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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Evaluation of Fuel Consumption Potential of 

Medium and Heavy Duty Vehicles through 

Modeling and Simulation

Report to National Academy of Sciences

500 Fifth Street NW

Washington DC 20001

October 23, 2009

Contract Number: DEPS-BEES-001

Prepared by

Antoine Delorme, Dominik Karbowski, Phil Sharer
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Contents

1 Introduction ........................................................................................................................................10

2 Assumptions........................................................................................................................................11

2.1 Data Collection Process and Sources..........................................................................................11

2.2 Vehicle Model Description..........................................................................................................11

2.3 Vehicle Specifications..................................................................................................................13

2.3.1 Pickup Truck Class 2b..........................................................................................................13

2.3.2 Utility Truck Class 6.............................................................................................................13

2.3.3 Transit Bus...........................................................................................................................14

2.3.4 Line Haul Class 8..................................................................................................................14

3 Model Validation.................................................................................................................................16

3.1 Line Haul Class 8 Model Validation.............................................................................................16

3.1.1 Class 8 Validation with West Virginia University ................................................................16

3.1.2 Class 8 Validation with U.S.EPA ..........................................................................................18

3.2 Comparison between PSAT and Published Studies....................................................................18

3.2.1 Weight Reduction ...............................................................................................................19

3.2.2 Rolling Resistance and Aerodynamics Reduction ...............................................................19

3.2.3 Improved Transmission.......................................................................................................21

4 Importance of Metrics........................................................................................................................22

4.1 Limitations of Traditional Fuel Economy Measurements...........................................................22

4.2 Introducing Payload in Fuel Efficiency Measurements...............................................................23

5 Energy/ Power Flow Analysis..............................................................................................................25

5.1 Steady-state ................................................................................................................................25

5.2 Standard Drive Cycles .................................................................................................................28

6 Impact of Drive Cycles on Fuel Consumption .....................................................................................30

6.1 Impact of Real World Drive Cycles..............................................................................................30

6.1.1 Pickup Truck Class 2b..........................................................................................................30

6.1.2 Line Haul Class 8..................................................................................................................31

6.2 Issues Following the Trace ..........................................................................................................32

6.3 Potential Approach to Representing Fuel Efficiency ..................................................................33

7 Impact of Single Technologies on Fuel Consumption.........................................................................35

7.1 Aerodynamic ...............................................................................................................................35
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

7.1.1 Utility Truck Class 6.............................................................................................................35

7.1.2 Line Haul Class 8..................................................................................................................37

7.2 Type of Fuel.................................................................................................................................39

7.2.1 Pickup Truck Class 2b..........................................................................................................40

7.2.2 Utility Truck Class 6.............................................................................................................42

7.3 Tractor-trailer Hybridization .......................................................................................................44

7.3.1 Hybridization Principles ......................................................................................................44

7.3.2 Hardware Design.................................................................................................................45

7.3.3 Control Design.....................................................................................................................49

7.3.4 Standard Drive Cycles Results.............................................................................................50

7.3.5 Hybridization and Grade .....................................................................................................53

8 Impact of Combined Technologies on Fuel Consumption..................................................................58

8.1 Baseline Vehicle Assumptions.....................................................................................................58

8.2 Assumptions for Technology Improvements..............................................................................58

8.2.1 Vehicle Weight....................................................................................................................59

8.2.2 Aerodynamics .....................................................................................................................59

8.2.3 Rolling Resistance ...............................................................................................................59

8.2.4 Transmission .......................................................................................................................60

8.2.5 Engine..................................................................................................................................60

8.2.6 Hybrid..................................................................................................................................60

8.3 Fuel Savings for Various Technology Combinations...................................................................61

8.4 Comparison with TIAX Estimates................................................................................................65

9 Conclusion...........................................................................................................................................68

Appendix A – Overview of Drive Cycles......................................................................................................69

Appendix B – Energy / Power Flow.............................................................................................................76

Bus - 10% Load........................................................................................................................................76

Bus - 50% Load........................................................................................................................................78

Bus - 100% Load......................................................................................................................................80

Class 2b (Pick-up) - 10% Load..................................................................................................................82

Class 2b (Pick-up) - 50% Load..................................................................................................................84

Class 2b (Pick-up) - 100% Load................................................................................................................86

Class 6 (Pick-up and Delivery) - 10% Load...............................................................................................88
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Class 6 (Pick-up and Delivery) - 50% Load...............................................................................................90

Class 6 (Pick-up and Delivery) - 100% Load.............................................................................................92

Class 8 (Tractor-Trailer) - 10% Load........................................................................................................94

Class 8 (Tractor-Trailer) - 50% Load........................................................................................................96

Class 8 (Tractor-Trailer) - 100% Load......................................................................................................98

Bibliography ..........................................................................................................................................100
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

List of Tables

Table 1: Pickup Truck Class 2b Assumptions...............................................................................................13

Table 2: Utility Class 6 Truck Assumptions..................................................................................................14

Table 3: Transit Bus Assumptions...............................................................................................................14

Table 4: Line Haul Class 8 Truck Assumptions............................................................................................15

Table 5: Details of the Peterbilt Truck and Test Conditions .......................................................................16

Table 6: Peterbilt Truck PSAT Validation with Chassis (Test weight 56000 lb)...........................................17

Table 7: Navistar ProStar Truck PSAT Validation– Fuel Economy (mpg) ....................................................18

Table 8: Impact of Improved Transmission on Fuel Consumption for a Class 8 Truck ...............................21

Table 9: Vehicle Applications, Cycles and Weight Assumptions used in Metric Study ..............................22

Table 10: Utility Class 6 Truck Vehicle Assumptions for Drag Coefficient Study ........................................35

Table 11: Utility Class 6 Truck Drive Cycle and Steady States Assumptions for Drag Coefficient Study ....35

Table 12: Line Haul Class 8 Truck Vehicle Assumptions for Drag Coefficient Study...................................37

Table 13: Line Haul Class 8 Truck Drive Cycle and Steady States Assumptions for Drag Coefficient Study38

Table 14: Gasoline and Diesel Assumptions for the Pickup Truck Class 2b................................................40

Table 15: Fuel Consumption of Gasoline and Diesel Class 2b Vehicles for different Drive Cycles.............41

Table 16: Gasoline and Diesel Assumptions for the Utility Truck Class 6...................................................42

Table 17: Fuel Consumption of Gasoline and Diesel Class 6 Vehicles for different Drive Cycles...............43

Table 18: Summary of component sizes.....................................................................................................49

Table 19: Summary of Control Strategy......................................................................................................50

Table 20: Main Characteristics of Drive cycles ...........................................................................................51

Table 21: Assumptions for the Pickup Class 2b used in the study of Technology Combination impact on 

Fuel Consumption.......................................................................................................................................58

Table 22: Impact of Weight Reduction alone on Fuel Consumption for the Class 2b................................59

Table 23: Impact of Aerodynamics alone on Fuel Consumption for the Class 2b......................................59

Table 24: Impact of Rolling Resistance alone on Fuel Consumption for the Class 2b................................59

Table 25: Impact of Transmission alone on Fuel Consumption for the Class 2b........................................60

Table 26: Impact of Engine Efficiency alone on Fuel Consumption for the Class 2b..................................60

Table 27: Impact of Hybridization on Fuel Consumption for the Class 2b .................................................61
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

List of Figures

Figure 1: Example of Vehicle Model in PSAT ..............................................................................................11

Figure 2: PSAT GUI Example........................................................................................................................12

Figure 3: Peterbilt Truck..............................................................................................................................16

Figure 4: Peterbilt Truck Engine Fuel Rate Comparison .............................................................................17

Figure 5: Navistar ProStar Truck Engine Speed Comparison ......................................................................18

Figure 6: Impact of Gross Vehicle Weight Reduction on Fuel Consumption for a Class 8 Truck................19

Figure 7: Impact of Drag Coefficient Reduction on Fuel Consumption (Rolling Resistance fixed at 0.0055)

....................................................................................................................................................................20

Figure 8: Impact of Drag Coefficient Reduction on Fuel Consumption (Rolling Resistance fixed at 0.0045)

....................................................................................................................................................................20

Figure 9: Comparison of Fuel Economy and Fuel Consumption.................................................................22

Figure 10: Comparison of Payload Fuel Economy and Load Specific Fuel Consumption ...........................23

Figure 11: Comparison of Fuel Economy and Load Specific Fuel Consumption for a Class 8 Truck...........24

Figure 12: Power Flow Diagram for a Class 8 Truck (Steady-State, 65 mph, 70% load).............................26

Figure 13: Distribution of losses for a Class 8 Truck for Various Steady-State Speeds (70% load).............26

Figure 14: Distribution of losses for a Class 8 at 65 mph for 10% load (Right) and 100% Load (Left)........27

Figure 15: Distribution of losses for a Class 8, Bus, and Class 6 at 50 mph at GVWR.................................27

Figure 16: Distribution of losses for a Class 2b at 50 mph at GVWR ..........................................................28

Figure 17: Power Flow Diagram for a Bus on CBD cycle (50% load)...........................................................28

Figure 18: Power Flow Diagram for a Class 6 on HTUF cycle (75% load)....................................................29

Figure 19: Power Flow Diagram for a Class 8 on HHDDT 65 cycle (72% load)............................................29

Figure 20: Power Flow Diagram for a Class 8 on UDDS Truck cycle (72% load) .........................................29

Figure 21: Fuel Consumption as a function of Average Cycle Vehicle Speed for a sample of Real World 

Drive Cycles for a Pickup Class 2b...............................................................................................................30

Figure 22: Fuel Consumption as a function of Average Cycle Vehicle Speed for a sample of Real World 

Drive Cycles for a Class 8 Truck...................................................................................................................31

Figure 23: Automatic vs Manual Transmission for a Class 8 Truck.............................................................32

Figure 24: Fuel Consumption as a function of Steady State Vehicle Speeds for different Payloads..........33
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 25: Fuel Consumption as a function of Average Cycle Vehicle Speed for RWDC and Steady States 

for a Pickup Truck Class 2b..........................................................................................................................34

Figure 26: Impact of Drag Coefficient on Class 6 Fuel Consumption for various Drive Cycles and Steady 

States. .........................................................................................................................................................36

Figure 27: Percent of Fuel Saved by Reducing the Drag Coefficient for Each Drive Cycle and their Steady 

State Speed Counterpart for Class 6...........................................................................................................37

Figure 28: Impact of Drag Coefficient on Class 8 Fuel Consumption for various Drive Cycles and Steady 

States. .........................................................................................................................................................38

Figure 29: Percent of Fuel Saved by Reducing the Drag Coefficient for Each Drive Cycle and their Steady 

State Speed Counterpart for Class 8...........................................................................................................39

Figure 30: Fuel Consumption of Gasoline and Diesel Class 2b Vehicles for different Drive Cycles............42

Figure 31: Fuel Consumption of Gasoline and Diesel Class 6 Vehicles for different Drive Cycles..............44

Figure 32 – Schematic of the series-parallel configuration (full-hybrid) ....................................................47

Figure 33 – Schematic of the starter-alternator configuration (mild-hybrid) ............................................48

Figure 34: Fuel Consumption of conventional and hybrid trucks on standard cycles................................51

Figure 35: Fuel Saved by hybrid trucks with respect to conventional truck, on standard cycles...............52

Figure 36: Percentage of Braking Energy Recovered at the Wheels ..........................................................52

Figure 37: Average Engine Efficiency of conventional and hybrid trucks on standard cycles....................53

Figure 38: Sectional View of roads (partial) with the same maximum (3%) grade but 3 different hill 

periods........................................................................................................................................................54

Figure 39: Motor use uphill and downhill on a road with a hill period of 1 km, and 2.5% (left) or 4% 

(right) maximum grade, for a full-hybrid ....................................................................................................55

Figure 40: Section View of the actual trip for a conventional and a full-hybrid truck (4% maximum grade, 

1 km hill period)..........................................................................................................................................56

Figure 41: Fuel Consumption of Conventional, Mild-hybrid and full hybrid trucks on a sinusoidal road as a 

function of grade (and for various hill periods)..........................................................................................57

Figure 42: Fuel savings of hybrid trucks with respect to conventional truck as a function of maximum 

grade (for various hill periods)....................................................................................................................57

Figure 43: Fuel Consumption Savings by combining Aerodynamics and Weight improvements on a 

Conventional and Hybrid Baseline..............................................................................................................62

Figure 44: Fuel Consumption Savings by combining Aerodynamics, Rolling Resistance and Weight 

improvements on a Conventional and Hybrid Baseline. ............................................................................63

Figure 45: Fuel Consumption Savings by combining Aerodynamics, Rolling Resistance, Transmission and 

Weight improvements on a Conventional and Hybrid Baseline.................................................................64
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 46: Fuel Consumption Savings by combining all improvements on a Conventional and Hybrid 

Baseline.......................................................................................................................................................64

Figure 47: Fuel Consumption Savings by combining all technology improvements and hybridization on a 

Conventional Baseline.................................................................................................................................65

Figure 48: Fuel Consumption Savings of Improvement Package using Simulation or TIAX Estimates.......66

Figure 49: Fuel Consumption Savings of Improvement Package using Simulation or TIAX Estimates when 

using the same baseline Transmission........................................................................................................67
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Acknowledgement

This report was prepared for the National Academy of Sciences (NAS) as part of their prime contract 

with the National Highway Traffic Safety Administration (NHTSA) to assess fuel consumption

technologies for medium and heavy duty vehicles. The Transportation Research Board’s Division on 

Engineering and Physical Sciences was responsible for this work and assigned the effort to the Board on 

Energy and Environmental Systems. The project identifier is BEES-J-08-A. The NAS project director was 

Mr. Duncan Brown and the ANL principal investigator was Phil Sharer. Dr. Andrew Brown, Jr. chaired the 

NAS committee, initiated the project, and provided valuable guidance to help direct and focus ANL’s 

research along with the other members of the committee.

We would also like to thank all the companies who provided state-of-the-art component data and 

control logic to allow proper modeling and simulation of numerous medium and heavy duty trucks 

applications.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

1 Introduction

The main objective of this report is to provide quantitative data to support the Committee in its task of 

establishing a report to support rulemaking on medium- and heavy-duty fuel efficiency improvement. In 

particular, it is of paramount importance for the Committee to base or illustrate their conclusions on 

established models and actual state-of-the art data.

The simulations studies presented in the report have been defined and requested by the members of 

the National Academy committee to provide quantitative inputs to support their recommendations. As 

such, various technologies and usage scenarios were considered for several applications. One of the 

objective is to provide the results along with their associated assumptions (both vehicle and drive 

cycles), information generally missing from public discussions on literature search. Finally, the

advantages and limitations of using simulation will be summarized.

The study addresses several of the committee tasks, including:

- Discussion of the implication of metric selection

- Assessing the impact of existing technologies on fuel consumption through energy balance 

analysis (both steady-state and standard cycles) as well as real world drive cycles

- Impact of future technologies, both individually and collectively
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

2 Assumptions

2.1 Data Collection Process and Sources

The vehicle configurations and technical specifications described below were gathered from 

different sources. Various collaborations with component and vehicle manufacturers as well as 

literature review were considered. Although eight vehicle applications were modeled, only four of them 

were actually simulated due time constraints and greater interest from the Committee. Therefore, we 

will only provide the assumptions for these four vehicles: Pickup Truck (Class 2b), Utility Truck (Class 6), 

Transit Bus (Class 8) and Line Haul Truck (Class 8).

2.2 Vehicle Model Description

The Powertrain Analysis Toolkit (PSAT), developed by Argonne National laboratory, has been used to 

perform the vehicle simulations. PSAT is a forward-looking simulation package (also called driverdriven). A driver model follows any standard or custom driving cycle, sending a power demand to the 

vehicle controller, which, in turn, sends a demand to the propulsion components. Component models 

react to the demand and feed back their status to the vehicle controller, and the process iterates to 

achieve the desired result. Each component model is a Simulink/Stateflow box, which uses the Bond 

graph formalism. 

The components boxes are then “assembled” according to the powertrain configuration chosen by 

the user in the Graphical User Interface (GUI). 

Figure 1: Example of Vehicle Model in PSAT

Clutch command

Motor command

Shift command Brake command Engine command

Accelerator/Brake pedal

Controller Commands
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

The user-friendly GUI (Figure 2) allows the user to build a vehicle model within a few minutes. 

First, the user selects the drivetrain configuration. Each configuration is built according to user input so 

that vehicle architectures can be compared and the most appropriate one selected. More than 300 preselected configurations are available. Secondly, the user selects a model for each powertrain 

component, its initialization file, and tunes the initial parameters. Similarly, the controller strategy is 

chosen and tuned. The user then selects the combination of cycles to be simulated, and finally launches 

the simulation. Once the simulation is completed, the GUI provides the user with a wide range of plots 

and calculation, particularly useful for analysis. 

Figure 2: PSAT GUI Example

The plant models used in the study were based on steady-state lookup tables to represent the losses. 

The shifting algorithm and vehicle level control logics have been developed to be adapted to any 

combination of components and validated for several applications with OEMs. All the results are 

provided for hot operating conditions.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

2.3 Vehicle Specifications

2.3.1 Pickup Truck Class 2b

Because this vehicle class is close to its light duty counterpart (Class 2a), the assumptions used 

were all derived from the literature. The amount of information for this application was widely available.

The assumptions for the Pickup Truck were based on the GMC Sierra 2500 HD [1]. This vehicle 

has a Gross Vehicle Weight (GVWR) of 4172 kg and consequently belongs to the class 2b. Furthermore, 

as shown later in paragraph 7.2, this particular pickup also offer the advantage of offering specifications 

for both gasoline and diesel configurations. Table 1 summarizes the main assumptions used. The engines 

specified by the manufacturer were not available in the modeling and simulation database. As such, the 

Cummins ISB 6.7L and the GM LM7 5.3L were selected as alternatives. For more details about how these 

engines were scaled to match the manufacturer specifications, please see paragraph 7.2. Unless 

specified, the pickup truck class 2b was simulated with the diesel engine.

Component Model Characteristics

Engine Diesel: Cummins 6.7L 272kW

Gasoline: GM LM7 5.3L 276kW

Transmission Allison 1000 - Automatic 6 Speed

Ratios : 3.1 , 1.81 , 1.41 , 1, 0.71, 0.61

Final Drive Ratio 3.73

Tire P245/75/R16

Radius = 0.387 m

Rolling Resistance = 0.007

Vehicle Losses Drag Coefficient = 0.44

Frontal Area = 3.233 m2

Curb Weight 2659 kg

GVWR 4172 kg

Max Payload 1513 kg

Table 1: Pickup Truck Class 2b Assumptions

2.3.2 Utility Truck Class 6

The following assumptions for the Utility Truck class 6 are based on the GMC C-series C5C042 

2WD regular cab. As for the pickup truck class 2b, this brand and model of truck has the advantage of 

being produced with both gasoline and diesel options, which will be used later in paragraph 7.2. The 

Cummins ISB 6.7L for diesel and the GM LM7 5.3L were used and scaled to match specifications. The 

vehicle losses specifications (drag coefficient and frontal area) were derived from the PACCAR T270 

truck. Unless specified, the Utility Truck class 6 was simulated with the diesel engine.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Component Model Characteristics

Engine Diesel : Cummins ISB 6.7L 246kW

Gasoline : GM LM7 5.3L 240kW

Transmission Allison 1000 Series Automatic 6 Speed

Ratios : 3.1 , 1.81 , 1.41 , 1, 0.71, 0.61

Torque Converter AllisonTC211

Final Drive Ratio Diesel : 4.88

Gasoline : 5.29

Tire P245/70/R19.5

Radius = 0.419 m

Rolling Resistance = 0.009

Vehicle Losses Drag Coefficient = 0.6

Frontal Area = 9 m2

Curb Weight 4472 kg

GVWR 11791 kg

Max Payload 7319 kg

Table 2: Utility Class 6 Truck Assumptions

2.3.3 Transit Bus

The assumptions shown below for the transit bus application are all based on the 40 ft Orion V 

model. The curb weight was set to 13061 kg (28800 lb) and the GVWR to 18412 kg (40,600 lb) as 

specified by the manufacturer.

Component Model Characteristics

Engine Cummins ISL 8.9L 243kW

Transmission Allison B500 Automatic 6 Speed

Ratios : 3.51 , 1.91 , 1.43 , 1, 0.74, 0.64

Torque Converter AllisonTC541

Final Drive Ratio Diesel : 4.33

Tire 12R22.5

Radius = 0.541 m

Rolling Resistance = 0.008

Vehicle Losses Drag Coefficient = 0.65

Frontal Area = 7.96 m2

Curb Weight 13061 kg

GVWR 18412 kg

Max Payload 54 passengers @ 150 lb = 3673 kg

Table 3: Transit Bus Assumptions

2.3.4 Line Haul Class 8

The Line Haul class 8 truck was designed through collaborations with component and vehicle 

manufacturers. The baseline truck which was used to collect component data was a Kenworth T660 with 

a GVWR of 36280 kg (80,000 lb). This model of truck is equipped with a Cummins ISX 14.9L engine 
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

available in the PSAT database. A 10 speed manual transmission was selected due to its wide usage for 

the application.

Component Model Characteristics

Engine Cummins ISX 14.9L 317kW

Transmission Fuller FRM 15210B Manual 10 Speed

Ratios : 1st gear 14.8, 10th gear 1.0

Final Drive Ratio 2.64

Tire P295/75R22.5

Radius = 0.51054 m

Rolling Resistance = 0.005

Vehicle Losses Drag Coefficient = 0.565

Frontal Area = 10.38 m2

Curb Weight 8936 kg(tractor) – 6759 kg(empty trailer)

GVWR 36280 kg

Max Payload 20586 kg

Table 4: Line Haul Class 8 Truck Assumptions
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

3 Model Validation

The purpose of this chapter is to provide examples of vehicle validation using PSAT for the 

applications considered. While additional validations have been performed in collaboration with 

manufacturers, the results could not be shared to the proprietary information

3.1 Line Haul Class 8 Model Validation

3.1.1 Class 8 Validation with West Virginia University

A model of a 1996 long haul Peterbilt, tested at West Virginia University, was developed and 

validated. Figure 3 shows the Peterbilt truck used in this research. Table 5 presents the details of the 

vehicle configuration. 

Figure 3: Peterbilt Truck

Table 5: Details of the Peterbilt Truck and Test Conditions 

Description Model Characteristics

Vehicle Manufacturer Peterbilt

Vehicle Model Year 1996

Gross Vehicle Weight 20909 kg / 46000 lb(tractor only)

36364 kg / 80000 lb (assumed value with 

trailer) 

Vehicle tested weight 25455 kg / 56000 lb

Odometer Reading (mile) 441097

Transmission Type Manual

Transmission Configuration 18 speed

Engine Type Caterpillar 3406E
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Engine Model year 1996

Engine Displacement (liter) 14.6

Number of Cylinders 6

Primary Fuel D2

Test Cycle UDDS (also termed TEST_D)

Test Date 4/21/06

As for any validation, the critical aspect is to match the efforts and flows of the different 

components along with the fuel rate at every sample time of the test. Figure 4 show a good correlation 

between the instantaneous fuel rates from simulation and test.

Figure 4: Peterbilt Truck Engine Fuel Rate Comparison

Table 6 shows the summary of the fuel consumption results for the test conditions considered.

Table 6: Peterbilt Truck PSAT Validation with Chassis (Test weight 56000 lb)

Parameters Measured Simulation Relative Error

UDDS Cycle (mile) 5.44 5.37 1.29

Fuel Econ. (MPG) 3.82 3.82 0.00

Fuel Cons (Gal/100 mile) 26.17 26.17 0.00

Fuel Mass (kg) 4.58 4.52 1.31

Eng. Fuel Rate (g/s) 4.40 4.30 1.27

CO2 (g/mile) 2639.8 2685.5 -1.73

0 500 1000 1500 0

5

10

15

20

25

UDDS Time (s)

Engine Fuel Rate (g/s)

Measured

PSAT
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

3.1.2 Class 8 Validation with U.S.EPA

Another long haul application was validated in collaboration with the U.S. Environmental 

Protection Agency. The vehicle, tested at SouthWest Research Institute (SwRI) was modeled in PSAT and 

validated using dynamometer test data. The truck is a Navistar ProStar with a Cummins ISX ST400 and a 

10 speed manual transmission from EATON.

Figure 5 shows the close correlation between the simulated and measured engine speed. The 

other components effort and flow were matched as well resulting in good comparison for the fuel 

economy for several cycles as shown in Table 7.

Figure 5: Navistar ProStar Truck Engine Speed Comparison

Table 7: Navistar ProStar Truck PSAT Validation– Fuel Economy (mpg)

Cycle Measured Simulation Relative Error

7D 6.03 5.99 0.6

8D 7.31 7.1 2.8

3.2 Comparison between PSAT and Published Studies

Since a large portion of the study focuses on evaluating the impact of several technologies on fuel 

consumption, in this section, we will vary a few parameters that are essential to fuel consumption 
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

reduction and compare the results with other published studies. Additional simulations will then be 

performed to (a) verify some published values form the literature as well as (b) generate new analysis to 

generate values for missing applications or technologies.

3.2.1 Weight Reduction

Simulations were performed to assess the impact of GVWR reduction on fuel consumption. The 

baseline truck had a GVWR of 36280 kg. The vehicle was simulated for different weight on the 

HHDDT65 drive cycle which combines the various HHDDT cycles developed by the CARB [2]. The fuel 

consumption results and the percentage of fuel saved are shown below along with estimates by SwRI in 

the NESCCAF study (Presentation to NAS - December 4 2008).

Figure 6: Impact of Gross Vehicle Weight Reduction on Fuel Consumption for a Class 8 Truck

The simulations show a 9.6% fuel consumption reduction when decreasing the GVWR from 

80,000 to 65,000 lb. In other terms, we can expect a 0.6% fuel saving for every 1,000 lb weight 

reduction. In comparison, the NESCCAF study estimates were 0.5% and the Smartway ones 0.4%. 

However, it is important to keep in mind that the use of different engine maps, transmissions, shifting 

schedules, drive cycles or accessories can affect these estimates.

3.2.2 Rolling Resistance and Aerodynamics Reduction

Simulations were performed to assess the impact of drag coefficient reduction on fuel 

consumption. The baseline truck is a line haul class 8 with a GVWR of 36280 kg, a drag coefficient of 0.63 

and a rolling resistance coefficient of 0.0068. As for the previous paragraph, the truck was simulated on 

the HHDDT65 cycle and the simulation results were compared with other studies.

0

2

4

6

8

10

12

16

16.5

17

17.5

18

18.5

19

19.5

29478 

kg 

(65000 

lb)

31745 

kg 

(70000 

lb)

34013 

kg 

(75000 

lb)

36280 

kg 

(80000 

lb)

Percent of fuel saved

Fuel Consumption 

(gallon/100miles)

GVWR (lbs)

Fuel Consumption

Percent Fuel Saved

Percent Fuel Saved 

(NESCCAF Estimate)
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 7: Impact of Drag Coefficient Reduction on Fuel Consumption (Rolling Resistance fixed at 0.0055)

Figure 8: Impact of Drag Coefficient Reduction on Fuel Consumption (Rolling Resistance fixed at 0.0045)

0

5

10

15

20

25

0

5

10

15

20

25

0.4 0.45 0.5 0.55 0.6 0.63

Percent fuel saved

Fuel Consumption (gallon/100miles)

Drag Coefficient

Impact of Drag Coefficient Reduction on Fuel 

Consumption (Crr=0.0055)

Fuel Consumption

Percent Fuel Saved

Percent Fuel Saved 

(NESCCAF Estimate)

0

5

10

15

20

25

30

35

0

5

10

15

20

25

0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.63

Percent Fuel Saved

Fuel Consumption (gallon/100miles)

Drag Coefficient

Impact of Drag Coefficient Reduction on Fuel 

Consumption (Crr=0.0045)

Fuel Consumption

Percent Fuel Saved

Percent Fuel Saved 

(NESCCAF Estimate)
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 7 depicts the set of simulations which used a fixed rolling resistance of 0.0055. The drag 

coefficient varied from 0.63 to 0.4. Results show that reducing the drag coefficient from 0.63 to 0.5 lead 

to a 15.2% fuel consumption reduction. In comparison, the NESCCAF study indicated 14% fuel savings 

for the same scenario. 

Figure 8 shows a more aggressive scenario as the rolling resistance value is set to 0.0045 and the drag 

coefficient is then lowered from 0.63 to 0.3. In this case, reducing the drag coefficient from 0.63 to 0.4 

leads to a 26.7% fuel consumption reduction. Again, these results are close to the NESCCAF estimates 

which indicated 24.6% fuel savings for this situation.

3.2.3 Improved Transmission

Using a line haul class 8 truck, we studied the impact of increasing the number of transmission 

gears on fuel consumption. Based on two existing class 8 truck configurations, we simulated two 

vehicles were equipped with a 10 speed manual and an 18 speed manual transmission respectively. The 

drive cycle used was the HHDDT65 and the trucks were simulated at a GVWR of 36280 kg. The results 

are shown in Table 8.

Table 8: Impact of Improved Transmission on Fuel Consumption for a Class 8 Truck

Component Baseline Truck Improved Truck

Transmission Fuller FRM 15210B Manual 10 Speed

Ratios : 1st gear 14.8, 10th gear 1.0

Fuller RTLO 18918B Manual 18 Speed

Ratios : 1st gear 14.4, 10th gear 0.73

Final Drive Ratio 2.64 3.55

Simulation Vehicle 

Mass

36280 kg 36280 kg

Fuel Consumption 

(gallon/100mile)

18.42 18.38

The simulations resulted in no significant changes in fuel consumption. This study is very sensitive to 

the shifting logic design and to the use of a drive cycle including grade. Indeed, by tuning the shifting 

control parameters to ensure that the 18 speed shifts at lower engine speeds than the 10 speed, the fuel 

saving could reach 1 to 2%. Estimates collected from OEMs by TIAX mentioned a 1 to 5% fuel 

consumption reduction which is in the same range as the simulation predictions.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

4 Importance of Metrics

4.1 Limitations of Traditional Fuel Economy Measurements

The use of fuel economy versus fuel consumption is very often discussed for light duty vehicles. Due 

to its inverse relationship with fuel consumption, fuel economy fails to accurately represent the actual 

saving in fuel. The main issue using fuel economy is that a 10 mpg reduction will not be translated in the 

same amount of fuel saving if the original value was 40 or 20. The use of fuel consumption is thus often 

recommended especially for a comparison between several vehicles. However, for heavy duty vehicles 

even fuel consumption itself has some limitations that are discussed below.

Four different vehicles are considered: pickup class 2b, utility class 6, transit bus and line haul class 

8. Each vehicle is simulated on its specific drive cycle at two different payloads: 10% payload and GVWR.

The following table summarizes the simulation assumptions.

Table 9: Vehicle Applications, Cycles and Weight Assumptions used in Metric Study

Pickup Truck Utility Transit Bus Line Haul

Cycle(s) used UDDS+HWFET HTUF P&D Class6 Manhattan HHDDT65

Weight @ 10% payload (kg) 2810 5204 13428 17753

Weight @ GVWR (kg) 4172 11791 18412 36280

Figure 9: Comparison of Fuel Economy and Fuel Consumption

On Figure 9, we represented both fuel economy in mile/gallon and fuel consumption in 

gallons/100miles for the four vehicle applications. The two extremities of the blue bar are for the 10% 

payload and GVWR simulations. One notices that from one vehicle class to another, the fuel efficiency 
23

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

differences are not clearly shown. For example, when looking at the fuel consumption plot, it appears 

that the class 6 and class 8 truck are as fuel efficient. However, these two vehicles do not realize the 

same work, i.e. they do not carry the same weight. Furthermore, when considering the class 2b 

application, the impact of driving with 10% payload or at GVWR is not significantly emphasized since the 

bar on the fuel consumption plot is almost reduced to a single point. Consequently, the use of payload 

becomes necessary to fairly and accurately measure fuel efficiency and compare heavy duty vehicles.

4.2 Introducing Payload in Fuel Efficiency Measurements

Using the same vehicle simulations as for the previous paragraph, we will now represent the results 

using payload fuel economy (mpg multiplied by the payload weight) and load specific fuel consumption 

(fuel consumption divided by the payload weight). The units are respectively “ton.mpg” and 

“gallons/100miles/ton” using metric tons.

Figure 10: Comparison of Payload Fuel Economy and Load Specific Fuel Consumption

The trend shown in Figure 10 is completely different than what was depicted on Figure 9. The fuel 

consumption variations due to different payload are now clearly described. For example, according to 

the load specific fuel consumption (LSFC) graph (on the right), the transit bus is almost 10 times more 

fuel efficient when fully loaded than when carrying 10% load. The line haul class 8 truck is now the most 

fuel efficient vehicle among the four applications as the amount of fuel consumed in regard to the load 

carried is the best. These four applications can now be fairly compared by taking the payload into 

consideration when measuring their fuel efficiency.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 11: Comparison of Fuel Economy and Load Specific Fuel Consumption for a Class 8 Truck

Figure 11 compares the fuel economy and LSFC for different payloads. In this case, a class 8 line haul 

truck was simulated at various weights (0, 10, 20, 30...90, 100% payload) on the HHDDT65 cycle and its 

fuel economy as well as its LSFC were reported on the graph. Note that in order to avoid division by 

zero, the LSFC starts at 10% payload. When solely looking at the fuel economy, the graph analysis would 

tell us that carrying an empty trailer or the full load would only have a change of 25% in the fuel 

efficiency. However if LSFC is considered, the change in fuel efficiency between 10% load and GVWR is 

nearly 90%. This better depicts the impact of the payload on the efficiency of the work done by the 

truck.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

5 Energy/ Power Flow Analysis

To improve the fuel consumption of specific vehicles, one needs to understand the origin of the 

losses throughout the drivetrain for different operating conditions (e.g., speed, grade). This paragraph 

describes the methodology used to generate the energy / power flow analysis for several applications 

on both steady-states and drive cycles. While the process is described below for a specific example, the 

complete set of results is provided in Appendix 1.

5.1 Steady-state

All heavy-duty vehicles classes described in section 2.3 were simulated and analyzed at various 

steady-state speeds and loads. Even though the simulations included an acceleration phase to avoid 

initialization issues, the numerical values provided are solely based on the steady-state part of the cycle, 

during which the vehicle speed is constant. The speed ranges simulated ranged from 20 to 50 mph for 

the bus, 30 to 70 mph for the class 2b and class 6, and 50 to 70 mph for the class 8. The load, meaning 

the payload, is hereafter expressed in percentage of the maximum payload. 0% means that the 

simulation vehicle weight is the weight of the empty vehicle, while 100 % means the GVWR.

An example of power flow diagram is displayed on Figure 12. Average power, an intensive 

physical property, is preferred to simply energy, an extensive physical property. In the case of a steadystate, the average power is also the instantaneous power. The diagram can simply become an energy 

balance by multiplying the average power by the trip time, or an energy consumption balance by 

dividing the average power figures by the average speed. For example, in the case of Figure 12, the 

engine input average power is 395 kW, which at 65 mph average speed is equivalent to 395/65 = 6 

kWh/mi. 

A block represents a power converting component (engine, motor, transmission or axle), an 

accessory (mechanical or electrical) or a loss due to the interaction with environment (tires/rolling 

resistance, aerodynamic drag). For an automatic transmission (class 2b, class 6, bus), the “transmission” 

block encompasses the gearbox and the torque converter. “Axle” includes the final drive(s) and the 

transfer case when there is one (class 8). 

The arrows represent the power flow; their width is proportional to the energy/ average power 

exchanged, though arrow sizes are not comparable between different power flow diagrams. Horizontal 

arrows represent exchanged flows between blocks, while vertical ones represent losses. The leftmost 

arrow which is the input to both the engine and the entire system represents the power contained in 

the fuel. Each block contains a “%Loss” value, which represents the contribution to the total losses (i.e. 

ratio of component loss to engine input), as well as efficiency for power converting devices. 
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 12: Power Flow Diagram for a Class 8 Truck (Steady-State, 65 mph, 70% load) 

Various power flow diagrams are available in Appendix A.

Other diagrams are available to analyze the sensitivity to load, speed or application. For 

example, Figure 13 illustrates the impact of speed on the repartition of losses. Pie charts can show the 

impact of load (Figure 14) or application (Figure 15, Figure 16).

Figure 13: Distribution of losses for a Class 8 Truck for Various Steady-State Speeds (70% load) 

engine

η=41.9%

%Loss=58.1%

395 kW

230 kW

mech. acc.

η=N/A

%Loss=1.3%

166 kW

5.2 kW

elec. acc.

η=N/A

%Loss=0.1%

161 kW

0.36 kW

gearbox

η=98.1%

%Loss=0.8%

160 kW

3.04 kW

axle

η=98%

%Loss=0.8%

157 kW

3.13 kW

tires

η=N/A

%Loss=16.5%

154 kW

65.4 kW

aero

η=N/A

%Loss=22.4%

88.6 kW

88.5 kW

 

40 50 60 70 80

0

20

40

60

80

100

120

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - class8 / SS / 70 % Load

engine

mech. acc.

elec. acc.

gearbox

axle

tires

aero

Total losses x.1 (kW)
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 14: Distribution of losses for a Class 8 at 65 mph for 10% load (Right) and 100% Load (Left) 

Figure 15: Distribution of losses for a Class 8, Bus, and Class 6 at 50 mph at GVWR

58%

< 1% 1%< 1%< 1%

19%

21%

Loss Repartition - class8 / SS 65 mph / 100% Load

(Losses = 425 kW)

59%

2%< 1% < 1% < 1%

11%

26%

Loss Repartition - class8 / SS 65 mph / 10% Load

(Losses = 338 kW)

engine

mech. acc.

elec. acc.

gearbox

axle

tires

aero

59%

2%< 1% < 1% < 1%

21%

15%

Loss Repartition - class8 / SS 50 mph / 100% Load

(Losses = 260 kW)

engine

mech. acc.

elec. acc.

gearbox

axle

tires

aero

59%

7%

< 1%1%< 1%

16%

15%

Loss Repartition - bus / SS 50 mph / 100% Load

(Losses = 239 kW)

63%

< 1% < 1%2%

< 1%

15%

19%

Loss Repartition - cl6 / SS 50 mph / 100% Load

(Losses = 198 kW)
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 16: Distribution of losses for a Class 2b at 50 mph at GVWR

5.2 Standard Drive Cycles

A similar methodology can be used to analyze power flows on non-steady-speed cycles. Similarly 

to the steady-state diagrams, the numerical values associated to a flow represent the average power of 

that flow (total flow energy divided by time). A new block is however necessary, and is called “inertia”. It 

represents the kinetic energy the vehicle acquires when accelerating and that it loses when 

decelerating. Most of it is lost in friction losses during braking. A regenerative braking system, as used in 

hybrids, can recover part of that energy and add it back to the system. Several diagrams for various 

applications and corresponding duty cycles are showed hereinafter (Figure 17, Figure 18, Figure 19 and 

Figure 20).

Figure 17: Power Flow Diagram for a Bus on CBD cycle (50% load) 

77%

< 1% 1% < 1%

10%

11%

Loss Repartition - cl2b / SS 50 mph / 100% Load

(Losses = 92.4 kW)

engine

elec. acc.

trans.

axle

tires

aero

engine

η=40.1%

%Loss=59.9%

123 kW

73.6 kW

mech. acc.

η=N/A

%Loss=13.8%

49.3 kW

17 kW

elec. acc.

η=N/A

%Loss=1.6%

32.3 kW

2 kW

trans.

η=80.8%

%Loss=4.7%

30.3 kW

5.81 kW

axle

η=97%

%Loss=0.6%

24.5 kW

0.725

kW

tires

η=N/A

%Loss=5.6%

23.8 kW

6.88 kW

aero

η=N/A

%Loss=0.9%

16.9 kW

1.06 kW

inertia

η=N/A

%Loss=12.7%

15.9 kW

Energy Balance - bus / cbd2 (13 mph average) / 50% Load / 26.1 gal/100mi
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 18: Power Flow Diagram for a Class 6 on HTUF cycle (75% load) 

Figure 19: Power Flow Diagram for a Class 8 on HHDDT 65 cycle (72% load) 

Figure 20: Power Flow Diagram for a Class 8 on UDDS Truck cycle (72% load) 

engine

η=30.4%

%Loss=69.6%

56.1 kW

39.1 kW

mech. acc.

η=N/A

%Loss=0.5%

17 kW

0.276

kW

elec. acc.

η=N/A

%Loss=1%

16.8 kW

0.554

kW

trans.

η=83.5%

%Loss=4.8%

16.2 kW

2.68 kW

axle

η=98%

%Loss=0.5%

13.5 kW

0.269

kW

tires

η=N/A

%Loss=5.8%

13.3 kW

3.24 kW

aero

η=N/A

%Loss=3.1%

10 kW

1.73 kW

inertia

η=N/A

%Loss=14.7%

8.28 kW

Energy Balance - cl6 / HTUF Class 6 P&D (10 mph average) / 75% Load / 15.0 gal/100mi

engine

η=40.9%

%Loss=59.1%

317 kW

187 kW

mech. acc.

η=N/A

%Loss=1.5%

130 kW

4.84 kW

elec. acc.

η=N/A

%Loss=0.1%

125 kW

0.36 kW

trans.

η=98.1%

%Loss=0.7%

125 kW

2.36 kW

axle

η=98%

%Loss=0.8%

122 kW

2.43 kW

tires

η=N/A

%Loss=15.6%

120 kW

49.6 kW

aero

η=N/A

%Loss=16.8%

70.1 kW

53.2 kW

inertia

η=N/A

%Loss=6.1%

16.9 kW

Energy Balance - cl8 / HHDDT65 ( 50 mph average) / 72 % Load / 17.0 gal/100mi

engine

η=36.9%

%Loss=63.1%

164 kW

104 kW

mech. acc.

η=N/A

%Loss=2.7%

60.5 kW

4.35 kW

elec. acc.

η=N/A

%Loss=0.2%

56.1 kW

0.36 kW

trans.

η=97.8%

%Loss=0.7%

55.7 kW

axle

η=98%

%Loss=0.7%

54.5 kW

1.08 kW

tires

η=N/A

%Loss=9.7%

53.5 kW

16 kW

aero

η=N/A

%Loss=4.9%

37.5 kW

8.07 kW

inertia

η=N/A

%Loss=20.3%

29.4 kW

Energy Balance - cl8 / udds truck (18 mph average) / 72 % Load / 24.2 gal/100mi

1.21 kW
30

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

6 Impact of Drive Cycles on Fuel Consumption

6.1 Impact of Real World Drive Cycles

In this paragraph, we will study the impact of real world drive cycles on fuel consumption. We will 

first compare this study with the drive cycles generally used for simulation and then look at the 

differences with steady states results from Paragraph 5. 

6.1.1 Pickup Truck Class 2b

For the pickup truck application, real world drive cycles gathered by the U.S.EPA in Kansas City in 

2005 were used for simulation. This set of data consists in 110 daily driving cycles recorded on various 

light duty car, SUVs and pickup trucks. We assumed that the driving patterns of a pickup truck class 2b 

were close enough to light duty vehicles to justify the use of Kansas City cycles. Only the speed as a 

function of time was extracted from the set of cycles. This information then became the cycle constraint 

to follow by the driver model of the pickup truck class 2b vehicle. The fuel consumption results are 

plotted on Figure 21 as well as the UDDS and HWFET cycles commonly used for this application.

Figure 21: Fuel Consumption as a function of Average Cycle Vehicle Speed for a sample of Real World Drive Cycles for a 

Pickup Class 2b

10 20 30 40 50 60 4

6

8

10

12

14

16

18

Fuel Consumption (gallons/100mile)

Average Cycle Vehicle Speed (mile/hour)

Fuel Consumption for a Pickup Class 2b on Real World Drive Cycles

RWDC 

Interpolation 

UDDS

HWFET
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

For a clearer analysis of the data, an interpolation of the Kansas City cycle simulations was also 

reported on Figure 21. The green and black stars represent the UDDS and HWFET fuel consumptions 

respectively. This graph mainly shows that by using a combination of the UDDS and the HWFET cycles 

we can reach the area where most of the RWDC are located (around an average vehicle speed of 30 to 

35 mph). However, the fuel consumption of these two cycles taken separately or combined is still lower 

than the trend shown by RWDC which is a common remark.

While the correlation coefficient of the interpolation is only 0.64, the graph clearly shows a high 

correlation between fuel consumption and average cycle speed. The difference for a specific average 

speed is mainly due to the driver aggressiveness.

6.1.2 Line Haul Class 8

For the class 8 application, the real world drive cycles gathered for the simulations were 

recorded by Oak Ridge National Laboratory. The limited number of data (8 cycles) limits the analysis. An 

interpolation of the simulation fuel consumption results was performed but more RWDC would be 

needed to better attempt to characterize a trend between average cycle vehicle speed and fuel 

consumption.

Figure 22: Fuel Consumption as a function of Average Cycle Vehicle Speed for a sample of Real World Drive Cycles for a Class 

8 Truck

0 10 20 30 40 50 60 70 14

16

18

20

22

24

26

28

30

32

Fuel Consumption (gallons/100mile)

Fuel Consumption for a Line Haul Class8 on Real World Drive Cycles

RWDC

 Interpolation

HHDDT65
32

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

As shown in Figure 21, the fuel consumption on the HHDDT65 cycle is lower than the RWDC with a 

similar average cycle vehicle speed. This is the same conclusion as for the pickup truck class 2b. Note 

that the correlation coefficient of the interpolation is only about 0.66 and shows that more RWDC would 

be necessary to get a better fitting.

6.2 Issues Following the Trace

One of the many challenges of heavy duty vehicle modeling is to select a drive cycle that can be 

driven by most configuration of a vehicle class including different weights, transmissions, etc... This can

indeed become a crucial issue especially for class 8 trucks where manual configurations are widely 

available and weight can dramatically vary (from a 10% load to GVWR). For an 18 speed manual 

transmission for example, the typical average shifting time is around two seconds and the shifting 

events are extremely frequent. On the other hand, automatic transmissions have little power 

interruptions and a lower gear number. Consequently, if we compare both transmissions on the same 

drive cycle, with the rest of the powertrain being identical, the vehicles might not follow the trace 

similarly.

Figure 23: Automatic vs. Manual Transmission for a Class 8 Truck
33

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 23 clearly depicts this issue. On this graph, we show the beginning of the HHDDT65 drive 

cycle (in blue) as well as the vehicle speed of a manual (red) and automatic (green) class 8 truck 

attempting to follow this trace. The multiple shifting events of the manual truck moves the vehicle 

speed away from the trace whereas the automatic truck better follows the speed demand. 

Consequently, if we compare the simulation results for these two trucks, the manual vehicle has a better 

fuel consumption than the automatic because it has a lower average speed throughout the cycle since it 

does not follow the same trace. Therefore, there is a need of introducing an additional parameter in the 

fuel efficiency results: the average cycle vehicle speed.

6.3 Potential Approach to Representing Fuel Efficiency

This paragraph shows a graphical example of how fuel efficiency could be represented for regulatory 

purposes and in order to fairly compare different truck configurations within the same vehicle class. The 

steady state results simulated for the line haul class 8 in paragraph 5 are used and plotted on Figure 24.

Figure 24: Fuel Consumption as a function of Steady State Vehicle Speeds for different Payloads

Figure 24 gives an original approach to decide what fuel consumption to expect from a class 8 truck 

according to its cycle average vehicle speed and the weight of load carried. Taking the previous example 

50 55 60 65 70 75 10

12

14

16

18

20

Speed [mph]

 Fuel Consumption [gal/100 mi]

Fuel Consumption for Various Fractions of Maximum Payload (class8, SS)

0 % Load

10 % Load

20 % Load

30 % Load

40 % Load

50 % Load

60 % Load

70 % Load

80 % Load

90 % Load

100 % Load
34

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

of the manual and automatic transmission class 8 trucks simulated on the HHDDT65 cycle, we could 

determine what fuel consumption such trucks should achieve according to their cycle average speed. 

This would lead to two different values since they did not follow the trace similarly. If the truck with an 

automatic transmission loaded at GVWR completed the HHDDT65 at an average speed of 60 mph, the 

100% load curve on Figure 24 would then indicate 16 gallons/100miles fuel consumption for this 

particular truck. On the other hand, if the truck with a manual transmission completed the same cycle at 

an average speed of 58 mph, the same curve would indicate 15.5 gallons/100miles. Consequently, these 

two trucks will not have the same criteria to meet for regulation and the truck with the manual 

transmission might not be the most fuel efficient one even if its fuel consumption value is lower.

The question brought by the previous paragraph is: how accurately can steady states predict fuel 

consumption? To answer this we will take the same graph as Figure 24 but for a pickup truck class 2b 

and we will merge it with the RWDC fuel consumptions data (see paragraph 6.1.1). The resulting plot is 

shown on Figure 25.

Figure 25: Fuel Consumption as a function of Average Cycle Vehicle Speed for RWDC and Steady States for a Pickup Truck 

Class 2b.

As expected, steady states are showing better fuel consumptions than RWDC for the same average 

vehicle speed. However, the difference is not dramatic and the trend between the steady state curves 

and the RWDC interpolated curve is similar.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

7 Impact of Single Technologies on Fuel Consumption

In the following sections, the impact of several technologies on fuel consumption will be assessed, 

including:

- Aerodynamics

- Fuel

- Hybridization

7.1 Aerodynamic

7.1.1 Utility Truck Class 6

The configuration used for the Utility Class 6 Truck had the following specifications:

Table 10: Utility Class 6 Truck Vehicle Assumptions for Drag Coefficient Study

Simulation 1 Simulation 2

GVWR 11791 kg

Simulation Vehicle Mass 9070 kg

Rolling Resistance 0.007

Drag Coefficient 0.7 0.55

Six different steady state speeds along with several driving cycles were chosen to represent 

various driving conditions. The Truck UDDS represents urban type driving and the HTUF cycle is similar 

to the light duty UDDS cycle. Finally, the HHDDT Cruise and High Speed were developed by CARB and are 

both highway cycles with an average vehicle speed of 40 mph and 50 mph respectively.

Table 11: Utility Class 6 Truck Drive Cycle and Steady States Assumptions for Drag Coefficient Study

Steady States Driving Cycles

10 mph Truck UDDS

20 mph HTUF P&D Class 6

30 mph HHDDT Cruise

40 mph HHDDT High Speed

55 mph

65 mph

The simulation results are shown on Figure 26. Fuel consumption is shown in gallons/100miles 

as a function of average vehicle speed. Note: the fuel efficiency results for steady states were computed 

by removing the acceleration part which leads to the steady state, ensuring that the results are pure 
36

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

steady states. The lines represent the steady states (plain for Cd=0.55 and dotted for Cd=0.7) and the 

scattered points (circles for Cd=0.55 and x for Cd=0.7) depict the drive cycles. 

Figure 26: Impact of Drag Coefficient on Class 6 Fuel Consumption for various Drive Cycles and Steady States.

Figure 26 shows that the fuel consumption values from steady states and drive cycles are much 

closer to each other when the average vehicle speed of the cycle is high (>40mph) whereas they widely 

differ in low average vehicle speed areas. This is understandable considering that most of the drive 

cycles with an average vehicle speed of 40 mph or higher usually represent highway driving and 

consequently do not have much acceleration / deceleration. On the other hand, a drive cycle with a low

average vehicle speed (e.g., 25 mph) characterizes an urban cycle with multiple transient phases leading 

to higher fuel consumption than a steady state cycle at the same speed.

Figure 27 shows the percentage of fuel consumption reduction when the drag coefficient is 

lowered from 0.7 to the 0.55 for drive cycles and their associated steady state speed. The values were 

generated by taking the average speed for each of the four cycles and calculated the steady state fuel 

consumption values corresponding to the speed by intersecting the lines from Figure 26.

0 10 20 30 40 50 60 70 0

2

4

6

8

10

12

14

16

18

20

Fuel Consumption (gallons/100miles)

Cycle Average Vehicle Speed

Fuel Consumption vs Cycle Average Vehicle Speed for a Class 6 Truck

Drive Cycles with Cd=0.55

Drive Cycles with Cd=0.7

Steady States with Cd=0.55

Steady States with Cd=0.7

UDDS

Truck

HHDDT

Cruise

HHDDT

High Speed

HTUF

Class 6
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 27: Percent of Fuel Saved by Reducing the Drag Coefficient for Each Drive Cycle and their Steady State Speed 

Counterpart for Class 6

In Figure 27, it appears that the drag coefficient reduction has consistently a greater impact on 

the fuel consumption of drive cycles than the one from steady states. However, the difference seems to 

be greater at average vehicle speeds between 25 and 45 mph than at low and high speeds. The benefits 

from aerodynamics being related to the cube of the vehicle speed, any higher speed portion above the 

average will decrease the fuel consumption. Since higher speed variations are seen for lower average 

speeds, the difference between Steady State and drive cycle is greater at average speeds.

7.1.2 Line Haul Class 8

The configuration used for the Line Haul Class 8 Truck has the following specifications:

Table 12: Line Haul Class 8 Truck Vehicle Assumptions for Drag Coefficient Study

Simulation 1 Simulation 2

GVWR 36280 kg

Simulation Vehicle Mass 29931 kg

Rolling Resistance 0.007

Drag Coefficient 0.6 0.5

0

5

10

15

Percentage Improvement from high to low Cd

Comparison of Aerodynamic Fuel Savings for Drive Cycles vs Steady States

HTUF Class 6/

21 mph SS

UDDS Truck/

26 mph SS

HHDDT Cruise/

42 mph SS

HHDDT High Speed/

53 mph SS

Drive Cycles

Steady States
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Six different steady state speeds and driving cycles were used to represent various driving 

conditions. As for the Utility class 6 vehicle, the Line Haul is simulated on the Truck UDDS cycle as well as 

the three HHDDT cycles developed by CARB.

Table 13: Line Haul Class 8 Truck Drive Cycle and Steady States Assumptions for Drag Coefficient Study

Steady States Driving Cycles

15 mph Truck UDDS

20 mph HHDDT Transient

30 mph HHDDT Cruise

40 mph HHDDT High Speed

55 mph

65 mph

The simulation results are shown on Figure 28. The lines represent the steady states (plain for 

Cd=0.5 and dotted for Cd=0.6) and the scattered points (circles for Cd=0.5 and x for Cd=0.6) depict the 

drive cycles.

Figure 28: Impact of Drag Coefficient on Class 8 Fuel Consumption for various Drive Cycles and Steady States.

10 20 30 40 50 60 70 0

5

10

15

20

25

30

Fuel Consumption (gallons/100miles)

Cycle Average Vehicle Speed

Fuel Consumption vs Cycle Average Vehicle Speed for a Class 8 Truck

Drive Cycles with Cd=0.5

Drive Cycles with Cd=0.6

Steady States with Cd=0.5

Steady States with Cd=0.6

HHDDT

Transient

UDDS

Truck

HHDDT

High

HHDDT Speed

Cruise
39

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

As shown in Figure 28, fuel consumptions achieved during steady states are closer to one from the 

drive cycles when the average vehicle speed is higher than 40 mph.

Figure 29: Percent of Fuel Saved by Reducing the Drag Coefficient for Each Drive Cycle and their Steady State Speed 

Counterpart for Class 8

In Figure 29, the same conclusions as for the class 6 utility truck can be drawn. However another 

interesting point can be made. Except for the lowest vehicle speed drive cycle, both trucks were 

simulated on the same cycles but the fuel savings vary widely from the class 6 to the class 8. For 

example, the class 6 truck reduced its fuel consumption by more than 14% on the HHDDT cruise against 

only 6% for the long haul. This difference is due to the similar aerodynamic specifications of these trucks 

taking into consideration the weight discrepancy (9 tons vs 30 tons). The aerodynamic losses 

representing a greater percentage of the overall powertrain losses for the class 6, the drag coefficient 

reduction will have a greater impact on the vehicle fuel efficiency.

7.2 Type of Fuel

This paragraph explores the impact of using either Gasoline or Diesel fuels for two vehicle 

applications: the pickup truck class 2b and the utility truck class 6.

0

1

2

3

4

5

6

7

Percentage Improvement from high to low Cd

Comparison of Aerodynamics Fuel Savings for Cycles vs Steady States

HHDDT Transient/

17 mph SS

UDDS Truck/

26 mph SS

HHDDT Cruise/

42 mph SS

HHDDT High Speed/

53 mph SS

Drive Cycles

Steady States
40

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

7.2.1 Pickup Truck Class 2b

7.2.1.1 Assumptions

The GMC Sierra 2500 HD pickup truck was selected since both gasoline and diesel engines were 

available. Table 14 shows the main specifications [1]:

Table 14: Gasoline and Diesel Assumptions for the Pickup Truck Class 2b

Diesel Gasoline

GVWR 4172 kg 4172 kg

Towing Capacity 4535 kg 4535 kg

Engine Model DURAMAX 6.6L V8 VORTEC 6.0L

Engine Power/Torque 272 kW / 895 Nm 268 kW / 515 Nm

Gearbox Allison 1000 Series – 6 Speed Allison 1000 Series – 6 Speed

Axle Ratio 3.73 3.73

Tires 245/75R16 245/75R16

Since the latest Duramax and the Vortec engines are not available in PSAT, similar engines were 

used and scaled to match the specifications. The Gasoline engine is a GM V8 LM7 5.3L with overhead 

valves, two valves per cylinder and sequential fuel injection which offers very similar specifications than 

the Vortec engine in terms of rated maximum torque and power [5]. The closest available diesel engine 

was a Cummins ISB 6.7L calibrated for vehicle test procedure purposes (i.e. suitable for a class 2b pickup 

truck contrary to other heavier duty versions of the ISB engine calibrated for emissions). The engine 

power and torque curves of the Duramax can be found in the literature [3].

The power and torque curves of the Cummins ISB being proprietary data, they will not be shown 

in the report. However, we can mention that after scaling, the engine had a peak torque of 940 Nm at 

1600 rpm and a peak power of 272 kW at 2950 rpm. No cylinder deactivation technology was 

considered for this study.

7.2.1.2 Simulation Scenarios

Two different sets of simulations were completed for this vehicle: 

- Scenario A : The first scenario uses the peak power values found in the literature for the two 

GMC Sierra versions (272 kW for diesel and 268 kW for gasoline).

- Scenario B : The second scenario uses an automated sizing algorithm to ensure that both 

vehicles have the same performance specifications. Using the diesel as a reference, we 

simulated an acceleration test from 0 to 60 mph. The gasoline vehicle was then designed to 

match the performance. Note: the diesel vehicle takes into consideration a 6% penalty in 
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

acceleration time due to turbo lag. The vehicles achieved the acceleration test in 9 seconds and 

the resulting engine powers were 272 kW for diesel and 276 kW for gasoline.

7.2.1.3 Simulation Results

Four different drive cycles were used to offer various aggressiveness conditions. Due to the 

similarities with light duty pickup truck, the UDDS, HWFET, LA92 and US06 cycles were selected. All 

vehicles were simulated at gross vehicle weight.

Table 15 shows the fuel consumption for the two vehicles according to the different scenarios. 

All values are in gallon/100miles and unadjusted. For the diesel vehicles, the first value is volumetric fuel 

consumption (gallons of diesel consumed per 100 miles) and the second one in parenthesis is in gasoline 

fuel consumption equivalent.

Table 15: Fuel Consumption of Gasoline and Diesel Class 2b Vehicles for different Drive Cycles

UDDS HWFET LA92 US06

Scenario A Gasoline 8.56 5.34 9.03 8.86

Diesel 6.99 (7.78) 3.99 (4.44) 7.19 (7.99) 6.41 (7.13)

Percent Fuel Saved 18.3% (9.1%) 25.3% (16.9%) 20.4% (11.5%) 27.7% (19.5%)

Scenario B Gasoline 8.65 5.38 9.07 8.84

Diesel 6.99 (7.78) 3.99 (4.44) 7.19 (7.99) 6.41 (7.13)

Percent Fuel Saved 19.2% (10.1%) 25.8% (17.5%) 20.7% (11.9%) 27.5% (19.3%)

The amount of fuel saved by a diesel pickup truck compared to its gasoline counterpart ranges

between 19.2 to 27.5% when comparing volumetric fuel consumptions (9.1 to 19.5% when in gasoline 

equivalent). The trend showed by the different cycles is that the more aggressive/faster the driving 

pattern, the greater the advantage of diesel. 

These results could seem lower than the common Diesel/Gasoline comparison for light duty 

vehicles (commonly used value of 30% for volumetric fuel consumption). In this case, the two class 2b 

trucks were simulated at GVWR. However, these vehicles are designed to be able to tow an additional 

10,000 to 15,000 lb trailer. Consequently, both engines did not operate at full load since the simulation 

did not require so. Both engines are operated at low loads (typically lower than 200 Nm) where their

efficiency maps are similar. These are the typical conditions observed on the UDDS cycle which explains 

why the fuel consumption advantage of the diesel is only around 19%. On the other hand when the 

engine is operated at higher loads (more than 200 Nm), the diesel engine operates a higher efficiencies 

than for the diesel engine. As a consequence, the US06 cycle shows a greater fuel consumption 

advantage for the diesel engine (around 28%).
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 30: Fuel Consumption of Gasoline and Diesel Class 2b Vehicles for different Drive Cycles

7.2.2 Utility Truck Class 6

7.2.2.1 Assumptions

The GMC C-series C5C042 2WD regular cab was selected since both gasoline and diesel engines 

were available. Table 16 shows the main specifications [4]:

Table 16: Gasoline and Diesel Assumptions for the Utility Truck Class 6

Diesel Gasoline

GVWR 11791 kg 11791 kg

Engine Model DURAMAX 6.6L V8 VORTEC 8.1L

Engine Power/Torque 246 kW / 820 Nm 240 kW / 610 Nm

Gearbox Allison 2200 HS/RDS Series – 6 Speed Allison 2200 HS/RDS Series – 6 Speed

Axle Ratio 4.88 5.29

Tires 245/70R19.5 245/70R19.5

As for the pickup Class 2B application, we used the GM LM7 5.3L gasoline engine since it is the 

closest data available in the PSAT database. For diesel, we used a Cummins ISB 6.7L engine calibrated for 

UDDS LA92 HWFET US06 3

4

5

6

7

8

9

10

Fuel Consumption (gallons/100miles)

Drive Cycle

Fuel Consumption for a Pickup Truck Class 2B on various cycles

Diesel

Gasoline
43

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

engine dynamometer certification and thus not the same version as for the pickup truck. The gasoline 

engine was scaled to match the peak power specification. For the Cummins ISB diesel engine was scaled 

as well. The original power and torque curves as they are defined for this GMC truck for the two engines 

can be found in the literature [3].

7.2.2.2 Simulation Scenarios

For the Class 6 vehicle, a single simulation scenario was used. The engine peak power was 

directly derived from the GMC truck used as a reference. The value of 240 kW was used for the gasoline 

engine peak power and 246 kW for the diesel one.

7.2.2.3 Simulation Results

Three drive cycles were used for simulation: the HTUF Pickup and Delivery Class6, HHDDT65 and 

the Truck UDDS. The vehicles were run at a GVWR of 26,000 lbs (11,791 kg). The following table shows 

the fuel consumption results in unadjusted gallons/100miles. For the diesel vehicles, the first value is in 

Diesel fuel consumption and the second one in parenthesis is in Gasoline fuel consumption equivalent.

Table 17: Fuel Consumption of Gasoline and Diesel Class 6 Vehicles for different Drive Cycles

HTUF Class 6 Truck UDDS HHDDT65

Gasoline 21.41 20.53 18.69

Diesel 15.92 (17.73) 15.31 (17.03) 13.81 (15.38)

Percent Fuel Saved 25.6% (17.2%) 25.4% (17%) 26.1% (17.7%)

The amount of fuel saved by the diesel configuration compared to the gasoline is 26% on

average for volumetric fuel consumptions (around 17% when in gasoline equivalent). This value is closer 

to the common Gasoline/Diesel comparison accepted for light duty vehicles. Indeed, a quick ratio of the 

engine map peak efficiency would give a 16% advantage for the diesel engine. In the case of the class 6, 

the engine is operated closer to the full load and to its peak efficiency more often.
44

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 31: Fuel Consumption of Gasoline and Diesel Class 6 Vehicles for different Drive Cycles

7.3 Tractor-trailer Hybridization

7.3.1 Hybridization Principles

Hybrid electric vehicles have demonstrated their ability to significantly reduce fuel consumption 

for several medium and heavy duty applications. While much work is available in the literature for 

buses, delivery truck or utility trucks, little information is available for long hauls. This section focuses 

on analyzing the hybridization potential of several powertrain configurations for Class 8 long haul.

Most of the energy losses occurring in a truck come from the engine. On a urban cycle, the 

engine average efficiency is only 37 %, which means the engine could be operated more efficiently. On 

the other hand, on the highway there is less opportunity for improvement as the engine is already 

operated close to its peak efficiency (41 % average). Operating the engine more efficiently can be 

achieved mainly in two ways: not using the engine at all during those low efficiency operation moments, 

or shifting the operation point to a more efficient level – for example by increasing the engine output 

and storing it an energy storage system, or by decreasing the engine speed.

The losses due the tires and aerodynamic losses cannot be displaced by hybridization, since the 

vehicle follows the same cycle, and requires the same amount of power regardless of the source of 

power. The losses due to the driveline could be in part displaced if the electric power source is put 

HTUF udds HHDDT65 0

5

10

15

20

Fuel Consumption (gallons/100miles)

Drive Cycle

Fuel Consumption for a Class 6 on various cycles

Diesel

Gasoline
45

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

closer to the wheels (e.g. series w/o transmission, post-transmission parallel, in-hub motors, etc.), but 

that is not a practical solution for heavy-duty applications.

The accessory load can be affected by hybridization, as some of the mechanical accessories 

(pumps, compressors, etc.) can be replaced by electric systems. This is a difficult exercise to replicate in 

simulation, as it requires the knowledge of the mechanical accessory load in both conventional and 

hybrid case. In this study, some of the load is displaced from mechanical to electrical.

A conventional vehicle also loses much of the kinetic energy it acquired during acceleration 

through friction when braking. A regenerative braking system can recover part of this energy and 

recharge the energy storage system, and that energy can in turn be used for the accessory load and/or 

for propulsion.

Hybridization could lead to other indirect fuel savings opportunities, that are not necessarily 

well represented in a cycle-type testing procedure (either actual on a dynamometer or in simulation). If 

performance (meaning here higher acceleration capability) is improved or shifting time is reduced, the 

vehicle will be less likely to “lose” the trace – i.e. the vehicle speed dropping below the target trace 

speed – and will not need to accelerate as much later, while performing more “work” (higher distance). 

On the other hand the availability of improved performance can lead the driver to request more power

in real-world driving conditions, possibly leading to a less efficient use of the hybrid system.

7.3.2 Hardware Design

7.3.2.1 Hybrid Configurations Overview

A hybrid vehicle can have one or more electric machines that can be positioned at various points 

of the powertrain, leading to a large number of configurations. The main configuration families are 

presented hereinafter.

Series. In a series configuration, the vehicle is only propelled by electrical power. The engine 

output power is converted into electricity through a generator and then is either stored in the battery or 

converted back into mechanical power by the propulsion motor. The latter can be directly connected to 

the final drive, or to a gearbox with a lower number of gears than a conventional one thanks to high 

torque availability at low speed and increased motor speed range. This configuration is generally the 

easiest to implement because the propulsion is 100 % electric, while the generator set is almost an 

independent system, relatively easy to control. A drawback of this configuration is that both electric 

machines have to be oversized: the propulsion one to the vehicle power/torque requirements, and the 

generator to the engine power. Another drawback is that at cruising speed the de facto electric 

transmission has a poor efficiency due to the double conversion of engine mechanical energy. One note 

that variations of series configurations are currently trying to address this limitation.
46

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Parallel. In a parallel configuration, the vehicle can either be propelled directly from thermal or 

electrical power. The vehicle usually has at least one clutch and a multispeed gearbox close to a 

conventional model. That means the engine-to-wheels path goes through the gearbox, in a similar 

fashion to a conventional powertrain, thus resulting in a relatively good efficiency at cruising speeds. 

The electric machine can either provide positive torque, contributing to the propulsion of the vehicle, or 

recharge the energy storage by diverting part of the engine torque. There are several variants of the 

configuration, based on the position of the electric machine. 

In a starter-alternator position, the electric machine is between the engine flywheel and the 

clutch; when the clutch is open, the motor is disconnected from the drivetrain. This configuration is used 

in micro-hybrids or mild-hybrids allowing the engine to be shut down at idle, and quickly started again it 

back when the driver requires the vehicle to start moving. Its main advantage is its ease of 

implementation and cost effectiveness. However expected gains are limited by the level of regenerative 

braking.

In a pre-transmission, the electric machine is between the clutch and the gearbox. In a posttransmission, the electric machine is between the gearbox and the final drive (or transfer case). When 

the clutch is open the engine is disconnected from the drivetrain, while the electric machine is not, 

therefore allowing an electric-only mode. In the pre-transmission case, the electric machine benefits 

from the gearbox torque multiplication, which provides more freedom in terms of electric machine

speed range choice, and ensures that the electric machine can be operated above its base speed most of 

the time. On the other hand, in the post-transmission case, the motor-to-wheels path is more efficient 

as it does not include the transmission; also there is no torque interruption during shifting. For both preand post- transmission configurations, the clutch control is often a challenging engineering problem.

Series-parallel. This configuration combines the benefits of the series and parallel pre-/posttransmission configurations. When the clutch is open, the engine can be off or can be on and generate 

electricity through the generator, creating a series path. Generally the series-path is used at low speeds, 

while parallel is chosen for higher cruising speeds. The series-parallel can be combined with gearboxes

with a lower number of gears

One mode power split. This configuration is used by Toyota (e.g., Prius) and Ford (e.g., Escape). 

The engine and a motor-generator are connected to a planetary gearset, to the output of which another 

electric machine is connected. In this configuration, the engine power is split: part of it is transferred to 

the wheels, while another goes through the electrical path, with a double energy conversion, similar to 

the series. The planetary gearset and the electric machines act as an electric-variable transmission (EVT). 

The engine speed can be chosen relatively independently from the vehicle speed; the control can 

therefore choose to consistentyly operate the engine in an efficient area. At cruising speed, the EVT may 

not be as efficient as a conventional gearbox, depending of the level of recirculation. Furthermore, this 

configuration leads to significant oversizing on heavier vehicles in order for them to be able to operate 

in a broad range of operations.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Multi-mode transmission. A multi-mode transmission combines several power-split modes, 

each of them suitable for different operational requirements, therefore avoiding component oversizing. 

It can also be combined with fixed gear(s) - adding parallel paths - for extra flexibility on grades or 

cruising. 

7.3.2.2 Configurations selected for the study

Two hybrid configurations were selected for this study: series-parallel and starter-alternator. 

The conventional series configuration is not well suited for tractor-trailer applications because it is not 

efficient at cruising highway speeds, which is the most frequent use of such a truck. A multimode hybrid 

with fixed gear could be an option, but due to the complexity of its design and its control, it will not be 

considered in this study. The parallel pre-transmission is similar to the series-parallel.

The series-parallel with one electric machine in pre-transmission position (between the clutch 

and the gearbox) is chosen to be a full-hybrid, with electric-only mode capability. Thanks to another 

electric machine, the series mode will allow easy engine starts, as well as a recharging capability when 

the vehicle is stopped. 

Figure 32 – Schematic of the series-parallel configuration (full-hybrid)

The starter-alternator, thanks to a low power electric machine and low energy battery is 

selected for a “mild-hybrid” truck, i.e. with engine shut-downs at idle and regenerative braking possible, 

but with no electric-only mode. Thanks to a low power electric machine and low energy battery, the 

mild-hybrid requires lower upfront investment than the full-hybrid option.

Engine 

To 

Clutch Driveline

Gearbox

Energy

Storage 

System

Elec. 

Acc.

Mech. 

Acc.

MG2 MG1
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 33 – Schematic of the starter-alternator configuration (mild-hybrid)

7.3.2.3 Component Sizing

For light-duty applications, typical sizing requirements are made of four criteria: acceleration 

(e.g. 0-60 mph time), passing (30 to 50 mph time), gradeability at a given speed and top speed. For a 

hybrid, the electric system cannot be used for the grade requirement, as there would not be enough 

energy to sustain a continuous grade over a long period, so the engine must be sized for that specific 

requirement. The electric system can however be used for the acceleration/passing requirement,; 

because the most restrictive factor is in general the acceleration requirement, an engine downsizing can

therefore be achieved – that is generally the case with production light-duty hybrids.

The same type of requirements could be applied to tractor-trailers. However, there is no 

industry-wide standard, as trucks are customized to fleets requirements. Another major difference 

between the two applications is that heavy-duty vehicles often operate at maximum power, especially 

during grades. From a conventional truck, no engine downsizing can be done because the battery energy 

limits the electric propulsion to a short duration, while grades can be long. In this study the engine size is 

therefore the same as in for the conventional version.

In the case of the less expensive and simpler starter-alternator, the electric machine power is 

set at 50 kW. For the series-parallel truck, the same size of electric machine is used for the generator 

(motor 2), while the propulsion electric machine (motor 1) has a 200 kW power. A electric machine

power sensitivity or a design optimization study could provide a more precise choice of electric machine 

power, but is out of the scope of the present study.

The battery power matches the electric machine power, while the battery energy is based on 

hotel loads. The average load is estimated to 1.5 kW, including air-conditioning in the summer, cabin 

and engine block heating and various electric accessories (fridge, tv, lights, etc.). This value is based on 

existing literature and accessory/idle-specific devices specifications. In the case of the full-hybrid, the 

Engine 

To 

Clutch Driveline

Gearbox

Energy

Storage 

System

Elec. 

Acc.

Mech. 

Acc.

Motor -

Generator
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

battery energy is such that it can provide the 1.5 kW load for the duration of a hotel stop of 10 hours, if 

fully loaded at the beginning of the stop. The usable battery energy for a lithium-ion technology is 60% 

of its total energy (operating range between 90% and 30% of state-of-charge), resulting in a 25 kWh 

battery. In the case of the mild-hybrid, the battery is only 5 kWh to limit the cost of the system. It would 

be sufficient for a 2 hour period, after which the engine would have to be started in order to quickly 

recharge the battery. Since the power at which the engine would be operated would considerably be 

higher than during a conventional idling, this solution would still be more efficient.

For both hybrid trucks, the gearbox remains unchanged compared to the conventional.. In the 

case of the series-parallel, the number of gears could however probably be reduced. If the truck is 

always operated in series mode up to a certain vehicle speed, some of the higher gear ratios can be 

removed, provided that the propulsion electric machine has the proper speed and torque ranges. 

Finding the right combination of gear number, ratio and electric machine design is a study in itself that is 

outside of the scope of the present study. A specific transmission is however unlikely to bring significant 

energy efficiency improvements, as the full-hybrid simulated here is already very efficient. A different 

gearbox could however reduce cost, space and improve drivability.

Table 18: Summary of component sizes

Conventional Mild Hybrid Full Hybrid

Engine Power (kW) 317 317 317

MG1 Power (kW) - 50 200

MG2 Power (kW) - - 50

Battery Energy 

(kWh) - 5 25

Battery Power (kW) - 50 200

Transmission 10 speed (14.8 - 1) 10 speed (14.8 - 1) 10 speed (14.8 - 1)

Mech. Acc. (kW) 5.2 1 1

Elec. Acc. (kW) 0.3 3 3

Mass (t) 26.26 26.26 26.26

7.3.3 Control Design

The vehicle level controller manages the different hybrid powertrain components: engine, 

electric machine(s) and transmission (clutch and gearbox) in order to optimize fuel consumption, while 

maintaining the battery state-of-charge within appropriate levels. Table 19 summarizes the control for 

both configurations.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Table 19: Summary of Control Strategy

Mild Hybrid Full Hybrid

Engine ON/OFF - ON when the vehicle is moving.

- OFF when the vehicle is stopped

- ON if the power request is 

above a certain threshold, or if 

motor is saturated

- OFF if the power request is 

below a certain threshold, and 

below a vehicle speed threshold

SOC regulation - hysteresis: if SOC is below a 

threshold, engine is ON and charges 

the battery until the SOC reaches a 

higher threshold

- the level of torque assist depends 

on the SOC

- hysteresis: if SOC is below a 

threshold, engine is ON and 

charges the battery until the 

SOC reaches a higher threshold

- the level of torque assist 

depends on the SOC

Shifting/Transmission - same shifting control as for 

conventional manual

- series mode at low speeds, 

parallel otherwise; clutch open 

when engine is off.

- quick shifting time due to 

speed synchronization by 

electric motors

Torque Assist - difference between requested 

torque and peak engine torque if 

the engine is saturating

- percentage of total torque 

demand, when it is high enough

- no assist above a vehicle speed 

threshold that depends on SOC

- difference between requested 

torque and peak engine torque 

if the engine is saturating

- percentage of total torque 

demand, when it is high enough

- no assist above a vehicle speed 

threshold that depends on SOC

Braking - engine fuel is cut-off

- clutch locked to allow 

regenerative braking

- engine fuel is cut-off

- clutch locked if engine is ON, 

open otherwise

7.3.4 Standard Drive Cycles Results

All versions of the truck (conventional, mild and full hybrid) were simulated on various standard 

cycles, both highway cycles (HHDDT 65, HHDDT Cruise, HHDDT high speed) and transient/urban (HHDDT 

Transient, UDDS Truck). 

Table 20 summarizes the main characteristics of each cycle.

When testing or simulating a hybrid vehicle, it is necessary to ensure that the results are not 

biased by the battery energy – the test/simulation needs to be “charge balanced”. Several iterations of 

the same cycles were run, so that difference in battery SOC (between the start and the end of the 

simulation), and therefore the battery energy used become negligible.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Table 20: Main Characteristics of Drive cycles

Average 

Speed 

(mph)

Max. 

Speed 

(mph)

Max. 

Accel. 

(m/s2)

Max. 

Decel. 

(m/s2)

Distance 

(mi)

Duration 

(s)

Time 

Stopped 

(%)

HHDDT 65 50 66.7 2 -2.8 26.5 1904 5

HHDDT 

Cruise 39.9 59.1 0.42 -0.59 23.1 2083 6

HHDDT High 

Speed 50.2 66.1 0.69 -1.2 10.5 757 6

HHDDT 

Transient 15.3 47.5 1.32 -2.4 2.8 668 17

UDDS Truck 18.7 57.7 1.9 -2.1 5.5 1060 33

Figure 34 shows the fuel consumption of all 3 trucks, while Figure 35 illustrates the fuel savings 

compared to conventional. For both hybrids, the fuel savings are lower on the highway cycles, which is 

to be expected since the hybrid system does not help much at cruising speeds where the engine already 

operates efficiently. The mild-hybrid shows fewer saving than the full hybrid, peaking at 11 %, while the 

full-hybrid can save up to 40% on a urban cycle.

Figure 34: Fuel Consumption of conventional and hybrid trucks on standard cycles

16.1

13.8

16.4

24.5

22.7

15.7

13.3

15.9

22.0

20.1

15.3

12.6

15.2 14.8

16.2

0.0

5.0

10.0

15.0

20.0

25.0

30.0

HHDDT65 HHDDT Cruise HHDDT High 

Speed

HHDDT 

Transient

udds_truck

Fuel Consumption (gal/100 mi)

CONV MILD FULL
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 35: Fuel Saved by hybrid trucks with respect to conventional truck, on standard cycles

Most of the gains originate in the energy recovered during braking. Figure 36 shows the fraction 

of the total braking energy that is recovered at the wheel – meaning not including the driveline and 

electric machine losses involved in the channeling of that energy into the battery. The recovery rate 

depends on the cycle aggressiveness during deceleration. On the HHDDT Cruise cycle, which has the 

lowest deceleration levels among all the cycles, the full-hybrid manages to recover almost all of the 

braking energy – i.e. mechanical brakes are not rarely used– but only half of it in the HHDDT 65. The 

mild-hybrid recovers about 25% of the braking energy on most cycles, and peaking at 55% on the 

HHDDT Cruise. This is due to the much lower power of the electric machine, combined with a higher 

torque interruption time during shifting.

Figure 36: Percentage of Braking Energy Recovered at the Wheels

2.8 4.0 3.5

10.3 11.3

5.3

9.0 7.3

39.5

28.8

0

5

10

15

20

25

30

35

40

45

HHDDT65 HHDDT Cruise HHDDT High 

Speed

HHDDT 

Transient

udds_truck

Fuel Savings w.r.t. to conventional (%)

CONV MILD FULL

24.62

55.24

32.8

22.92 20.9

57.79

97.8

80.12

75.62 74.57

0

10

20

30

40

50

60

70

80

90

100

HHDDT65 

filtererd

HHDDT Cruise HHDDT High 

Speed

HHDDT 

Transient

udds_truck

Recovered Braking Energy (%)

CONV MICRO MILD
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

The engine efficiency does however not improve significantly in most cases, as shown on Figure

37. In particular, in the mild-hybrid case, the engine efficiency is even slightly lower than in the 

conventional case. The main difference in engine operations between the conventional and the mildhybrid is that the engine is shut down when the vehicle is stopped for the mild-hybrid while the 

operations are similar when the vehicle is moving. In addition, the mechanical accessory load is much 

higher for the conventional (5 kW vs. 1 kW), and additional load generally improves efficiency. For the 

full hybrid, the efficiency improvements are limited on the highway cycles but are significant on the 

transient/urban cycles, where the low efficiency operations can be replaced by electric-only mode.

Figure 37: Average Engine Efficiency of conventional and hybrid trucks on standard cycles

7.3.5 Hybridization and Grade

7.3.5.1 Description of the Study

In the previous simulations, the road driven was flat – i.e. no grade. In real-world, trucks 

regularly drive uphill or downhill. Driving downhill may involve braking, which can be an opportunity for 

fuel savings when using regenerative braking. Due to the lack of real world drive cycles that included 

grade, to illustrate the potential benefits of hybridization in a “hilly” terrain, idealized sinusoidal road 

profiles were created. The elevation of such a road is a sinusoidal function of the horizontal distance, 

with a “hill” period varying between 1 and 3 km. Maximum grades also vary from 0 to 4 %. All 

combinations of maximum grade and period were analyzed. Figure 38 shows an example of elevation 

change as a function of horizontal distance for roads with same maximum grades but different hill 

periods. The hill period can be seen as twice the approximate distance traveled between the bottom of 

the hill (“valley”) and the top of the hill (“summit”). The vehicle speed target is 60 mph. The maximum 

positive grade is achieved halfway to the “summit”, and the maximum negative grade halfway between 
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

the “summit” and the “valley” – there is a (horizontal) phase difference of a quarter of a period between 

the grade and the elevation.

Figure 38: Sectional View of roads (partial) with the same maximum (3%) grade but 3 different hill periods

7.3.5.2 Adaptive Control

The control described in 7.3.3 was designed to ensure proper SOC fluctuations, but on steadystates, it generally needs to be tuned to operate efficiently. For example, the default set of control 

parameters does not allow torque assist at higher speeds and as a result, the battery SOC increases after 

each downhill braking event. The control was therefore tuned so that the energy recovered downhill is 

spent for accessories during the entire hill and for torque assist during uphill. The tuning is generally a 

function of maximum grade. The strategy adopted is likely to be the optimal way of driving such a cycle 

as it does not involve any battery charging from the engine (except at low grades). The results may 

therefore be slightly optimistic for hybrids, but an intelligent controller, e.g. GPS based, should be able 

to come close to that solution in a real-world situation.

An illustration of the control can be seen on Figure 39 for two different maximum grade values. 

At time t=266, the negative grade is maximal in both cases, and the electric machine can recuperate 

some energy from braking, all the more that the grade is intense. At time t=247s, the grade is maximal 

and so is the level of torque assist. However, one can notice that the powers, and energies, are different 

from one grade to the other, while SOC is balanced in both cases.

0 2 4 6 8 10

0

5

10

15

20

25

30

Horizontal Distance (km)

Elevation (m)

Hill Period D = 1 km

Hill Period D = 2 km

Hill Period D = 3 km
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Figure 39: Motor use uphill and downhill on a road with a hill period of 1 km, and 2.5% (left) or 4% (right) maximum grade, 

for a full-hybrid

7.3.5.3 Simulation Paradigm

A simulation performed on a time basis, as it is done in PSAT may lead in some cases to an 

incorrect representation of how a trip is performed – the same reasoning applies to dynamometer tests 

with a vehicle speed trace. When the simulation is performed based on time, the vehicle speed and 

grade targets are given at each time step. So long the vehicle follows the speed trace closely, the 

difference between what the vehicle is supposed to do (as per the cycle) and what it actually does (in 

simulation) is negligible, and gives a good representation of making a similar trip in real life. This is a 

non-issue for light-duty applications, where the vehicle is always able to meet the trace. On the other 

hand, heavy-duty vehicles, especially tractor-trailers, often operate close to their peak power. There are 

therefore more chances that the vehicle cannot follow the trace. A loss of speed relative to the trace 

leads to a lower travelled distance; when looking at consumption per unit of distance, this is somehow 

cancelled, but still different works are performed. In particular this is an issue for grades. Let’s take a 

simple example: let’s assume that the target speed is 90 km/h and there is a constant grade during 30s 

and then there is a flat portion; let us assume truck A can go uphill at 90 km/h, but truck B can go only 

75 km/h with that grade. After 30 s, truck A would have climbed 750 m, and truck B only 625 m. After 30 

s, both trucks go on the flat portion whereas truck B has still 125 m left to the end of the hill! In this 

study, the conventional truck is not able to sustain all the grades, contrary to the full-hybrid. Using the 

grade signal and the actual vehicle speed (from simulation), the sectional views of the roads actually 

performed are showed on Figure 40 for the conventional and the full-hybrid. The difference of phase is 

due to the acceleration part (on flat terrain) done before starting the hills: the shifting time is much 

shorter for the hybrid, involving little or no vehicle speed loss contrary to the conventional truck. Since 

the conventional truck is not able to sustain the target speed (60 mph) during the whole hill, after the 

time the climbing is supposed to last, the elevation gain is lower. Going downhill, the truck has no issues 

meeting the speed target, the elevation loss will be what it is supposed to be. As a result the 

conventional truck ends up lower (in terms of elevation) than the hybrid truck. After 30 km in such hills, 

240 245 250 255 260 265 270 275

-150

-100

-50

0

50

100

Time (s)

Grade x10 (%)

∆SOCx10 (%)

Motor Mech. Power (kW)

240 245 250 255 260 265 270 275

-150

-100

-50

0

50

100

Time (s)

Grade x10 (%)

∆SOCx10 (%)

Motor Mech. Power (kW)
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with a maximum grade of 4%, the conventional ends up 7 m (more than half the elevation of one hill) 

below where it started, while the full-hybrid is at the same level.

Figure 40: Section View of the actual trip for a conventional and a full-hybrid truck (4% maximum grade, 1 km hill period)

The quantitative impact on fuel consumption of that is not addressed in this study, but the 

reader should keep in mind the uncertainty added by an inability to follow the trace. 

Another uncertainty in the representativeness of this simulation is the constant speed 

assumptions. It may be the case that the driver will not brake downhill so that he can be at a higher 

speed before starting the next hill. If there is no braking, there is little or no gain to expect from hybrid 

models.

7.3.5.4 Results

Figure 41 shows the fuel consumption of the three versions of the trucks on various hills. The 

fuel savings achieved by both hybrid trucks are showed on Figure 42. 

With a 1% grade, there is no need for the driver to brake in order to stay at 60 mph and 

regenerative braking is not possible, so hybridization gains are limited. 

At 2% grade, there is some limited amount of braking, but even at full recuperation rate, the 

energy recovered is not enough to supply the energy for the accessory load. Charge balancing is hard to 

achieve in that mode, and charging from engine may occur, which explains the difference in trends. 

4 4.2 4.4 4.6 4.8 5

0

2

4

6

8

10

12

Horizontal Distance (km)

Elevation (m)

Conventional

Mild Hybrid Full -hybrid
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At or above 2.5 %, the downhill grade is steep enough to recover enough energy for the 

accessory load and for some torque assist. 

Above 3% grade, the mild-hybrid savings stop increasing because the additional braking energy 

available cannot be recovered by the small motor. For high grades, the fuel savings for the full hybrid are 

all the higher that the hill period is shorter. This is not due to the hybrid itself, but to the conventional, 

which consumes more fuel when the hill period is shorter (and elevation is lower). 

Figure 41: Fuel Consumption of Conventional, Mild-hybrid and full hybrid trucks on a sinusoidal road as a function of grade 

(and for various hill periods).

Figure 42: Fuel savings of hybrid trucks with respect to conventional truck as a function of maximum grade (for various hill 

periods)

0 1 2 3 4

13

14

15

16

17

18

Max Grade (%)

Fuel Cons. (gal/100 mi)

Conv

Hill Period=1 km

Hill Period=2 km

Hill Period=3 km

0 1 2 3 4

13

14

15

16

17

18

Max Grade (%)

Mild HEV

Hill Period=1 km

Hill Period=2 km

Hill Period=3 km

0 1 2 3 4

13

14

15

16

17

18

Max Grade (%)

Full HEV

Hill Period=1 km

Hill Period=2 km

Hill Period=3 km

0 1 2 3 4

0

2

4

6

8

10

12

14

Max Grade (%)

Fuel Savings (%)

Mild

Hill Period=1 km

Hill Period=2 km

Hill Period=3 km

0 1 2 3 4

0

2

4

6

8

10

12

14

Max Grade (%)

Fuel Savings (%)

Full

Hill Period=1 km

Hill Period=2 km

Hill Period=3 km
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8 Impact of Combined Technologies on Fuel Consumption

The objective of this paragraph is to evaluate the impact of various technology improvement 

packages on fuel consumption. The objective is to demonstrate and quantify that the gain of several 

technologies is not the sum of the gain of each separate ones. The pickup truck class 2b was considered 

for the study.

8.1 Baseline Vehicle Assumptions

Table 21: Assumptions for the Pickup Class 2b used in the study of Technology Combination impact on Fuel Consumption

Component Model Characteristics Source – Based on... 

Engine Gasoline– GM LM7 5.3L – 268kW (34.7% 

peak efficiency)

Transmission Allison 1000 Automatic 6 Speed

Ratios : 3.1 , 1.81 , 1.41 , 1, 0.71, 0.61 

GMC Sierra 2500HD 

Final Drive Ratio 3.73 GMC Sierra 2500HD 

Tire P245/75/R16 – Radius = 0.387 m

Rolling Resistance = 0.007

GMC Sierra 2500HD 

Aero Drag Coefficient = 0.44

Curb Weight 2659 kg GMC Sierra 2500HD 

GVWR 4152 kg

Max Payload 1513 kg GMC Sierra 2500HD 

The assumptions for the baseline pickup truck vehicle are based on the 2009 GMC Sierra 2500 HD. 

As previously explained, the GM LM7 5.3L was selected as an alternate gasoline engine since the Vortec 

6.0L data was not available. The engine was scaled to match the Vortec specifications. Although a 6-

speed automatic transmission appears to be the standard reference gearbox for a 2009 pickup class 2b, 

we will also consider the case of having a 4-speed automatic vehicle.

8.2 Assumptions for Technology Improvements

Since the technology improvements could have different impacts on fuel consumption whether they 

are applied to a conventional or a hybrid, we will consider two different paths. The first path will use a 

baseline conventional vehicle which will benefit of successive technology improvements (such as aero, 

transmissions...) with hybridization only applied at the end. The second path will start from a baseline 

hybrid vehicle which will also benefit of aerodynamic improvements, optimized transmissions... In the 

following individual technology tables, we will show both the fuel consumption reductions in 
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

comparison to conventional and hybrid baselines. In bold are the assumptions that were used for 

simulation. The results were generated based on the combined drive cycle (UDDS + HWFET).

8.2.1 Vehicle Weight

Table 22: Impact of Weight Reduction alone on Fuel Consumption for the Class 2b

Weight Reduction (kg) Percent Fuel Saved for 

Conventional (%)

Percent Fuel Saved for Hybrid 

(%)

-100 +1.05 +0.97

-136 +1.39 +1.39

-200 +2.09 +2.02

For the package simulation, we will use a weight reduction of 300 lb (about 136 kg).

8.2.2 Aerodynamics

Table 23: Impact of Aerodynamics alone on Fuel Consumption for the Class 2b

Drag Coefficient Percent Fuel Saved for 

Conventional (%)

Percent Fuel Saved for Hybrid 

(%)

0.44 0 0

0.35 +2.66 +3.40

0.34 +2.98 +3.81

0.33 +3.29 +4.22

If the drag coefficient is reduced from 0.44 to 0.34 (-22%), we could expect up to 3% fuel savings

for the conventional and almost 4% for the hybrid. This is consistent with light duty fuel consumption 

reduction estimates which predict a 1.5% fuel saving for each 10% reduction in drag coefficient.

8.2.3 Rolling Resistance

Table 24: Impact of Rolling Resistance alone on Fuel Consumption for the Class 2b

Rolling Resistance Percent Fuel Saved for 

Conventional (%)

Percent Fuel Saved for 

Hybrid (%)

0.007 0 0

0.00665 +0.57 +0.85

0.0063 +1.18 +1.59

0.0059 +1.82 +2.43

0.0058 +2.02 +2.69
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Several rolling resistance improvements were considered and are described in Table 24. The 

value corresponding to a 10% rolling resistance improvement was chosen and could allow about 1.18% 

of fuel savings.

8.2.4 Transmission

Table 25: Impact of Transmission alone on Fuel Consumption for the Class 2b

Gearbox Percent Fuel Saved if 

reference is 6-Speed 

(Conventional)

Percent Fuel Saved if 

reference is 4-Speed 

(Conventional)

Percent Fuel Saved 

if reference is 6-

Speed (Hybrid)

6-Speed Automatic 0 +4.59 0

8-Speed Automatic +1.72 +6.23 1.39

An 8 speed automatic transmission was selected as the improved technology. If the baseline is a 

6-Speed automatic, only 1.72% of savings could be expected. However, if the reference vehicle is now 

equipped with a 4-Speed automatic gearbox, then the amount of fuel saved could reach 6.23%.

8.2.5 Engine

The modeling assumptions for the engine technology focused on the improvement of the 

efficiency through linear scaling of the entire map. Other technologies such as gasoline direct injection, 

turbo charging and downsizing could be considered but were not modeled. 

Table 26: Impact of Engine Efficiency alone on Fuel Consumption for the Class 2b

Engine Peak Efficiency (%) Percent Fuel Saved for 

Conventional (%)

Percent Fuel Saved for Hybrid 

(%)

34.7 0 0

35 +0.77 -

36 +3.54 -

37 +6.16 -

38 +8.59 +8.86

The peak efficiency was linearly scaled to match the improvement goal. If this value is increased 

from 34.7% to 38%, roughly 9% of fuel savings can be expected for both conventional and hybrid. For all 

the package simulations where engine improvement was applied, a 38% peak efficiency value was used.

8.2.6 Hybrid

The hybridization of the class 2b truck was assumed to be a parallel Hybrid Electric Vehicle equipped 

with a 50 kW electric machine. The features offered by such technologies are Engine Start/Stop
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

operations, regenerative braking, electric launch at low vehicle speeds and a blend of engine power and 

motor power depending on the Battery State of Charge. 

Table 27: Impact of Hybridization on Fuel Consumption for the Class 2b

Rolling Resistance Percent Fuel Saved compared 

to Conventional(%)

Parallel HEV – 50kW motor –

No change in weight

+14.81

Parallel HEV – 50kW motor –

+100Kg weight

+13.94

Parallel HEV – 100kW motor –

No change in weight

+15.27

Parallel HEV – 100kW motor –

+200Kg weight

+13.42

Drive cycles such as UDDS or HWFET do not require a electric machine with a power greater than 50 

kW in order to capture most of the braking energy. Consequently, the hybrid option with a 100kW 

electric machine was dismissed. The option which was chosen for package simulations was the 50kW 

electric machine with no change in weight.

8.3 Fuel Savings for Various Technology Combinations

In most cases, the sum of the fuel consumption benefits of individual technologies is greater than 

their combination. It is also interesting to notice that the fuel consumption reduction is always higher 

for the hybrid than for the conventional when the same technologies are applied.
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 43: Fuel Consumption Savings by combining Aerodynamics and Weight improvements on a Conventional and Hybrid 

Baseline.

Figure 43 shows an example of improvement package. In this case, a reduction in drag coefficient 

and weight is applied to both the conventional and the hybrid baseline vehicles. The sum of individual 

technologies either equals the combination (for the conventional) or is greater than the combination 

(for the hybrid). This figure shows that by combining a lighter weight with improved aerodynamics, fuel 

consumption could drop by 4 to 5%. For most technology improvements, the hybrid baseline benefits 

more from these changes than the conventional. If we take the example of the drag coefficient, this can 

be explained by the fact that reducing it not only lowers the vehicle aerodynamic losses but also lowers 

the energy provided by the motor and thus the battery will require less charging from the engine.

4.4% 5.1%

1.4% 1.4%

3.0%

3.8%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

Each 

technology 

(Conv)

Combination

(Conv)

Each 

technology

(Hybrid)

Combination

(Hybrid)

Percent Fuel Saved

Impact of Aero and Weight reduction on Fuel Consumption

Cd

Weight

Hybrid 

improvements
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 44: Fuel Consumption Savings by combining Aerodynamics, Rolling Resistance and Weight improvements on a 

Conventional and Hybrid Baseline.

Figure 44 considers an additional improvement with the reduction of rolling resistance. In this 

situation also, the hybrid fuel savings are greater than for the conventional when looking at individual 

technologies or packages. The combination of a light weighted vehicle with low rolling resistance and 

improved aerodynamics could save between 5.5 to 6.6%.

5.5%

6.6%

1.4% 1.4%

3.0% 3.8%

1.2%

1.6%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

Each 

technology 

(Conv)

Combination

(Conv)

Each 

technology

(Hybrid)

Combination

(Hybrid)

Percent Fuel Saved

Impact of Aero, Rolling Resistance and Weight on Fuel 

Consumption

RR

Cd

Weight

Hybrid 

improvements

Baseline 

improvements
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 45: Fuel Consumption Savings by combining Aerodynamics, Rolling Resistance, Transmission and Weight 

improvements on a Conventional and Hybrid Baseline.

Figure 45 adds the impact of an improved transmission to the previous figure. The percentage 

showed is for an 8-Speed transmission in comparison to a 6-Speed baseline vehicle. Since the reference 

vehicle has already an efficient transmission, this package does not reduce fuel consumption by a 

significant amount.

Figure 46: Fuel Consumption Savings by combining all improvements on a Conventional and Hybrid Baseline.

6.9%

7.9%

1.4% 1.4%

3.0% 3.8%

1.2%

1.6% 1.7%

1.4%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

Each 

technology 

(Conv)

Combination

(Conv)

Each 

technology

(Hybrid)

Combination

(Hybrid)

Percent Fuel Saved

Impact of Aero, Rolling Resistance, Weight and Transmission 

on Fuel Consumption

Transmission

RR

Cd

Weight

Hybrid 

improvements

Baseline 

improvements

14.9% 15.9%

1.4% 1.4%

3.0% 3.8%

1.2%

1.7% 1.6%

1.4%

8.6%

8.9%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

20.0%

Each 

technology 

(Conv)

Combination

(Conv)

Each 

technology

(Hybrid)

Combination

(Hybrid)

Percent Fuel Saved

Impact of All Technologies on Fuel Consumption

Engine

Transmission

RR

Cd

Weight

Hybrid 

improvements

Baseline 

improvements
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

As showed by Figure 46, adding the improved engine efficiency to the combination package 

increases the fuel savings dramatically. This package can provide up to 15% fuel savings for the 

conventional and 16% for the hybrid.

Figure 47: Fuel Consumption Savings by combining all technology improvements and hybridization on a Conventional 

Baseline.

Finally, Figure 47 shows the impact of the full improvement package (including all the previous 

discussed technologies and the hybridization of the vehicle to a parallel HEV). This combination predicts 

a 28.4% fuel consumption reduction.

8.4 Comparison with TIAX Estimates 

This section compares the fuel consumption reduction simulation estimates with the values 

generated by TIAX for the NAS committee. 

28.4%

1.4%

3.0%

1.2%

1.7%

8.6%

14.8%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

Each 

technology (Conv)

Combination(Conv)

Percent Fuel Saved

Impact of All technologies and Hybridization on Fuel 

Consumption Hybrid CS

Engine

Transmission

RR

Cd

Weight

Baseline 

improvements
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Figure 48: Fuel Consumption Savings of Improvement Package using Simulation or TIAX Estimates

In Figure 48, one notices that the main differences come from the transmission and the engine. TIAX 

used a 4-Speed transmission baseline vehicle whereas the simulation assumptions were based on a 6-

Speed configuration. In addition, the engine improvements for simulation only focused on peak 

efficiency while TIAX considered more advanced technologies. On Figure 49 the same comparison is 

made where both simulation and TIAX use a 4-Speed baseline vehicle. Therefore the only major 

difference between the two studies remains in the engine technology improvement. For all the other 

technologies, TIAX and PSAT estimates are not significantly different.

28.4%

44.5%

1.4% 0.8%

3.0% 3.0%

1.2% 2.0%

1.7%

7.5%

8.6%

23.0%

14.8%

18.0%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

Each 

technology 

(PSAT)

Combination

(PSAT)

Each 

technology

(TIAX)

Combination

(TIAX)

Percent Fuel Saved

Technology Combination Impact for Simulation vs TIAX

Hybrid CS

Engine

Transmission

RR

Cd

Weight

Hybrid improvements

Baseline improvements
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Figure 49: Fuel Consumption Savings of Improvement Package using Simulation or TIAX Estimates when using the same 

baseline Transmission

31.7%

44.5%

1.4% 0.8%

3.0% 3.0%

1.2% 2.0%

6.2% 7.5%

8.6%

23.0%

14.8%

18.0%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

Each 

technology 

(PSAT)

Combination

(PSAT)

Each 

technology

(TIAX)

Combination

(TIAX)

Percent Fuel Saved

Technology Combination Impact for Simulation vs TIAX

(same baseline transmission)

Hybrid CS

Engine

Transmission

RR

Cd

Weight

Hybrid improvements

Baseline improvements
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

9 Conclusion

Numerous simulation studies were performed to provide quantitative inputs to support the National 

Academy committee recommendations. The simulation tool along with the vehicle and component 

assumptions was defined. Specific drive cycles were selected for the different applications considered.

The study of the different metrics pointed out to the need to use fuel consumption rather than fuel 

economy. In addition, the payload should be considered as well to properly represent the work of the 

truck. As such, some metric related to Load Specific Fuel Consumption seem most appropriate to 

evaluate truck technologies. 

The energy / power analysis highlighted the importance of the engine losses compared to the rest of the 

drivetrain. In addition, the average vehicle speed should be carefully considered when evaluating a 

technology since its influence on fuel consumption will greatly differ.

While the average vehicle speed of a drive cycle correlates well with fuel consumption, the fuel 

consumed is always higher than during steady-state operations, especially for urban driving (low 

average speed). Since a particular technology might have different influence based on the vehicle 

weight, representing its impact of several payloads would allow a more accurate evaluation.

The impact of several individual technologies, both individual and cumulated, was assessed, including 

aerodynamic, rolling resistance, fuel type, transmission, engine and hybridization. The difference 

between the sums of each individual technology was compared with the gains of the cumulated 

technologies.

The study demonstrated the usefulness of vehicle modeling and simulation to assess the potential of 

numerous technologies for different drive cycles and operating conditions (e.g., payloads). However, 

because of the large number of applications and the fact that some vehicles are specifically designed for 

customers, there is currently no widely accepted Vehicle Technical Specifications – VTS - (e.g., maximum 

vehicle speed, grade, performance...) for each option. Since technologies should be compared based on 

similar VTS, the definition of the vehicle characteristics for powertrains such as HEVs becomes 

problematic. In addition, the limited access to specific state-of-the-art data for all applications leads to 

using component with similar technologies, which is non-ideal.
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Appendix A – Overview of Drive Cycles
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Appendix B – Energy / Power Flow

Bus - 10% Load

engine

η=38%

%Loss=62%

90.7 kW

56.3 kW

mech. acc.

η=50.6%

%Loss=18.7%

34.4 kW

17 kW

elec. acc.

η=88.5%

%Loss=2.2%

17.4 kW

2 kW

trans.

η=89.3%

%Loss=1.8%

15.4 kW

1.64 kW

axle

η=97.1%

%Loss=0.4%

13.8 kW

0.4 kW

tires

η=20.2%

%Loss=11.8%

13.4 kW

10.7 kW

aero

η=16.3%

%Loss=2.5%

2.71 kW

2.27 kW

Power Flow Diagram - bus / SS 20 mph / 10%

Load

engine

η=39.9%

%Loss=60.1%

138 kW

82.8 kW

mech. acc.

η=69%

%Loss=12.4%

54.9 kW

17 kW

elec. acc.

η=94.7%

%Loss=1.5%

37.9 kW

2 kW

trans.

η=94.7%

%Loss=1.4%

35.9 kW

1.89 kW

axle

η=97%

%Loss=0.7%

34 kW

1.01 kW

tires

η=38.3%

%Loss=14.8%

33 kW

20.3 kW

aero

η=3.4%

%Loss=8.8%

12.6 kW

12.2 kW

Power Flow Diagram - bus / SS 35 mph / 10% Load

engine

η=41.2%

%Loss=58.8%

220 kW

129 kW

mech. acc.

η=81.3%

%Loss=7.7%

90.7 kW

17 kW

elec. acc.

η=97.3%

%Loss=0.9%

73.7 kW

2 kW

trans.

η=96.8%

%Loss=1%

71.7 kW

2.27 kW

axle

η=97%

%Loss=0.9%

69.4 kW

2.07 kW

tires

η=53.3%

%Loss=14.3%

67.4 kW

31.4 kW

aero

η=1.2%

%Loss=16.1%

35.9 kW

35.5 kW

Power Flow Diagram - bus / SS 50 mph / 10% Load
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Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

10 20 30 40 50 60

0

20

40

60

80

100

120

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - bus / SS / 10 % Load

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero

Total losses x.1 (kW)

62%

19%

2%

< 1%2%

12% 3%

20 mph (Losses = 90.2 kW)

61% 17%

2%

< 1%2%

13%

4%

25 mph (Losses = 102 kW)

60%

15%

2%

< 1%1%

15%

7%

30 mph (Losses = 113 kW)

60%

12%

< 1%

1%1%

15%

9%

35 mph (Losses = 137 kW)

59%

11%

< 1% 1%1%

15%

12%

40 mph (Losses = 156 kW)

59%

9%

< 1% 1%1%

15%

14%

45 mph (Losses = 187 kW)

59%

8%

< 1% < 1% 1%

14%

16%

50 mph (Losses = 219 kW)

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero
78

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Bus - 50% Load

engine

η=38.1%

%Loss=61.9%

93.8 kW

58.1 kW

mech. acc.

η=52.5%

%Loss=18.1%

35.8 kW

17 kW

elec. acc.

η=89.3%

%Loss=2.1%

18.8 kW

2 kW

trans.

η=89.5%

%Loss=1.9%

16.8 kW

1.77 kW

axle

η=97.1%

%Loss=0.5%

15 kW

0.437

kW

tires

η=18.6%

%Loss=12.6%

14.6 kW

11.8 kW

aero

η=16.3%

%Loss=2.4%

2.71 kW

2.27 kW

Power Flow Diagram - bus / SS 20 mph / 50% Load

engine

η=40%

%Loss=60%

144 kW

86.2 kW

mech. acc.

η=70.4%

%Loss=11.8%

57.4 kW

17 kW

elec. acc.

η=95%

%Loss=1.4%

40.4 kW

2 kW

trans.

η=94.5%

%Loss=1.5%

38.4 kW

2.11 kW

axle

η=97%

%Loss=0.7%

36.3 kW

1.07 kW

tires

η=35.8%

%Loss=15.7%

35.2 kW

22.6 kW

aero

η=3.4%

%Loss=8.5%

12.6 kW

12.2 kW

Power Flow Diagram - bus / SS 35 mph / 50% Load

engine

η=41.2%

%Loss=58.8%

229 kW

134 kW

mech. acc.

η=82%

%Loss=7.4%

94.3 kW

17 kW

elec. acc.

η=97.4%

%Loss=0.9%

77.3 kW

2 kW

trans.

η=96.9%

%Loss=1%

75.3 kW

2.34 kW

axle

η=97%

%Loss=1%

73 kW

2.18 kW

tires

η=50.7%

%Loss=15.3%

70.8 kW

34.9 kW

aero

η=1.2%

%Loss=15.5%

35.9 kW

35.5 kW

Power Flow Diagram - bus / SS 50 mph / 50% Load
79

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

10 20 30 40 50 60

0

20

40

60

80

100

120

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - bus / SS / 50 % Load

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero

Total losses x.1 (kW)

62% 18%

2%

< 1%2%

13% 2%

20 mph (Losses = 93.3 kW)

61% 16%

2%

< 1%2%

14%

4%

25 mph (Losses = 106 kW)

59%

14%

2%

< 1%1%

16%

7%

30 mph (Losses = 118 kW)

60%

12%

1%

< 1%1%

16%

9%

35 mph (Losses = 143 kW)

59%

10%

< 1% 1%1%

16%

11%

40 mph (Losses = 163 kW)

59%

9%

< 1% 1%1%

16%

13%

45 mph (Losses = 194 kW)

59%

7%

< 1% < 1% 1%

15%

16%

50 mph (Losses = 228 kW) engine

mech. acc.

elec. acc.

trans.

axle

tires

aero
80

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Bus - 100% Load

engine

η=39.9%

%Loss=60.1%

92.6 kW

55.7 kW

mech. acc.

η=54%

%Loss=18.4%

36.9 kW

17 kW

elec. acc.

η=90%

%Loss=2.2%

19.9 kW

2 kW

trans.

η=91.9%

%Loss=1.6%

17.9 kW

1.45 kW

axle

η=97.1%

%Loss=0.5%

16.5 kW

0.482

kW

tires

η=16.8%

%Loss=14.4%

16 kW

13.3 kW

aero

η=15.5%

%Loss=2.5%

2.69 kW

2.27 kW

Power Flow Diagram - bus / SS 20 mph / 100% Load

engine

η=40.1%

%Loss=59.9%

151 kW

90.5 kW

mech. acc.

η=71.9%

%Loss=11.3%

60.5 kW

17 kW

elec. acc.

η=95.4%

%Loss=1.3%

43.5 kW

2 kW

trans.

η=94.3%

%Loss=1.6%

41.5 kW

2.38 kW

axle

η=97%

%Loss=0.8%

39.1 kW

1.16 kW

tires

η=33.2%

%Loss=16.8%

38 kW

25.4 kW

aero

η=3.5%

%Loss=8.1%

12.6 kW

12.2 kW

Power Flow Diagram - bus / SS 35 mph / 100% Load

engine

η=41.3%

%Loss=58.7%

240 kW

141 kW

mech. acc.

η=82.8%

%Loss=7.1%

98.8 kW

17 kW

elec. acc.

η=97.6%

%Loss=0.8%

81.8 kW

2 kW

trans.

η=97%

%Loss=1%

79.8 kW

2.43 kW

axle

η=97%

%Loss=1%

77.4 kW

2.31 kW

tires

η=47.8%

%Loss=16.4%

75.1 kW

39.2 kW

aero

η=1.2%

%Loss=14.8%

35.9 kW

35.5 kW

Power Flow Diagram - bus / SS 50 mph / 100% Load
81

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

10 20 30 40 50 60

0

20

40

60

80

100

120

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - bus / SS / 100 % Load

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero

Total losses x.1 (kW)

60% 18%

2%

< 1%2%

14%

2%

20 mph (Losses = 92.1 kW)

61% 15%

2%

< 1%2%

15%

4%

25 mph (Losses = 111 kW)

59%

14%

2%

< 1%1%

17%

6%

30 mph (Losses = 124 kW)

60%

11%

1%

< 1%2%

17%

8%

35 mph (Losses = 150 kW)

59%

10%

< 1% 1%1%

17%

11%

40 mph (Losses = 171 kW)

59%

8%

< 1% < 1% 1%

17%

13%

45 mph (Losses = 203 kW)

59%

7%

< 1% < 1% 1%

16%

15%

50 mph (Losses = 239 kW) engine

mech. acc.

elec. acc.

trans.

axle

tires

aero
82

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Class 2b (Pick-up) - 10% Load

engine

η=7.8%

%Loss=92.2%

89.2 kW

82.2 kW

mech. acc.

η=100%

%Loss=0%

6.97 kW

0 kW

elec. acc.

η=89.4%

%Loss=0.8%

6.97 kW

0.74 kW

trans.

η=89.9%

%Loss=0.7%

6.23 kW

0.63 kW

axle

η=97.1%

%Loss=0.2%

5.6 kW

0.163

kW

tires

η=41.5%

%Loss=3.6%

5.44 kW

3.18 kW

aero

η=6.9%

%Loss=2.4%

2.26 kW

2.1 kW

Power Flow Diagram - cl2b / SS 30 mph / 10% Load

engine

η=16.1%

%Loss=83.9%

112 kW

93.6 kW

mech. acc.

η=100%

%Loss=0%

18 kW

0 kW

elec. acc.

η=95.9%

%Loss=0.7%

18 kW

0.74 kW

trans.

η=94.8%

%Loss=0.8%

17.2 kW

0.891

kW

axle

η=97%

%Loss=0.4%

16.4 kW

0.486

kW

tires

η=62.4%

%Loss=5.3%

15.9 kW

5.96 kW

aero

η=1.6%

%Loss=8.7%

9.91 kW

9.75 kW

Power Flow Diagram - cl2b / SS 50 mph / 10% Load

engine

η=24.4%

%Loss=75.6%

163 kW

123 kW

mech. acc.

η=100%

%Loss=0%

39.6 kW

0 kW

elec. acc.

η=98.1%

%Loss=0.5%

39.6 kW

0.74 kW

trans.

η=96%

%Loss=1%

38.9 kW

1.56 kW

axle

η=97%

%Loss=0.7%

37.3 kW

1.11 kW

tires

η=74.4%

%Loss=5.7%

36.2 kW

9.27 kW

aero

η=0.6%

%Loss=16.5%

26.9 kW

26.8 kW

Power Flow Diagram - cl2b / SS 70 mph / 10% Load
83

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

20 40 60 80

0

20

40

60

80

100

120

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - cl2b / SS / 10 % Load

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero

Total losses x.1 (kW)

92%

4%< 1% < 1% < 1% 2%

30 mph (Losses = 88.9 kW)

92%

4%< 1% < 1% < 1% 3%

35 mph (Losses = 109 kW)

86%

< 1% < 1% < 1%

6% 6%

40 mph (Losses = 80.7 kW)

85%

< 1% < 1%

6%

8%

45 mph (Losses = 94.1 kW)

84%

< 1% < 1% < 1%

5%

9%

50 mph (Losses = 111 kW)

78%

< 1% < 1%

7%

13%

55 mph (Losses = 102 kW)

78%

< 1% < 1%1%

6%

14%

60 mph (Losses = 121 kW)

77%

< 1% < 1%1%

6%

15%

65 mph (Losses = 140 kW)

76%

< 1%

6%

16%

70 mph (Losses = 162 kW)

engine

elec. acc.

trans.

axle

tires

aero
84

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Class 2b (Pick-up) - 50% Load

engine

η=8.6%

%Loss=91.4%

89.2 kW

81.5 kW

mech. acc.

η=100%

%Loss=0%

7.71 kW

0 kW

elec. acc.

η=90.4%

%Loss=0.8%

7.71 kW

0.74 kW

trans.

η=90.5%

%Loss=0.7%

6.97 kW

0.66 kW

axle

η=97.1%

%Loss=0.2%

6.31 kW

0.184

kW

tires

η=36.9%

%Loss=4.3%

6.12 kW

3.86 kW

aero

η=6.9%

%Loss=2.4%

2.26 kW

2.1 kW

Power Flow Diagram - cl2b / SS 30 mph / 50% Load

engine

η=17.3%

%Loss=82.7%

112 kW

92.2 kW

mech. acc.

η=100%

%Loss=0%

19.4 kW

0 kW

elec. acc.

η=96.2%

%Loss=0.7%

19.4 kW

0.74 kW

trans.

η=95%

%Loss=0.8%

18.6 kW

0.938

kW

axle

η=97%

%Loss=0.5%

17.7 kW

0.526

kW

tires

η=57.8%

%Loss=6.5%

17.1 kW

7.24 kW

aero

η=1.6%

%Loss=8.7%

9.9 kW

9.75 kW

Power Flow Diagram - cl2b / SS 50 mph / 50% Load

engine

η=25.3%

%Loss=74.7%

164 kW

123 kW

mech. acc.

η=100%

%Loss=0%

41.7 kW

0 kW

elec. acc.

η=98.2%

%Loss=0.5%

41.7 kW

0.74 kW

trans.

η=96.2%

%Loss=1%

40.9 kW

1.57 kW

axle

η=97%

%Loss=0.7%

39.4 kW

1.18 kW

tires

η=70.5%

%Loss=6.9%

38.2 kW

11.3 kW

aero

η=0.6%

%Loss=16.3%

26.9 kW

26.8 kW

Power Flow Diagram - cl2b / SS 70 mph / 50% Load
85

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

20 40 60 80

0

20

40

60

80

100

120

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - cl2b / SS / 50 % Load

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero

Total losses x.1 (kW)

92%

< 1% < 1% 2%4%

30 mph (Losses = 88.9 kW)

91%

< 1% < 1% < 1% 3%4%

35 mph (Losses = 109 kW)

85%

< 1% < 1% < 1%

7%

6%

40 mph (Losses = 80.7 kW)

84%

< 1% < 1%

7%

8%

45 mph (Losses = 94.1 kW)

83%

< 1% < 1%

7%

9%

50 mph (Losses = 111 kW)

77%

< 1% < 1% 1%

8%

12%

55 mph (Losses = 104 kW)

77%

< 1% < 1%1%

7%

14%

60 mph (Losses = 123 kW)

76%

< 1% < 1%1%

7%

15%

65 mph (Losses = 142 kW)

75%

< 1%

7%

16%

70 mph (Losses = 164 kW)

engine

elec. acc.

trans.

axle

tires

aero
86

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Class 2b (Pick-up) - 100% Load

engine

η=9.7%

%Loss=90.3%

89.2 kW

80.5 kW

mech. acc.

η=100%

%Loss=0%

8.63 kW

0 kW

elec. acc.

η=91.4%

%Loss=0.8%

8.63 kW

0.74 kW

trans.

η=91.1%

%Loss=0.8%

7.89 kW

0.699

kW

axle

η=97.1%

%Loss=0.2%

7.19 kW

0.211

kW

tires

η=32.4%

%Loss=5.3%

6.98 kW

4.72 kW

aero

η=6.9%

%Loss=2.4%

2.26 kW

2.1 kW

Power Flow Diagram - cl2b / SS 30 mph / 100%

Load

engine

η=22.7%

%Loss=77.3%

92.6 kW

71.6 kW

mech. acc.

η=100%

%Loss=0%

21 kW

0 kW

elec. acc.

η=96.5%

%Loss=0.8%

21 kW

0.74 kW

trans.

η=95.4%

%Loss=1%

20.3 kW

0.935

kW

axle

η=97%

%Loss=0.6%

19.3 kW

0.575

kW

tires

η=52.8%

%Loss=9.6%

18.8 kW

8.85 kW

aero

η=1.6%

%Loss=10.5%

9.9 kW

9.75 kW

Power Flow Diagram - cl2b / SS 50 mph / 100% Load

engine

η=26.5%

%Loss=73.5%

167 kW

122 kW

mech. acc.

η=100%

%Loss=0%

44.2 kW

0 kW

elec. acc.

η=98.3%

%Loss=0.4%

44.2 kW

0.74 kW

trans.

η=96.4%

%Loss=0.9%

43.5 kW

1.58 kW

axle

η=97%

%Loss=0.8%

41.9 kW

1.25 kW

tires

η=66.2%

%Loss=8.3%

40.7 kW

13.8 kW

aero

η=0.6%

%Loss=16.1%

26.9 kW

26.8 kW

Power Flow Diagram - cl2b / SS 70 mph / 100% Load
87

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

20 40 60 80

0

20

40

60

80

100

120

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - cl2b / SS / 100 % Load

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero

Total losses x.1 (kW)

90%

< 1% < 1% < 1%

2%5%

30 mph (Losses = 88.9 kW)

90%

< 1% < 1%

3%5%

35 mph (Losses = 109 kW)

83%

< 1% < 1% < 1%

8%

6%

40 mph (Losses = 80.7 kW)

82%

< 1% < 1%

8%

8%

45 mph (Losses = 94.1 kW)

77%

< 1% < 1%1%

10%

11%

50 mph (Losses = 92.4 kW)

76%

< 1% < 1%1%

9%

12%

55 mph (Losses = 106 kW)

75%

< 1% < 1%1%

9%

13%

60 mph (Losses = 125 kW)

74%

< 1% < 1%

9%

15%

65 mph (Losses = 144 kW)

74%

< 1%

8%

16%

70 mph (Losses = 166 kW)

engine

elec. acc.

trans.

axle

tires

aero
88

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Class 6 (Pick-up and Delivery) - 10% Load

engine

η=22.7%

%Loss=77.3%

83.4 kW

64.5 kW

mech. acc.

η=97.4%

%Loss=0.6%

18.9 kW

0.5 kW

elec. acc.

η=94.6%

%Loss=1.2%

18.4 kW

1 kW

17.4 kW

1.67 kW

axle

η=98%

%Loss=0.4%

15.7 kW

0.31 kW

tires

η=53%

%Loss=8.7%

15.4 kW

7.24 kW

aero

η=2.6%

%Loss=9.5%

8.17 kW

7.96 kW

trans.

η=90.4%

%Loss=2%

Power Flow Diagram - cl6 / SS 30 mph / 10% Load

engine

η=38%

%Loss=62%

282 kW

175 kW

mech. acc.

η=99.5%

%Loss=0.2%

107 kW

0.5 kW

elec. acc.

η=99.1%

%Loss=0.4%

107 kW

1 kW

trans.

η=96.6%

%Loss=1.3%

106 kW

3.61 kW

axle

η=98%

%Loss=0.7%

102 kW

2.03 kW

tires

η=81.5%

%Loss=6.6%

99.9 kW

18.5 kW

aero

η=0.3%

%Loss=28.8%

81.4 kW

81.2 kW

Power Flow Diagram - cl6 / SS 65 mph / 10% Load

engine

η=36.7%

%Loss=63.3%

152 kW

96.2 kW

mech. acc.

η=99.1%

%Loss=0.3%

55.8 kW

0.5 kW

elec. acc.

η=98.2%

%Loss=0.7%

55.3 kW

1 kW

trans.

η=94.7%

%Loss=1.9%

54.3 kW

2.87 kW

axle

η=98%

%Loss=0.7%

51.5 kW

1.02 kW

tires

η=73.6%

%Loss=8.8%

50.4 kW

13.3 kW

aero

η=0.6%

%Loss=24.3%

37.1 kW

36.9 kW

Power Flow Diagram - cl6 / SS 50 mph / 10% Load
89

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

20 40 60 80

0

20

40

60

80

100

120

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - cl6 / SS / 10 % Load

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero

Total losses x.1 (kW)

78%

< 1%1%

< 1%2%

9%

10%

30 mph (Losses = 83.1 kW)

77%

< 1%

< 1%2%

8%

11%

35 mph (Losses = 111 kW)

63%

< 1%1%

< 1% 2%

11%

21%

40 mph (Losses = 90 kW)

63%

< 1% < 1%< 1% 2%

10%

23%

45 mph (Losses = 116 kW)

63%

< 1% < 1%< 1% 2%

9%

24%

50 mph (Losses = 152 kW)

61%

< 1%< 1% 1%

8%

28%

55 mph (Losses = 178 kW)

62%

< 1%< 1% 1%

7%

28%

60 mph (Losses = 226 kW)

62%

< 1% < 1% 1%

7%

29%

65 mph (Losses = 281 kW)

63%

< 1% < 1% 1%

6%

29%

70 mph (Losses = 350 kW) engine

mech. acc.

elec. acc.

trans.

axle

tires

aero
90

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Class 6 (Pick-up and Delivery) - 50% Load

engine

η=26.6%

%Loss=73.4%

87.7 kW

64.3 kW

mech. acc.

η=97.9%

%Loss=0.6%

23.4 kW

0.5 kW

elec. acc.

η=95.6%

%Loss=1.1%

22.9 kW

1 kW

trans.

η=90.9%

%Loss=2.3%

21.9 kW

1.99 kW

axle

η=98%

%Loss=0.4%

19.9 kW

0.393

kW

tires

η=41.9%

%Loss=12.9%

19.5 kW

11.3 kW

aero

η=2.6%

%Loss=9.1%

8.16 kW

7.95 kW

Power Flow Diagram - cl6 / SS 30 mph / 50% Load

engine

η=37.9%

%Loss=62.1%

311 kW

193 kW

mech. acc.

η=99.6%

%Loss=0.2%

118 kW

0.5 kW

elec. acc.

η=99.1%

%Loss=0.3%

117 kW

1 kW

trans.

η=96.7%

%Loss=1.2%

116 kW

3.85 kW

axle

η=98%

%Loss=0.7%

112 kW

2.25 kW

tires

η=73.8%

%Loss=9.3%

110 kW

28.9 kW

aero

η=0.3%

%Loss=26.1%

81.4 kW

81.1 kW

Power Flow Diagram - cl6 / SS 65 mph / 50% Load

engine

η=37.3%

%Loss=62.7%

172 kW

108 kW

mech. acc.

η=99.2%

%Loss=0.3%

64.2 kW

0.5 kW

elec. acc.

η=98.4%

%Loss=0.6%

63.7 kW

1 kW

trans.

η=94.2%

%Loss=2.1%

62.7 kW

3.64 kW

axle

η=98%

%Loss=0.7%

59.1 kW

1.18 kW

tires

η=64.1%

%Loss=12.1%

57.9 kW

20.8 kW

aero

η=0.6%

%Loss=21.4%

37.1 kW

36.9 kW

Power Flow Diagram - cl6 / SS 50 mph / 50%

Load
91

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

20 40 60 80

0

20

40

60

80

100

120

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - cl6 / SS / 50 % Load

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero

Total losses x.1 (kW)

74%

< 1%1%

< 1%2%

13%

9%

30 mph (Losses = 87.4 kW)

73%

< 1%

< 1%2%

12%

11%

35 mph (Losses = 115 kW)

61%

< 1% < 1%< 1% 2%

16%

19%

40 mph (Losses = 101 kW)

62%

< 1% < 1%< 1% 2%

14%

20%

45 mph (Losses = 133 kW)

63%

< 1%

< 1% 2%

12%

21%

50 mph (Losses = 172 kW)

61%

< 1%< 1% 1%

12%

24%

55 mph (Losses = 201 kW)

62%

< 1%< 1% 1%

10%

25%

60 mph (Losses = 251 kW)

62%

< 1% < 1% 1%

9%

26%

65 mph (Losses = 310 kW)

63%

< 1% < 1% 1%

8%

27%

70 mph (Losses = 379 kW)

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero
92

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Class 6 (Pick-up and Delivery) - 100% Load

engine

η=31.1%

%Loss=68.9%

93.1 kW

64.1 kW

mech. acc.

η=98.3%

%Loss=0.5%

28.9 kW

0.5 kW

elec. acc.

η=96.5%

%Loss=1.1%

28.4 kW

1 kW

trans.

η=91.3%

%Loss=2.6%

27.4 kW

2.4 kW

axle

η=98%

%Loss=0.5%

25 kW

0.497

kW

tires

η=33.2%

%Loss=17.6%

24.6 kW

16.4 kW

aero

η=2.6%

%Loss=8.5%

8.15 kW

7.94 kW

Power Flow Diagram - cl6 / SS 30 mph / 100% Load

engine

η=37.5%

%Loss=62.5%

198 kW

124 kW

mech. acc.

η=99.3%

%Loss=0.3%

74.4 kW

0.5 kW

elec. acc.

η=98.6%

%Loss=0.5%

73.9 kW

1 kW

trans.

η=94%

%Loss=2.2%

72.9 kW

4.35 kW

axle

η=98%

%Loss=0.7%

68.6 kW

1.37 kW

tires

η=55.2%

%Loss=15.2%

67.2 kW

30.1 kW

aero

η=0.6%

%Loss=18.6%

37.1 kW

36.9 kW

Power Flow Diagram - cl6 / SS 50 mph / 100% Load

engine

η=38.1%

%Loss=61.9%

345 kW

214 kW

mech. acc.

η=99.6%

%Loss=0.1%

131 kW

0.5 kW

elec. acc.

η=99.2%

%Loss=0.3%

131 kW

1 kW

trans.

η=96.8%

%Loss=1.2%

130 kW

4.16 kW

axle

η=98%

%Loss=0.7%

126 kW

2.51 kW

tires

η=66%

%Loss=12.1%

123 kW

41.9 kW

aero

η=0.3%

%Loss=23.5%

81.3 kW

81.1 kW

Power Flow Diagram - cl6 / SS 65 mph / 100% Load
93

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

20 30 40 50 60 70

0

20

40

60

80

100

120

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - cl6 / SS / 100 % Load

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero

Total losses x.1 (kW)

69%

< 1%1%3%< 1%

18%

9%

30 mph (Losses = 92.8 kW)

69%

< 1%3%< 1%

16%

10%

35 mph (Losses = 120 kW)

61%

< 1% < 1%< 1% 2%

19%

16%

40 mph (Losses = 120 kW)

62%

< 1%

< 1% 2%

17%

17%

45 mph (Losses = 155 kW)

63%

< 1%

< 1% 2%

15%

19%

50 mph (Losses = 198 kW)

61%

< 1%< 1% 1%

15%

21%

55 mph (Losses = 230 kW)

61%

< 1%< 1% 1%

13%

23%

60 mph (Losses = 282 kW)

62%

< 1%< 1% 1%

12%

24%

65 mph (Losses = 344 kW)

62%

< 1% < 1% 1%

11%

24%

69 mph (Losses = 397 kW)

engine

mech. acc.

elec. acc.

trans.

axle

tires

aero
94

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Class 8 (Tractor-Trailer) - 10% Load

engine

η=38.7%

%Loss=61.3%

196 kW

120 kW

mech. acc.

η=N/A

%Loss=2.7%

75.9 kW

5.21 kW

elec. acc.

η=N/A

%Loss=0.2%

70.7 kW

0.36 kW

gearbox

η=98.1%

%Loss=0.7%

70.3 kW

1.34 kW

axle

η=98%

%Loss=0.7%

69 kW

1.37 kW

tires

η=N/A

%Loss=13.9%

67.6 kW

27.3 kW

aero

η=N/A

%Loss=20.5%

40.3 kW

40.3 kW

Power Flow Diagram - class8 / SS 50 mph / 10% Load

engine

η=40.7%

%Loss=59.3%

280 kW

166 kW

mech. acc.

η=N/A

%Loss=1.9%

114 kW

5.2 kW

elec. acc.

η=N/A

%Loss=0.1%

109 kW

0.36 kW

gearbox

η=98.1%

%Loss=0.7%

109 kW

2.06 kW

axle

η=98%

%Loss=0.8%

106 kW

2.12 kW

tires

η=N/A

%Loss=12.4%

104 kW

34.6 kW

aero

η=N/A

%Loss=24.8%

69.7 kW

69.6 kW

Power Flow Diagram - class8 / SS 60 mph / 10% Load

engine

η=40.5%

%Loss=59.5%

407 kW

242 kW

mech. acc.

η=N/A

%Loss=1.3%

165 kW

5.2 kW

elec. acc.

η=N/A

%Loss=0.1%

160 kW

0.36 kW

gearbox

η=98.1%

%Loss=0.7%

159 kW

3.03 kW

axle

η=98%

%Loss=0.8%

156 kW

3.11 kW

tires

η=N/A

%Loss=10.5%

153 kW

42.6 kW

aero

η=N/A

%Loss=27.2%

111 kW

111 kW

Power Flow Diagram - class8 / SS 70 mph / 10% Load
95

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

40 50 60 70 80

0

10

20

30

40

50

60

70

80

90

100

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - class8 / SS / 10 % Load

engine

mech. acc.

elec. acc.

gearbox

axle

tires

aero

Total losses x.1 (kW)

61%

3%< 1% < 1% < 1%

14%

21%

50 mph (Losses = 196 kW)

60%

2%< 1% < 1% < 1%

13%

23%

55 mph (Losses = 234 kW)

59%

< 1% 2%< 1% < 1%

12%

25%

60 mph (Losses = 280 kW)

59%

< 1% 2%< 1% < 1%

11%

26%

65 mph (Losses = 338 kW)

59%

< 1% < 1% 1%< 1%

10%

27%

70 mph (Losses = 406 kW)

engine

mech. acc.

elec. acc.

gearbox

axle

tires

aero
96

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Class 8 (Tractor-Trailer) - 50% Load

engine

η=39.6%

%Loss=60.4%

225 kW

136 kW

mech. acc.

η=N/A

%Loss=2.3%

89.1 kW

5.21 kW

elec. acc.

η=N/A

%Loss=0.2%

83.9 kW

0.36 kW

gearbox

η=98.1%

%Loss=0.7%

83.5 kW

1.59 kW

axle

η=98%

%Loss=0.7%

81.9 kW

1.63 kW

tires

η=N/A

%Loss=17.8%

80.3 kW

40 kW

aero

η=N/A

%Loss=17.9%

40.3 kW

40.3 kW

Power Flow Diagram - class8 / SS 50 mph / 50%

Load

engine

η=41.7%

%Loss=58.3%

314 kW

183 kW

mech. acc.

η=N/A

%Loss=1.7%

131 kW

5.2 kW

elec. acc.

η=N/A

%Loss=0.1%

126 kW

0.36 kW

gearbox

η=98.1%

%Loss=0.8%

125 kW

2.38 kW

axle

η=98%

%Loss=0.8%

123 kW

2.44 kW

tires

η=N/A

%Loss=16.2%

120 kW

50.7 kW

aero

η=N/A

%Loss=22.2%

69.7 kW

69.6 kW

Power Flow Diagram - class8 / SS 60 mph / 50% Load

engine

η=40.9%

%Loss=59.1%

453 kW

268 kW

mech. acc.

η=N/A

%Loss=1.1%

186 kW

5.2 kW

elec. acc.

η=N/A

%Loss=0.1%

180 kW

0.36 kW

gearbox

η=98.1%

%Loss=0.8%

180 kW

3.42 kW

axle

η=98%

%Loss=0.8%

177 kW

3.51 kW

tires

η=N/A

%Loss=13.8%

173 kW

62.4 kW

aero

η=N/A

%Loss=24.4%

111 kW

111 kW

Power Flow Diagram - class8 / SS 70 mph / 50% Load
97

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

40 50 60 70 80

0

10

20

30

40

50

60

70

80

90

100

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - class8 / SS / 50 % Load

engine

mech. acc.

elec. acc.

gearbox

axle

tires

aero

Total losses x.1 (kW)

60%

2%< 1% < 1% < 1%

18%

18%

50 mph (Losses = 225 kW)

59%

< 1% 2%< 1% < 1%

17%

20%

55 mph (Losses = 264 kW)

58%

< 1% 2%< 1% < 1%

16%

22%

60 mph (Losses = 314 kW)

58%

< 1% 1%< 1% < 1%

15%

24%

65 mph (Losses = 375 kW)

59%

< 1% 1%< 1% < 1%

14%

24%

70 mph (Losses = 453 kW)

engine

mech. acc.

elec. acc.

gearbox

axle

tires

aero
98

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Class 8 (Tractor-Trailer) - 100% Load

engine

η=40.6%

%Loss=59.4%

260 kW

155 kW

mech. acc.

η=N/A

%Loss=2%

106 kW

5.21 kW

elec. acc.

η=N/A

%Loss=0.1%

100 kW

0.36 kW

gearbox

η=98.1%

%Loss=0.7%

100 kW

1.9 kW

axle

η=98%

%Loss=0.8%

98.1 kW

1.95 kW

tires

η=N/A

%Loss=21.5%

96.1 kW

55.8 kW

aero

η=N/A

%Loss=15.5%

40.3 kW

40.3 kW

Power Flow Diagram - class8 / SS 50 mph / 100% Load

engine

η=42.3%

%Loss=57.7%

359 kW

207 kW

mech. acc.

η=N/A

%Loss=1.4%

152 kW

5.2 kW

elec. acc.

η=N/A

%Loss=0.1%

146 kW

0.36 kW

gearbox

η=98.1%

%Loss=0.8%

146 kW

2.78 kW

axle

η=98%

%Loss=0.8%

143 kW

2.85 kW

tires

η=N/A

%Loss=19.7%

141 kW

70.8 kW

aero

η=N/A

%Loss=19.4%

69.7 kW

69.6 kW

Power Flow Diagram - class8 / SS 60 mph / 100% Load

engine

η=40.6%

%Loss=59.4%

520 kW

309 kW

mech. acc.

η=N/A

%Loss=1%

211 kW

5.2 kW

elec. acc.

η=N/A

%Loss=0.1%

206 kW

0.36 kW

gearbox

η=98.1%

%Loss=0.8%

206 kW

3.91 kW

axle

η=98%

%Loss=0.8%

202 kW

4.01 kW

tires

η=N/A

%Loss=16.7%

198 kW

87.1 kW

aero

η=N/A

%Loss=21.3%

111 kW

111 kW

Power Flow Diagram - class8 / SS 70 mph / 100% Load
99

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

59%

2%< 1% < 1% < 1%

21%

15%

50 mph (Losses = 260 kW)

58%

< 1% 2%< 1% < 1%

21%

18%

55 mph (Losses = 302 kW)

58%

< 1% 1%< 1% < 1%

20%

19%

60 mph (Losses = 359 kW)

58%

< 1% < 1% 1%< 1%

19%

21%

65 mph (Losses = 425 kW)

59%

< 1% < 1% 1%< 1%

17%

21%

70 mph (Losses = 519 kW)

engine

mech. acc.

elec. acc.

gearbox

axle

tires

aero

40 50 60 70 80

0

10

20

30

40

50

60

70

80

90

100

Average speed (mph)

Contribution to total loss (%)

Repartition of losses - class8 / SS / 100 % Load

engine

mech. acc.

elec. acc.

gearbox

axle

tires

aero

Total losses x.1 (kW)
100

Argonne National Laboratory – Report to NAS – Contract DEPS-BEES-001 – October 2009

Bibliography

1. http://www.gmc.com/sierra/2500HD/

2. http://www.dieselnet.com/standards/cycles/hhddt.html

3. http://eogld.ecomm.gm.com/images/mediumduty/techspecs/engine.pdf

4. http://eogld.ecomm.gm.com/NASApp/mediumduty/gmmd_home.jsp

5. http://media.gm.com/us/powertrain/en/product_services/2007/Spec%20Sheet/Gen%20III/

2007%20LM7_L59%20V8.xls