with the longevity and higher torque 

capacity of a wet clutch. In damp clutch DCTs, a limited spray is applied to cool the clutch 

materials. A damp clutch requires a lubrication system but is more efficient due to improved 

control, leading to reduced windage and churning losses. 

4.4.4 Launch Device: Dry Clutch Advancements 

The standard dry clutch requires advanced materials to dissipate heat and prevent slipping. The 

thermal load resulting from engagement prevents dry clutches from being used in high torque 

and heavy duty cycle applications, even though they are more efficient since they significantly 

reduce parasitic shear fluid losses and do not require an additional lubrication system. The GHG 

emissions benefit of a dry clutch over a wet clutch should be realized at launch and during 

transient driving, thus primarily for city driving. Advancements in materials or electric assist 

could enable this technology to be used in larger LDVs and more severe duty cycles by the 

study timeframe, but is generally assumed to be prevalent in the smaller vehicle classes. 
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F13Figure 4.12: Typical transverse wet clutch DCT arrangement. (Ricardo and PQA, 2008)

4.4.5 Launch Device: Multi-Damper Torque Converter 

Dampers added to the torque converter enable a lower lockup speed, therefore decreasing the 

more fuel-intensive period of hydrodynamic power transfer. Multi-damper systems provide 

earlier torque converter clutch engagement; however, drivability and limited ratio coverage have 

limited the deployment of this technology to date. The technology must be integrated during 

transmission design. The GHG emissions benefit should come from reduced slippage and 

smoother shifting. 

4.4.6 Shifting Clutch Technology 

Shift clutch technology improves the thermal capacity of the shifting clutch to reduce plate count 

and lower clutch losses during shifting. Reducing the number of plates for the shifting process 

and reducing the hydraulic cooling requirements will increase the overall transmission efficiency 

for similar drivability characteristics. Technology deployment has been limited by industry 

prioritization of drivability over shift efficiency, especially since shift events are a very small 

portion of typical driving. The technology will be best suited to smaller vehicle segments 

because of reduced drivability expectations—this technology may not be suitable for higher 

torque applications. 

4.4.7 Improved Kinematic Design 

Improved kinematic design uses analysis to improve the design for efficiency by selecting the 

kinematic relationships that optimize the part operational speeds and torques. Large 

improvements in efficiency have been noted for clean sheet designs for six-speed and eightspeed transmissions. This approach will provide a GHG emissions benefit across all vehicle 

classes and operating conditions. 
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4.4.8 Dry Sump 

A dry sump lubrication system provides benefits by keeping the rotating members out of oil, 

which reduces losses due to windage and churning. This approach will provide a GHG 

emissions benefit across all vehicle classes, with the best benefits at higher speeds. 

4.4.9 Efficient Components 

Continuous improvement in seals, bearings and clutches aimed at reducing drag in the system 

should provide GHG emissions benefits without compromising transmission performance. 

4.4.10 Super Finishing 

This technology approach chemically treats internal gearbox parts for improved surface finish. 

The improved surface finish reduces drag which increases efficiency over the full range of 

operation. 

4.4.11 Lubrication 

New developments in base oils and additive packages will reduce oil viscosity while maintaining 

temperature requirements, thereby improving transmission efficiency over the full range of 

operation. 

4.5 Vehicle Technologies 

Several vehicle technologies were also considered for the study to the extent that they help 

support future ranges of vehicle mass, aerodynamic drag, and rolling resistance for each of the 

vehicle classes in the study. The potential levels of improvement for these "road load reduction" 

technologies were not explicitly quantified; rather, they were included as independent input 

variables within the complex systems modeling approach. 

Technologies considered include mass reduction through use of advanced materials with a 

higher strength to mass ratio and through consolidation and optimization of components and 

systems. Aerodynamic drag is expected to see improvements through adoption of both passive 

and active aerodynamic features on vehicles in the 2020–2025 timeframe. Continued 

improvement in tire design is expected to reduce rolling resistance and thereby provide a benefit 

to fuel consumption. 

In addition, vehicle accessory systems such as the cooling pumps and power steering systems 

are expected to become electrified by the 2020–2025 timeframe. These electrified accessories 

should reduce the power required to keep them active, which will also improve fuel 

consumption, and are described in greater detail below. 

4.5.1 Intelligent Cooling Systems 

Intelligent cooling systems use an electric coolant pump to circulate engine coolant, removing 

the power required for this pump from the FEAD. Removing the coolant pump from the FEAD 

also enables independent pump speed control. Rather than running at a fixed multiple of the 

engine speed, the coolant pump can spin at the appropriate speed for the current cooling 

requirements. Standard cooling systems are sized to provide cooling at maximum load and 

ambient conditions, but most vehicles only rarely operate under these extreme conditions. 
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Intelligent cooling also enables quicker warm-up of the engine by controlling coolant flow. This 

reduces engine friction by increasing engine temperature during the warm up process. The 

effects of the cooling system performance were integrated into the vehicle performance model. 

Ricardo estimates this technology will lower fuel consumption over the FTP cycle. BMW is 

implementing this technology on their twin-turbo 3-L inline-6 cylinder engine, introduced in 2007 

in their 335i model. This technology is projected to be readily available by the 2020–2025 

timeframe. 

4.5.2 Electric Power Assisted Steering 

Electric Power Assisted Steering (EPAS) uses either rack or column-drive electric motors to 

assist driver effort instead of a hydraulic power assist system. EPAS replaces the engine-driven 

hydraulic pump, hydraulic hoses, fluid reservoir, fluid, and hydraulic rack. The efficiency of this 

system is a result of reduced FEAD losses and improved energy management that comes from 

decoupling the load from the engine. This technology is currently available for small and 

medium sized passenger vehicles, and it is likely that this will be commercially available for 

LDVs up to the LDT class by the 2020–2025 timeframe. This technology is required for vehicles 

with any electrical launch or EV mobility, so that the vehicle can be steered during EV mode. 

5. TECHNOLOGY BUNDLES AND SIMULATION MATRICES 

The program team and EPA, with input from the Advisory Committee, bundled the technologies 

described in Chapter 4, Technology Review, into a set of technology packages to be evaluated 

in the seven LDV classes described in Section 2.2, Ground Rules for Study. These LDV classes 

are Small Car, Standard Car, Small MPV, Full Size Car, Large MPV, LDT, and LHDT. 

Engineering judgment was used to select technology combinations deemed most appropriate 

for each vehicle class. For example, the larger LDV classes were assumed to have wet clutch 

DCTs to accommodate the higher torques from their engines. 

5.1 Technology Options Considered 

Definitions of the hybrid powertrain, engine, and transmission technology packages are 

presented in Tables 5.1–5.3. The engine technologies are defined in Table 5.1; hybrids, in Table 

5.2; and transmissions, in Table 5.3. Many of the engines in Table 5.1 use some measure of 

internal EGR, but for this table "Yes" means significant EGR flow through an external EGR 

system. All of the advanced transmissions in Table 5.3 include the effects of the transmission 

technologies described in Section 4.4, including dry sump, improved component efficiency, 

improved kinematic design, super finish, and advanced driveline lubricants. 

5.2 Vehicle configurations and technology combinations 

Vehicles were assessed using three basic powertrain configurations: conventional stop-start, P2 

hybrid, and Input Powersplit hybrid. Each vehicle class considered in the study was modeled 

with a set of technology options, as shown in Table 5.4 for the baseline and conventional 

powertrains and Table 5.5 for the hybrid powertrains. Each of the 2020 engines marked for a 

given vehicle class in Table 5.4 was paired with each of the advanced transmissions marked for 

the same vehicle class. Tables 5.4 and 5.5 also show the ranges of the continuous 

parameters—expressed as a percentage of the nominal value—used in the DoE study for the 

conventional and hybrid powertrains, respectively. The ranges were kept purposely broad, to 
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cover the entire span of practical powertrain design options, with some added margin to allow a 

full analysis of parametric trends. 

T1Table 5.1: Engine technology package definition.

 

T2Table 5.2: Hybrid technology package definition.

 Powertrain Configuration 

Function 2010 Baseline Stop-Start P2 Parallel Powersplit 

Engine idle-off No Yes Yes Yes 

Launch assist No No Yes Yes 

Regeneration No No Yes Yes 

EV mode No No Yes Yes 

CVT (Electronic) No No No Yes 

Power steering Belt Electrical Electrical Electrical 

Engine coolant pump Belt Belt Electrical Electrical 

Air conditioning Belt Belt Electrical Electrical 

Brake Standard Standard Blended Blended 

T3Table 5.3: Transmission technology package definition.

Transmission Launch Device Clutch 

Baseline Automatic Torque Converter Hydraulic 

Advanced Automatic Multidamper Control Hydraulic 

Dry clutch DCT None Advanced Dry 

Wet clutch DCT None Advanced Damp 

 

EGR CPS DVA

2010 Baseline NA PFI No No No

Stoich DI Turbo Boost DI No Yes No

Lean-Stoich DI Turbo Boost DI No Yes No

EGR DI Turbo Boost DI Yes Yes No

Atkinson NA DI No Yes Yes

Diesel Boost DI Yes Yes No

Engine

Fuel 

Injection

Air Valvetrain

System
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T4Table 5.4: Baseline and Conventional Stop-Start vehicle simulation matrix. 

TT5Table 5.5: P2 and Input Powersplit hybrid simulation matrix. 

Vehicle Class

 Stoich DI Turbo with CPS Lean DI Turbo with CPS EGR DI Turbo with CPS 2020 Diesel 6-Speed Automatic 6-Speed Dry DCT 8-Speed Automatic 8-Speed Dry DCT 8-Speed Wet DCT

Small Car X X X X X X X

Standard Car X X X X X X

Small MPV X X X X X X

Full Size Car X X X X X X X

Large MPV X X X X X X X

LDT X X X X X X X

LHDT X X X X X X X X

Advanced Engine Advanced Transmission

Baseline Engine & 2010 6-Speed Automatic Trans.2010 Diesel & 2010 6-Speed Automatic Transmission

Parameter

Engine Displacement 50 125

Final Drive Ratio 75 125

Rolling Resistance 70 100

Aerodynamic Drag 70 100

Mass 60 120

DoE Range (%)

Vehicle Class

 P2 Hybrid with 2020 DCT Input Powersplit Stoich DI Turbo with CPS Lean DI Turbo with CPS EGR DI Turbo with CPS Atkinson with CPS Atkinson  with DVA

Small Car X X X X X X X

Standard Car X X X X X X X

Small MPV X X X X X X X

Full Size Car X X X X X X X

Large MPV X X X X X X X

LDT X XXXXX

LHDT

Hybrid Architecture Advanced Engine

Engine Displacement 50 150 50 125

Final Drive Ratio 75 125 75 125

Rolling Resistance 70 100 70 100

Aerodynamic Drag 70 100 70 100

Mass 60 120 60 120

Electric Machine Size 50 300 50 150

P2 Hybrid Powersplit

DoE Range (%)

Parameter
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6. VEHICLE MODEL 

Vehicle models were developed to explore the complete design space defined by the 

technologies, vehicle classes, and powertrain architectures included for the 2020–2025 

timeframe. The modeling process started by developing baseline models to compare against 

data for current (2010) vehicles, as described in Section 6.1, Baseline Conventional Vehicle 

Models, and Section 6.2, Baseline Hybrid Vehicle Models. Specific subsystems were also 

implemented into the simulation package for the study, and these modeling activities are 

described in Sections 6.3–6.8. 

6.1 Baseline Conventional Vehicle Models 

For each of the seven LDV classes considered in this project, vehicle models were developed 

and correlated to a corresponding 2010 exemplar for each LDV class for the purposes of 

establishing a comparison against known vehicle data. A detailed comparison between baseline 

model results and vehicle test data were used to validate the models. These correlation models 

were then modified to form the 2010 baseline models by converting all of them to use a 2010-

level six-speed automatic transmission and stop-start systems. These baseline models, while 

representing an advance from current production vehicles, provide a better basis for comparison 

with the advanced LDVs for the 2020–2025 timeframe. 

The starting point for the vehicle models was to use the existing road-load coefficients from the 

EPA Test Car List, which are represented as the target terms for the chassis dynamometer. 

Known as target A-B-C terms, the coefficients were used to derive the physical properties of 

rolling resistance, linear losses, and aerodynamic drag. These properties were then used in the 

simulation to provide the appropriate load on the vehicle at any given speed. 

A physics-based vehicle and powertrain system model such as the one shown in Figure 6.1 was 

developed and implemented in MSC.Easy5TM. MSC.Easy5TM is a commercially available 

software package widely used in industry for vehicle system analysis, which models the physics 

in the vehicle powertrain during a drive cycle. Examples of vehicle performance simulation using 

MSC.Easy5TM include work by Anderson, et al. (2005) and Fulem, et al. (2006), as well as the 

previous EPA study for 2012–2016 LDV configurations (Ricardo and PQA, 2008). Torque 

reactions are simulated from the engine through the transmission and driveline to the wheels. 

The model reacts to simulated driver inputs to the accelerator or brake pedals, thus enabling the 

actual vehicle acceleration to be determined based on a realistic control strategy. The model is 

divided into a number of subsystem models. Within each subsystem the model determines key 

component outputs such as torque, speeds, and heat rejection, and from these outputs, 

appropriate subsystem efficiencies can be calculated or reviewed as part of a quality audit. 

The seven vehicle classes considered in this study are shown in Table 6.1, along with the 

baseline vehicles for each class. Each of the baseline exemplar vehicle models had vehiclespecific vehicle, engine, and transmission model parameters. The models were exercised over 

the FTP75 and HWFET fuel economy drive cycles, and the results compared with the EPA 

Vehicle Certification Database (Test Car List) fuel economy data for each of the baseline 

exemplar vehicles. 
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F14Figure 6.1: MSC.Easy5 conventional vehicle model.

T6Table 6.1: Vehicle classes and baseline exemplar vehicles. 

Vehicle Class Baseline Exemplar 

Small car Toyota Yaris 

Standard car Toyota Camry 

Small MPV Saturn Vue 

Full sized car Chrysler 300 

Large MPV Dodge Grand Caravan 

LDT Ford F150 

LHDT Chevy Silverado 3500HD 

6.2 Baseline Hybrid Vehicle Models 

For each hybrid technology, Ricardo developed a baseline model to calibrate the hybrid control 

strategy and vehicle, engine, and driveline parameters. As with the conventional vehicles 

described in Section 6.1, a full physical model of each baseline hybrid vehicle was developed 

and implemented in MSC.Easy5TM. The hybrid control algorithms are also implemented in the 

respective MSC.Easy5TM models. The vehicles were modeled using published information from 

various sources and Ricardo proprietary data. 

6.3 Engine Models 

The engines considered in the design space are defined by their torque curve, fueling map, and 

other input parameters. For the 2010 baseline vehicles, the engine fueling maps and related 

parameters were developed for each specific baseline exemplar vehicle. For the engines used 

in the 2020–2025 vehicles, reference engine models were developed, which were then scaled 

to each of the LDV classes. 
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As described in Section 4.2, Engine Configurations, and illustrated in Section 4.2.6, Fueling Map 

Development Examples, the program team used two methods to develop the engine models for 

the 2020–2025 timeframe. The first was to look at the reported performance of current research 

engines, and translate these to the production engines of the 2020–2025 timeframe. With this 

method, current research engines would be refined to meet production standards, including 

manufacturability, cost, and durability. The second method was to start from current production 

engines and then determine a pathway of technology improvements over the next 10–15 years 

that would lead to an appropriate engine configuration for the 2020–2025 timeframe. 

The fueling maps and other engine model parameters used in the study were based on 

published data and Ricardo proprietary data. These initial maps were then developed into a 

map reflecting the effects on overall engine performance of the combination of the future 

technologies considered. Specifically, the effects of the valve actuation system, fueling system, 

anti-knock calibration, and boost system were integrated into the final torque curves and fueling 

maps, therefore subsystem performance maps, such as turbine and compressor efficiency 

maps, are not relevant to this study. 

Each proposed map was then reviewed and approved by EPA and the Advisory Committee. 

This process was repeated for each of the engine technologies included in the simulation 

matrix, as shown in Tables 5.4 and 5.5 for conventional stop-start and hybrid powertrain 

configurations, respectively. 

Engine downsizing effects were captured using a standard engineering method, by changing 

the engine displacement in the given vehicle. This approach assumes that the downsized 

engines have the same brake mean effective pressure (BMEP), which scales the engine's 

delivered torque by the engine swept volume, or displacement. The BSFC of the scaled engine 

map is also adjusted by a factor that accounts for the change in heat loss that comes with 

decreasing the cylinder volume, and thereby increasing the surface to volume ratio of the 

cylinder. These adjustment factors are plotted in Figure 6.2, and are drawn from Ricardo 

proprietary data on the effect of displacement on BSFC. The minimum number of cylinders in an 

engine was set to three, and the minimum per-cylinder volume, to 0.225 liters. These 

constraints then set the minimum engine displacement in the design space to 0.675 liters. 

Engine efficiency is therefore function of engine speed and BMEP, with specific fueling rates 

(mass per unit time) calculated from the torque. Thus, downsizing the engine directly scales the 

delivered torque, and the fueling map is adjusted accordingly. The engine speed range was held 

constant over the engine displacement ranges of interest. 

Turbo lag was represented in the model by applying a first order transfer function between the 

driver power command and the supplied engine power at a given speed. This transfer function 

was only used during the performance cycle, which is a hard acceleration from a full stop used 

to assess vehicle acceleration performance. The transfer function approximates the torque rise 

rate expected in the engines with turbocharger systems during vehicle launch. Adjusting the 

time constant in the transfer function allowed the acceleration performance to see the effect of 

turbo lag. A time constant of 1.5 seconds was selected to represent the expected delay in 

torque rise on the advanced, boosted engines from the spool up of the turbine. Referring back 

to the General Motors 2.0-l SIDI engine, turbo transient performance is also characterized by 

Schmuck-Soldan, et al. (2011), as shown in Figure 4.5. The transient response depicted here 

is in line with the representation used in this study. EPA also reviewed its own engine 

development data and corroborated the 1.5 second time constant. 
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 F15Figure 6.2: Change in BSFC resulting from cylinder heat loss. 

6.3.1 Warm-up Methodology 

A consistent warm-up modeling methodology was developed for the study to account for the 

benefits of an electrical water pump and of warm restart for the advanced vehicles. To account 

for engine warm-up effects, Ricardo used company proprietary data to develop an engine warmup profile. This engine warm-up profile is used to increase the fueling requirements during the 

cold start portion of the FTP75 drive cycle. This correction factor for increased fueling 

requirements is applied to the fuel flow calculated during the warm-up period in the FTP75 drive 

cycle. Section 6.7 provides additional details on how this correction factor was modeled. 

6.3.2 Accessories Models 

Parasitic loads from the alternator were assumed constant over the drive cycles and were 

included in the engine model. Alternator efficiency was assumed to be 55% for baseline vehicle 

simulations. Ricardo suggested a 70% efficient alternator in all of the advanced technology 

package simulations to represent future alternator design improvements. EPA agreed that this 

assumption was consistent with confidential industry projections. 

Power-assisted steering (PAS) systems—full electric or electric hydraulic—were modeled as 

being independent of engine speed and were included in the engine model for each baseline 

vehicle. The EPAS systems assumed no engine parasitic loads on the EPA drive cycles and 

acceleration performance cycles, which require no steering input. All advanced package 

simulations included the benefit of EPAS. The LHDT and LDT classes used electric hydraulic 

PAS, whereas the five smaller vehicle classes used full electric PAS. 

250 300 350 400 450 500 550 600 650

BSFC change (%)

Volume per cylinder 

SI Engine

CI Engine

0
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The LDT and LHDT models also include engine parasitic losses due to a belt-driven engine 

cooling fan. The other vehicles were assumed to have electric radiator fans, with the load being 

drive cycle dependent and added to the vehicle’s base electrical load. These accessory loads 

are shown in Tables 6.3 and 6.4. 

T7Table 6.3: Accessory loads for conventional stop-start and P2 hybrids. 

T8Table 6.4: Mechanical cooling fan loads for LDT and LHDT. 

Current production cars have begun incorporating advanced alternator control to capture 

braking energy through electrical power generation. This is done by running the alternator near 

or at full capacity to apply more load on the engine when the driver demands vehicle 

deceleration. It is believed that this feature will be widespread in the near future and, hence, the 

study captures it by incorporating this function into the Conventional Stop-Start model. As in the 

earlier study (Ricardo and PQA, 2008), the alternator efficiency was increased to 70% to reflect 

an improved efficiency design for 2020 vehicle configurations. The advanced alternator control 

strategy monitors vehicle brake events and captures braking energy when available. The control 

strategy also limits the maximum power capture to 2800 Watts based on the assumption that 

the advanced alternator is limited to 200 Amps at 14 Volts charging for a standard (12V) 

advanced glass-mat battery. By integrating power, energy is accumulated from every brake 

event and when there is available "stored" brake energy, the control strategy switches the 

parasitic draw from the engine to the battery until the accrued energy is consumed, at which 

point the load switches back to the engine. For the five smaller LDV classes, both the fan and 

base electrical loads are included in the advanced charging system as electric fans are 

employed. The system will only benefit the two truck classes, LDT and LHDT, in terms of base 

electrical load as these vehicle classes use mechanical fans. 

Base

FTP 

cooling fan

HWFET 

cooling fan Base

FTP 

cooling fan

HWFET 

cooling fan

Small car 153 127 280 84 70 154

Standard car 153 127 280 84 70 154

Small MPV 153 127 280 84 70 154

Full sized car 153 127 280 84 70 154

Large MPV 153 127 280 84 70 154

LDT 153 * * 84 * *

LHDT 153 ** ** — — —

Vehicle Class

Conventional Accessories (W) P2 Hybrid Accessories (W)

*LDT **LHDT

500 242 290

1000 500 600

2000 1058 1270

2500 1323 1588

6200 3550 4260

Engine Cooling Fan (W)

Speed (rpm)
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6.4 Transmission Models 

The transmission models use a simplified efficiency curve, where the gearbox efficiency is a 

function of gear ratio, as shown in Figure 4.11. Efficiencies for each gear ratio were calculated 

based on data from several transmission and final drive gear tests, were averaged over the 

expected speed and load ranges for the transmission in a given gear, and incorporate hydraulic 

pumping losses. Transmission efficiencies were calculated to represent the average of the 

leading edge for today’s industry and not one particular manufacturer’s design. 

Different efficiency curves were mapped for planetary, automatics, and dual-clutch, with the 

DCT efficiency modified depending on whether a dry or wet clutch is used. Advanced automatic 

transmission designs are projected to reduce losses by 20–33% from current automatic 

transmissions. In addition, the advanced automatic transmissions use advanced torque 

converters, described below in Section 6.5. Wet clutch DCT efficiencies are also projected to 

approach current dry clutch DCT efficiencies. 

The gear ratios chosen for the six and eight speed advanced transmission are taken from 

current production values for gear ratios. These are shown below in Table 6.5. Moreover, 

transmission inertias were adapted from Ricardo proprietary data on contemporary 

transmissions and reflect the effects of the technologies described in Sections 4.4.6–4.4.11. 

T9Table 6.5: Transmission gear ratios for six-speed and eight-speed transmissions. 

In anticipation of future technology packages, it is expected that some advanced level of 

transmission shift optimization will be implemented in year 2020–2025 vehicles. For the 2020–

2025 Conventional Stop-Start architecture, an advanced transmission controller was 

implemented to determine the most favorable gear for a given driver input and vehicle road 

load. This approach takes the place of predefined calibration shift maps based on throttle and 

vehicle speed. 

The advanced transmission shift optimization strategy tries to keep the engine operating near its 

most efficient point for a given power demand. In this way, the new shift controller emulates a 

traditional CVT by selecting the best gear ratio for fuel economy at a given required vehicle 

power level. In conjunction, gear efficiency of the desired gear is also taken into account. More 

often than not, the optimal gear ratio will be in between two of the fixed ratios, and the shift 

optimizer will then decide when to shift up or down based on a tunable shift setting. This will 

enable the shift optimizer to make proper shift decisions based on the type of vehicle and the 

desired aggressiveness of the shift pattern. To protect against operating conditions out of 

normal range, several key parameters were identified, such as maximum engine speed, 

minimum lugging speed, and minimum delay between shifts. For automatic transmissions, the 

8 Spd Advanced 6 Spd Baseline

1 4.700 4.148

2 3.130 2.370

3 2.100 1.556

4 1.670 1.155

5 1.290 0.859

6 1.000 0.686

7 0.840

8 0.670

Gear Ratio
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torque converter is also controlled by the shift optimizer, with full lockup only achievable when 

the transmission is not in first gear. Shift time for all transmissions was kept constant at 0.7 

second duration as the sensitivity of this parameter was not enough to alter fuel economy 

predictions over the EPA drive cycles. Furthermore, torque interrupt during shift is handled 

automatically by the MSC.Easy5TM model component. During development of this strategy, it 

was noted that fuel economy benefits of up to 5% can be obtained when compared to traditional 

shift maps. Figure 6.4 compares the desired gear ratio from a CVT and the comparable DCT 

fixed gear ratio selected by the shift optimizer strategy. 

F16Figure 6.4: Comparison of CVT and optimized DCT gear ratios over drive cycle. 

Analysis of the optimized shift strategy model output data shows no evidence to suggest an 

increase in shift busyness compared to a baseline transmission shift strategy for a given 

gearset. Figure 6.5 shows transmission gear plotted over time for a section of the FTP drive 

cycle for the 2020 Small Car with 6-speed automatic transmission (and stoichiometric DI turbo 

engine) nominal run with optimized shifting, compared to the 2010 Small Car baseline. For the 

complete FTP cycle, the baseline vehicle shifted a total of 238 times, whereas the 2020 vehicle 

with optimized shifting strategy shifted 228 times—in this case, leading to a decrease in shift 

busyness. 

CVT DCT (shift optimizer) 
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F17Figure 6.5: Comparison of shift activity for traditional and optimized shifting 

strategies. 

6.5 Torque Converter Models 

Torque converter characteristics curves for torque ratio and K-factor were generated using 

typical industry standards for efficiency. Each vehicle’s torque converter characteristics for 

torque ratio and K-factor were tailored for the application based on Ricardo experience with 

production systems. Impeller and turbine rotational inertias are also input to the model and were 

estimated based upon Ricardo experience and benchmarking data. Vehicle simulations with 

advanced automatic transmissions include a slight improvement in torque converter efficiency. 

A lockup clutch model was used with all torque converters and was of sufficient capacity to 

prevent clutch slip during all simulation conditions. For the baseline models with six-speed 

automatics, lockup was allowed in fourth, fifth, and sixth gears. During light throttle conditions a 

minimum engine operating speed of 1400 rpm for I3 engines, 1300 rpm for I4 engines, 

1200 rpm for V6 engines, and 1100 rpm for V8 engines with the converter clutch locked was 

considered in developing the baseline lock/unlock maps. The advanced automatic transmission 

applications allow torque converter lockup in any gear except first gear, up to sixth for the Small 

Car or eighth for the other LDV classes. This aggressive lockup strategy minimizes losses in the 

torque converter. 

6.6 Final Drive Differential Model 

Baseline final drive ratios were taken from published information and driveline efficiencies and 

spin losses were estimated based upon Ricardo experience for typical industry differentials. The 

spin losses of the 4-wheel-drive LDT and LHDT front axle and transfer case were included in 

the model to capture the fuel economy and performance of the 4-wheel-drive powertrain 
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operating in 2-wheel-drive mode. This approach is similar to the EPA procedure for emissions 

and fuel economy certification testing. 

6.7 Driver Model 

The vehicle model is forward facing and has a model for the driver. The driver model applies the 

throttle or brake pedal as needed to meet the required speed defined by the vehicle drive cycle 

within the allowed legislative error. This allows the modeling of the actual vehicle response to 

meet the target drive cycle. 

The driver model contains the drive cycle time/velocity trace, controls the throttle and brake 

functions, and maintains vehicle speed to the desired set point. Vehicle simulations for fuel 

economy were conducted over the EPA FTP75 (city), HWFET (highway) and US06 drive cycles. 

The FTP75 cycle consists of three "bags" for a total of 11.041 miles on the conventional 

vehicles and an additional bag 4 on hybrid vehicles for a total of 14.9 miles. A ten minute 

engine-off soak is performed between bags 2 and 3 (after 1372 seconds of testing). A bag 1 

correction factor is applied to the simulated "hot" fuel economy result of the vehicles to 

approximate warm-up conditions of increased engine and driveline friction and sub-optimal 

combustion. The correction factor reduces the fuel economy results of the FTP75 bag 1 portion 

of the drive cycle by 20% on the current baseline vehicles and 10% on 2020–2025 vehicles that 

take advantage of fast warm-up technologies. 

6.8 Hybrid Models 

The hybrid models include all of the conventional vehicle components with the addition or 

replacement of components for electric motor-generators, high voltage battery, high voltage 

battery controller/bus, transmission, regenerative braking and hybrid supervisory controller. Of 

these, the critical systems for the model were the electric machines (motor-generators), power 

electronics, and high-voltage battery system. For each of these systems, current, state of the art 

technologies such as those described in Staunton, et al. (2006) or Burress, et al. (2008) were 

adapted to an advanced, 2020–2025 version of the system. 

Technology improvements applied included decreasing losses in the electric machine and 

power electronics to represent continued improvements in technology and implementation, so 

that a contemporary motor-inverter efficiency map such as that shown in Figure 6.6 would end 

up with higher peak efficiency and a broader island of good efficiency. There are several 

potential sources of losses in both the inverter and the motor, and the program team assumed 

each source would be improved somewhat, leading to an overall 10% reduction in losses in the 

inverter and an overall 25% reduction in losses in the motor. 

As for the battery pack, a ground rule of the study is that the battery pack would use a generic 

lithium ion chemistry representative of what is expected to be in production by the 2020–2025 

timeframe. The assumptions for this future class of batteries include a lower overall internal 

resistance. Likewise, future hybrid vehicles are assumed to use 40% of the overall SOC range 

of the pack, which will reduce the overall battery pack size for a given energy storage 

requirement. The capacity of the battery packs in the model was assumed to be sufficiently 

large that it did not limit the vehicle performance. The electric machines were swept over a 

sufficiently large range such that the design space included configurations where 90% of the 

mechanical braking energy on the US06 to be captured by the hybrid electrical system. The 

electrical system architecture assumes a DC/DC converter between the battery pack and the 

inverter, so the specific pack architecture and voltage are not relevant to the simulation. 
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F18Figure 6.6: 2007 Camry motor-inverter efficiency contour map. (Burress, et al., 2008)

F19Figure 6.7: High level state flow diagram for the hybrid control strategy. 

In addition, a Ricardo proprietary methodology was used to identify the optimum boundaries of 

fuel consumption for a given hybrid powertrain configuration over the drive cycles of interest: 

FTP, HWFET, and US06. The methodology used the drive cycle profile to identify the features 
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and thresholds of a control strategy that could provide fuel consumption over the drive cycle that 

approaches the boundary value. The result of this assessment enabled the development of a 

robust energy management system to control power flow. The simulation results using the 

hybrid controller were then compared against the offline strategy to ensure that the hybrid 

controller in the models is obtaining the most out of the hybrid powertrain. Furthermore, the 

control strategy was designed to allow for a wide range of input parameters while striving for the 

most efficient operation modes. Figure 6.7 illustrates the state flow diagram for the hybrid 

control strategy used as the baseline for the hybrid control algorithm implemented in 

MSC.Easy5TM, as well as the state variables, driver inputs and system parameters that were 

used to define the state transitions. There are six main operation state modes, 

 Idle engine off mode: This mode will shut the engine off and set the throttle command to 

zero. 

 Electric vehicle mode: This mode will leave the engine off and use the throttle command 

from the driver to determine the torque command for the electrical machine. 

 Engine-Vehicle synch mode: This mode will start the engine. 

 Normal driving model: This mode determines the ratio of electrical machine and engine 

power that will be transmitted to the wheel to achieve the desired demand. 

 Idle mode: This mode starts the countdown for idle engine off mode. 

 Regen mode: This mode determines if regenerative braking is possible and how much of the 

requested brake torque will be assigned to foundation brakes and to the electrical machine. 

The following inputs and variables or states should be defined and available within the controller 

in order to full define the state transitions, 

 Driver inputs: throttle and brake pedals 

 Battery State of Charge (SOC) 

 Vehicle speed 

 Engine: power and speed 

 Motor: max power, max torque, speed, and torque/power. 

Because the design space encompasses a large range of engine displacement and motor sizes, 

the input parameters were normalized to take into account these changes and automatically 

adjust the controller thresholds to meet the new demands. Figure 6.8 depicts the engine 

demand curve that targets high efficiency operation. 

A key feature of the hybrid controller is that it used a hybrid load following and load averaging 

strategy to help keep the engine on or near its line of best efficiency on the engine operating 

map with some accommodation for the efficiency of the overall powertrain. If the engine is 

required to be on during low-load conditions, the engine can be made to work harder and more 

efficiently and store the excess energy in the battery. While there have been concerns about the 

effectiveness of a load averaging strategy given the roundtrip efficiency of energy storage and 

retrieval, with the improvements expected in the 2020–2025 timeframe, the engine is likely to be 

a critical factor in the balance of efficiency improvements. In the simulation environment, two 

identical vehicles were analyzed, one with load averaging active and the other, not. The case 

with load averaging showed a slight improvement in fuel consumption over the EPA drive 

cycles. In other cases, the energy in the battery can be used to provide launch assist or EV 

mode driving. All hybrid vehicle simulations were repeated over the drive cycles until the change 

in SOC from start to finish was within 1% of total capacity. Therefore, there is no net 

accumulation or net depletion of energy in the battery, and the fuel consumption value reported 

is an accurate measure of the effectiveness of technologies. Figure 6.9 shows the energy 

supervisory strategy of the hybrid powertrains. 
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F20Figure 6.8: Best BSFC curve superimposed on fueling map.

F21Figure 6.9: Hybrid powertrain energy supervisory strategy. 
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7. MODEL VALIDATION RESULTS 

Before executing the DoE simulation matrix, the vehicle models described in Chapter 6 were 

validated. Baseline exemplar vehicles were modeled, and the simulation results compared 

against publicly available data on vehicle performance, including acceleration times and fuel 

economy. Details of the model validation process and results are presented below. In addition, 

nominal runs were prepared for each major powertrain type to provide a reference point for the 

input parameters against which to compare the full design space explored in the DoE simulation 

matrix. 

7.1 Validation Cases and 2010 Baseline Vehicle Models 

Vehicle models were developed for a 2010 validation case for each of the seven LDV classes. 

Each LDV class was assigned a representative exemplar vehicle for the purposes of 

establishing a baseline against known vehicle data. Ricardo leveraged the peer-reviewed 

validation baseline models from its 2008 study with PQA (now SRA) for the five LDV classes 

from Standard Car through LDT to provide the validation case models, and to build new 

validation case models for the Small Car and LHDT classes. The validation case models are 

based on the corresponding exemplar vehicles listed in Table 6.1, and therefore use automatic 

transmissions and engines with comparable characteristics, including number of gears, peak 

torque, and displacement. 

Vehicle performance simulation results for the validation case models are shown below in 

Table 7.1, comparing the raw fuel economy results in the EPA Test Car List (EPA, 2010) 

against the calculated results. In addition to the fuel economy tests, the launch performance 

was also assessed for each of the exemplar vehicles, with particular attention paid to the 0–60 

mph acceleration time, as this is readily available for validation. 0–60 mph acceleration times for 

the exemplar models were within a few tenths of a second of published times for each vehicle. 

Because production P2 hybrids were not available to provide data in 2010, no direct comparison 

was made. Furthermore, any production hybrid vehicle will be optimized for a specific 

combination of engine, electric machine, and battery, whereas this study used a generic but 

effective controller that allowed the entire design space to be robustly simulated. 

T10Table 7.1: Validation vehicle fuel economy performance.

Following the model validation phase, 2010 baseline vehicles were established. Rather than 

using the validation vehicles and corresponding fuel economy results, a new set of baseline 

values were determined to facilitate a uniform comparison between the advanced (future) 

concepts and today’s current technologies. These new reference 2010 baseline vehicles add an 

efficient alternator and stop-start operation to a common 6-speed automatic transmission, and 

retain the engine maps from the validation case models. Appendix 3 presents the 2010 baseline 

model fuel economy and CO2 output equivalents for all classes of vehicles considered in this 

FTP75 HWFET FTP75 HWFET FTP75 HWFET

Small car 2010 Toyota Yaris 37 48 37 48 -0.8% 0.2%

Standard car 2007 Toyota Camry 27 42 27 42 0.9% -1.0%

Small MPV 2008 Saturn Vue 24 37 25 36 3.9% -2.6%

Full sized car 2007Chrysler 300 21 34 22 33 3.7% -4.6%

Large MPV 2007 Dodge Grand Caravan 20 32 20 29 1.6% -9.1%

LDT 2007 Ford F150 16 23 15 23 -4.1% -0.4%

LHDT 2010 Chevy Silverado 

3500HD (diesel)

— — 13 21 — —

Vehicle Class Baseline Exemplars

EPA Test List (mpg) Simulation Results (mpg) Difference (%)
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study. Note that the CO2 equivalents used in these tables were provided by the EPA as 

9,087 g/gal of fuel for gasoline and 10,097 g/gal for diesel. 

7.2 Nominal Runs 

Once the models were developed and validated, a series of nominal runs were prepared to 

assess the accuracy and robustness of the model. For the conventional vehicles, the nominal 

condition was calculated using the same vehicle parameter values, such as for mass and 

aerodynamic drag, as the 2010 baseline vehicles. The advanced engine size was then adjusted 

to match the baseline 0–60 mph acceleration time, thus defining the nominal displacement for 

each advanced engine. In addition, the nominal condition includes use of a baseline six-speed 

automatic transmission for all LDV classes and implementation of stop-start technology. In this 

way, the nominal condition is placed on a corner of the design space for each LDV class and 

therefore, the nominal conditions serve as the reference point for the design space explored by 

the DoE simulations. 

For the Powersplit and P2 hybrids, the nominal engine size was reduced by 20% from the 

conventional nominal engine size to allow for motor assist to match the aforementioned 0–60 

mph performance metric. The 20% engine displacement reduction for the Powersplit and P2 

hybrids was determined using Ricardo's engineering judgment and an assessment of existing 

hybridization strategy. The nominal electric machine size was then set so that the 0–60 mph 

acceleration time was matched for the hybrid nominal cases. 

It is not possible to provide validation examples of the nominal vehicle models as they represent 

predicted 2020 technology. Also, separate models showing the incremental benefits of 

individual technologies were not studied as steps to the overall advanced packages. However, 

the program team reviewed detailed output data for over one hundred distinct variables at a 10 

Hz sampling rate to confirm that all of the nominal runs reflected reasonable real-world vehicle 

behavior. After the nominal runs passed these quality checks, Ricardo proceeded to the DoE 

simulation phase of the project. 

The full table of nominal runs results for the conventional stop-start, P2 hybrid, and Input 

Powersplit hybrid vehicle combinations is in Appendix 5, and presents the key output factors 

defined in Appendix 4. These summary results and the rest of the simulation output data were 

used to assess the quality of the simulation results before executing the DoE simulation matrix, 

for example, by assessing power flows to and from the battery over the drive cycle. 

8. COMPLEX SYSTEMS MODEL VALIDATION 

Complex systems modeling (CSM) is an objective, scientific approach for evaluating several 

potential options or configurations for benefits relative to each other and to a baseline. For this 

program, the CSM methodology was used to define the design space for LDVs in the 2020–

2025 timeframe, and then to effectively evaluate LDV performance over this large design space. 

8.1 Evaluation of Design Space 

The purpose of the DoE simulation matrix is to efficiently explore the potential design space for 

LDVs in the 2020–2025 timeframe. The simulation matrix was designed to generate selected 

performance results, such as fuel consumption or acceleration times, over selected drive cycles. 
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The DoE approach allows an efficient exploration of the design space while limiting the number 

of runs needed to survey the design space. 

For each discrete combination of vehicle class, powertrain architecture, engine, and 

transmission in the design space, the continuous input variables, including applied road load 

reductions, were varied over the ranges shown in Tables 8.1 and 8.2 for the conventional and 

hybrid powertrains, respectively. These continuous input variable ranges are with respect to the 

nominal value for each LDV class. In the analysis, continuous input variables are evaluated 

using a combination of the design corner points in a two-level full factorial design and design 

points within the space based on a Latin hypercube sampling methodology. Note that vehicle 

mass is considered independently of the combination of discrete technologies; for example, 

switching from an automatic transmission to a DCT does not automatically adjust the vehicle 

mass in the simulation. 

To size the electric machines, hybrid vehicle simulations were performed with the conventional 

vehicle counterparts to assess the overall braking energy over the drive cycles. This knowledge 

was then applied to the hybrid models by sweeping the electric machine sizes over the ranges 

shown in Table 8.2 until the overall regenerative energy equaled or exceeded 90% of the total 

braking energy, excluding the innate vehicle road load losses. 

T11Table 8.1: Continuous input parameter sweep ranges with conventional powertrain. 

T12Table 8.2: Continuous input variable ranges for P2 and Powersplit hybrid powertrains. 

 

Latin hypercube sampling is a statistical method originally developed by McKay et al. (1979), 

used to generate a set of parameter values over a multidimensional parameter space. The 

method randomly samples the multidimensional parameter space in a way that provides 

comprehensive and relatively sparse coverage for best efficiency. It also allows one to efficiently 

continue to fill the multidimensional parameter space by further random sampling. It provides 

more flexibility than traditional multi-level factorial designs for assessing a large parametric 

space with an efficient number of experiments. 

The vehicle simulations were run in batches and the results were collected and processed. 

Vehicle fuel economy and performance metrics were recorded as well as diagnostic variables 

Parameter

Engine Displacement 50 125

Final Drive Ratio 75 125

Rolling Resistance 70 100

Aerodynamic Drag 70 100

Mass 60 120

DoE Range (%)

Engine Displacement 50 150 50 125

Final Drive Ratio 75 125 75 125

Rolling Resistance 70 100 70 100

Aerodynamic Drag 70 100 70 100

Mass 60 120 60 120

Electric Machine Size 50 300 50 150

P2 Hybrid Powersplit

DoE Range (%)

Parameter
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such as the total number of gear shifts and the distance traveled during the drive cycle. The 

data were reviewed using a data mining tool and outliers were analyzed, and, as necessary, 

debugged and re-run. This approach allowed issues to be detected and diagnosed very quickly 

within a large amount of data. Once the data were reviewed and approved, response surface 

models were generated. 

8.2 Response Surface Modeling 

Response surface models (RSM) were generated in the form of neural networks. The goal was 

to achieve low residuals while not over-fitting the data. Initially, 66% of the data were used for 

fitting the model while the remainder was used to validate the response surface model’s 

prediction performance. Once a good fit was found, all the data were used to populate the RSM. 

Each neural network fit contains all of the continuous and discrete variables used in the study 

for a given transmission. One neural network fit per transmission was generated to improve the 

quality of the fits. 

9. RESULTS 

The key project results consist of the raw data sets obtained from over 350,000 individual 

vehicle simulation cases, the Data Visualization Tool developed to query the response surfaces 

based upon the raw data sets, and this report describing these results. These key results are 

discussed below. A separate User Guide for the Data Visualization Tool will be released with 

the tool. 

9.1 Basic Results of Simulation 

Each of the simulation cases generated data at 10 Hz2

 which allowed evaluation of the 

performance of a specific vehicle configuration in the design space over each of the drive 

cycles. These results include parameters such as vehicle speed, calculated engine power, and 

instantaneous fueling rate. The detailed data from each simulation run were then distilled into 

the main output factors of interest, such as acceleration time and fuel economy, that were then 

used in the parametric fit of the RSM. 

For this study, the main output factors include raw fuel economy and GHG emissions over each 

of the drive cycles studied and performance metrics, such as 0–60 mph acceleration times. The 

complete list of output factors is listed in Appendix 4. 

9.2 Design Space Query 

The Design Space Query within the Data Visualization Tool allows the user to assess a specific 

vehicle configuration in the design space by selecting a platform, engine, and transmission and 

then setting the continuous variables within the design space range. The generated 

performance results are then reported in a table that is exportable to Excel. The user can 

assess multiple vehicle configurations and compare them in Excel. The tool table also allows 

the user to apply spreadsheet formulas for quick, on-the-side computation. An example of the 

Design Space Query is shown in Figure 9.1. 

 

2

 To maintain manageable file sizes at an adequate level of fidelity, EPA requested that output files be 

generated at a 10 Hz sampling rate—far slower than the Easy5 process rate—for its own data quality 

checks. 
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9.3 Exploration of the Design Space 

A more comprehensive survey of the design space can be conducted using the Design Space 

Analysis in the Data Visualization Tool, which allows the user to assess the performance of 

multiple vehicle configurations from a significant portion of the design space simultaneously. 

Each design is generated by selecting a vehicle platform, engine, and transmission, and then by 

selecting ranges for the continuous input variables. Figure 9.2 shows the screen where the 

design space analysis is set up. For each of the continuous variables, values are generated 

using a Monte Carlo analysis from a uniform distribution over the range selected. 

Once generated, the results at the design points are stored and may be plotted to visualize the 

effects of varying vehicle parameters over the design space. By carefully building a design and 

varying the parameters, the user can gain an understanding of the effect of each technology 

and the interactions between technologies. Figures 9.3–9.5 show examples of plots that 

compare two design space analyses. In these cases, the red points are for a Full Size Car with 

advanced diesel engine and dry-clutch DCT, whereas the blue points are for a Full Size Car 

with stoichiometric DI turbo engine and automatic transmission. The black point is the 2010 

baseline value. For these examples, the engine displacement was varied from 50% to 125% of 

nominal, or 0.71 to 1.8 l displacement for the stoichiometric DI turbo engine and 1.4 to 3.6 l for 

the diesel, and the vehicle mass, from 70% to 100% of nominal, or 2800 to 4000lb. 

The example in Figure 9.6 compares various configurations of the Standard Car, all with the 

EGR DI Turbo engine but with different powertrains. The two Conventional Stop-Start cases 

have the advanced eight-speed automatic and dry-clutch DCT, shown in blue and gray, 

respectively. The Powersplit hybrid is shown in green, and the P2 Hybrid, in red. Again, the 

black point is the 2010 baseline value. By contrast, the example in Figure 9.7 compares fuel 

economy performance across all seven LDV classes. Here, each LDV class has had its engine 

displacement and vehicle mass varied from the minimum to the maximum of the design space. 

9.4 Identification and Use of the Efficient Frontier 

Part of assessing the selected regions of the design space is to find configurations that balance 

efficiency and performance. The Data Visualization Tool identifies an Efficient Frontier, which is 

the bound of the sampled design space that has the most desirable performance. The user 

must first define a dataset using the Design Space Query, described above in Section 9.2, and 

then select the Efficient Frontier tab in the Data Visualization Tool. An example of the Efficient 

Frontier screen is shown in Figure 9.8. The Efficient Frontier is marked out in red, and the user 

can click on the data points along the frontier to discover the vehicle configurations that lie on 

the frontier. 
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F22Figure 9.1: Design Space Query screen in Data Visualization Tool. 

 

F23Figure 9.2: Design Space Analysis screen in Data Visualization Tool. 
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F24Figure 9.3: Full Size Car Design Space Analysis example. Black point is 2010 baseline; 

red points are for advanced diesel and dry-clutch DCT; blue points, Stoichiometric DI 

Turbo with advanced automatic transmission.

F25Figure 9.4: Full Size Car Design Space Analysis example. Black point is 2010 baseline; 

red points are for advanced diesel and dry-clutch DCT; blue points, Stoichiometric DI 

Turbo with advanced automatic transmission.
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F26Figure 9.5: Full Size Car Design Space Analysis example. Black point is 2010 baseline; 

red points are for advanced diesel and dry-clutch DCT; blue points, Stoichiometric DI 

Turbo with advanced automatic transmission.

F27Figure 9.6: Standard Car design space analysis example comparing powertrains with 

EGR DI Turbo engine. Blue points are with advanced automatic; gray, dry-clutch DCT; 

green, Powersplit; and red, P2 Hybrid. Black point is 2010 baseline. 

0

5

10

15

20

25

30

35

40

45

50

55

60

65

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

Combined FTP-HWFET (mpg)

Engine Displacement (L)

Baseline

Stoich DIT+8AT

Diesel+DCT
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F28Figure 9.7: Full design space example showing all seven vehicle classes using 

Stoichiometric DI Turbo engine and advanced automatic transmission with varying 

vehicle mass and engine displacement. 

F29Figure 9.8: Efficient Frontier screen of Data Visualization Tool with example plot. 

0

10

20

30

40

50

60

70

0 2000 4000 6000 8000 10000 12000

Combined FTP-HWFET (mpg)

Vehicle Mass (lb)

Small Car

Standard Car

Small MPV

Full Size Car

Large MPV

Light Duty Truck

HLDT
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10. RECOMMENDATIONS FOR FURTHER WORK 

Ricardo has the following recommendations for further work on this program: 

 Thoroughly analyze and simulate turbo lag effects in the advanced, boosted engines 

through engine performance simulation tied in with the vehicle models. 

 Run the models over additional drive cycles, such as the NEDC, JC08, or the cold 

ambient FTP, to understand how the technology packages may apply to other global 

regions. 

 Expand the design space to mix 2010 baseline engines and transmissions with the 

advanced technologies to better understand the relative contributions of engine or 

transmission technology to the performance of the advanced vehicles. 

 Include additional engines with different technology packages, such as a version of the 

Stoichiometric DI Turbo engine that has a single, fixed cam profile instead of using the 

CPS valvetrain. 

 Develop correlation models for the P2 and Input Powersplit hybrid powertrains to 

establish a baseline within the simulated design space. 

 Implement a Two-Mode Powersplit hybrid powertrain to assess the benefits of 

hybridization in the larger LDV classes. 

 Study the simulation results to understand main and interaction effects between 

technologies. 

11. CONCLUSIONS 

The following conclusions are supported by this program's results: 

 An independent, objective, and robust analytical study of the effectiveness of selected 

LDV technologies expected to be prevalent in the 2020–2025 timeframe, and their 

effects on vehicle performance has been completed. 

 A comprehensive review process was completed to identify technologies likely to be 

available in the 2020–2025 timeframe and to estimate their future performance given 

current trends and expected developments. 

 The vehicle performance models were based upon the underlying physics of the 

technologies and have been validated with good result to available test data. Quality 

assurance checks have been made throughout the study to ensure accuracy of the 

trends in the results. 

 The Data Visualization Tool allows EPA and other stakeholders to efficiently examine 

the design space developed through the program's complex systems modeling approach 

and to assess trade-offs between various vehicle configurations and their performance. 

The tool provides the necessary functionality to assess specific vehicle designs or more 

comprehensively explore the design space. 

 
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12. ACKNOWLEDGEMENTS 

Ricardo wishes to acknowledge the contributions of the team that supported the technical work 

through the course of the program, which included the following: 

 David Boggs, Technical Specialist 

 Paul Bosker, Program Manager 

 Nick Bouhamdan, Program Manager 

 Felipe Brandao, Technology Leader 

 Anrico Casadei, Senior Project Engineer 

 Mark Christie, Vice President of Engineering Operations 

 Jennifer Durfy, Project Engineer and Subject Matter Expert 

 Josef Fulem, Senior Fuel Cell Product Engineer 

 Keith Gilbert, Project Engineer and Subject Matter Expert 

 Daniel Gross, Project Engineer 

 Tom Gutwald, Innovations Department Manager 

 Stuart Horswill, Chief Engineer and Subject Matter Expert 

 Henry Huang, Project Engineer 

 Neville Jackson, Chief Technology and Innovations Officer 

 Fred Jacquelin, Technical Specialist 

 Carl Jenkins, Product Group Director 

 Angela Johnson, Principal Engineer 

 Neil Johnson, Project Engineer and Subject Matter Expert 

 John Kasab, Chief Engineer 

 Chris Mays, Project Director and Subject Matter Expert 

 Shaun Mepham, Product Group Director 

 Richard Osborne, Chief Engineer and Subject Matter Expert 

 Pascal Reverault, Principal Engineer and Subject Matter Expert 

 Cedric Rouaud, Chief Engineer and Subject Matter Expert 

 Daniel Shepard, Associate Engineer 

 John Stokes, Gasoline Technical Specialist and Subject Matter Expert 

 Qiong Sun, Program Manager 

 Wayne Thelen, Chief Engineer and Subject Matter Expert 

 Marc Wiseman, Principal (Ricardo Strategic Consulting) 

 
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13. REFERENCES 

Anderson, S.R., D.M. Lamberson, T.J. Blohm, and W. Turner, 2005, "Hybrid route vehicle fuel 

economy." SAE Technical Paper 2005-01-1164. 

Beazley, R., 2010, "EBDI® – Application of a high BMEP downsized spark ignited engine". 

Presented at 2010 DEER Conference, Detroit, Mich. 

Biltgen, P., T. Ender, and D. Mavris, 2006, "Development of a collaborative capability-based 

tradeoff environment for complex system architectures. 44th AIAA Aerospace Sciences Meeting 

and Exhibit. AIAA Technical Paper 2006-728 

Burress, T.A., C.L. Coomer, S.L. Campbell, L.E. Seiber, R.H. Staunton, and J.P. Cunningham, 

2008, "Evaluation of the 2007 Toyota Camry Hybrid Synergy Drive System." ORNL technical 

report TM-2007/190. 

Coltman, D., J.W.G. Turner, R. Curtis, D. Blake, B. Holland, R.J. Pearson, A. Arden, and H. 

Nuglisch, 2008, "Project Sabre: A close-spaced direct injection 3-cylinder engine with 

synergistic technologies to achieve low CO2 output." SAE Technical Paper 2008-01-0138. 

Cruff, L., M. Kaiser, S. Krause, R. Harris, U. Krueger, M. Williams, 2010, "EBDI® – Application of 

a fully flexible high BMEP downsized spark ignited engine." SAE Technical Paper 2010-01-

0587. 

Environmental Protection Agency, 2010, "Test Car List Data Files", available from 

www.epa.gov/oms/tcldata.htm. 

Fiat Powertrain Technologies, S.p.A., 2009, "MultiAir: The ultimate air management strategy". 

http://www.fptmultiair.com/flash_multiair_eng/home.htm 

Fulem, J., J.J. Kasab, S. Russell, and C.J. Mitts, 2006, "Advanced computational tools for 

systems engineering of fuel cell powertrains." Presented at Fuel Cell Seminar, Nov. 2006. 

Hellenbroich, G., and V. Rosenburg, 2009, "FEV's new parallel hybrid transmission with single 

dry clutch and electric torque support." Aachener Koloquium Fahrzeug- und Motorentechnik 

2009 18:1209–1222. 

Hohenner, H., 2010, "Current trends on powertrain development – Downsizing and 

downspeeding." 4th CTI Symposium on Automotive Transmissions and Drivetrains – North 

America, Jun 2010. 

Honda Motor Company, 2011, "The VTEC breakthrough: Solving a century-old dilemma". 

http://world.honda.com/automobile-technology/VTEC/ 

Kinnunen, M.J., 2006, Complexity Measures for System Architecture Models. Masters' thesis at 

Massachusetts Institute of Technology. 

Lumsden, G., D. OudeNijeweme, N. Fraser, and H. Blaxill, 2009, "Development of a 

turbocharged direct injection downsizing demonstrator engine". SAE Technical Paper 2009-01-

1503. 
Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020–2025 Timeframe 

29 November 2011 Ricardo, Inc. Page 59 

Luskin, P., 2010, A Systems Engineering Methodology for Fuel Efficiency and its Application to 

a Tactical Wheeled Vehicle Demonstrator. Masters' thesis at Massachusetts Institute of 

Technology. 

McCarthy, I.P., T. Rakotobe-Joel, and G. Frizelle, 2000, "Complex systems theory: Implications 

and promises for manufacturing organizations." Int. J. Manufacturing Technology and 

Management, 2(1-7): 559–579. 

McKay, M.D.; Beckman, R.J.; Conover, W.J., 1979, "A comparison of three methods for 

selecting values of input variables in the analysis of output from a computer code." 

Technometrics 21(2): 239–245. 

“MSC Easy5 Advanced Controls Simulation”, downloaded from 

http://www.mscsoftware.com/Products/CAE-Tools/Easy5.aspx. Last accessed 12 Aug 2011 

Muta, K., Y. Makoto, and J. Tokieda, 2004, "Development of new-generation hybrid system 

THS II – Drastic improvement of power performance and fuel economy." SAE Technical Paper 

2004-01-0064. 

Ricardo and PQA, 2008, A Study of Potential Effectiveness of Carbon Dioxide Reducing Vehicle 

Technologies. EPA Report 420-R-08-004a. 

Schaeffler Group, 2010, "Important Facts About UniAir/MultiAir". 

http://www.ina.de/content.ina.de/en/press/press-releases/press-details.jsp?id=3429505 

Schmuck-Soldan, S., A. Königstein, and F. Westin, 2011, “Two-Stage Boosting of Spark Ignition 

Engines.” Internationales Wiener Motorensymposium 2011 Europe S.r.l., Torino. 

Shaw, J.R., 2009, “Testimony to Joint EPA/NHTSA Hearing on Proposed Rulemaking to 

Establish Light Duty Vehicle Greenhouse Gas Emissions Standards and Corporate Average 

Fuel Economy Standards”. Downloaded from www.autosteel.org last accessed 27 Oct 2009 

Staunton, R.H., C.W. Ayers, L.D. Marlino, J.N. Chiasson, T.A., Burress, 2006, "Evaluation of 

2004 Toyota Prius Hybrid Electric Drive System". ORNL technical report TM-2006/423. 

Turner, J.W.G., R.J. Pearson, R. Curtis, and B. Holland, 2009, "Sabre: A cost-effective engine 

technology combination for high efficiency, high performance and low CO2 emissions." Low 

Carbon Vehicles 2009: Institution of Mechanical Engineers (IMechE) conference proceedings. 

Weissier, P., 2011, "Engine stop-start deployment in U.S. faces challenge from loss of A/C." 

AEI, 5 July 2011, pp. 10–12. 

 
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APPENDICES 

Appendix 1, Abbreviations 

AMT Automated manual transmission 

ARB California Air Resources Board 

BEV Battery electric vehicle 

BMEP Brake mean effective pressure 

BSFC Brake specific fuel consumption 

CI Compression ignition 

CPS Cam profile switching 

CSM Complex systems modeling 

CVT Continuously variable transmission 

DCT Dual clutch transmission 

DI Direct injection 

DoE Design of experiments 

DVA Digital valve actuation 

EGR Exhaust gas recirculation 

EPA United States Environmental 

Protection Agency 

EPAS Electric power assisted steering 

EV Electric vehicle 

FCEV Fuel cell electric vehicle 

FEAD Front end accessory drive 

FIE Fuel injection equipment 

FMEP Friction mean effective pressure 

GHG Greenhouse gas 

ICCT International Council on Clean 

Transportation 

ICE Internal combustion engine 

IMEP Indicated mean effective pressure 

KERS Kinetic energy recovery system 

LDT Light-duty truck 

LDV Light-duty vehicle 

LEV Low emissions vehicle 

LHDT Light heavy-duty truck 

LNT Lean NOx trap 

MPV Multi-purpose vehicle 

NA Naturally aspirated 

NMEP Net mean effective pressure 

NOx Nitrogen oxides 

NVH Noise, vibration, and harshness 

OEM Original equipment manufacturer 

ORNL Oak Ridge National Laboratory 

OTAQ Office of Transportation and Air 

Quality 

PAS Power assisted steering 

PFI Port fuel injection 

PHEV Plug-in hybrid electric vehicle 

PMEP Pumping mean effective pressure 

PQA Perrin Quarles Associates 

RSM Response surface model 

SCR Selective catalytic reduction 

SI Spark ignited 

SME Subject matter expert 

SOC State of charge 

SULEV Super ultra low emissions vehicle 

V2I Vehicle to infrastructure 

V2V Vehicle to vehicle 

VA Valve actuation 

 
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Appendix 2, Assessment of Technology Options 

At the start of the program, Ricardo and EPA, with input from the Advisory Committee, 

developed a comprehensive list of technology options for further consideration by Ricardo's 

Subject Matter Experts. The technologies are listed below. The technologies considered further 

for assessment are in the related document "Assessment of Technology Options" (Ricardo 

reference RD.11/ 342305.1), included as Attachment A. 

Engine technologies considered included the following: 

 Engine downsizing 

 Direct injection 

 Turbocharging 

 Valvetrain technologies and subsystems, including 

o CPS valvetrains 

o DVA or variable valve timing (VVT) valvetrains 

 Stratified charge DI 

 Homogeneous charge compression ignition (HCCI) or controlled auto-ignition (CAI) 

combustion 

 Exhaust energy recovery, including 

o Mechanical turbo-compounding 

o Electrical turbo-compounding 

o Thermoelectric devices 

 Second-generation biofuels 

 Friction reduction technologies 

 Closed-loop combustion control 

 Adjustments to compression ratio 

 Advanced boosting technologies 

 Enhanced EGR and charge air cooling 

 Pre-turbine catalysis 

 Calibration optimization for low GHG emissions 

 Narrow speed range operation 

 Optimization of engines for use with hybrid powertrains 

Engine configurations considered included the following: 

 Stoichiometric DI turbocharged 

 Lean DI turbocharged 

 High-load EGR engines 

 Multi-mode (2 stroke–4 stroke) 

 Engines optimized for hybrid powertrains, including 

o Stop-start powertrains 

o Full hybrid powertrains 

Hybrid powertrain technologies, including 

 Micro hybrid or stop-start system 

 Integrated belt starter-generator (BSG) 

 Integrated crank starter-generator (ISG) or Integrated motor assist (IMA) 

 P2 parallel hybrid powertrain 

 Input Powersplit hybrid powertrain 

 Two-mode Powersplit hybrid powertrain 
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 Series hybrid 

 Parallel hydraulic hybrids 

Transmission technologies, including 

 Advanced automatic transmissions 

 AMTs 

 CVTs 

 DCTs 

 Launch devices 

o Wet clutch 

o Damp clutch 

o Dry clutch 

o Multi-damper torque converter 

o Magnetic clutch 

 Shifting clutch technology 

 Smart kinematic design 

 Dry sump 

 Efficient components 

 Super finishing 

 Lubricant improvements 

Vehicle technologies, including 

 Mass reduction through use of 

o Advanced high strength steels 

o Aluminum alloys 

o Magnesium alloys 

o Plastics and fiber-reinforced composites 

 Mass reduction through component optimization 

 Passive and active aerodynamics improvements 

 Active aerodynamics systems 

 Thermoelectric generators 

 HVAC system load reduction 

 Tire rolling resistance 

 Intelligent cooling systems 

 Electric PAS 

 
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Appendix 3, Baseline Vehicle Parameters and Runs Results 

T13Table A3.1: Baseline Vehicle Parameters and Runs Results. Vehicle Class Representative Vehicle Engine Peak Torque Output (N-m) Transmission ETW (lb) GCW (lb) Other Technologies EPA City FE, CO2 Equivalent (mpg, g/mile) EPA Highway FE, CO2 Equivalent (mpg, g/mile) EPA Combined FE, CO2 Equivalent (mpg, g/mile) Small Car Yaris 1.5L I4 DOHC 4V 145 6 Speed Auto 2,625 N/A 70% Eff. Alt w/Regen, Stop-Start 39.8, 228.3 48.7, 186.6 43.4, 209.5 Standard Car Camry 2.4L I4 DOHC 4V 219 6 Speed Auto 3,625 N/A 70% Eff. Alt w/Regen, Stop-Start 30.0, 302.9 43.5, 208.9 34.9, 260.6 Full Size Car 300 3.5L V6 SOHC 4V 335 6 Speed Auto 4,000 N/A 70% Eff. Alt w/Regen, Stop-Start 23.8, 381.8 33.7, 269.6 27.4, 331.3 Small MPV Vue 2.4L I4 DOHC 4V 219 6 Speed Auto 4,000 N/A 70% Eff. Alt w/Regen, Stop-Start 27.0, 336.6 36.1, 251.7 30.5, 298.4 Large MPV Caravan 3.8L V6 OHV 2V 319 6 Speed Auto 4,250 N/A 70% Eff. Alt w/Regen, Stop-Start 22.0, 413.0 30.7, 296.0 25.2, 360.4 Light-Duty Truck F150 5.4L V8 SOHC 3V 495 6 Speed Auto 4,500 N/A 70% Eff. Alt w/Regen, Stop-Start 16.2, 560.9 22.6, 402.1 18.6, 489.4 Light Heavy-Duty Truck 3500HD 6.0L V8 OHV 2V 515 6 Speed Auto 6,000 15,800 70% Eff. Alt w/Regen, Stop-Start 11.2, 811.3 15.1, 601.8 12.7, 717.0

Light Heavy-Duty Truck 3500HD 6.6L V8 OHV 4v 895 6 Speed Auto 9,000 21,200 70% Eff. Alt w/Regen, Stop-Start 15.6, 647.2 19.0, 531.4 17.0, 595.1

Baseline Vehicles

Vehicle Class Baseline Exemplars ETW (lb) Mass (kg) Cd·A (m2

)

Tire RR 

Coeff

Wheel velocity 

coeff (N·s)

Tire rolling 

radius (m)

Wheel inertia 

(kg·m2

)

Roadload Power 

at 50 mph (hp)

Small car 2010 Toyota Yaris 2625 1191 0.736 0.0094 0.100 0.282 0.90 10.8Standard car 2007 Toyota Camry 3625 1644 0.690 0.0082 0.137 0.320 0.91 11.3

Small MPV 2008 Saturn Vue 4000 1814 0.925 0.0069 0.400 0.340 0.97 15.1Full sized car 2007Chrysler 300 4000 1814 0.792 0.0113 0.205 0.342 0.97 14.8

Large MPV 2007 Dodge Grand Caravan 4500 2041 0.952 0.0072 0.400 0.330 0.94 15.8

LDT 2007 Ford F150 6000 2722 1.341 0.0081 0.580 0.382 1.00 22.9LHDT 2010 Chevy Silverado 

3500HD (diesel)

9000 4082 1.394 0.0083 1.192 0.374 1.05 31.1
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Appendix 4, Output Factors for Study 

Raw fuel economy in miles per US gallon and GHG emissions in grams of CO2 per mile over 

 FTP75 

 HWFET 

 US06 

 HWFET and FTP combined 

Acceleration performance metrics, including 

 0–10 mph acceleration time 

 0–30 mph acceleration time 

 0–50 mph acceleration time 

 0–60 mph acceleration time 

 0–70 mph acceleration time 

 30–50 mph acceleration time 

 50–70 mph acceleration time 

 Top speed at 5% grade 

 Top speed at 10% grade 

 Velocity at 1.3 sec 

 Velocity at 3.0 sec 

 Distance at 1.3 sec 

 Distance at 3.0 sec 

 Maximum grade at 70 mph at GCW 

 Maximum grade at 60 mph at GCVW (LDT and LHDT only) 

 
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Appendix 5, Nominal Runs Results 

The table lists the baseline (2010) vehicles first, followed by results by vehicle class. The P2 

Hybrids have an electric machine size listed, and all use the DCT. There were no Conventional 

Stop-Start nominal runs that used the DCT. For the Input Powersplit hybrids, only the traction 

motor size is listed, as the generator size is a function of the engine and traction motor sizes. 

Abbreviations used exclusively in the following table of Nominal Runs Results include the 

following: 

Baseline The 2010 baseline engine for the given vehicle class 

Stoich DIT Stoichiometric DI Turbo engine 

Lean DIT Lean-Stoichiometric DI Turbo engine 

EGR DIT EGR DI Turbo engine 

Adv Diesel Advanced (2020) diesel 

Atk CS Atkinson cycle engine with CPS 

Atk DVA Atkinson cycle engine with DVA 

AT6 Six-speed automatic transmission (baseline or advanced, as appropriate) 

AT8 Eight-speed automatic transmission (advanced only) 

DCT Dry or wet clutch DCT, per simulation matrix. 

PS Powersplit planetary gearset 

 
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T14Table A5.1: Nominal Runs Results. 

 Engine Vehicle Class Type Displ (L) FTP75 HWFET US06 0-10mph 0-30mph 0-50mph 0-60mph 0-70mph 30-50mph 50-70mph 5% Grade 10% Grade 60 mph 70 mph 1.3 sec 3 sec 1.3 sec 3 sec Small Car Baseline 1.5 145 — AT6 39.8 48.7 30.3 1.4 4.0 7.4 9.9 13.0 3.4 5.6 94.6 82.2 — 10 2.6 14.7 9.3 22.8 Standard Car Baseline 2.4 219 — AT6 30.0 43.5 29.1 1.0 3.1 6.3 8.3 11.4 3.2 5.1 110.4 86.7 — 15 3.9 20.5 14.1 29.5 Full Size Car Baseline 3.5 335 — AT6 23.8 33.7 23.6 1.2 3.2 6.1 7.7 9.5 2.9 3.4 127.5 99.6 — 33 3.2 19.3 12.0 29.2 Small MPV Baseline 2.4 219 — AT6 27.0 36.1 24.1 1.1 3.4 6.8 9.0 12.6 3.4 5.8 97.9 85.1 — 13 3.3 18.4 12.5 26.9 Large MPV Baseline 3.8 319 — AT6 22.0 30.7 21.0 1.1 2.9 6.1 8.6 11.5 3.2 5.4 95.7 82.2 — 16 3.4 20.4 12.9 31.2 LDT Baseline 5.4 495 — AT6 16.2 22.6 15.1 1.1 3.1 6.0 8.2 10.8 2.9 4.8 101.4 88.3 20 — 3.4 19.9 12.6 29.8 LHDT Base SI 6.0 515 — AT6 11.2 15.1 9.8 1.0 3.1 6.9 9.9 13.3 3.8 6.4 92.8 69.8 15 — 3.7 20.7 14.2 29.9 LHDT Base Diesel 6.6 895 — AT6 15.6 19.0 12.3 1.0 3.0 6.7 9.4 13.1 3.7 6.4 99.3 79.3 17 — 4.0 21.3 14.7 30.4 Small Car Stoich DIT 0.74 157 — AT6 53.2 55.1 32.4 1.5 4.0 7.4 10.0 13.1 3.4 5.7 96.2 79.3 — 14 2.4 14.1 8.8 22.3 Small Car Lean DIT 0.74 157 — AT6 55.1 56.0 32.6 1.5 4.0 7.4 10.0 13.1 3.4 5.7 96.2 79.3 — 14 2.4 14.1 8.8 22.3 Small Car EGR DIT 0.74 157 — AT6 55.1 57.4 33.9 1.5 4.0 7.4 10.0 13.1 3.4 5.7 96.2 79.3 — 14 2.4 14.1 8.8 22.3 Small Car Adv Diesel 1.23 221 — AT6 55.8 59.4 41.5 1.2 3.7 7.3 9.8 13.2 3.6 5.9 94.0 76.0 — 13 3.2 16.8 10.9 25.1 Small Car Atk CS 1.66 138 14 DCT6 70.8 59.0 38.1 1.4 3.7 7.5 10.0 13.6 3.8 6.1 85.4 62.1 — 8 2.5 15.5 9.8 24.4

Small Car Atk DVA 1.66 138 14 DCT6 71.7 60.5 39.4 1.4 3.7 7.5 10.0 13.6 3.8 6.1 85.4 62.1 — 8 2.5 15.5 9.8 24.4Small Car Stoich DIT 0.59 124 14 DCT6 68.2 57.3 37.0 1.4 3.8 7.2 9.6 12.6 3.4 5.4 87.5 70.7 — 10 2.4 15.1 9.4 23.6Small Car Lean DIT 0.59 124 14 DCT6 68.4 57.7 37.3 1.4 3.8 7.2 9.6 12.6 3.4 5.4 87.5 70.7 — 10 2.4 15.1 9.4 23.6Small Car EGR DIT 0.59 124 14 DCT6 70.2 59.9 39.0 1.4 3.8 7.2 9.6 12.6 3.4 5.4 87.5 70.7 — 10 2.4 15.1 9.4 23.6Small Car Atk CS 1.66 138 40 PS 64.2 59.5 38.0 1.8 4.7 7.9 9.8 12.2 3.2 4.3 93.5 77.4 — 8 1.5 11.1 6.7 18.5Small Car Atk DVA 1.66 138 40 PS 67.3 60.0 39.0 1.8 4.7 7.9 9.8 12.1 3.2 4.2 93.5 77.9 — 8 1.5 11.1 6.7 18.5Small Car Stoich DIT 0.59 124 40 PS 64.7 57.2 35.2 1.9 4.8 8.2 10.4 13.1 3.4 4.9 89.5 71.3 — 8 1.5 10.8 6.5 18.1Small Car Lean DIT 0.59 124 40 PS 65.8 57.4 35.2 1.9 4.8 8.2 10.4 13.1 3.4 4.9 89.1 71.3 — 8 1.5 10.8 6.5 18.1Small Car EGR DIT 0.59 124 40 PS 67.7 60.1 36.7 1.9 4.8 8.2 10.4 13.1 3.4 4.9 89.1 71.3 — 8 1.5 10.8 6.5 18.1

Standard Car Stoich DIT 1.04 220 — AT8 44.8 54.5 32.5 1.0 3.1 6.2 8.5 11.4 3.1 5.2 107.7 86.2 — 15 3.7 20.7 14.0 29.7Standard Car Lean DIT 1.04 220 — AT8 46.6 55.5 32.8 1.0 3.1 6.2 8.5 11.4 3.1 5.2 107.7 86.2 — 15 3.7 20.7 14.0 29.7

Standard Car EGR DIT 1.04 220 — AT8 46.4 56.7 34.0 1.0 3.1 6.2 8.5 11.4 3.1 5.2 107.7 86.2 — 15 3.7 20.7 14.0 29.7Standard Car Atk CS 2.40 200 24 DCT8 64.6 59.7 39.8 1.2 3.4 6.5 8.6 11.4 3.1 4.9 101.3 78.4 — 11 2.8 17.4 11.0 27.3Standard Car Atk DVA 2.40 200 24 DCT8 65.9 61.0 40.5 1.2 3.4 6.5 8.6 11.4 3.1 4.9 101.3 78.4 — 11 2.8 17.4 11.0 27.3Standard Car Stoich DIT 0.83 176 24 DCT8 61.9 57.2 36.9 1.3 3.6 6.5 8.6 11.3 2.9 4.8 98.1 77.4 — 12 2.6 16.6 10.5 25.8Standard Car Lean DIT 0.83 176 24 DCT8 62.9 58.0 36.7 1.3 3.6 6.5 8.6 11.3 2.9 4.8 98.1 77.4 — 12 2.6 16.6 10.5 25.8Standard Car EGR DIT 0.83 176 24 DCT8 65.1 59.7 38.4 1.3 3.6 6.5 8.6 11.3 2.9 4.8 98.1 77.4 — 12 2.6 16.6 10.5 25.8Standard Car Atk CS 2.40 200 80 PS 53.3 51.7 36.8 1.4 3.6 6.2 8.0 10.2 2.6 4.0 105.2 85.5 — 10 2.2 15.2 9.3 25.1Standard Car Atk DVA 2.40 200 80 PS 56.4 53.3 37.6 1.4 3.6 6.2 8.0 10.2 2.6 4.0 105.2 85.8 — 10 2.2 15.2 9.3 25.1Standard Car Stoich DIT 0.83 176 80 PS 55.6 51.7 35.4 1.5 3.7 6.6 8.7 11.3 2.9 4.7 99.0 78.1 — 10 2.1 14.9 9.1 24.4Standard Car Lean DIT 0.83 176 80 PS 57.9 53.5 36.0 1.5 3.7 6.6 8.7 11.3 2.9 4.7 99.0 78.1 — 10 2.1 14.9 9.1 24.4Standard Car EGR DIT 0.83 176 80 PS 58.0 54.8 37.1 1.5 3.7 6.6 8.7 11.3 2.9 4.7 99.0 78.1 — 10 2.1 14.9 9.1 24.4

Small MPV Stoich DIT 1.13 239 — AT8 38.8 42.6 25.7 1.2 3.3 6.5 8.9 12.0 3.2 5.5 99.8 81.2 — 14 3.1 18.7 11.6 28.3Small MPV Lean DIT 1.13 239 — AT8 40.3 43.1 25.9 1.2 3.3 6.5 8.9 12.0 3.2 5.5 99.8 81.2 — 14 3.1 18.7 11.6 28.3Small MPV EGR DIT 1.13 239 — AT8 40.3 44.4 27.0 1.2 3.3 6.5 8.9 12.0 3.2 5.5 99.8 81.2 — 14 3.1 18.7 11.6 28.3Small MPV Atk CS 2.60 217 20 DCT8 52.9 45.5 29.6 1.4 3.7 7.1 9.3 12.6 3.4 5.5 91.3 76.7 — 10 2.3 15.4 9.4 25.1Small MPV Atk DVA 2.60 217 20 DCT8 54.1 46.8 30.3 1.4 3.7 7.1 9.3 12.6 3.4 5.5 91.3 76.7 — 10 2.3 15.4 9.5 25.1Small MPV Stoich DIT 0.90 190 20 DCT8 50.1 44.2 28.5 1.5 3.9 7.0 9.4 12.3 3.1 5.3 90.6 72.7 — 11 2.1 14.6 8.9 23.7Small MPV Lean DIT 0.90 190 20 DCT8 50.8 44.5 28.5 1.5 3.9 7.0 9.4 12.3 3.1 5.3 90.6 72.7 — 11 2.1 14.6 8.9 23.7Small MPV EGR DIT 0.90 190 20 DCT8 52.0 46.1 29.8 1.5 3.9 7.0 9.4 12.3 3.1 5.3 90.6 72.7 — 11 2.1 14.6 8.9 23.7Small MPV Atk CS 2.60 217 70 PS 44.3 39.6 25.1 1.9 4.6 7.4 9.1 11.1 2.8 3.7 98.3 81.4 — 9 1.4 10.5 6.1 18.0Small MPV Atk DVA 2.60 217 70 PS 49.3 42.3 28.6 1.9 4.6 7.4 9.1 11.1 2.8 3.7 98.3 81.6 — 9 1.4 10.5 6.1 18.0Small MPV Stoich DIT 0.90 190 70 PS 49.1 42.2 27.4 1.9 4.7 8.0 10.3 13.1 3.3 5.1 92.2 73.3 — 8 1.4 10.4 6.1 17.7Small MPV Lean DIT 0.90 190 70 PS 50.8 42.7 27.3 1.9 4.7 8.0 10.3 13.2 3.3 5.2 92.2 73.3 — 8 1.4 10.4 6.1 17.7Small MPV EGR DIT 0.90 190 70 PS 51.3 44.9 28.8 1.9 4.7 8.0 10.3 13.2 3.3 5.2 92.2 73.3 — 8 1.4 10.4 6.1 17.7

Velocity (mph) at Distance (m) in Top Speed (mph) on Max grade at Acceleration times (s) Raw fuel economy (mpg) Peak Trq 

(N.m)

EM Pwr 

(kW)

Transmission
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 Engine Vehicle Class Type Displ (L) FTP75 HWFET US06 0-10mph 0-30mph 0-50mph 0-60mph 0-70mph 30-50mph 50-70mph 5% Grade 10% Grade 60 mph 70 mph 1.3 sec 3 sec 1.3 sec 3 sec Full Size Car Stoich DIT 1.41 298 — AT8 37.1 43.2 27.2 1.2 3.0 5.7 7.4 9.8 2.7 4.1 116.1 95.8 — 20 3.2 19.7 12.1 30.7 Full Size Car Lean DIT 1.41 298 — AT8 38.8 44.0 27.6 1.2 3.0 5.7 7.4 9.8 2.7 4.1 116.1 95.8 — 20 3.2 19.7 12.1 30.7 Full Size Car EGR DIT 1.41 298 — AT8 38.6 44.9 28.5 1.2 3.0 5.7 7.4 9.8 2.7 4.1 116.1 95.8 — 20 3.2 19.7 12.1 30.7 Full Size Car Adv Diesel 2.85 503 — AT8 38.2 46.5 32.5 1.1 2.9 5.6 7.5 9.8 2.7 4.2 113.7 94.9 — 19 3.5 20.2 12.4 31.1 Full Size Car Atk CS 3.80 317 28 DCT8 49.9 46.2 31.5 1.2 3.0 5.5 7.1 9.0 2.5 3.5 113.4 87.9 — 22 2.8 18.6 11.4 30.1 Full Size Car Atk DVA 3.80 317 28 DCT8 51.1 47.4 31.9 1.2 3.0 5.5 7.1 9.0 2.5 3.5 113.4 87.9 — 22 2.8 18.6 11.4 30.1 Full Size Car Stoich DIT 1.13 238 28 DCT8 49.8 46.5 31.3 1.3 3.4 6.1 7.7 10.0 2.7 3.9 105.9 86.6 — 15 2.5 16.9 10.5 27.1 Full Size Car Lean DIT 1.13 238 28 DCT8 50.4 46.8 31.4 1.3 3.4 6.1 7.7 10.0 2.7 3.9 105.9 86.6 — 15 2.5 16.9 10.5 27.1 Full Size Car EGR DIT 1.13 238 28 DCT8 51.7 48.3 32.6 1.3 3.4 6.1 7.7 10.0 2.7 3.9 105.9 86.6 — 15 2.5 16.9 10.5 27.1 Full Size Car Atk CS 3.80 317 120 PS 40.3 38.7 29.2 1.3 3.2 5.6 7.1 8.7 2.4 3.1 119.2 103.5 — 16 2.7 17.7 10.7 28.6 Full Size Car Atk DVA 3.80 317 120 PS 43.0 40.8 29.8 1.3 3.2 5.6 7.1 8.7 2.4 3.1 119.2 103.5 — 16 2.7 17.7 10.7 28.7 Full Size Car Stoich DIT 1.13 238 120 PS 46.6 42.0 29.8 1.3 3.2 6.0 7.8 10.0 2.8 4.0 106.2 87.6 — 12 2.6 17.2 10.4 28.2 Full Size Car Lean DIT 1.13 238 120 PS 48.0 41.8 29.9 1.3 3.2 5.9 7.8 10.0 2.7 4.1 106.2 87.7 — 12 2.6 17.2 10.4 28.3

Full Size Car EGR DIT 1.13 238 120 PS 47.9 43.6 31.1 1.3 3.2 6.0 7.8 10.0 2.8 4.0 106.2 87.7 — 12 2.6 17.2 10.4 28.2

Large MPV Stoich DIT 1.31 277 — AT8 34.8 39.2 23.7 1.1 3.2 6.4 8.6 11.5 3.2 5.1 103.7 84.5 — 15 3.4 19.8 13.2 29.1Large MPV Lean DIT 1.31 277 — AT8 36.0 39.8 23.9 1.1 3.2 6.4 8.6 11.5 3.2 5.1 103.7 84.5 — 15 3.4 19.8 13.2 29.1Large MPV EGR DIT 1.31 277 — AT8 36.2 40.9 24.9 1.1 3.2 6.4 8.6 11.5 3.2 5.1 103.7 84.5 — 15 3.4 19.8 13.2 29.1Large MPV Adv Diesel 2.61 460 — AT8 37.3 43.3 29.4 1.1 3.0 6.2 8.6 11.5 3.2 5.3 101.9 83.9 — 14 3.7 20.9 13.3 30.5Large MPV Atk CS 3.15 263 25 DCT8 48.3 42.4 27.5 1.4 3.6 6.7 8.8 11.6 3.1 4.9 95.5 82.3 — 11 2.4 15.7 9.7 26.0Large MPV Atk DVA 3.15 263 25 DCT8 48.8 43.5 27.7 1.4 3.6 6.7 8.8 11.6 3.1 4.9 95.5 82.3 — 11 2.4 15.7 9.7 26.0Large MPV Stoich DIT 1.05 221 25 DCT8 47.7 42.2 26.2 1.5 3.8 6.9 9.1 11.9 3.1 5.0 94.3 75.6 — 12 2.2 14.7 9.0 23.9Large MPV Lean DIT 1.05 221 25 DCT8 47.4 42.6 26.8 1.5 3.8 6.9 9.1 11.9 3.1 5.0 94.3 75.6 — 12 2.2 14.7 9.0 23.9Large MPV EGR DIT 1.05 221 25 DCT8 47.6 43.0 27.6 1.5 3.8 6.9 9.1 11.9 3.1 5.0 94.3 75.6 — 12 2.2 14.7 9.0 23.9Large MPV Atk CS 3.15 263 90 PS 41.7 38.6 26.5 1.8 4.2 7.0 8.8 11.1 2.8 4.1 103.4 86.0 — 11 1.5 11.7 6.8 20.2Large MPV Atk DVA 3.15 263 90 PS 44.3 39.6 27.0 1.8 4.2 7.0 8.8 11.1 2.8 4.1 103.4 86.5 — 11 1.5 11.7 6.8 20.2Large MPV Stoich DIT 1.05 221 90 PS 44.8 39.3 25.8 1.8 4.3 7.5 9.7 12.5 3.2 5.0 100.2 76.5 — 9 1.5 11.5 6.7 19.7Large MPV Lean DIT 1.05 221 90 PS 45.7 40.6 25.7 1.8 4.3 7.5 9.7 12.5 3.2 5.0 100.8 76.5 — 9 1.5 11.5 6.7 19.7Large MPV EGR DIT 1.05 221 90 PS 47.0 41.5 27.3 1.8 4.3 7.5 9.7 12.5 3.2 5.0 100.8 76.5 — 9 1.5 11.5 6.7 19.7

LDT Stoich DIT 1.94 410 — AT8 23.8 26.6 16.3 1.1 3.0 6.0 8.1 10.8 3.0 4.8 105.6 86.9 21 — 3.4 20.5 13.2 30.5LDT Lean DIT 1.94 410 — AT8 24.6 27.0 16.4 1.1 3.0 6.0 8.1 10.8 3.0 4.8 105.6 86.9 21 — 3.4 20.5 13.2 30.5LDT EGR DIT 1.94 410 — AT8 24.8 27.7 17.1 1.1 3.0 6.0 8.1 10.8 3.0 4.8 105.6 86.9 21 — 3.4 20.5 13.2 30.5LDT Adv Diesel 4.28 694 — AT8 26.4 30.4 20.5 1.0 2.9 5.8 8.0 10.6 2.9 4.8 104.6 87.2 20 — 3.7 21.4 13.5 31.5LDT Atk CS 4.60 384 50 DCT8 33.2 29.0 19.4 1.1 3.1 5.9 7.8 10.3 2.8 4.4 95.6 83.8 17 — 3.1 19.1 12.2 29.5LDT Atk DVA 4.60 384 50 DCT8 33.9 29.7 19.7 1.1 3.1 5.9 7.8 10.3 2.8 4.4 95.6 83.8 17 — 3.1 19.1 12.2 29.5LDT Stoich DIT 1.55 327 50 DCT8 32.5 28.4 18.9 1.2 3.3 6.1 7.9 10.4 2.8 4.3 96.1 78.0 16 — 3.0 18.2 11.7 27.9LDT Lean DIT 1.55 327 50 DCT8 33.0 28.6 18.8 1.2 3.3 6.1 7.9 10.4 2.8 4.3 96.1 78.0 16 — 3.0 18.2 11.7 27.9LDT EGR DIT 1.55 327 50 DCT8 33.8 29.6 19.7 1.2 3.3 6.1 7.9 10.4 2.8 4.3 96.1 78.0 16 — 3.0 18.2 11.7 27.9

LHDT Stoich DIT 2.30 486 — AT8 16.5 18.3 11.1 1.0 3.2 7.0 9.8 13.4 3.8 6.4 95.1 74.8 16 — 3.6 20.2 13.9 28.6LHDT Lean DIT 2.30 486 — AT8 16.8 18.4 11.2 1.0 3.2 7.0 9.8 13.4 3.8 6.4 95.1 74.8 16 — 3.6 20.2 13.9 28.6

LHDT EGR DIT 2.30 486 — AT8 17.2 19.1 11.7 1.0 3.2 7.0 9.8 13.4 3.8 6.4 95.1 74.8 16 — 3.6 20.2 13.9 28.6LHDT Adv Diesel 6.60 895 — AT8 19.8 21.5 14.1 0.9 2.9 6.3 8.8 11.8 3.4 5.5 101.5 79.3 17 — 4.2 22.2 15.1 31.0

Peak Trq 

(N.m)

EM Pwr 

(kW)

Transmission Raw fuel economy (mpg) Acceleration times (s) Top Speed (mph) on Max grade at Distance (m) in Velocity (mph) at
Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020–2025 Timeframe 

29 November 2011 Ricardo, Inc. Page 68 

DISCLAIMER 

Ricardo Inc. has taken all reasonable care in compiling the analyses and recommendations 

provided in this report. However, the information contained in this report is based on information 

and assumptions provided by the client or otherwise available to Ricardo which, in all the 

circumstances, is deemed correct on the date of writing. Ricardo does not assume any liability, 

provide any warranty or make any representation in respect of the accuracy of the information, 

assumptions, and consequently the analyses and recommendations contained in this report. 

The report has been compiled solely for the client's use. 

Any results of analysis and calculation are intended to be part of subsequent decision-making 

during design, development and problem-solving stages. Although analysis may reduce the 

effort required to validate a product through testing prior to production, such results shall not be 

relied on as a validation in its own right. 

Analysis and calculations which are intended to predict physical behaviors are inherently 

theoretical in nature as they are subject to a range of assumptions and approximations. Physical 

behaviors and the measurements of those behaviors may vary for a variety of factors, some 

being outside the control of Ricardo or the capability of the predictive methodology used by 

Ricardo. Therefore, where any such predictions are subsequently compared with measured 

data or physical behavior, it is to be expected that differences will be apparent. 

 
Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020–2025 Timeframe 

29 November 2011 Ricardo, Inc. Page 69 

ATTACHMENT A 

Attachment A is the document "Assessment of Technology Options", which includes Ricardo 

SME assessments of the technologies considered in study "Computer Simulation of Light Duty 

Vehicle Technologies for Greenhouse Gas Emission Reduction in the 2020–2025 Timeframe". 

These assessments were made of the technologies listed in Appendix 2. 
Assessment of Technology Options

Technologies considered in study "Computer Simulation of Light Duty Vehicle Technologies for Greenhouse Gas Emission Reduction in the 2020–2025 Timeframe"Date 30 September 2011Report RD 11/342305 1 RD.11/342305.1Project CG001019Prepared for EPA Office of Transportation and Air QualityReport by Jennifer Durfy 

Stuart Horswill Stuart Horswill

Chris Mays Richard OsborneJohn StokesWayne Thelen

RD.11/342305

Approved John J. Kasab
Outline

 Introduction Spark ignited engine technologies Diesel engine technologies Hybrid vehicle technologies Transmission technologies Transmission technologies Vehicle technologies Conclusions

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Introduction

 The following technology assessments were discussed by Ricardo

the Advisory Committee at the start of the study, "Computer SimulaD t Vehicle Technologies for Greenho se Gas Emission Red ctioDuty Vehicle Technologies for Greenhouse Gas Emission Reductio

2020–2025 Timeframe"

 Purpose of the assessments was to evaluate a large set of potentia

technologies against the following criteria: technologies against the following criteria:

– Effectiveness of Technology– Availability of Technology in 2020–2025– M k t P t ti f T h l i 2020 Market Penetration of Technology in 2020–2025– Long-Term Cost Viability– Current Technology Maturity

 Assessments used the scale on the following slide and were based 

Ricardo Subject Matter Experts' experience with the systems cons

 Based on the evaluation and discussion, a subset of these technol

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

, 

included in the final study. 
Details of the rating system

Effectiveness of Technology (tank to wheels basis) 1 = Worst = no CO2 benefit 2 = 1% CO benefit

Long-Term Cost Viability 1 = WORST = no pathway to long-te

 2 = 1% CO  3 = Needs to "cross commercializati

2 benefit

 5 = 5% CO2 benefit 8 = 10% CO2 benefit 10 = Best = ≥20% CO2 benefit

 3 Needs to cross commercializati 5 = Pathway to volume production c 7 = Return on investment clear 10 = Profitable in 2020-2025

Availability of Technology in 2020–2025 1 = University Research Laboratory 3 = Technology available but not in vehicles 4 = First Prototype in vehicles

Current Technology Maturity 1 = University Research Laboratory 3 = Technology available but not in 

4 First Prototype in vehicles  4 = First Prototype in vehicles

 6 = In Fleet Trials 7 = First entry into market 10 = Predominant technology in market place

yp

 6 = In Fleet Trials 7 = First entry into market 10 = Predominant technology in ma

Market Penetration of Technology in 2020–2025 1 = Worst = Demonstrated technology by 2025 3 = Only in niche applications 5 = Available, but not widespread (≥5% of market)

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

( )

 7 = Mass-market availability (≥10% of market)  10 = Best = Widespread (≥25% of market)
Outline

 Introduction Spark ignited engine technologies Diesel engine technologies Hybrid vehicle technologies Transmission technologies Transmission technologies Vehicle technologies Conclusions

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Baseline Gasoline Engines 

Technology Assessment – SI Engines

Technology and Status

 Concept: The baseline gasoline engines for 2020–2025 light-duty vehicles in 

Ratings o

the US market are a range of naturally-aspirated port fuel-injected (PFI) 

engines, featuring dual-independent cam phaser (VVT) systems

 Base Functioning: The baseline vehicles will achieve a fleet average 

emissions level of SULEV 2 (approximately EPA Tier 2 Bin 2)

 CO Benefit: Baseline (>35 5 mpg fleet average) Marke

Effectivenes

Availabilit

 CO2 Benefit: Baseline (>35.5 mpg fleet average) Costs: Baseline – powertrain and aftertreatment cost of ~$1500–$2000 for 

standard car segment

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 The following vehicle classes are the subject of this study:

– Small car (Ford Focus)

– St d d (T t C ) Standard car (Toyota Camry)– Small MPV (Saturn Vue)– Full-size car (Chrysler 300C)– Large MPV (Dodge Grand Caravan)– Truck (Ford F150)

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

– Heavy light-duty truck (Ford F250/F350)
Outline

 Introduction Spark ignited engine technologies

– D id i ownsized engines

– Advanced valvetrains– Combustion systems and fuels

– Engines for hybrid vehicles

 Diesel engine technologies Hybrid vehicle technologies Hybrid vehicle technologies Transmission technologies Vehicle technologies

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

 Conclusions
Stoichiometric Direct-Injection Turbocharged Engines 

Technology Assessment – SI Engines

Technology and Status

 Concept: Downsizing describes the replacement of a naturally-aspirated engine 

Ratings o

with a smaller-displacement turbocharged engine, having equivalent torque and power

 Base Functioning: Downsizing reduces pumping work by shifting operating 

points to higher load factors, and can also produce reductions in frictional losses

 CO Benefit: Drive cycle benefit of 8 10% Marke

Effectivenes

Availabilit

 CO2 Benefit: Drive-cycle benefit of

8

–10%

 Costs: 15–25% increase in engine and aftertreatment cost

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 Downsized DI turbo engines are applicable in all light-duty vehicle classes

– Likely to predominate in mid-size vehicles

 As a high compression ratio is maintained, downsized DI turbo engines provide 

fuel economy benefits across the majority of the operating map

– As a result, both city and highway fuel economy will benefit

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Lean Direct-Injection Turbocharged (LDIT) Engines

Technology Assessment – SI Engines

Technology and Status

 Concept: In the LDIT concept the octane requirement is controlled using direct 

Ratings o

injection and lean operation at full load

 Base Functioning: LDIT engines combine the downsizing benefits described 

on the previous slide with the additional efficiency benefit of homogeneous lean 

operation at high load

 CO Benefit: Drive cycle benefit of 20 22

% Marke

Effectivenes

Availabilit

 CO2 Benefit: Drive-cycle benefit of 20

–22

%

 Costs: 50–60% increase in engine and aftertreatment cost

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 LDIT engines are applicable to all vehicle classes

– Likely to predominate in mid-size vehicles and premium vehicles

 As a high compression ratio is maintained and lean operation is applied at all 

conditions LDIT engines provide fuel economy benefits across the majority of the operating map

– As a result, both city and highway fuel economy will benefit

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
High-Load EGR Engines

Technology Assessment – SI Engines

Technology and Status

 Concept: This downsized DI engine concept is analogous to LDIT, but octane 

Ratings o

requirement is controlled by EGR dilution at full load rather than lean operation.

 Base Functioning: High-load EGR engines combine the benefits of downsizing 

described previously with the additional efficiency improvement of EGR dilution at high load

 CO Benefit: Drive cycle benefit of 15 18% Marke

Effectivenes

Availabilit

 CO2 Benefit: Drive-cycle benefit of 15–18% Costs: 40–45% increase in engine and aftertreatment cost

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 High-load EGR engines are applicable to all vehicle classes As a high compression ratio is maintained and EGR dilution is applied at all 

conditions, High-load EGR engines provide fuel economy benefits across the 

operating map

– As a result, both city and highway fuel economy will benefit

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Two-Stroke/Four-Stroke (2S-4S) Switching Engines

Technology Assessment – SI Engines

Technology and Status

 Concept: The vast majority of passenger cars use the four-stroke cycle, but 

Ratings o

some characteristics of two-stroke engines—especially high specific torque—remain attractive for automotive application. 2S-4S engines combine a combustion system capable of operating as both two-stroke and four-stroke with advanced valvetrain and boosting systems.

 Base Functionin

g: 2S-4S en

gines offer the 

greatest opportunit

y for en

gine Marke

Effectivenes

Availabilit

g g gppyg

downsizing, and hence improvement in efficiency

 CO2 Benefit: Drive-cycle benefit of 25–27% Costs: 70–80% increase in engine and aftertreatment cost

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 2S-4S engines operate in four-stroke mode for the majority of drive-cycle 

operation, so the emissions and fuel economy characteristics are those of a heavily downsized 4S DI turbo engine heavily downsized 4S DI turbo engine

 2S-4S engines are most likely to be applied in premium vehicle segments

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Outline

 Introduction Spark ignited engine technologies

– D id i ownsized engines

– Advanced valvetrains– Combustion systems and fuels

– Engines for hybrid vehicles

 Diesel engine technologies Hybrid vehicle technologies Hybrid vehicle technologies Transmission technologies Vehicle technologies

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

 Conclusions
Cam-Profile Switching Engines

Technology Assessment – SI Engines

Technology and Status

 Concept: Cam-profile switching (CPS) systems allow selection between two or 

Ratings o

three cam profiles by means of a hydraulically-actuated mechanical system

– CPS systems have been developed by a number of Japanese and European 

OEMs, such as the Honda VTEC, Mitsubishi MIVEC, Porsche VarioCam and Audi Valvelift (pictured)

 Base Functioning: CPS systems can be optimised either to improve low speed Marke

Effectivenes

Availabilit

 Base Functioning: CPS systems can be optimised either to improve low-speed

torque, or to improve fuel economy by reducing pumping losses at light load

 CO2 Benefit: Drive-cycle benefit of 5–7% Costs: 8–10% increase in engine and aftertreatment cost

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 Cam-profile switching systems are applicable in all light-duty vehicle classes CPS systems produce most fuel economy benefit for part-load operation, so 

most benefit occurs for city driving and less for highway use

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Outline

 Introduction Spark ignited engine technologies

– D id i ownsized engines

– Advanced valvetrains– Combustion systems and fuels

– Engines for hybrid vehicles

 Diesel engine technologies Hybrid vehicle technologies Hybrid vehicle technologies Transmission technologies Vehicle technologies

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

 Conclusions
Stoichiometric Direct-Injection Engines

Technology Assessment – SI Engines

Technology and Status

 Concept: Stoichiometric, homogeneous direct-injection gasolines operate in a 

Ratings o

very similar manner to port fuel-injected engines, except that fuel is injected directly into the cylinder. GDI engines were first introduced in Japan in 1996, and a significant number of new gasoline engines now feature direct injection.

 Base Functioning: The application of direct injection produces modest fuel 

econom

y benefits, resultin

g from the abilit

y to apply hi

gher com

pression ratio. Marke

Effectivenes

Availabilit

y , g y pp y g p

 CO2 Benefit: Drive-cycle benefit of ~3% Costs: 8–10% increase in engine and aftertreatment cost

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 Stoichiometric DI engines are applicable in all vehicle classes  The higher compression ratio facilitated by DI improves both part-load and highload efficiency, and therefore both highway and city fuel economy

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Stratified Charge Direct-Injection Engines

Technology Assessment – SI Engines

Technology and Status

 Concept: In stratified-charge engines the fuel is injected late in the 

Ratings o

compression stroke with single or multiple injections. The aim is to produce an overall lean, stratified mixture, with a rich area in the region of the spark plug to enable stable ignition.

 Base Functioning: Stratified lean operation allows the gasoline engine to 

o

perate unthrottled, eliminatin

g the majorit

y of 

pum

pin

g losses. Marke

Effectivenes

Availabilit

p , gj

y

p

p

g

 CO2 Benefit: Drive-cycle benefit of 8–10% Costs: 15–25% increase in engine and aftertreatment cost

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 As a result of the FIE and aftertreatment costs, lean DI systems are most 

applicable in premium vehicles 

 As the fuel economy benefit derives from the reduction of pumping work, lean 

DI engines produce most improvement in city driving

– There is limited benefit for highway driving

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
HCCI/CAI Combustion

Technology Assessment – SI Engines

Technology and Status

 Concept: Homogeneous charge compression ignition (HCCI), also known as 

Ratings o

controlled auto-ignition (CAI) combustion are distinct from the conventional SI and CI engine operating modes

– In the idealized case HCCI/CAI combustion initiates simultaneously at 

multiple sites within the combustion chamber, and there is little or no flame 

propagation Marke

Effectivenes

Availabilit

p pg

 Base Functioning: Dual mode operation, with HCCI/CAI at part-load, and SI 

for high-load, idle and starting

 CO2 Benefit: Drive-cycle benefit of 2–10% (depending on whether the benefits 

of the constituent technologies are included or not)

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability

Visualizatio

 Costs: 20–30% increase in engine and aftertreatment cost

 HCCI/CAI combustion is unlikely to be an attractive technology for light-duty 4 5

5.0

 HCCI/CAI combustion is unlikely to be an attractive technology for light-duty

gasoline vehicles in 2020–2025

– The operating envelope for HCCI/CAI combustion is very limited, and the 

additional benefits over the necessary constituent technologies (advanced valvetrains, GDI etc.) are also small

IMEP [bar]

2.53.03.54.04.5

1.60

1.20

0.80

0.6

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

2.0

En

500 1000 1500 
Exhaust Energy Recovery

Technology Assessment – SI Engines

Technology and Status

 Concept: Exhaust energy recovery encompasses a number of technologies, 

Ratings o

such as turbo-compounding and thermoelectric devices

– In turbo-compounding a radial turbine is connected through a mechanical 

transmission directly to the crankshaft 

 Base Functioning: Turbines are generally sized to recover energy at high load 

operation; a variable speed transmission between engine and turbine can be Marke

Effectivenes

Availabilit

operation; a variable-speed transmission between engine and turbine can be

used to improve the efficient operating range

 CO2 Benefit: Turbo-compounding has a drive-cycle benefit of 3–5% Costs: Not established for light-duty vehicles

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 Turbo-compounding is currently only applied to premium long-haul trucks

– In 2020 it will still be most applicable to the heavy light-duty truck segment, 

and the benefits will be reduced in comparison to heavy-duty vehicles

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Second-Generation Biofuels

Technology Assessment – SI Engines

Technology and Status

 Concept: Second-generation biofuels refer to fuels coming from non-food 

Ratings o

sources (in this case gasoline-like fuels)

 Base Functioning: Wherever possible biofuels should operate in a manner 

identical to conventional gasoline

– Increasing blending of conventional gasoline and biofuels is likely to occur Marke

Effectivenes

Availabilit

 CO2 Benefit: The CO2 benefits from the use of biofuels are complex and 

disputed

 Costs: There is no significant engine cost associated with the use of single-fuel 

biofuels (although appropriate materials must be applied in the fuel system)

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 Biofuels are applicable to all vehicle classes Tank-to-wheels fuel economy for biofuels is similar to that for conventional 

gasoline engines – benefits occur from the higher octane number of ethanolbased fuels

 Additional CO2 benefits can be attributed to biofuel use if the complete life-cycle 

is considered (cellulosic ethanol, etc.)

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Outline

 Introduction Spark ignited engine technologies

– D id i ownsized engines

– Advanced valvetrains– Combustion systems and fuels

– Engines for hybrid vehicles

 Diesel engine technologies Hybrid vehicle technologies Hybrid vehicle technologies Transmission technologies Vehicle technologies

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

 Conclusions
Engines Optimized Micro-Hybrid (Stop-Start) Vehicles

Technology Assessment – SI Engines

Technology and Status

 Concept: Application of stop-start or micro-hybrid concepts requires only very 

Ratings o

minor changes in base engine architecture. Typically a belt-driven startergenerator is applied in place of a separate starter motor and alternator. 

 Base Functioning: See hybrid vehicle slides CO2 Benefit: See hybrid vehicle slides Marke

Effectivenes

Availabilit

 Costs: Base engine costs are largely unchanged for stop-start systems. 

Additional engineering cost is required to implement the stop-start calibration.

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 Stop-start should applied in all vehicle segments for the 2020 timeframe Given hybrid inititives, it is likely that most new engine development projects will 

consider integrating stop start functionality in program.

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Engines Optimized for Full Hybrid Vehicles

Technology Assessment – SI Engines

Technology and Status

 Concept: In hybrid electric vehicle applications the gasoline engine can be 

Ratings o

optimised for use in the limited modes required by the full hybrid powertrain.

 Base Functioning: See hybrid vehicle slides CO2 Benefit: Strong function of degree of limited operating conditions. Costs: Base engine costs may be slightly reduced for hybrid vehicle Marke

Effectivenes

Availabilit

applications through the use of lower specification engines. Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visualizatio

 Engine technology optimization for hybrid powertrains in infancy. Clear trend 

towards system level optimization to obtain best overall performance. 

 Hybrid features such as stop-start, CVT operation, electrical launch, and 

electrical assist provide an oportuntity to optimize the engine system in ways not offered by conventional drivelines. 

 Electrical assist offers opportunity to reduce engine size and specific power in 

h

ybrid vehicle and utilize lower s

pecific 

power / increased BSFC technolo

gies

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

y p p g
SI Engine Technology Applicability

Technology Assessment – SI Engines

 Please note that the applicability of hybrid powertrains is covered e

this report

Stoichiometric

Lean Boost D

EGR Boost DI

2S-4S Switchi

Cam-Profile S

Stoichiometric

Stratified-Cha

c DI Turbo

I

ng Engine

witching

c Direct injection

arge DI

n

Small Car (Ford Focus) XXX XStandard Car (Toyota Camry) XXX

X X 

Small MPV (Saturn Vue)

X

X

X

X

X

Vehicle Classification

Small MPV (Saturn Vue)

X

X

X

X

X

Full-sized Car (Chrysler 300C) XXX X X

X

X

Large MPV (Dodge Grand Caravan) XXX X X

X

X

Truck (Ford F150)

X

X

X

X

X

X

X

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Truck (Ford F150)

X

X

X

X

X

X

X

Heavy light-duty truck (Ford F250/F350) XXX X X X X
Outline

 Introduction Spark ignited engine technologies Diesel engine technologies Hybrid vehicle technologies Transmission technologies Transmission technologies Vehicle technologies Conclusions

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Technology Area Overview

Technology Assessment – Diesel Engines

 For this technology area, we have the following thoughts for the sit

2020–2025: 

 Diesel Technology will continue to be developed driven largely by t

market but a gradual penetration will be seen in the US market

 Impq g rovement is required in technologyp y cost, particularly turbocharg 

aftertreatment for significant penetration

 US market penetration for domestic producers is assumed to comm

the heavier vehicles in the study cascading down in size as technoacceptance improves, and CO2 legislation drives incremental fleet 

 Baseline is T2B5 (LEV II) applications currently in market

– Represents ca. 20% CO2 benefit from current baseline SI engin– 2020 diesel engines assumed to meet LEV III (approximately cu

SULEV II) emissions

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Technology Status – Diesel Powertrain

Consideration made across all sectors of study

Technology Assessment – Diesel Engines

 Technology has very low take rate in US market in passenger car a

truck applications versus Europe

– P d t t i ll l il bl i i t d Pro

duct typically only avail

able in importe

d passenger car (e.g., 

BMW and Mercedes)

– Domestic Product generally offered in LHDT (e.g. Ford Superdu

– European Diesel share is half of market and covers all product f

European Diesel share is half of market and covers all product f

sub-B (Fiat 500 class) to LHDT (Dodge Sprinter Class)

– European Market has a competitive CO

2 driver leading to Diese

branding (e.g. Ford Econetic, Mercedes Bluetec, VW Bluemotio

 European Diesel Technology has seen many technology advances

– Sequential turbocharging– Combustion correction techniques (e.g. UEGO, cylinder pressur

– L EGR l ith h t b Large EGR coolers with

h

ot gas 

bypass

– Third generation FIE – 2000 Bar and multiple injections– Mature DPF technology

SCR technology applied

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

– SCR technology applied– Advanced materials – Al alloy heads and blocks, CGI blocks
Diesel Technology List for US Applications

Technology Assessment – Diesel Engines

 Closed Loop Combustion Control Reduced Compression Ratio Advanced Boosting Technologies Enhanced EGR and Charge Air Cooling Variable Valve Timing (With Application To Vary Compression Rat

Variable Valve Timing (With Application To Vary Compression Rat

 Pre-Turbine Catalysis Electric Turbo-Compounding Calibration "System" Optimization for CO Calibration "System" Optimization for CO (Engine + Trans + Aftert

2 (Engine

+ Trans

+ Aftert

 Narrow Speed Range Operation System Integration at Engine Level Engine Downsizing 

– no slide 

– duplication with SI Engine

 Engine Friction Reduction – no slide

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Closed Loop Combustion Control

Technology Assessment – Diesel Engines

Technology and Status

 Concept: Provide feedback from combustion by means of direct cylinder 

Ratings o

pressure measurement and analysis in EMS

 Base Functioning: Measure cylinder pressure during combustion to provide 

feedback for air, EGR, and fuel injection control to minimize error and correct for fuel quality allowing better trade-off for CO2 emissions versus NOx and PM

 CO Benefit: <1% from maintaining optimal combustion and facilitates further Marke

Effectivenes

Availabilit

 CO2 Benefit: <1% from maintaining optimal combustion and facilitates further

combustion optimization 

 Costs: Added variable costs for glowplug, added inputs and processing power 

in engine control unit. Additional development time will be required to characterize the signal responses and tune calibration correction responses

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Technology is applicable to light duty diesel applications commonly fitted with 

glowplugs. For heavier duty applications not engineered for glowplug alternate head gasket technology would need to be employed

Visualizatio

head gasket technology would need to be employed

 Highway benefits – closed loop combustion feedback allows for real world benefit 

plus closer margin between legal limits and development targets allowing further CO2 combustion optimization

 City benefits – Further real world benefit available from combustion correction 

di t i t t 1 Pl 

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during transient events

 Other – lower cylinder to cylinder variation

Picture: www.beru.com

1. Plug2. High voltage connection3. Circuit board with electr4. Gasket
Reduced Compression Ratio

Technology Assessment – Diesel Engines

Technology and Status

 Concept: Reduction of the compression ratio reduces the peak firing pressure 

Ratings o

of the engine. This reduces the pumping losses and allows for higher specific power to be achieved

 Base Functioning: Pumping losses contribute to the total frictional losses 

(FMEP) of an engine. Reduction of the losses means less fuel energy is wasted resulting in higher fuel efficiency Marke

Effectivenes

Availabilit

g g y

 CO2 Benefit: 1% per ratio plus additional from downsizing opportunity Costs: Reduced compression ratio requires additional effort to start the 

engine in colder ambient conditions. An enabler for significant compression ratio reduction would be increased starter energy availability allowed by high voltage h brid ISG s stems

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Applicable to Diesel ISG applications to enable increased cranking speed for start 

performanceHi h b fit I d ifi f th i bl i

Visualizatio

hybrid ISG systems

 Highway benefits – Increased specific power from the engine enables engine 

downsizing. Reduced pumping loss gives benefit across the full speed and load 

range

 City benefits – As pumping losses are a greater proportion of part load operation 

the benefit should be more marked in city operation

Vis

A

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

 Idle-stop benefits – Idle fuelling will be reduced although pre-cursor of ISG 

enables full stop-start benefit
Advanced Boosting Technologies

Technology Assessment – Diesel Engines

Technology and Status

 Concept: Improvements in air handling through a suite of boosting 

Ratings o

technologies either standalone or in combination

 Base Functioning: Provision of higher specific torque and power to enable 

downsized engines. Technologies include eBoost (e-machine in CHRA or electrical separation by e-Turbine and e-Compressor); supercharging (advances to avoid variable drive); variable nozzle com

pressor Marke

Effectivenes

Availabilit

);

p

 CO2 Benefit: 2% (more if engine downsized for equivalent performance) Costs: Increase in turbocharger air system matching and development time, 

increased complexity in engine controller. Variable cost of turbocharger doubles plus additional air cooling requirement, sensors and actuators

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Technology applicable to all sectors of diesel application Highway benefits – improved transient response from engine allows downsizing. 

M i ll i d i i f f NO d PM t l i i

Visualizatio

More air allows improve

d emission performance for NOx an

d PM control giving 

leeway for CO2 reduction.

 City benefits – much improved transient performance allowing downsizing. 

Operation in more efficient area of turbocharger map gives more noticeable CO2

benefit in city driving

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

 In conjunction with enhanced EGR allows for premixed or homogeneous 

combustion in part load operation for very clean emissions. Design can facilitate the use of pre-TC catalyst for quick aftertreatment light-off

Picture: http://honeyw
Enhanced EGR Flow & Cooling 

(Plus Increased Charge Air Cooling)

Technology Assessment – Diesel Engines

Technology and Status

 Concept: Low Pressure EGR Circuit for increased EGR flow rate in conjunction 

Ratings o

with separate low temperature cooling circuit to cool EGR and provide additional charge air cooling

 Base Functioning: Increased EGR and cooler charger enables homogeneous, 

fully premixed and partially premixed combustion concepts. These concepts reduce NOx and PM emissions allowing more margin for CO2 optimization. Lo er charge temperat re pro ides a larger P V area and increases specific Marke

Effectivenes

Availabilit

Lo

wer charge temperat

ure pro

vides

a larger

P-V area and increases specific

power and economy

 CO2 Benefit: 2–4% from combined emission and cooling benefit Costs: Increased development cost for EGR and cooling system packaging. 

Additional work to optimize cooling pack. EGR cost increases 40–50% plus 

incremental costs for additional cooling system components and material

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability

 Applicable to Light Duty Chassis Certification Applications requiring EGR at low 

Visualizatio

incremental costs for additional cooling system components and material

revisions necessary to cope with corrosive environment in charge cooler with 

EGR present

speed and load:

 Highway benefits – Fuel economy improvement from increased charge cooling 

and improved compressor efficiency (EGR flows through TC compressor)

 City benefits – Significant emission benefit allowing combustion to be optimized 

more for CO2. Compressor efficiency improved for reduced pumping loss

A significant challenge remains for TC compressor d rabilit ith hea EGR flo

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305



A significant challenge remains for TC compressor

d

urability with heavy EGR flow 

rates Picture: VW Tech Rep

29. Internationales Wi
Variable Valve Timing

(With Application To Vary Compression Ratio)

Technology Assessment – Diesel Engines

Technology and Status

 Concept: Variable Valve Events enable valve events to be optimzed for 

Ratings o

oeprating point and also enable effective compression ratio variation

 Base Functioning: Intake and Exhaust Valve Events varied for rapid 

aftertreatment warm-up and best breathing at operating condition rather than global optimization. With more complex system, compression ratio can also be varied to reduce frictional losses and increase specific power Marke

Effectivenes

Availabilit

 CO2 Benefit: 1–2% from warm-up & improved breathing. Additional gain if 

aftertreatment warmup creates NOx advantage to be used for CO2 benefit

 Costs: Costs increase for valvetrain technology with some offset in 

aftertreatment cost. Additional development cost to develop for diesel engine application with incremental engine controller costs for drive circuits

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Applicable to complete diesel line-up from small car to MDV Highway benefits – Increased specific power from the engine enables engine 

d i i R d d i l i b fit th f ll d d l d

Visualizatio

application with incremental engine controller costs for drive circuits

downsizing. Reduced pumping loss gives benefit across the full speed and load

range

 City benefits – As pumping losses are a greater proportion of part load operation 

the benefit should be more marked in city operation

 Idle-stop benefits – ability to raise compression ratio allows stop start to be more 

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

readily employed than reduced compression ratio alone as ISG is not necessary for restart

Picture: Valeo e-Valv
Pre-Turbine Catalysis

Technology Assessment – Diesel Engines

Technology and Status

 Concept: Small Oxidation Catalyst (DOC) is placed before first turbocharger 

Ratings o

very close to the engine

 Base Functioning: Small pre-turbine catalyst with low thermal inertia lights off 

quickly allowing further exotherm to warm up rest of aftertreatment more rapidly. 

Reduced warm-up will require lower use of fuel for heating strategies reducing CO2 emissions Marke

Effectivenes

Availabilit

Technology Applicability

2

 CO2 Benefit: <1% – more for cold start cycles.  Costs: Additional cost for pre-turbine catalyst precious metal partially offset 

by reduced precious metal in remainder of aftertreatment system

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Applicable to all diesel technology applications but with more relevance on 

applications with larger engines and large aftertreatment systems with greater thermal inertia

 Highway benefits – Minimal benefit and only soon after starting when 

Visualizatio

aftertreatment is cold

 City benefits – Benefit most noticeable for real world situations when vehicle is 

used frequently for short journeys from cold or cool start when aftertreatment is 

below effective operating temperature

 Pre-turbine catalyst allows for less aggressive heating strategies to keep 

aftertreatment in correct operating temperature window

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

aftertreatment in correct operating temperature window

 Component durability must be considered in placing catalyst closer to engine and 

may require metallic catalyst substrate Picture: www.emitec
Electric Turbo-Compounding

Technology Assessment – Diesel Engines

Technology and Status

 Concept: Electric turbo-compounding device recovers waste exhaust energy 

Ratings o

and converts this to electrical energy 

 Base Functioning: Exhaust energy that would otherwise be wasted is used to 

drive a turbine coupled to an electrical generator to generate electrical power. The electrical power can be stored in conjunction with hybridization or fed back as shaft power directly to reduce fuel demand on engine Marke

Effectivenes

Availabilit

p y g

 CO2 Benefit: 4–5% improvement in fuel efficiency depending on cycle Costs: Technology is proven on heavy duty applications but specific 

development would be required for lighter duty matching and application. Incremental variable cost for ETC and power electronics.

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Already applied to heavy duty applications – more applicable to heavier 

applications Hi h b fit i ifi t b fit t 5% d di d t l d

Visualizatio

 Highway benefits – significant benefit – up to 5% depending on duty cycle and

engine load on highway

 City benefits – transient low speed and load does not offer the same quality of 

exhaust energy for energy recovery. There is potential for worsened fuel economy due to increased back-pressure at some parts of operation 

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 Idle-stop benefits would be acheived if coupled with hybridization More benefit would be obtained with electrification of accessories. Picture: Source: John 
Calibration "System" Optimization for CO

2

(Engine + Transmission + Aftertreatment)

Technology Assessment – Diesel Engines

Technology and Status

 Concept: Application of a sytem level technology selection to add increased 

Ratings o

NOx aftertreatment allowing optimization of engine out emissions for lower CO2and higher NOx (and revised total gearing)

 Base Functioning: Instead of minimizing engine out NOx for smaller NOx 

aftertreatment a system approach for CO2 could oversize NOx aftertreatment 

and allow increased engine out NOx emissions with reduced engine out CO2. 

Combined ith transmission ratio selection for CO rather than NO Marke

Effectivenes

Availabilit

Combined with transmission ratio selection for CO2 rather than NO

x

 CO2 Benefit: 2–4% offset by increased DEF utilization and partially offset by 

increased fuel consumption during warm-up to light off aftertreatment

 Costs: Aftertreatment cost would rise in line with additional reduction 

capacity. DEF system would also need to be resized to account for additional DEF consumption

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Technology applicable to all areas of diesel application Highway benefits – lower CO2 emission by reduced engine speed operation from 

hi h i d ti l CO lib ti ith i d i t NO

Visualizatio

DEF consumption

hi

g

her gearing an

d more optimal CO2 calibration with increase

d engine out NO

x

 City benefits – lower engine speed and improved transient CO2 provide lower 

speed and load benefits

 Idle-stop – stop start operation would need to be treated carefully to maintain 

aftertreatment operating temperature

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 Increase DEF consumption woudl offset cost benefit to end-user and extend 

payback duration

Picture: Ricardo, Inc.
Narrow Speed Range Operation

Technology Assessment – Diesel Engines

Technology and Status

 Concept: Powertrain designed to enable the engine to operate within a narrow 

Ratings o

speed band range with full emissions and economy optimization in this range

 Base Functioning: Powertrain coupled to hybrid systems and/or highly flexible 

transmissions allowing engine to be optimized for narrow speed band for best emissions and economy. Contrast to traditional optimization that considers entire speed load range requirements with many compromisesCO B fit

2 4% f ti i ti f b ti l t it b

Marke

Effectivenes

Availabilit

 CO2 Benefit: 2

–4% from opti

mization of com

bustion plus more opportunity 

by 

limiting higher engine speed for friction reduction with design factors for narrow speed range envelope

 Costs: Little impact to cost if highly flexible transmissions and/or hybrid already 

selected. Reduced engine optimization development offset by increased 

powertrain system development

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Applicable to all classes of vehicles using hybrid systems or high numbers of gear ratios 

that allow engine speed range to be very narrow

 Highway benefits

– Improved economy by maintaining engine in high efficiency island

Visualizatio

powertrain system development

 Highway benefits Improved economy by maintaining engine in high efficiency island. )

Enhanced benefit if emission spikes in transient operation can be avoided allowing further optimization for fuel economy

 City benefits – As highway plus ability to set speed and load on engine for rapid 

aftertreatment warm-up. Engine speed set point can be matched to provide optimal electrical energy generation efficiency for recharging hybrid energy reserve enhancing idle and stop benefits

Engine Torque (Nm)

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idle and stop benefits

 Constant speed operation may prove un-desirable noise characteristic compared to 

traditional powertrain solutions

Picture: Ricardo Inc.

Engin
System Integration at Engine Level

Technology Assessment – Diesel Engines

Technology and Status

 Concept: Combine components to reduce mass and thermal inertia giving 

Ratings o

improved package and faster warm-up. Electrify ancillaries to eliminate FEAD and allow variable performance independent of engine speed

 Base Functioning: Combination of components (e.g. exhaust manifold and 

cylinder head) to improve response time for turbocharging and aftertreatment warm-u

p. Electrification of FEAD reduces 

parasitic losses and allows o

peration Marke

Effectivenes

Availabilit

p pp

to be optimized to most efficient condition for operating point (e.g electrical coolant pump, oil pump or AC compressor)

 CO2 Benefit: 1–2% Costs: Added variable costs for more complex production offset by reduced 

material Electrification in conj nction ith h bridi ation

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Technology is applicable to all diesel technology sectors Highway benefits – reduced frictional losses at higher speed and load points by 

d i i d i ill i t ti l diti

Visualizatio

material. Electrification in conj

unction with

h

ybridi

zation.

designing an

d running ancillaries at optimal conditions

 City benefits – Rapid aftertreatment warm-up reduces fuel consumption in warmup phase and allows earlier transition to warm fuel efficient maps. Ability to run 

ancillaries faster at lower engine speeds will enable lower power loss and should enable component downsizing

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture: Ricardo, Inc.
Diesel Engine Technology Applicability

Technology Assessment – Diesel Engines

 Please note that the applicability of hybrid powertrains is covered i

part of this report

C

R

A

C

E

V

P

E

losed Loop Com

Reduced Compres

Advanced Boostin

Enhanced EGR an

Cooling

Variable Valve Tim

Pre-Turbine Catal

Electric Turbo-Co

mbustion Control

ssion Ratio

ng Technologies

nd Charge Air 

ming 

ysis

ompounding

s

Small Car (Ford Focus) X X X XX Standard Car (Toyota Camry) X X XX

X 

Small MPV (Saturn Vue) X X XX

X 

Vehicle Classification

( )

Full-sized Car (Chrysler 300C) X X XX X X Large MPV (Dodge Grand Caravan) X X XX

X

X

X 

Truck (Ford F150) X

X

X

X

X

X

X

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

( )

X

X

X

X

X

X

X

Heavy light-duty truck (Ford F250/F350) X XX

X XX
Outline

 Introduction Spark ignited engine technologies Diesel engine technologies Hybrid vehicle technologies Transmission technologies Transmission technologies Vehicle technologies Conclusions

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Hybrid Functionality Matrix

Technology Assessment – Hybridized Powertrains

Hybrid technology’s primary purpose is to enable vehicle functionally that offers fuel eff

None Micro Micro Mild Full Full Full Full 

Conventional

Belt 

starter / 

generator 

Belt 

mounted 

parallel

Crank 

mounted 

parallel 

(IMA)

P2 parallel 

hybrid

Input 

Powersplit

Compound 

powersplit

2-mode 

powersplit

h

E

Engine idle off No Yes Yes Yes Yes Yes Yes Yes 

Launch assist No No Small amount Some Yes Yes Yes Yes 

Regeneration No No Small amount g Some Yes Yes Yes Yes 

Electrical only 

mobility No NO No No Yes Yes Yes Yes 

CVT No No No No No Yes Yes Yes 

Power Steering Belt Electrical Electrical Electrical Electrical Electrical Electrical Electrical E

Ai di i i B l B l B l B l Belt or Belt or Belt or Belt or Air conditioning Belt Belt Belt Belt Belt or electrical Belt or electrical Belt or electrical Belt or electrical 

e

Brakes Standard Standard Standard Standard or blended Blended Blended Blended Blended B

City Driving 0 + ++ ++ +++ ++++ ++++ ++++ 

Highway Driving 0 00 + + + + + 

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Hybrid Technology Area Considerations

Technology Assessment – Hybridized Powertrains

 Hybrid technology largely available now but needs cost reduction efforts to 

financial justification to consumers; largely expected to come through volum(economy of scale) & commodity mindset (economy of scale)

& commodity mindset

 Pace of development

– Change in fuel prices (or fuel tax legislation) could dramatically accelera

hybrid development and implementation. CAFE requirements will drive 

development in near term development in near term.

– Li-ion battery development largely in flux as well, but not necessarily an 

hybrid development, as NiMH is sufficient (i.e., Li-ion required for EV ancurrent strong hybrid technology)

 Many hybrid applications today being consumed by early (technology) adop

those focused on environmental impact and energy independence

– Hybridization still difficult to justify based purely on financial business ca

– Governmental le

gislation (e.

g., CAFE or CO

2 g (g , re

quirements) lar

gel

y res

p

2 q ) gy p

hybrid investment

 Benefits of hybrid technologies are generally independent of component te

(Electrical machine & energy storage) due to good round trip efficiency attrtechnologies.

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

technologies.

– Some small correlation exists, and with parameterization in model, oppo

sweep parameters to evaluation sensitivity. 
Micro Hybrid: Stop-Start

Technology Assessment – Hybridized Powertrains

Technology Description and Status

 Concept: Most basic of hybridization, allows for simple engine shut-off during 

Ratings o

idle periods; typically employs enhanced starter motor and limited use of driver 

comfort features during engine off (e.g. Radio, some heat, but no A/C)

 Base Functioning: Decreases wasted fuel by minimzing idling but provides no 

benefit for highway use or when air conditioning is required/desired

 CO Benefit: 3 5% over city cycles 0% over highway Marke

Effectivenes

Availabilit

 CO2 Benefit: 3–5% over city cycles. 0% over highway Costs: This is the lowest cost hybrid system and can be implemented relatively 

quickly on most vehicles on the market today. Stop-start systems are somewhat mature and readily available off the shelf. Further development will yield increased user acceptance (e.g. Transparent integration with little to no detriment to e isting ehicles in terms of NVH acceleration etc )

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Stop-start technology can be applied to almost all vehicles including passenger 

cars, medium and heavy duty trucks and even off-highway or agricultural vehicles

Visualizatio

detriment to existing vehicles in terms of NVH, acceleration, etc.)

vehicles.

 Benefits are limited, though, to vehicle applications that have some periods of 

idling. For example, long-haul trucks with extended highway operation will see little to no benefit. Similiarly, as air conditioning is not available during engine-off periods, users may experience some degradation in performance that could be unacceptable

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

unacceptable.
Mild Hybrid: Integrated Belt Starter-Generator (IBSG)

Technology Assessment – Hybridized Powertrains

Technology Description and Status

 Concept: The alternator is replaced with a new electric machine that can 

Ratings o

provide lauch assist as well as replacing the electrical supply of the alternator 

during normal vehicle operation. Typically this machine can also be used for energy recapture during braking.. 

 Base Functioning: Provides stop-start functionality (see “Stop-Start“ slide) as 

well as electric launch assist, which, when cou

pled to a dedicated energy Marke

Effectivenes

Availabilit

,, p gy

storage system with a charge sustaining strategy, can decrease fuel consumption during acceleration from a stop.

 CO2 Benefit: 3–7% over city cycles, ~0% over highway cycles Costs: Several IBSG systems are on the market today so development costs 

are largel s nk P rchase costs of the s stem are no decreasing as ol me

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability IBSG systems can be applied to a wide variety of applications including 

Visualizatio

are largely 

s

unk. 

P

urchase costs of the

s

ystem are now decreasing as vol

ume

grows such that financial payback may be viable soon.

passenger cars and medium and heavy duty trucks with benefits seen in city cycles. Due to the small size of the IBSG, relatively limtied ability to downsize, 

but some bennefit.

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Mild Hybrid: Integrated Crank Starter-Generator (ICSG) 

[also known as Integrated Motor Assist (IMA)]

Technology Assessment – Hybridized Powertrains

Technology Description and Status

 Concept: An e-machine is added to or replaces the flywheel. Larger than the 

Ratings o

e-machine used in an ISBG, the motor can provide lauch assist and regenerative braking as well additional power during a variety of vehicle operating modes and, thus, is applied in conjunction with a downsized engine. 

 Base Functioning: Provides stop-start functionality and launch assist. This 

provides the opportunit

y to use of a smaller en

gine to increase efficienc

y Marke

Effectivenes

Availabilit

p ppy g ythroughout the operating range of the vehicle, not just during launch from a stop. 

 CO2 Benefit: 16–20% on city cycles, ~0% on highway cycles Costs: ICSG systems are on the market today so development costs are 

largel s nk P rchase costs of the s stem are no decreasing as ol me

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability ICSG systems can be applied to a wide variety of applications including

Visualizatio

largely 

s

unk. 

P

urchase costs of the

s

ystem are now decreasing as vol

ume

grows and the greater fuel efficiency is great enough to provide reasonable financial payback today.

 ICSG systems can be applied to

a wide variety of applications including

passenger cars and medium and heavy duty trucks with benefits mostly seen in city drive cycles. The reduced engine sizes enabled by the hybrid system provide highway bennefits.

 Typically, these systems have been used with a CVT to avoid Torque converter 

losses

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

losses.
Full Hybrid: P2 parallel Hybrid

Technology Assessment – Hybridized Powertrains

T h l d St t Technology and Status

 Concept: An e-machine is inserted between the engine and the transmission, 

typically with a clutch between the engine and e-machine. Larger than the emachine used in an ISBG, the motor can provide lauch assist and regenerative 

braking as well additional power during a variety of vehicle operating modes 

Ratings o

and, thus, is applied in conjunction with a downsized engine. 

 Base Functioning: Provides stop-start, electrical launch, and launch assit. This 

optimizes the use of a smaller engine to increase efficiency throughout the operating range of the vehicle, not just during launch from a stop. 

 CO2 Benefit: 18–22% on city cycles ~0% on highway cycles (downsizing Marke

Effectivenes

Availabilit

 CO2 Benefit: 18 22% on city cycles, 0% on highway cycles (downsizing

offers bennefits)

 Costs: No P2 parallel hybrids are in production today, so development costs 

will still need to be invested, however parts bin exists today. The cost of the system is higher thana ICSG, however, the system has only 1 electrical machine so its costs should be lower than more advanced hybrids

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability

 P2 hybrids can be applied to a wide variety of applications including passenger 

Visualizatio

so its costs should be lower than more advanced hybrids

cars and medium and heavy duty trucks with benefits seen mostly in city drive cycles. The reduced engine sizes enabled by the hybrid system provide highway bennefits.

 System can be used with an AT, however, To maintain efficiency, a CVT or DCT 

should be used to avoid Torque converter losses.

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Full Hybrid: Input Power Split Hybrid

Technology Assessment – Hybridized Powertrains

Technology Description and Status

 Concept: Power split hybrids use an electric machine directly integrated into 

Ratings o

the transmission, and either provide an additional input parallel to the engine or 

act as an additional output from the transmission. Both varieties permit an electric (only) operating mode. 

 Base Functioning: Power split encompasses all of the aforementioned 

technology

providin

g sto

p-start, launch, and en

gine downsizin

g benefits in 

plus Marke

Effectivenes

Availabilit

gy p g p ,,g g p

the ability to provide an electric-only operating mode, when used in conjunction 

with the appropriate electric accessories.

 CO2 Benefit: 22–33% in city driving, some bennefit in highway driving Costs: Development is ongoing with room for both performance improvement 

and cost red ction b t initial s stems are no idel spread in the market place

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability As a full or strong hybrid, the power split hybrid offers very good benefit of

Visualizatio

and cost red

uction

b

ut initial

s

ystems are now widely spread in the market place

(e.g. Ford Fusion and Escape and Toyota Prius).

As

a full or strong hybrid, the power split hybrid offers very good benefit of

hybridization

 Challange with cost due to two electrical machine solution. Fuel efficiency improvement is found across the range and in all operating cycles 

since engine downsizing and electric accessories optimize performance and efficiency of the combustion engine and the vehicle as a whole

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

efficiency of the combustion engine and the vehicle as

a whole
Full Hybrid: Two-Mode Power Split

Technology Assessment – Hybridized Powertrains

Technology Description and Status

 Concept: Two-Mode hybrids use electric machines (usually two) directly 

Ratings o

integrated into the transmission for maximum operating flexibility with operation as input powersplit or compound power split gearing configuration via clutch actuation.

 Base Functioning: Two-Mode encompasses all of the aforementioned 

technology

providin

g sto

p-start, launch, and enables en

gine downsizin

g benefits Marke

Effectivenes

Availabilit

gy p g p ,, g g

in plus the ability to provide an electric-only operating mode, when used in 

conjunction with the appropriate electric accessories.

 CO2 Benefit: 22–33% in city drive cycle. Some bennefit in highway driving Costs: Development is ongoing as Two-Mode hardware is still very expensive, 

pro iding little commercial pa back to the c stomer c rrentl Ho e er T o

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability As a full or strong hybrid the Two Mode hybrid offers maximum benefit of

Visualizatio

pro

viding little commercial pa

yback to the

c

ustomer

c

urrently. Ho

w

e

ver, Tw

oMode systems are proliferating in the market place with GM offering truck and 

SUV variants now, and BMW, Mercedes and Chrysler products coming soon).

 As

a full or strong hybrid, the Two-Mode hybrid offers maximum benefit of

hybridization but is also the most costly and complex of all architectures to 

implement. 

 Fuel efficiency improvement is found across the range and in all operating cycles 

since engine downsizing and electric accessories optimize performance and efficiency of the combustion engine and the vehicle as a whole

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

efficiency of the combustion engine and the vehicle as

a whole
Full Hybrid: Series Electrical

Technology Assessment – Hybridized Powertrains

Technology and Status

 Concept: Series electrical hybrid systems include two electrical machines and 

Ratings o

a battery. One EM is located on drvie axle and is sized for peak loads, and second EM is located on engine and is sized for average loads.

 Base Functioning: Energy storage system enables load averageing and 

engine off operation. As driveline and engine are decoupled, engine can be single point engine or operate on best-efficiency line engine. Marke

Effectivenes

Availabilit

gp g p y g

 CO2 Benefit: 22–33% in city drive cycle. Potenally reduced in highway 

driving, depending on degree of reduced engine size enabled.

 Costs: The cost implications of two electrical machines (one large and one 

small) and a battery have limited the appeal of this technology to the industry.

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability

 Series hybrids are not currently in production, and technology approach has not 

been embraced by industry (has been championed in research community) due

Visualizatio

B tt been embraced by industry (has been championed in research community) due

to the costs associated with multiple large electrical machine size & a battery.

 With introduction of EVs, opportuntity for industry to gain comfert with series 

electrical and increase volumes to reduce costs.

Battery

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Full Hybrid: Series Hydraulic

Technology Assessment – Hybridized Powertrains

Technology Description and Status

 Concept: Hydraulic accumulators are used to aid in deceleration, then the 

stored energy is released back into the vehicle for launch assist using hydraulic

Ratings o

stored energy is released back into the vehicle for launch assist using hydraulic

pumps connected to an axle or transmission.

 Base Functioning: Kinetic energy that would otherwise be translated to heat in 

the braking system is recaptured for later use. Can also be used for engine downsizing. Marke

Effectivenes

Availabilit

 CO2 Benefit: 22–33% in city drive cycle. Potenally reduced in highway 

driving, depending on degree of reduced engine size enabled.

 Costs: Hydraulic hybridization is still in early development with only a few 

demonstration vehicles on the road today. Application of hydraulic hybridization is much less costly in vehicles that already employ extensive hydraulic systems 

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Hydraulic hybrid systems typically suggested in niche applications such as refuse

Visualizatio

y y p y y y

for specific vocations (e.g., garbage compactor) and increased efficiency is limited to vocations with extreme stop-start cycles and agressive deceleration.

 Hydraulic hybrid systems typically suggested in niche applications such as refuse

trucks, where large power required for regeneration is well suited to hydraulic systems. 

 Potentially reduced fuel economy in highway driving, depending on degree of 

reduced engine size enabled.

 Hydraulic hybrid technology development has been significantly slower than

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

 Hydraulic hybrid technology development has been significantly slower than

electrical hybrid technology development rate, and use of hydraulic driveline is not consistent with other high profile technology initiatives such as EVs, PHEVs and vehicle electrification. 
Outline

 Introduction Spark ignited engine technologies Diesel engine technologies Hybrid vehicle technologies Transmission technologies Transmission technologies Vehicle technologies Conclusions

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Technology Area Overview

Technology Assessment – Transmissions

 For this technology area, we have the following thoughts for the sit

2020–2025: 

– North American market will continue to be dominated by automatic transmissions for IC engines 

increasing launch device efficiency and smart kinematics design increasing launch device efficiency and smart kinematics design

– Higher presence of more fuel efficient AMT’s and DCT’s expected

– Increase in simplified single/two speed gearboxes for hybrid applications

– CVT development expected to be on the decline in the North American market (although still be

Japanese market)

 Pace of development

– Development of AMT and DCT technology expected to be implemented from European and Jap– Detroit 3 actively pursuing DCT technology, with teaming arrangements established between OE

develop technologies develop technologies

– Improvements for automatic transmissions are on-going with new technologies being implement

vehicles and then cascaded down to other vehicle classes.

– Single/two speed gearboxes for hybrid applications require minimal investment and lead time

 Comparison to baseline Comparison to baseline

– Given 94% of North American transmissions are automatic, improvements in efficiency (resulting 

improvements) will be realized through: 

• Smart kinematics design (2–5%)• Component efficiency improvement or alternative technologies (3%)

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

• Launch devices (2–6%)• Dry sump technology (2%)

– Estimates of improvement depend on the drive cycle, are not simply additive, and are subject to 
Transmission Summary

Technology Assessment – Transmissions

 Hydraulically operated, using a fluid coupling or 

torque converter and a set of gearsets to provide 

f ti

 AMT operates similarly to a ma

except that it does not require c

Automatic (with Torque Converter) AMT (Automatic Manual Tr

a range of gear ratios

 Decrease in efficiency associated with viscous 

losses from torque converter

except that it does not require c

shifting by the driver. 

 Automatic shifting is controlled 

(shift-by-wire) and performed bsystem or electric motor. 

 P hift lit h l d d 

Poor shift quality has excluded 

from the study

 Rather than using gears, the CVTs in 

currently available vehicles utilize a 

pair of variable-diameter pulleys 

 Uses two separate clutches 

for even and odd gear sets

 Eliminates the use of a

CVT (Continuous Variable Transmission) DCT (Dual Clutch Trans

p p yconnected by a belt or chain that can produce an infinite number of engine/wheel speed ratios. 

 Reliability and efficiency issues 

prevent this technology from

Eliminates the use of a

torque converter and utilizes either wet or dry type launch clutches

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

prevent this technology from

roadmap development
Technology Area Summary

Technology Assessment – Transmissions

 Launch Devices

– Wet Clutch

– Damp Clutch– Dry Clutch– Multi-damp q er Torque converter– Magnetic clutch

 Shifting Clutch Technology S t Ki ti D i Smart Kinematic Design Dry Sump Efficient Components Super Finishing Lubrication

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Launch Device: Wet Clutch

Technology Assessment – Transmissions

Technology and Status

 Concept: provides torque transmission during operation by means of friction 

Ratings of T

action between surfaces wetted by a lubricant 

 Base Functioning: Increases fuel effieciency by reducing hydraulic parasitic 

losses over a conventional torque converter when it is slipping.

 CO2 Benefit: Benefit realized at launch and during transient driving Marke

Effectivenes

Availabilit

 Costs: up to 20% less than a conventional torque converter Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Technology applicable to planetary, parallel-axis, AMT and dual clutch 

transmissionsR i i l l b i ti t l b i t t ti f b l b i ti

Visualizatio

 equires special lubrication system or lubricant to satisfy gearbox lubrication 

requirements and actuation requirements.

 Parasitic losses of lubrication system diminish overall benefit over torque 

converter.

 Improvement in city driving, little for highway

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture: www.cerom.ls

*Note: Effectiveness relates to improvement in transmission efficiency
Launch Device: Damp Clutch

Technology Assessment – Transmissions

Technology and Status

 Concept: Similar concept as a wet clutch but only a limited spray is applied to 

Ratings o

achieve cooling

 Base Functioning: Still requires a lubrication system but is more efficient due 

to controlled environment (less windage and churning)

 CO2 Benefit: Similar benefits as a dry clutch Marke

Effectivenes

Availabilit

 Costs: ~$25 above wet clutch Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visu

 Applicable to most automatic transmissions – best of both worlds, efficiency of a 

dry clutch matched with the longevity and higher torque capacity of a wet clutch

 A f th th l h d i th i i ffi i i li bl tl t As for the other launch devices, the increase in efficiency is applicable mostly to 

city driving.

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture: w

*Note: Effectiveness relates to improvement in transmission efficiency
Launch Device: Dry Clutch Advancements

Technology Assessment – Transmissions

Technology and Status

 Concept: Standard manual clutch require advanced materials to provide heat 

Ratings o

dissipation to be used in automatic applications or electric assist (on/off) to prevent slipping

 Base Functioning: Thermal load resulting from engagement prevent dry 

clutches from being used in high torque and heavy duty cycle applications but are more effiecient since the

y don‘t re

quire an additional lubrication s

ystem and Marke

Effectivenes

Availabilit

y q

y

significatntly reduce parasitic shear fluid losses.

 CO2 Benefit: Benefit realized at launch and during transient driving Costs: Dry Clutch materials +10-20%, Electric motor $1500

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Advancements in material or electric assist could enable this technology to be 

used in larger vehicles and more severe duty cyclesCit d i i i t

Visu

 City 

driving improvement

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture: w

*Note: Effectiveness relates to improvement in transmission efficiency
Launch Device: Multi-Damper Torque Converter

Technology Assessment – Transmissions

Technology and Status

 Concept: Dampers in torque converter enable lower lock-up speed

Ratings o

 Base Functioning: The more fuel-intensive period of hydrodynamic power 

transfer is shorter

 CO2 Benefit: Increase in efficiency from reduced slippage and smoother 

shifting Marke

Effectivenes

Availabilit

 Costs: Increase Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visu

 Multi-damper systems provide earlier much early TC clutch engagement, 

however, drivability and limitied ratio coverage have limited the deployment of this technology. 

 Technology is best suited for deployment in 6 speed tranmssions and required to 

be integrated during transmission design.

 Technology provides improved efficiency for automatic transmissions at an 

increase in cost.

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Pictu

*Note: Effectiveness relates to improvement in transmission efficiency
Launch Device: Magnetic Clutch

Technology Assessment – Transmissions

Technology and Status

 Concept: Using magnetic force to engage the clutch

Ratings o

 Base Functioning: Non contact engagement launch device to prevent frictional 

losses

 CO2 Benefit: Benefit realized at launch and during transient driving Costs: Cost impact unclear due to technology in early stage of development Marke

Effectivenes

Availabilit

Techn

ology Applicability

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

ec o ogy pp cab ty

Visu

 Technology is still under early development and it use will be constrained by 

limited torque transfer capabilities, uncertian reliability, and significant engineering 

development to mature.

 Offers opportuinty to remove hydraulic sub Offers opportuinty to remove hydraulic sub-system compoenets and associated system compoenets and associated

losses. Technology requires current draw to operate, thus idealy suited for highly electrified vehicles.

 Technology best suited to low torque applications with miniminal refinement 

vehicles and technology will need to be integrated in clean sheet transmissions with large ratio coverage

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture: w

with large ratio coverage.

*Note: Effectiveness relates to improvement in transmission efficiency
Shifting Clutch Technology

Technology Assessment – Transmissions

Technology and Status

 Concept: Utilizing high thermal capacity technolgoy to reduce plate count and 

Ratings o

lower clutch losses during shifting

 Base Functioning: Reduced number of plates for shifting process and reduced 

hydraulic cooling requirements result in increased overall transmission efficiency for similiar drivability. 

 CO Benefit: Through all driving conditions potentially including idle Marke

Effectivenes

Availabilit

 CO2 Benefit: Through all driving conditions potentially including idle Costs: similar to AMT cost

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visu

 Technology deployment required during transmission design phase and has been 

limited by industry prioritization t limited by industry prioritization to drivability over shift efficiency. drivability over shift efficiency.

 Technology will be best suited to smaller vehicle segments due to reduced 

drivability expectations – there will be a struggle to develop this technology for 

higher torque applications

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture: w

*Note: Effectiveness relates to improvement in transmission efficiency
Smart Kinematic Design

Technology Assessment – Transmissions

Technology and Status

 Concept: Using analysis to design for efficiency by selecting the kinematic 

Ratings o

relationships to optimize the part operational speeds and torques for efficiency

 Base Functioning: Large improvements in efficiency have been noted for 

clean sheet designs for 6-speed and 8-speed transissions

 CO2 Benefit: Increase in efficiency reduces fuel consumption Marke

Effectivenes

Availabilit

 Costs: Low cost – analysis part of design phase Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visu

 All applications and vehicle classes benefit from this design approach Benefits are realized in city and highway driving Benefits are realized in city and highway driving

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture

*Note: Effectiveness relates to improvement in transmission efficiency
Dry Sump

Technology Assessment – Transmissions

Technology and Status

 Concept: Dry sump lubrication systerm keeps the rotating members out of oil

Ratings o

 Base Functioning: Reduces losses due to windage and churning CO2 Benefit: Fuel efficiency increases with transmission efficiency Costs: Adds cost (~$50/pc) but as technology matures cost will go down

Marke

Effectivenes

Availabilit

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visu

 All applications and vehicle classes benefit from this lubrication design Most benefit achieved at higher speeds Most benefit achieved at higher speeds

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture: w

*Note: Effectiveness relates to improvement in transmission efficiency
Efficient Components

Technology Assessment – Transmissions

Technology and Status

 Concept: Continous improvement in seals, bearings and clutches all aimed at 

Ratings o

reducing drag in the system

 Base Functioning: A reduction in drag with out a reduction in performance 

increases the efficiency of the transmission

 CO2 Benefit: Fuel efficiency increases with transmission efficiency Marke

Effectivenes

Availabilit

 Costs: New materials, designs are expensive when they hit market (20%) Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visu

 All applications and vehicle classes benefit from this lubrication design City and highway driving fuel effieciency improvements City and highway driving fuel effieciency improvements

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture: w

*Note: Effectiveness relates to improvement in transmission efficiency
Super Finishing

Technology Assessment – Transmissions

Technology and Status

 Concept: Chemically treating internal gearbox parts for improved surface finish

Ratings o

 Base Functioning: Improved surface finish reduces drag which increases 

efficiency

 CO2 Benefit: Fuel efficiency increases with transmission efficiency Costs: Currently ~$0.50/part Marke

Effectivenes

Availabilit

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Visu

 All applications and vehicle classes benefit from this lubrication design City and highway driving fuel effieciency improvements City and highway driving fuel effieciency improvements

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture: ww

*Note: Effectiveness relates to improvement in transmission efficiency
Lubrication

Technology Assessment – Transmissions

Technology and Status

 Concept: Development in the area of lubrication properties is ongoing

Ratings o

 Base Functioning: New developments in reducing oil viscosity while 

maintaining temperature requirements will have a positive effect on transmission efficiency

 CO2 Benefit: Benefit across all vehicle classes and operating conditions Marke

Effectivenes

Availabilit

 Costs: TBD Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability

 All applications and vehicle classes benefit from improved lubrications City and highway driving fuel effieciency improvements City and highway driving fuel effieciency improvements

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

*Note: Effectiveness relates to improvement in transmission efficiency
Transmission Technology Applicability

Technology Assessment – Transmissions

Launch Technology

Wet Clutc

Dry Clutc

Damp Clu

Multi Dampe

Torque Conv

Magnetic C

Shifting Clu

Technology

Smart Kinem

Desigh

Dry Sum

ch

ch

tch

er 

verter

lutch

utch 

y

matics 

mp

B

Automatic with Torque Converter

X X X X 

Base A t ti M l T i i

X

X

X

X

X

Transmission 

System

Automatic 

Manual Transmission

X

X

X

X

X

Dual Clutch X X ? X X X CVT

X

X X X X 

Small Car (Ford Focus) X X ? X X X Standard Car (Toyota Camry) X X X X X X 

Small MPV (Saturn Vue)

X X X X X X 

Vehicle 

Classification Full-sized car (Chrysler 300C)

X

X X X X 

Large MPV (Dodge Grand Caravan) X

X X X X 

Truck (Ford F150)

X

X X X X 

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Heavy light-duty truck (Ford F250/F350) X

X X X X 
Outline

 Introduction Spark ignited engine technologies Diesel engine technologies Hybrid vehicle technologies Transmission technologies Transmission technologies Vehicle technologies Conclusions

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Vehicle Summary (1 of 3)

Technology Assessment – Vehicle

 For a given set of performance targets, a heavy 

vehicle will require more power, thus consume 

R d ti i i ht

 Dependant on the compromise

manufacturing flexibility, passen

d ti i i ht l 

Mass Reduction: Material Substitution Mass Reduction: Component 

more energy. Reductions in weight can occur 

through material substitution (e.g., steel to aluminum).

reductions in weight can also o

component optimization.

 Vehicle Aerodynamics; have a greater influence 

on drive-cycles with a higher average speed. Dependant compromises chosen, significant 

 Gains from active aero through 

apertures, vehicle ride height copossible.

Aerodynamics: Passive Aerodynamics: Act

opportunity is available in shape development (passive aero). 

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Vehicle Summary (2 of 3)

Technology Assessment – Vehicle

 Thermo-Electric Generation (TEG); use the heat 

in exhaust gas (waste energy) to generate 

l t i it i th S b k ff t Thi b

 Reduced heat loading; by insul

the vehicle, using alternative te

l i d til ti t 

Thermo-Electric Generators HVAC System Load Re

electricity using the Seebeck effect. This can be 

used to drive ancillaries etc, reducing the power requirement of the engine.

glazing and ventilation systems

significantly reduce the energy the HVAC systems.

PHEW!

 On-going investment in research by the tire 

companies is reducing the energy necessary to drive a vehicle forwards.

Tire Rolling Resistance

 Improved engine thermal contro

coolant pump, electric fans and valve.

Intelligent Cooling Sy

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Vehicle Summary (3 of 3)

Technology Assessment – Vehicle

 Replaces FEAD-driven hydraulic steering 

assistance with electric motor. Increasingly 

l t i ll d di

Electric Power Assisted Steering

prevalent in small and medium passenger cars 

(particularly in Europe).

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Mass Reduction: Substitution

Technology Assessment – Vehicle

Technology and Status

 Concept: Replacement of current material with HSS/AHSS/Al/Mg/CF* etc.

Ratings 

 Base Functioning: Fuel economy improvements are through a reduction in the 

rolling resistance losses, i.e., the frictional force is reduced by reducing the normal force (weight) of the vehicle. A secondary effect is that a lighter vehicle with lower inertia can use a smaller powertrain to accelerate that reduced mass.

 CO Benefit: A 10% vehicle mass reduction can deliver a 2 7 4 1% fuel Marke

Effectivenes

Availabilit

 CO2 Benefit: A 10% vehicle mass reduction can deliver a 2.7–4.1% fuel

economy improvement with constant engine size, but a 4.7–6.7% improvement when the engine is downsized to maintain constant performance.

 Costs: Dependant on material selected and price reductions with increasing 

volume supply.

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Direct benefit, in growing market use, in all market sectors, and all powertrain 

variations.E bl i d i i

Visualization

 Enables engine down-sizing. Lowers inertia.

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* HSS=High Strength Steel, AHSS=Advanced High Strength Steel, Al=Aluminum, MG=Magnesium, 

CF=Carbon Fiber

Picture: www.automot

Aluminum
Mass Reduction: Optimization

Technology Assessment – Vehicle

Technology and Status

 Concept: Optimization of vehicle, vehicle systems and components for weight, 

Ratings 

not style, manufacturing flexibility or passenger volume. Examples; 30% wheel mass-saving, change from body-on-frame to unibody for trucks.

 Base Functioning: Fuel economy improvements are through a reduction in the 

rolling resistance losses, i.e. the frictional force is reduced by reducing the 

normal force, (wei

ght) of the vehicle. A secondar

y effect is due to a li

ghter Marke

Effectivenes

Availabilit

,( g )

y

g

vehicle with lower inertia can use a smaller powertrain to accelerate that reduced mass.

 CO2 Benefit: 10% mass reduction can improve fuel economy by 6.7%. Costs: Can be a cost REDUCTION; optimizing an aluminum wheel with a 

30% red ction in eight can gi e a cost SAVING of 25 40%

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Has the potential to be applied to many areas of a vehicle. Direct benefit, in 

growing market use, in all market sectors, and all powertrain variations.E bl i d i i

Visualization

30% red

uction in weight can gi

v

e

a cost SAVING of 25

–40%.



Enables engine 

down-sizing.

 Lowers inertia. Additional significant opportunity exists with vehicle size. Passenger vehicles 

have grown SIGNIFICANTLY in the past 3 decades. The manufacturers say that this is due to meet 'market requirements'. If vehicles can be forced to become 

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smaller with each successive iteration, rather than bigger, this equates to lighter. This has the additional benefit of smaller frontal area, thus (aero details remaining constant), the CdA reduces, thus the energy to drive the vehicle through the air is reduced. Picture: various sourc
Aerodynamics: Passive

Technology Assessment – Vehicle

Technology and Status

 Concept: Substantial opportunity still exists to lower the coefficient of drag (CD) 

Ratings 

through body shape development, smoothing under-floors, faring-in wheels etc.

 Base Functioning: A reduction in CD has a direct affect on reduction of the 

force required to enable forward motion. As drag force is dependant on the square of vehicle speed, at higher speeds, the fuel economy gain is increased.

 CO Benefit: A 10% reduction in drag can give a 2 5% improvement in fuel Marke

Effectivenes

Availabilit

 CO2 Benefit: A 10% reduction in drag can give a 2.5% improvement in fuel

economy.

 Costs: For most items, such as under-floor shields, wheel farings etc, there is 

some associated on-cost, some items would be low cost or free, such as body shape, and some, such as narrower tires, should be a cost reduction.

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability The faster the vehicle travels, the greater benefit this is. Most effective where 

significant freeway travel is required. Suits all powertrain variations.

D d t th d h h i ht lt th it l

Visualization

 Dependant on methods chosen, may have some weight penalty, thus city-only 

vehicles may be penalized.

 Additional significant opportunity exists with vehicle size. Passenger vehicles 

have grown SIGNIFICANTLY in the past 3 decades. The manufacturers say that this is due to meet "market requirements". Safety not withstanding, if vehicles 

b f d t b ll ith h i it ti th th

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

can be forced to become smaller with each successive iteration, rather than 

bigger, frontal area, thus drag force, will reduce (for the same CD).

 Suggested possible targets; sedans CD=0.25, SUVs CD=0.30, minivans CD=0.29, 

hatchbacks CD=0.28. Picture: www.green.au
Aerodynamics: Active

Technology Assessment – Vehicle

Technology and Status

 Concept: Opportunity exists to reduce overall vehicle drag through improved 

Ratings 

control of drag-affecting features (cooling apertures, ride-height etc). Radiator grill sizing is designed for maximum thermal rejection; at high ambients / high vehicle loads. Most of the time, the majority of vehicles need much less cooling. Thus openings can be significantly reduced, reducing vehicle drag.

 Base Functioning: A reduction in CD has a direct affect on reduction of the Marke

Effectivenes

Availabilit

g D

force required to enable forward motion. As drag force is dependant on the square of vehicle speed, at higher speeds, the fuel economy gain is increased

 CO2 Benefit: Active cooling aperture control could give an 8-10% vehicle drag 

reduction. A 10% reduction in drag can give a 2.5% improvement in fuel 

economy

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability The faster the vehicle is required to travel, the greater benefit this is. Most 

effective where significant freeway travel is required Suits all powertrain

Visualization

y

 Costs: Some associated on-cost

effective where significant freeway travel is required. Suits all powertrain

variations

 Has some (small) weight penalty, thus city-only vehicles may be penalized; 

however, city-only cars could have altered drive-cycles, as unlikely to need to drive up mountains in Death Valley, at GVWP t ti l i t th h li t t t l C 0 008 f

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

 Potential improvements through cooling system aperture control CD 0.008 for 

small and medium cars and 0.03 for large passenger cars and SUVs

 Where available, ride height reduction with increasing speed reduces the effective 

frontal area, and increases tire coverage Picture: www.parkview
Thermo-Electric Generators

Technology Assessment – Vehicle

Technology and Status

 Concept: Convert temperature differentials directly into electrical energy using 

Ratings 

the Seebeck effect (temperature differential creates current/voltage same as in thermocouples). A Thermo-Electric Generator (TEG) consists of hot side heat exchanger(s), cold side heat exchanger(s), thermoelectric materials (type and size depends on operating temperature) and compression assembly.

 Base Functioning: 40% of energy from fuel is lost as exhaust heat. TEGs take Marke

Effectivenes

Availabilit

g gy

advantage of high engine exhaust gas temperatures (waste energy) to generate electricity. This can be used to drive accessories or supplement power to an electric motor.

 CO2 Benefit: Currently expected to give a 5% fuel economy improvement, 

including the effects of the increased vehicle mass from the system (expected 

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Well suited to automotive application Recovers some waste energy; which is up

Visualization

g y ( p

to be in range of stop-start, brake regen, FEAD electrification).

 Costs: Target cost $100/% FE improvement; currently more than this.

 Well suited to automotive application. Recovers some waste energy; which is up

to 40% of the energy from burning fuel.

 More effective at higher temperature differences, thus closer to the engine*, and 

at high engine loads.

 Has some weight penalty, however the energy developed is expected to more 

than offset this

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than offset this.

 Currently under development by BSST, Ford, BMW, Visteon and others. Material 

development underway. Possible to be on production vehicles around 2015.

* May give some packaging challenges

Picture: www.customt
Reduced HVAC System Loading

Technology Assessment – Vehicle

Technology and Status

 Concept: Increasingly aerodynamic vehicles typically have larger front and rear 

Ratings 

windows (for the same class of vehicle). This increases solar loading. Improved thermal insulation reduces solar loading in the Summer and heat loss in the Winter.

 Base Functioning: Reduced thermal loading/heat loss reduces the energy 

re

quired b

y HVAC for coolin

g/heatin

g. Insulated 

panels, GFPs*, doubleglazing, Marke

Effectivenes

Availabilit

q y g g p, , g g,

reflective films, active ventilation, reduced thermal mass are all possible methods of realizing this. Optimization then enables smaller A/C components.

 CO2 Benefit: Suggest 8–10%, application dependant. May enable a doubling 

of fuel economy. Recent introduction of SC03 drive cycle will clarify A/C effects.

Costs Undefined b t e pected to impro e mpg (or range) for marketabilit

Penetratio

Curren

**Maturit

Long-Term 

Cost Viabilit

Technology Applicability Technology based on building applications and applies them to automotive use.

Visualization

 Costs: Undefined, b

ut e

xpected to impro

v

e mpg (or range) for marketability. 

Use of SC03 cycle may increase demand for reduced HVAC load.

Base

 VERY applicable to EVs, hybrids and high-mileage (mpg) vehicles, which are 

most sensitive to accessory usage as a percentage of the overall vehicle load. Increases mileage and range.

 The insulation on it's own has some weight penalty, however it allows reduction in 

the sizing of the HVAC components, so potentially weight neutral.

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 Reduces degradation of interior panels due to thermal loading / IR attack; may 

allow for cheaper materials (offsets the cost of the insulation application).

* GFP=Gas Filled Panels **Commercially available technology, to be optimized in vehicles

Picture: NREL Vehicle AnOut Report
Reduced Tire Rolling Resistance

Technology Assessment – Vehicle

 Concept: Tire rolling resistance is driven by tread and carcass deformation and 

Technology and Status Ratings 

relaxation as the tire rotates and moves into contact with the road and away. Hysteresis in the tire from this deformation creates heat. Reducing the heat generation reduces the rolling resistance.

 Activity is underway to initiate rolling resistance information labeling for tires, 

similar to that alread

y shown for wear, traction and tem

perature 

performance. Marke

Effectivenes

Availabilit

y , pp

 Base Functioning: Fuel economy improvements are through a reduction in the 

rolling resistance losses. Lower rolling resistance reduces the amount of energy necessary to drive a vehicle forwards.

 CO2 Benefit: 10% rolling resistance reduction can improve fuel economy by 

2 3% C rrentl a ailable tires can offer 10 20% resistance red ction o er

Penetratio

Curren

**Maturit

Long-Term 

Cost Viabilit

2-3%. 

C

urrently 

a

vailable tires can offer 10-20% resistance red

uction

o

ver

conventional equipment. Further rolling resistance reductions of up to 50% are predicted to be available in the next 10-15 years.

 Costs: 10% rolling resistance approximates to $5 increase.

Technology Applicability

Visualization

Technology Applicability Research into rolling resistance, and reducing compromises with traction and 

wear are on-going.

 Applicable to ALL vehicle types. On medium-duty trucks changing from duallys to single-wides offer a further

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

 On medium-duty trucks, changing from duallys to single-wides offer

a further

benefit of a weight reduction, potentially allowing further improving fuel savings.

**Based on current technology, is moving forwards, in all vehicle markets. Further gains dependant on 

further research by the tire companies

Picture: Bridgestone; T
Intelligent Cooling Systems

Technology Assessment – Vehicle

 Concept: Use an electric coolant pump to remove the FEAD load. By 

Technology and Status Ratings 

removing it from FEAD also enables speed control, so rather than running at a fixed speed related to engine speed, can be run at a speed suitable to the current vehicle operating condition. Combines well with electric cooling fan and improved flow routing control.

 Base Functioning: Standard cooling systems are sized to provide cooling at Marke

Effectivenes

Availabilit

g g y p g

maximum load and ambient conditions. For majority of life of most vehicles, this is not required. No FEAD load, more efficient operating point control. Enables 

quicker warm up from cold. Reduces engine friction by enabling optimum engine temperature operation, rather than over-cooling (on passive systems).

 Further gains possible by controlled high temperature running, subject to 

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

g p y g p g, j

suitable NOx after-treatment systems being fitted (when necessary).

 CO2 Benefit: 3% fuel economy benefit on FTP cycle (assumes gain from 

electric fan etc already taken).

 Costs: Higher cost (possibly 5-6 times). Provides packaging flexibility as no 

l d t b i td

Visualization

longer needs to be engine mounted.

Technology Applicability Applicable to all vehicle types using IC engines Enables improved soak-condition control using the engine pump

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

p g g pp

Picture: Pierburg Pump 
Electric Power Assisted Steering (EPAS)

Technology Assessment – Vehicle

 Concept: Uses either rack or column-drive electric motors to assist driver 

Technology and Status Ratings 

effort. Replaces engine-driven pump, hoses, reservoir, fluid and hydraulic rack.

 Base Functioning: Removes load on FEAD for a system which isn't used for 

much of the time (unless cornering or at slow speed).

 CO2 Benefit: On typical usage cycle, expect 2–3% improvement Marke

Effectivenes

Availabilit

 Costs: Reduced warranty, reduced servicing. Cost competitive with hydraulic 

systems. Enables integration with safety systems such as lane departure 

warning, stability control (using "anti-skid" feedback) etc.

Penetratio

Curren

Maturit

Long-Term 

Cost Viabilit

Technology Applicability Currently not available for truck weight-class vehicles. Ongoing developments in 

this field are making this more likely for all vehicles in the 2020-2025 time-frameR i d f hi l ith EV f ti lit t ll th t b t d i ll

Visualization



Require

d for vehi

cles with any EV functionality, to allow them to 

be steere

d in all

situations

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305

Picture: www.trwauto.c
Vehicle Technology Applicability

ubstitution

nt Optimization

on

uction; Material Su

uction; Componen

mics; Passive

mics; Active

lectric Generators

ad Reduction

esistance Reductio

 Mass Red

 Mass Red

 Aerodynam

 Aerodynam

 Thermo-el

 HVAC Loa

Rolling Re

Small Car (Ford Focus) XXXXXXXStandard Car (Toyota Camry) XXXXXXXSmall MPV (Saturn Vue) XXXXXXX

ssification Full-sized Car (Chrysler 300C)

X

X

X

X

X

X

X

Large MPV (Dodge Grand Caravan) XXXXXXXTruck (Ford F150) XXXXXXX

Vehicle Clas

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Heavy light-duty truck (Ford F250/F350) XXXXXXX
Outline

 Introduction Spark ignited engine technologies Diesel engine technologies Hybrid vehicle technologies Transmission technologies Transmission technologies Vehicle technologies Conclusions

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305
Conclusions

 A substantial list of technologies that could offer some benefit to G

in the 2020–2025 timeframe was developed

 These technologies were assessed by the Ricardo team

– These assessments were reviewed with EPA

– Advisory pp Committee provided input to assessments

 Based on EPA feedback, the large list of potential technologies wa

the set considered further in the study, "Computer Simulation of LigVehicle Technologies for Greenhouse Gas Emission Reduction in 2025 Timeframe"

– These are described further in the main program report 

(Ricardo reference RD.10/157405.8)

CG001019 Prepared for SRA and EPA 30 September 2011 RD.11/342305