Peer Review of the Greenhouse Gas 

Emissions Model (GEM) and 

EPA’s Response to Comments 

Phase II 
Peer Review of the Greenhouse Gas 


Emissions Model (GEM) and 


EPA’s Response to Comments 


Phase II
 

Assessment and Standards Division 

Office of Transportation and Air Quality 

U.S. Environmental Protection Agency 

Prepared for EPA by
 

Versar, Inc.
 

EPA Contract No. EP-C-12-045
 

Work Assignment No. 44
 

EPA-420-R-15-009 

June 2015 
 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

TABLE OF CONTENTS
 

A. INTRODUCTION................................................................................................................... 1
 

B. CHARGE TO REVIEWERS .................................................................................................. 3
 

C. SUMMARY OF PEER REVIEWER COMMENTS BY QUESTION................................... 6
 

GENERAL IMPRESSIONS................................................................................................... 7
 

CHARGE QUESTION 1 ........................................................................................................ 7
 

CHARGE QUESTION 2 ........................................................................................................ 8
 

CHARGE QUESTION 3 ........................................................................................................ 9
 

CHARGE QUESTION 4 ...................................................................................................... 10
 

CHARGE QUESTION 5 ...................................................................................................... 10
 

D. PEER REVIEWER COMMENTS BY CHARGE QUESTION.............................................. 12
 

Table 1. General Impressions................................................................................................ 13
 

Table 2. Charge Question 1................................................................................................... 18
 

Table 3. Charge Question 2................................................................................................... 27
 

Table 4. Charge Question 3................................................................................................... 54
 

Table 5. Charge Question 4................................................................................................... 57
 

Table 6. Charge Question 5................................................................................................... 60
 

Table 7. Specific Observations on Tool Description Entitled, “Vehicle Simulation Model”65
 

Table 8. Specific Observations on Electronic Model Entitled, “GEM Tool” ....................... 76
 

E. INDIVIDUAL PEER REVIEWER COMMENTS ............................................................... 82
 

Peer Reviewer # 1 ................................................................................................................. 83
 

Peer Reviewer # 2 ................................................................................................................. 92
 

Peer Reviewer # 3 ............................................................................................................... 108
 

Peer Reviewer # 4 ............................................................................................................... 114
 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

A. INTRODUCTION 

EPA, the National Highway Traffic Safety Administration (NHTSA), and the California Air 

Resources Board (CARB), in looking to reduce greenhouse gas emissions (GHG) and to improve 

fuel efficiency in medium- (MD) and heavy-duty (HD) vehicles, are considering recognizing the 

efficiency of various powertrain technologies within the context of any new full vehicle emission 

standard(s). For this option, it becomes critical to develop methods that assess the expected real 

world performance of those technologies, including vehicle engine, transmission and axle 

technologies. 

Enhancements have also been made to their HD vehicle simulation software tool, GEM 

(Greenhouse Gas Emission Model). At present, GEM is used by vehicle manufacturers to certify 

the expected GHG emissions of their products. With the enhancements, GEM could potentially 

have the ability to model a majority of the advanced technologies being incorporated into these 

vehicles and their engines and that are being recognized by engine and chassis dynamometer 

emission testing today. 

EPA and the other agencies consider the GEM tool as a principal support for the second round of 

HD GHG emissions regulations which are under development at the present time in both 

NHTSA and EPA. The model has undergone a formal peer review in an earlier iteration of the 

GEM tool (Phase I) and this newest version of GEM (Phase II) is the subject of this peer review. 

EPA is looking to assure the regulated community of the high quality of the agencies’ predictive 

tool and that the proposed structure (and overall development process) of the GEM model results 

in a tool that is simple, accurate and well-suited for the diversity of vehicles to which it may be 

applied. The purpose of the requested peer review is for EPA to receive written comments from 

experts on the concepts and methodologies upon which GEM relies and whether or not the 

model can be expected to execute these algorithms correctly. 

The purpose of the requested letter review is for EPA to receive written comments from 

individual experts on GEM Phase II tool and supporting documentation (“Vehicle Simulation 

Model”). 

Versar selected four senior scientists with expertise/experience in the following areas to serve as 

peer reviewers. The reviewers are familiar with the use of models to characterize vehicle 

simulations/operations; specifically, model design and model code and logic. Additionally, 

reviewers have expertise in one or more of the following areas: 

•	 vehicle operations and analysis, including the physical process of generating and
 

controlling vehicle emissions;
 

•	 linkages between mobile source emission modeling and transportation modeling and 

planning; and 

•	 application of current mobile source emissions models, w.r.t., heavy-duty vehicles, for 

analysis for regulatory purposes and/or policy evaluation, e.g., HD GHG Notice of 

Proposed Rulemaking. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Peer Reviewers: 

Christopher M. Atkinson, Sc.D. 

Atkinson, LLC 

Morgantown, WV 26508 

Nigel N. Clark, Ph.D. 

West Virginia University 

Morgantown, WV 26506-6203 

Oscar F. Delgado-Neira, Ph.D. 

The International Council on Clean Transportation 

Washington, DC, 20005 

Ashok Nedungadi, Ph.D., PE 

Future Is Now Consulting 

San Antonio, TX 78256 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

B. CHARGE TO REVIEWERS 

EPA developed a forward-looking MATLAB/Simulink-based tool, the Greenhouse Gas 

Emissions Model or GEM, for Class 2b through Class 8 vehicle compliance in 2011. At present, 

this model is being used by all medium- and heavy-duty vehicle manufacturers for their vehicle 

certifications. In order to meet EPA’s upcoming Phase 2 GHG rulemaking requirements, 

recognizing most of the vehicle technologies that are measured by both engine and chassis 

dynamometer testing, the original GEM tool (version1) has been considerably enhanced. 

Specifically, the following key technical features have been implemented into GEM: 

•	 Engine controller, including engine fuel cut-off algorithm during braking and 

deceleration, and more stable engine idle speed controller;
 

•	 Transmission model, which includes upgraded manual transmission, newly developed 

automatic transmission and automated manual transmission; and 

•	 Upgraded driver model, with distance-based driver. 

EPA has comprehensively validated its GEM model against over 130 vehicle variants, where all 

tests, including vehicle chassis and powertrain dynamometers, are conducted at Southwest 

Research Institute in San Antonio, TX. The summarized comparisons can be seen in the figure 

below. As can be seen, good agreements between simulation and testing data were obtained, with 

a few exceptions. For those outliers, it was found that the chassis roller may not be using friction 

force to correctly represent the truck running on the road, thus causing the chassis dynamometer 

testing to underestimate fuel consumption. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

It should be pointed out that CO2 reduction stringency standards in all certification categories are 

derived from GEM simulation runs by first selecting a range set of vehicle parameters and 

engine fuel maps. All to-be-certified vehicles from vehicle manufacturers use their own vehicle 

parameters together with some of the agencies pre-defined parameters to run GEM, and then 

their results are compared to what the agencies proposed. Since the comparisons are done in a 

relative base to see if the vehicles can meet standards, it is hoped that this kind of accuracy 

shown below would be adequate for use of certification purpose. 

Please note that GEM includes a pull-down menu mechanism by which it is able to account for 

those technologies that GEM is unable to model at the present time in development (due to either 

time constraints or lack of experimental data needed to validate the model). Unlike a model/tool 

used for research and development simulations where the model can be continuously upgraded 

and developed, GEM as a compliance tool is constrained by legislative authorities which makes 

both upgrading the tool and delivering the updated version to users difficult. 

Charge Questions 

EPA’s vehicle simulation model, GEM, was created to serve as the primary tool to certify Class
 

7/8 combination tractors and trailers and Classes 2b – 8 vocational vehicles in meeting EPA’s
 

and NHTSA’s proposed vehicle GHG emission levels and fuel efficiency requirements. As both 

agencies’ proposed compliance tool, GEM needed the following modeling attributes:
 

1) Models a wide array of MD and HD vehicles over various drive cycles;
 

2) Built with open source code (provides transparency in the model’s operation);
 

3) Available free to any user with minimal, or no, prior modeling experience;
 

4) Provides both optional and preset elements at input; and 

5) Managed by both EPA and NHTSA for compliance purposes. 

In general, the purpose of this peer review is for EPA to receive written comments on the
 

concepts and methodologies upon which the model relies and whether or not the model can be
 

expected to execute these algorithms correctly. In making comments on the model, please
 

distinguish between recommendations for clearly defined improvements that can be readily made 

based on data or literature reasonably available and improvements that are more exploratory or
 

dependent on information not readily available. Any comment(s) should be sufficiently clear and 

detailed to allow a thorough understanding by the Agencies or other parties familiar with the
 

model.
 

1. Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ 

compliance requirements) and whether the particular attributes found in the resulting model 

embodies that purpose. Were there critical results or issues that were not discussed or addressed 

by the GEM tool or its component sections? 

2. Please comment on the appropriateness and completeness of the contents of the overall model 

structure and its individual systems and their component models (i.e., using the 

MATLAB/Simulink version), if applicable, and considering the following: 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

a)	 Elements in each system used to describe different vehicle categories; 

b)	 Performance of each component model including the reviewer’s assessment of the 

underlying equations and/or physical principles coded into that component; 

c)	 Input and output structures and how they interact with the model to obtain the 

expected result, i.e., fuel consumption and CO2 over the given driving cycles; and 

d)	 Default values used for the input file, as shown in “Vehicle Simulation Model” 

document. 

3. When using the standard of good engineering judgment, is the program execution optimized 

by the chosen methodologies? 

4. Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 

emissions or fuel efficiency output file). 

5. In your opinion, are there any procedures or observations that would have added to the quality 

of the GEM tool? Any recommendations for specific improvements to the functioning of the 

outputs of the model? 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

C. SUMMARY OF PEER REVIEWER COMMENTS BY QUESTION
 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Summary of Peer Review Comments on EPA’s Heavy-Duty Greenhouse Gas Emission 

Model (GEM): Phase II and Supporting Documentation 

GENERAL IMPRESSIONS 

Overall, the reviewers found EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): 

Phase II and supporting documentation to be well structured, articulate, and a valuable resource 

for the EPA to represent the relative efficiency and emissions of heavy-duty vehicles. Reviewers 

commented that the tool will be very useful for compliance purposes since it is a reasonable 

compromise between accounting for all technology differences and advances, while remaining 

simple to execute. A number of improvements in the model and supporting documentation were 

suggested by the reviewers. 

One reviewer commented that the overall dynamic performance of the model prediction is 

difficult to judge because the results present a single-valued, integrated snap-shot of the model 

prediction, and the time-based instantaneous fuel efficiency and carbon dioxide emissions 

predictions are not available for review. 

Another reviewer commented that the material does not address quantitatively the experimental 

error that is likely in these types of comparisons, and measurement errors associated with rolling 

resistance and drag are not included in the data comparison. Overall agreement with 

experimental data (as vehicle fuel economy) does not validate each component model to the 

same degree, and this should be acknowledged more clearly. 

Additional suggestions were on the supporting documentation. One reviewer noted that there is 

an overall lack of key detail on certain technical features, such as descriptions of features, how 

they were developed, and quantitative results in several areas. 

CHARGE QUESTION 1 

Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ 

compliance requirements) and whether the particular attributes found in the resulting model 

embodies that purpose. Were there critical results or issues that were not discussed or 

addressed by the GEM tool or its component sections? 

In general, the reviewers found that the EPA’s overall approach to meet the agency’s compliance 

requirements is valid using the GEM Phase II model. The reviewers commented that a successful 

approach must yield well-defined, unambiguous results for manufacturers and agencies and also 

incorporate real world driving dynamics. All of the reviewers acknowledged that the input 

functions of the model were substantially more beneficial than the original GEM Phase I model. 

For example, adding fuel maps to the simulation by adding actual maps and drivetrain 

parameters makes the results more realistic, allows the model to capture the effects of matching 

engine and driveline, and ideally promotes right sizing of the engines to application. 

One limitation a reviewer noted was that the model is oriented toward diesel engines. Naturally 

aspirated gasoline, boosted gasoline, and natural gas engines are likely to increase in the next 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

five years and may warrant separate and careful consideration because their characteristics, 

torque curves, and efficiency maps differ substantially from the diesel engine properties. 

A few reviewers noted some limitations to the model that were unaddressed by GEM Phase II 

model. For instance, it is possible for the vehicle not to meet the driving cycle as a result of 

excessive grade or weight or other issues with the transmission/engine – the unaddressed issue in 

this regard is a feedback alert to the user during the time instances when the vehicle is 

significantly slowed down or does not meet the desired driving cycle. Another limitation is that 

GEM Phase II model does not address thermal characteristics of the engine cooling system or the 

heat rejection of the transmission fluids – these thermal issues affect the operational duty-cycle 

of the engine fan, which will affect fuel economy. 

One reviewer noted that in order for the public to have confidence in the regulatory program that 

is built on a mix of engine- and vehicle-model-specific inputs and modeled GEM outputs, the 

underlying data should be presented in full in downloadable data files (e.g., in Excel) as in 

other EPA regulations. 

Additional issues and limitations are addressed in the reviewers’ individual responses to the 

question. 

CHARGE QUESTION 2 

Please comment on the appropriateness and completeness of the contents of the overall model 

structure and its individual systems and their component models (i.e., using the 

MATLAB/Simulink version), if applicable, and considering the following: 

a)	 Elements in each system used to describe different vehicle categories; 

Overall, the model structure and its systems are appropriate and mostly complete for the 

designated purpose of the model. The specific selection of engines and transmissions chosen will 

cover a large portion of the current heavy-duty vehicle fleet. The modular structure and the 

hierarchical arrangement of modules to mimic a real vehicle system makes the integration of 

additional modules and capabilities easier to implement. One reviewer commented that GEM 

Phase II cannot predict the benefits of learning algorithms, look-ahead strategies, and intelligent 

vehicle systems for the optimization of powertrain efficiency on specific routes, but 

acknowledged that emerging approaches would take great effort to configure. 

One reviewer provided detailed comments on specific issues regarding model structure, 

individual systems, and default values, including: fixed payloads, drop-down technologies driver 

subsystem, transmission subsystem, engine fueling maps, modeling of idle cycle, trailers, and 

accessories. 

b)	 Performance of each component model including the reviewer’s assessment of the 

underlying equations and/or physical principles coded into that component; 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

The reviewers generally found the underlying equations and/or physical principles to be 

sufficient to characterize real world driving situations. For example, one reviewer commented 

that the distance-based approach was an important step to represent real life, but also commented 

that accelerations and grade of cycles must also represent real life. Other suggestions for 

improvements were also made. A couple reviewers commented on the steady-state maps and on 

the transient adjustment factor (TAF). For example, one reviewer noted that the use of an engine 

model steady-state map with a generic TAF does not encourage manufacturers to improve 

transient fuel efficiency, and provided two possible solutions. Another reviewer commented that 

in the case of nominally steady operation, the use of a steady-state fueling map is well-justified, 

but the quasi-steady assumption required to allow the extension of the use of such a map to 

transient operation requires additional justification. The reviewer also noted that the use of a 

single TAF for a specific engine or powertrain configuration has the potential to cause prediction 

inconsistencies. Comments were also made for other components, such as axle efficiency. One 

reviewer noted that it can be dangerous to employ the overall fuel economy computation to 

compare two approaches to modeling a single component, particularly if that component 

represents a small loss. 

c)	 Input and output structures and how they interact with the model to obtain the expected 

result, i.e., fuel consumption and CO2 over the given driving cycles; 

One reviewer commented that the format for the input and output structures follows good coding 

standards, making the input/output structures easy to use. One concern is whether there are any 

other parameters or fitting techniques used to obtain the observed correlations that were not 

listed in the documentation. Another reviewer commented, as guidance, that the manufacturers 

will be obliged to use the executable version of GEM Phase II a large number of times to 

compute an average value for compliance. 

d)	 Default values used for the input file, as shown in “Vehicle Simulation Model” document. 

Generally, the default data of GEM Phase II is complete and appropriate to execute a simulation 

of heavy-duty vehicle powertrain over one of the drive cycles available in the default drive cycle 

library. However, one reviewer thought it was not clear under what circumstances the user will 

be able or allowed to make modifications in the final model implementation. For instance, it is 

not clear that engine cooling fan loads have been adequately accounted for in the model as these 

are typically not considered in the engine dynamometer testing from which engine fueling maps 

are normally derived, and they can modify observed fueling rates by about 10% or more under 

specific engine operating conditions. 

CHARGE QUESTION 3 

When using the standard of good engineering judgment, is the program execution optimized 

by the chosen methodologies? 

The reviewers generally agreed that the chosen methods and execution of the model shows 

strong engineering judgment throughout. Two reviewers commented that it is difficult to 

comment on the execution optimization of GEM-II. However, one of these reviewers stated that 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

the results, computational time, and outputs displayed indicate that the chosen methodologies are 

suitable. The other reviewer stated that it appears that there are no S-functions within Simulink, 

which would make the execution faster if there are any non-standard user defined functions. 

Another reviewer commented that modeling accuracy would be raised if certain missing 

components were considered, such as longitudinal slip of tires, rolling resistance during 

crosswind correction, and the effects of yaw on drag. 

CHARGE QUESTION 4 

Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 

emissions or fuel efficiency output file). 

Some of the reviewers provided suggestions for making the data reports more complete. Some of 

these suggestions included adding (or clearly identifying) results for each drive cycle, adding 

actual simulated speeds and a measure of deviation from the speed-distance, and summarizing 

the results of the energy audit. One reviewer commented that users might be tempted to scale the 

load-based results in an inappropriate fashion. Another reviewer commented that the results are 

sufficiently comprehensive for the user who is not executing the program in MATLAB for 

research and design purposes, and that for a manufacturer a very succinct output would be 

sufficient. 

CHARGE QUESTION 5 

In your opinion, are there any procedures or observations that would have added to the quality 

of the GEM tool? Any recommendations for specific improvements to the functioning of the 

outputs of the model? 

The reviewers provided a number of recommendations for improving the quality of the tool or 

functioning of the model output. One reviewer suggested that GEM provide two different output 

reports, including one in an aggregated format with information only relevant for compliance 

purposes and one in a disaggregated format by cycle with other detailed information. In addition, 

the output fields should provide a range of valid and acceptable values for parameters such as 

number of shifts, ratio of number of shifts to number of gears in the transmission, distance 

traveled, and ratio of actual time to target time. Another suggestion was to make consistent the 

number of significant digits during each simulation, as the current presentation has a varying 

number of significant digits which does not meet recommended practices in the presentation of 

results and data. One reviewer also recommended adding language to remind users that if GEM 

is used to compare two competing but very different technology packages, it may not have the 

fidelity or granularity to evaluate which is better. Another recommendation was to provide a 

quantitative discussion of choice of test weight for GEM. A further step suggested by one 

reviewer would be to allow users to input their own cycles as is currently done with the VECTO 

(Vehicle Energy Consumption calculation Tool) model in Europe. A number of other potential 

model enhancements were recommended by another reviewer, such as including the ability to 

create input data from a user provided spreadsheet, allowing users to select plots of key 

component performance, having more detailed explanations of user provided data, providing 

feedback during execution (i.e. percent complete), having pre-defined sample input data 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

available, including the ability to turn on the feed forward term for the driver model, and having 

the ability to model accessory power draw in certain cases. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

D. PEER REVIEWER COMMENTS BY CHARGE QUESTION
 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Reviewer Name 

Reviewer 1 

Table 1. General Impressions 

Reviewer Comment 

The purpose of GEM in determining standards, providing a 

compliance tool, and estimating real-world benefits is clearly 

articulated. The proposed Phase II GEM tool has evolved 

substantially from the Phase I version, particularly by allowing 

additional user inputs that are necessary to acknowledge fuel 

efficiency design improvements. As a compliance tool GEM 

should seek to account for all technology advances and 

differences, yet remain simple to execute and employ readilymeasured and well-defined input variables. The Phase II GEM 

model has reached a reasonable compromise between these 

conflicting goals, and this is made clear in the narrative. The 

overall architecture is sound, the present component models are 

appropriate to the task in nearly all cases, and they are clearly 

described. The model yields credible results and credible responses 

to input variable changes. The overall model predicts fuel 

efficiency to within 5% of experimental measurements, and a clear 

summary of these comparisons is presented. However, the material 

does not address quantitatively the experimental error that is likely 

in these comparisons, and measurement errors associated with 

rolling resistance and drag are not included in the data comparison. 

Overall agreement with experimental data (as vehicle fuel 

economy) does not validate each component model to the same 

degree, and this should be acknowledged more clearly. As one 

example, overall fuel economy data are used to compare a 

component model with a fixed efficiency value. The difference 

overall was only 1.67%, but this represented more than a third of 

the losses for that component. The move to a distance-based 

strategy is justified and well-described, and represents a laudable 

advance. Addition of several transmission models is presented, as 

are thoughts on the addition of transient adjustment factors. Little 

is said of the “powertrain variant architecture,” although this may 

EPA Response to Comment 

Significant progress has been made since we 

initiated the GEM Peer Review. The technical 

research workshop held at Southwest Research 

Institute on December 10-11, 2014 features the 

progress done so far to the public. In this 

workshop, both experimental errors and GEM 

errors were addressed. The detailed progress 

reports can be seen at

http://www.epa.gov/otaq/climate/regsheavy-duty.htm. 

The supporting document, “Vehicle Simulation 

Model”, does provide partial validations on the 

component level, such as the engine and 

transmission, for selective cases. Due to the 

large number of vehicle tests and GEM 

simulations on over 130 vehicle variants, it 

would be challenging to show every single case 

validation at a component level. More 

importantly, the certification is only conducted 

at the final integrated and weighted fuel 

efficiency and CO2 level, and therefore, the 

focus of the model validations is on the overall 

performance comparisons. 

The supporting document, “Vehicle Simulation 

Model”, indicates that hybrid vehicles would 

not be part of the certification with GEM, and 

therefore, the powertrain described in this 

report only talks about the conventional 

powertrain system. 

We are seeking comment in the NPRM 

regarding the proposed transient correction 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 1. General Impressions 

Reviewer Name Reviewer Comment EPA Response to Comment 

prove important for integrated powertrains with or without a 

hybrid component. Transient Adjustment Factors are not yet 

finalized, and transient operation may warrant more than a single 

correction factor approach. 

factor of 1.05. We will finalize the transient 

correction factor after receiving all comments 

from stakeholders. 

Reviewer 2 This document summarizes the findings of the review of the US 

EPA's Heavy-Duty Greenhouse Gas Emission Model (Phase 2 

GEM) and supporting documentation ("Vehicle Simulation 

Model"). The tool will serve as the principal support for the second 

round of Heavy-Duty GHG emissions regulations, which are under 

development by NHTSA and EPA. The agencies are considering 

recognizing the efficiency of various vehicle, engine, and 

transmission technologies and they consider critical to develop 

methods that assess the expected real world performance of those 

technologies. The main purpose of this review is to evaluate how 

well the developed model can serve as a regulatory and 

compliance tool. The following represent my review of the tool 

and accompanying report based on my experience in modeling 

heavy-duty vehicles with full-vehicle simulation tools, as well as 

from our assessment at the International Council on Clean 

Transportation (ICCT) of other heavy-duty vehicle regulatory 

models used around the world. 

After reviewing the Matlab/Simulink model and the accompanying 

report, my general impression is that the "Phase 2 GEM" 

constitutes a valuable development effort by EPA to develop a 

rigorous tool that represents the relative efficiency and emissions 

of vehicles. The new modeling tools’ comprehensiveness, quality 

and amount of data inputs, and modeling structure reflect state-ofthe-art modeling techniques and accurately represent relative 

efficiency differences of vehicles in real-world conditions. 

The literature on vehicle simulation modeling is 

abundant over the last few decades. Some of 

the literature used in the supporting documents 

provides some equations for certain 

components. 

The “Vehicle Simulation Model” document 

was intended to represent a high level overview 

of the purpose and scope of Phase 2 GEM for 

regulatory purposes and therefore does not 

provide detailed technical insight into the 

model implementation. This document closely 

resembles the Draft RIA Chapter 4 included 

with the Notice of Proposed Rulemaking 

(NPRM) for the HD Phase 2 program. Also the 

final RIA Chapter 4 will add a few more 

references to provide more insight into the 

design and implementation of the model. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 1. General Impressions 

Reviewer Name Reviewer Comment EPA Response to Comment 

The model architecture is clear and easy to follow and has 

incorporated some key features that will enhance its overall 

accuracy with respect to real world performance of technologies, 

and will allow the model to capture fuel consumption reductions 

from a broader range of technologies. Overall, the tool offers a 

rigorous and comprehensive simulation accounting of both enginespecific and full-vehicle effects in a manner that is suitable for the 

regulatory compliance purposes as indicated. The model will be 

capable of performing its intended purpose of reflecting 

technology benefits for compliance purposes of most of the 

technologies that the agencies are considering. 

Some new vehicle modeling features are especially important, 

namely the ability of the model to incorporate user-defined engine 

fueling maps and driveline parameters, the development of 

different transmission options, the enhanced transmission gearshifting strategy, the inclusion of a distance-based routes with road 

grade, and the more comprehensive treatment of vocational truck 

technologies. The accompanying testing effort that was undertaken 

to validate the model is impressive and thorough, as capturing the 

effect of combinations of technologies in such close agreement 

with powertrain and chassis dynamometer testing is a difficult 

task. The model development demonstrates a thorough 

development process, and also shows a strong commitment to 

transparently presenting the data and methodology that were 

involved. 

The comments below provide additional details, as well as some 

suggestions that could also be considered by the agencies in the 

final model development. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 1. General Impressions 

Reviewer Name Reviewer Comment EPA Response to Comment 

Although the tool itself offers a suitable modeling platform, the 

document that describes modeling approach could provide further 

details in a number of areas. It appears as though the 

documentation available for this peer review was at an early draft 

stage. There is an overall lack of detail on key technical features 

that are new in the model. Interested readers would gain from 

better descriptions of such features, how they were developed, and 

perhaps, more quantitative results in several areas. Also, the 

quality of the report may be enhanced with more consistent use of 

terminology and a reduction in the number of self-references. 

Further details regarding areas where such documentation and 

enhanced information would be helpful are described below. 

Reviewer 3 The EPA Heavy-Duty Greenhouse Gas Emission Model (GEM) 

Phase 2 documentation accurately represents the structure, format, 

logic and algorithmic description of the model as presented. The 

supporting documentation is for the most part, clear and selfexplanatory. The results produced by the GEM model appear to be 

sound, although each set of results is presented as integrated fuel 

efficiency and carbon dioxide emissions results. As such the 

results present a single-valued, integrated snap-shot of the model 

prediction, and the time-based instantaneous fuel efficiency and 

carbon dioxide emissions predictions are not available for review. 

The overall dynamic performance of the model prediction is thus 

difficult to judge in the greater context of what is usually fully 

transient vehicle operation. Furthermore, in the version reviewed, 

the ability to vary input parameters and vehicle and drivetrain 

attributes is limited to modifying input files and not through a 

graphical user interface as described in the review instructions. 

We do agree that addition of a graphic user 

interface (GUI) could help the reviewers to 

understand the code better. However, the 

agencies do not intend to develop a GUI for 

single GEM runs based on discussions with the 

regulated stakeholders. 

Instead of a GUI, the NPRM includes a macroenabled input file based on an Excel 

spreadsheet (in addition to a standalone 

executable) with some simple interactive 

features (highlighting of out of range variables, 

for example) and a single button to allow batch 

processing of GEM runs. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 1. General Impressions 

Reviewer Name Reviewer Comment EPA Response to Comment 

Reviewer 4 Accuracy of information: 

The document provided, “Vehicle Simulation Model” provides a 

good background on GEM-II, its differences from GEM-I, and the 

Phase I certification process. Section 1.2, “Model Code 

Description” describes the model components and subcomponents, in adequate detail for the user to understand the depth 

and breadth of GEM-II. No underlying equations are provided. 

The section on Model validation is an important section for GEMII. The extent of the validation and the comparisons with 

dynamometer testing is impressive. This gives the reader 

additional confidence in the results produced by GEM-II. The 

validation process is well documented, concluding with the graph 

that summarizes all the 130 vehicle validations performed. The 

validation also includes graphs of component performance (engine 

speed, engine fuel rate, and transmission gear number) as a 

function of time 

The document does not explain the variable target.veh_style. The 

structure format used for the user input data is useful in collecting 

all user-provided data. 

A final conclusions section is missing in the document provided. 

‘target_veh_style’ is an internal variable used 

to track the regulatory subcategory of the 

simulation run and is not part of the user 

interface. 

A final conclusion section could be added into 

the document, but it is not a critical element, 

since the documentation was included in the 

Draft RIA Chapter 4 and is more like a user 

guide to help the user to understand the 

structure of the program. 

17
 
 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 2. Charge Question 1 

Charge Question 1: Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance 

requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or 

issues that were not discussed or addressed by the GEM tool or its component sections? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

Reviewer 1 Throughout this review, except where different fuels are 

mentioned, fuel efficiency improvement and GHG reduction are 

considered to be synonymous. 

Beyond the need for assurance of compliance is the need to reduce 

fuel use and climate change emissions from heavy-duty vehicles in 

revenue use. A successful EPA approach must be examined from 

two perspectives. First, it is necessary that the approach yields 

well-defined, unambiguous results to allow a manufacturer to 

compare against a standard without the process being unreasonably 

onerous. Second, it is necessary that that the vehicle attributes and 

behaviors embodied in the certification process are substantially 

representative of real world circumstances. These two necessities 

are often in conflict, because the real world scenario is complex, 

variable, and long in duration, whereas the standard must be 

concise and precise. The conflict is far greater in the heavy duty 

trucking arena than for light-duty vehicles or rail because truck 

architectures vary widely, and are used in an even wider fashion. 

Employing a model such as GEM to assure compliance provides 

some relief in the conflict described above because the model can 

be executed for a variety of activities and scenarios without 

excessive cost of time and resources. However, as the model is 

challenged to predict these varied (and emerging) scenarios with 

fidelity, the model complexity rises. As a result, the empirical 

tables or computational sub-models needed within the model grow 

The agencies discuss the proposed regulatory 

approach of separate engine and vehicle 

standards in the preamble to the HD Phase 2 

NPRM and how it may impact the criteria 

pollutants. We will consider the comments 

received during the comment period and make 

any needed changes in the final rule. 

18
 
 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 2. Charge Question 1 

Charge Question 1: Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance 

requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or 

issues that were not discussed or addressed by the GEM tool or its component sections? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

in number and demand substantial engineering time to prepare and 

verify. One might argue that “the more one models, the more one 

measures,” recognizing too that precise test protocols must 

accompany each measurement. 

Compromise is necessary between four fundamental needs: 

1. Relevance of the model to real world truck operation. 

Else the real world improvements will not match the 

changes in standards 

2. Accuracy of the model in predicting measured fuel 

efficiency (and GHG production). 

Else confidence in the model will be lost and the 

compliance will become artificial 

3. Accuracy of the model in predicting differential effects of 

technology changes on fuel efficiency (and GHG 

production). 

Else the drivers for technology advancement will be lost 

4. Control complexity and cost of modeling and compliance. 

Else the cost transferred to the consumers will be 

inappropriate 

The overall new GEM approach shows awareness of these 

necessities, and reaches a reasonable compromise. However, when 

some parameters are fixed by the agency, manufacturers may be 

discouraged from pursuing certain development opportunities in 

the following way. Both future fuel pricing and future fuel 

efficiency standards are unknown. If high fuel prices transcend the 

19
 
 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 2. Charge Question 1 

Charge Question 1: Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance 

requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or 

issues that were not discussed or addressed by the GEM tool or its component sections? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

standards, then manufacturers will pursue every cost-effective tool 

to reduce fuel use. However, if fuel prices are low and are not the 

driving force, and the GEM approach offers default values for 

factors such as engine transient adjustment factors or transmission 

efficiencies, some opportunities for real world reduction may be 

left on the table. GEM cannot rely on economic drivers to address 

technology advances that are not modeled. 

GEM is a vehicle-based tool that is geared towards road-load 

demands rather than engine-specific (“%load” and “%speed”) 

demands. Only the new distance-based cycles give a nod toward 

engine power. Criteria pollutants are still characterized using a 

paradigm based on engine rated output. Allowing different 

measurement methodologies for efficiency and criteria pollutant 

production will open a window for separate hardware and software 

optimization for each test. This may demean the benefits of the 

separate standards to some degree: in-use compliance for criteria 

pollutant measurement will not close this gap because 

measurement allowance for criteria pollutants reduces stringency 

for criteria pollutants. 

Reviewer 2 The proposed Phase 2 standards are predicated on the performance 

of a broader range of technological improvements than Phase 1, 

including changes to transmissions and better integration of 

engines and transmissions, so a more comprehensive model is 

required. The model in its current form will be capable of 

performing its intended purpose of reflecting technology benefits 

for compliance purposes of most of the technologies that the 

In principal, we agree with the comments

that the input and output data should be 

available to public. The agencies will

consider in a separate action whether the 

GEM inputs and outputs submitted by

manufacturer to demonstrate compliance 

with the Phase 2 standards are confidential 

20
 
 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 2. Charge Question 1 

Charge Question 1: Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance 

requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or 

issues that were not discussed or addressed by the GEM tool or its component sections? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

agencies are considering. 

The model is enhanced in various aspects with respect to its 

previous Phase 1 version. Fuel maps are one of the most important 

elements in simulation-based models and the new feature of using 

actual maps and drivetrain parameters would make the results more 

realistic, allow the model to capture the effects of matching engine 

and driveline, and ideally promote right sizing of the engines to 

application. Different transmission options are included in the 

model. The shifting behavior is now more realistic since is based 

on both throttle and speed inputs, and includes the effects of a 

clutch friction model. Phase 1 GEM shifting strategy was based 

only on vehicle speed and there was no torque interruption during 

shifting. Road grade has a major impact on fuel consumption and 

its addition to the tests cycles would also make the results more 

realistic. The treatment of vocational technologies, which were 

limited to the tires in Phase 1, is considerably enhanced. The 

approach followed by EPA to tackle the diversity of vocational 

truck applications is appropriate. A few drive cycles are simulated 

(ARB transient, 55 mph and 65 mph cruise with grade, and a new 

idle cycle) and weighted differently based on specific application. 

EPA’s approach involved a good amount of testing and validation. 

It must be said that most of these validation efforts only covered 

fuel consumption results from reduced weight, better 

aerodynamics, and better tires. The validation effort for 

transmission types and engine- transmission-vehicle interaction 

business information (CBI). The agencies

cannot release information claimed as CBI 

by manufacturers to the public. 

21
 
 

 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 2. Charge Question 1 

Charge Question 1: Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance 

requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or 

issues that were not discussed or addressed by the GEM tool or its component sections? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

was less comprehensive. However, based on the results presented, 

Phase 2 GEM model would be accurate enough to support 

regulation and drive technology adoption. 

More broadly, I make one final comment on how the overall 

modeling approach may meet EPA’s overall goals for the 

regulation, related to the public release of the GEM input and 

output data. The existing and Phase 2 heavy-duty vehicle 

regulation approach relies on the GEM inputs and outputs to 

determine compliance. The GEM data are analogous to the lightduty vehicle gram/mile1

, heavy-duty vehicle gram/brakehorsepower2

, and light-duty vehicle mile-per- gallon3 compliance 

values. For the heavy-duty use of the GEM in the greenhouse gas 

emission regulatory program to meet the agency’s own standard, 

the input and output data from GEM would ideally be made 

publicly available just as the regulatory data for the other 

regulations for each engine and vehicle. For the public to have 

confidence in the regulatory program that is built on a mix of 

engine- and vehicle-model-specific inputs and modeled GEM 

outputs, the underlying data would be presented in full in 

downloadable data files (e.g., in Excel) as in other EPA 

regulations. 

References: 

1 EPA http://www.epa.gov/otaq/crttst.htm 

2 EPA http://www.epa.gov/otaq/certdata.htm 

3 EPA http://www.epa.gov/otaq/tcldata.htm, 

22
 
 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 2. Charge Question 1 

Charge Question 1: Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance 

requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or 

issues that were not discussed or addressed by the GEM tool or its component sections? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

http://www.fueleconomy.gov/feg/download.shtml 

Reviewer 3 The model appears to meet the stated purpose for which it was 

intended, which is the prediction of integrated cycle-based vehicle 

fuel efficiency and carbon dioxide emissions for vehicles with 

preselected physical and drivetrain attributes. While this was the 

subject of some detailed explanation in the model documentation, 

the assumption of quasi-steady engine fueling and its extension to 

fully transient engine operation is not without complexity in the 

assessment of its validity. A further, acknowledged inadequacy of 

the model in its current form is the limited ability of the user to 

modify specific vehicle attributes, and component values and 

efficiencies. 

The agencies agree with the comments, and we 

fully recognize this limitation of the model in 

terms of the ability of the user to modify some 

vehicle attributes. As explained in the 

supporting document “Vehicle Simulation 

Model” and Draft RIA Chapter 4 the 

certification is conducted on a relative basis, 

and the report shows relative errors in the range 

of 2-3%, which is not perfect, but it is adequate 

for the purpose of certification. 

User inputs are limited to reduce complexity 

and to provide a more common basis for 

determining regulatory stringencies and to 

reduce the expense and number of test 

procedures required to provide accurate inputs 

to the model. The agencies are seeking 

comment in the preamble of the HD Phase 2 

NPRM regarding the inputs to GEM and the 

test procedures associated with them. 

Reviewer 4 EPA’s overall approach to meet the agency’s compliance 

requirements consists of making a validated simulation model 

(GEM –II) available to OEMs so that they can check the 

compliance of their vehicles against the agency’s guidelines. The 

extensive validation of GEM – II against dynamometer testing of 

the actual vehicle shows a good correlation between simulation and 

GEM PID controllers are not tunable modules, 

meaning that the user has no option to change 

any constants associated with this model. At 

this time, we have validated GEM against 130 

vehicle variants without noticing any issues 

23
 
 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 2. Charge Question 1 

Charge Question 1: Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance 

requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or 

issues that were not discussed or addressed by the GEM tool or its component sections? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

hardware to within ±5%. Most validations are well within ±3%. 

This provides the user with a high level of confidence that the 

physics has been correctly implemented and there are no 

unresolved “bugs” in GEM-II. 

Further, an additional level of confidence is achieved, with select 

validation from four representative vehicle classes, namely: Class 8 

Kenworth T700 truck, the Class 6 Ford F650 tow truck, the Class 6 

box truck, and the New Flyer Refuse truck. There is a very good 

correlation between GEM-II predicted engine speeds and 

transmission gear shifting versus the same on the actual vehicle. 

Recommendation: It is recommended that representative vehicles 

from each of the classes be modeled in GEM-II and validation 

results presented similar to 1.3.1 of the GEM-II Manual. It is the 

understanding of the reviewer, based on the provided manual that 

the following trucks were tested on a vehicle chassis: Class 6 

Kenworth T270, Class 6 Ford F650, Class 8 Kenworth T700, Class 

8 Cascadia Line Haul truck, and Class 8 New Flyer refuse truck. 

Issues/Results that were not addressed by GEM-II : 

During this review, the following unaddressed issues were 

identified for GEM-II: 

• GEM-II includes several PID controllers within its overall 

structure. For example, the engine idle speed controller of 

associated with PID controller. It should also 

be noted that many of the PID controllers, like 

the engine idle speed control, are scaled by 

non-user-defined parameters like engine inertia 

or vehicle mass to match their application. 

The planned interface which manufacturers will 

use to certify via GEM does not provide the 

option to output plots. The functionality is not 

considered necessary to complete the 

compliance requirements identified in the rule. 

Thermal modeling is always an issue. Ideally, 

it should be included in some form. However, 

it is challenging to develop a correlation to 

qualitatively predict the thermal impact 

associated with cooling and transmission heat 

rejection in terms of a certification tool. This 

development can be expensive and time 

consuming. This could place an additional 

burden on manufacturers who must submit 

certifiable reports to the agencies, which 

complicates the process of the certification. 

Mechanical loads can be also modeled through 

a simple correlation. However, similar to the 

thermal modeling issue, this could place an 

24
 
 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 2. Charge Question 1 

Charge Question 1: Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance 

requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or 

issues that were not discussed or addressed by the GEM tool or its component sections? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

the engine is implemented as a PID with three gains. The 

unaddressed issue in this regard is stability feedback to the 

user caused by unrealistic hunting for the idle speed. What 

safe-guards are in place within GEM to inform the user of 

clutch chattering since GEM does not model second order 

inertial effects caused during clutch engagement. 

• It is possible for the vehicle not to meet the driving cycle as 

a result of excessive grade or weight or other issues with 

the transmission/engine. The unaddressed issue in this 

regard is a feedback alert to the user during the time 

instances when the vehicle is significantly slowed down 

and does not meet the desired driving cycle. The output file 

does not alert the user on the number of time instances 

when vehicle tracking was compromised. 

• GEM-II does not address thermal characteristics of the 

engine cooling system or the heat rejection of the 

transmission fluids. These thermal issues affect the 

operational duty-cycle of the engine fan, which will affect 

the fuel economy. At present, GEM-II models the parasitic 

loads as a constant average number. 

Recommendation: Allow the user the ability to introduce an 

engine load dependent mechanical accessory curve which is 

more realistic than a constant average number. A simple 

heat model may be used to capture the effect of thermal 

characteristics of the multiple radiators in a typical MD and 

HD engine. 

• Although GEM-II does not model tire slip/lockup during a 

additional burden on manufacturers who must 

submit certifiable reports to the agencies, which 

complicates the process of the certification 

The supporting document, “Vehicle Simulation 

Model”, does show some detailed comparisons 

in a sub-model level, such as engine and 

transmission. It is extremely time consuming 

to show all 130 vehicle variants at such a 

detailed level. Furthermore, certification only 

requires composite and weighted values, and 

therefore, the program should serve this 

requirement as long as those composite and 

weighted values are correlated well against the 

testing data. 

In terms of transmission shifting, all 

independent transmission manufacturers we 

contacted are reluctant to share their shifting 

strategies with the vehicle manufacturers due to 

concerns over proprietary information. 

Therefore, the agencies developed their own 

generic shifting algorithm for modeling 

purposes. If GEM under-predicts the benefits 

of the transmission, manufacturers have the 

option to conduct powertrain testing where an 

engine and transmission are evaluated in a 

25
 
 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 2. Charge Question 1 

Charge Question 1: Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance 

requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or 

issues that were not discussed or addressed by the GEM tool or its component sections? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

hard deceleration, the effect of ignoring this on fuel 

economy is negligible. 

• The validation results included kinematic comparisons 

(speeds, gear number) between GEM-II and the actual 

vehicle on a chassis dynamometer. While, the kinematic 

comparisons look very favorable, the dynamic comparisons 

(engine load and engine fueling) are missing in the results 

section of GEM-II. 

• The transmission shift strategy can affect fuel economy and 

emissions. GEM-II allows the user to preselect different 

transmission types (manual, automatic or automatedmanual). However, it was not clear how to modify the 

GEM-II default shift strategy with an OEM proprietary 

shift strategy. 

• Although GEM-II results have been extensively validated 

against dynamometer test data in a controlled lab 

environment, it is unclear how well GEM-II will compare 

against real world road testing, especially with temperature 

fluctuations. For example, the lack of a thermal model in 

the engine model may cause GEM-II results to deviate from 

on-the-road test data, where the engine fan is cycled on and 

off based on thermal loads on the engine. Each time, the 

engine fan turns on, fuel economy is affected. 

powertrain dyno cell. 

The agencies fully recognize the importance of 

the GEM validation against real-world vehicle 

operations. However, it is expensive and time 

consuming to launch such a program. 

Currently, the agencies are working with SwRI 

to conduct this task in the hope that full GEM 

validation against real-world vehicle operations 

can be released to public in the second half of 

2015. 

26
 
 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

a) Elements in each system used to describe different vehicle categories; 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

Reviewer 1 The proposed GEM Phase II model represents a substantial 

advance over the model used to implement the first phase of 

truck efficiency legislation, and encourages more technology 

advances from manufacturers in consequence. Improvements in 

truck efficiency are based primarily on reductions in 

aerodynamic drag, tire rolling resistance and engine brake 

specific fuel consumption, and this was recognized in the first 

GEM model. Practically, there is less to be gained from 

aerodynamic improvements in most vocational truck operation 

than in long haul trucking and the GEM model as presented 

neglects vocational truck aerodynamics, and the modelers are 

right to exclude aerodynamic parameter entries for low speed 

trucks. However, the overall GEM structure is capable of 

modeling aerodynamic improvements for niche vocational 

designs, and has the flexibility to extend beyond the present 

exclusion of the drag coefficient. In this way, the capabilities of 

the model, as received, will be far greater than the executable 

version that is finally used for compliance. 

A major theme in the industry is that efficiency gains are 

significant from design integration, particularly powertrain 

integration. But it is understood that combined powertrain 

control is proprietary. The supporting language might address 

this more clearly, noting that the GEM model employs just 

steady-state maps and a defined set of gear ratios, and cannot 

predict the benefits of more sophisticated integration. In a 

The comments on gasoline and natural gas engines 

are well taken. The agencies are currently 

conducting a program at SwRI to address gasoline 

engine performance related to the rulemaking. We 

are also actively collecting the engine performance 

data on both types of engines from manufacturers. 

The GEM Phase 2 shift algorithm is based on the 

torque curve and fuel map of the engine and such 

will adapt shift points uniquely for every engine 

map provided, regardless of fuel type. 

Manufacturers will have the option to perform 

powertrain testing to account for improvements, 

such as those mentioned by the reviewer. 

The agencies are seeking comment on whether to 

include GEM inputs for vocational vehicle 

aerodynamics in the preamble to the HD Phase 2 

NPRM. 

27
 
 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

similar fashion GEM cannot predict the benefits of learning 

algorithms, look-ahead strategies and intelligent vehicle 

systems for the optimization of powertrain efficiency on 

specific routes. These are emerging approaches, but it is 

acknowledged that it would take great effort to configure GEM 

to deal with these details and it would be difficult to assure 

their generic benefit in revenue service. GEM has some checka-box options proposed for features that cannot be modeled. 

The model, as provided, was oriented to diesel engines. The 

shift strategies also considered the engine torque curve for 

execution. Naturally aspirated gasoline, boosted gasoline and 

natural gas engines are likely players in the next five years and 

may warrant separate and careful consideration because their 

characteristics, torque curves and efficiency maps differ 

substantially from the diesel engine properties. 

Reviewer 2 Overall the model structure and its systems are appropriate and, 

in large part, complete. Generally, the performance of each 

component model and the underlying equations and physical 

principles are valid throughout (see some finer details below). 

The input and output structures interact with the model to 

obtain the expected result in a way that is sound. The following 

sub-sections comment on specific issues regarding model 

structure, individual systems, as well as default values, in no 

particular order of importance. 

Fixed payloads 

Phase 1 GEM had predefined engines, driveline parameters, 

and payloads for every category. An issue that may arise when 

Fixed Payload 

The agencies are fully aware of the technical issues 

related to payload. However, allowing payload as 

a variable means that agencies must develop a 

standard that varies with payload, which would 

complicate the rulemaking, specifically the process 

of certification. Furthermore, it would be 

challenging to verify the in-use payload of a 

vehicle application, making audit challenging. In 

addition, this approach would force tractors 

running without trailer, or bobtail, to be considered 

28
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

using user-defined engine fueling maps in combination with 

predefined payloads is that some simulated vehicles, with lower 

power-to-weight ratios, will show higher deviations from the 

target speed-distance trace. This affects the simulation results 

since these underpowered vehicles will take more time to 

complete the assigned route and will show a lower average 

speed. This could lead to underpowered vehicles being 

improperly credited. 

Appropriate matching of engine, transmission gear ratios, axle 

ratios, and tire radius is only going to be promoted if the GEM 

payloads closely match actual vehicle operation. Right sizing of 

powertrains to application does not seem to be promoted when 

payloads are predefined for a particular vehicle category. In 

order to recognize engine power matching to vehicle road load, 

payload needs to be a user input rather than a predefined 

parameter. The regulatory approach and modeling would 

ideally recognize and promote market diversity and identify 

potential discrepancies between actual payloads and GEM 

payloads. There is an existing trend towards smaller engines, 

but also some applications require larger engines. On the other 

hand, if the truck manufacturer is allowed to input vehiclespecific payloads, some issues may arise in terms of 

enforceability (How do the regulatory agencies ensure that the 

vehicles are operated close to the payload values at which they 

were certified?), that may also open the door for the 

manufacturers to report numbers for their own benefit, and 

adds complexity. 

out of compliance because they are not carrying the 

declared payload. Therefore, the agencies simplify 

the process by proposing fixed payload values. 

Pull-Down Technologies 

Pull-down technologies are also known as the 

technology improvement inputs for the rulemaking. 

The supporting document, “Vehicle Simulation 

Model” and the HD Phase 2 NPRM preamble 

describe many aspects of the pull-down 

technologies. We also seek comment on whether 

the technology improvement inputs should be in 

terms of percent reduction or absolute grams of 

CO2 per ton-mile. Basically, the agencies have 

been actively talking to all relevant manufacturers 

regarding these technologies as selectable items. 

We proposed a conservative approach recognizing 

these potential technologies. All the technologies 

considered as pull-downs would be those that GEM 

would not be able to model or are not fully 

recognized over the limited certification drive 

cycles. Technologies mentioned by this reviewer, 

such as electric coolant pumps would only show a 

partial benefit in the engine fuel mapping process, 

and therefore the pull-down item associated with it 

accounts for the other remainder of the benefit seen 

on the road. 

29
 
 

 

 

 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

An option could be to adjust the payload on a few pre-defined 

bins based on certain parameters that are indicative of vehicle 

road load (e.g. engine displacement, engine power, final drive 

ratio). Under this option, a performance criterion that captures 

the trace-following capabilities of the simulated truck (e.g. a set 

threshold of percent difference between target speed and 

simulated speed) can be used to force certain engine-vehicle 

combinations to switch to a lower payload bin if they don’t 

follow the trace according to the specified criterion. Another 

option would be to impose a CO2 penalty based on the ratio of 

simulated average speed to target average speed. Ideally, the 

allowed deviations from the target trace should be minimized 

for the simulations to be considered valid and allow 

comparisons between them. 

Drop-down technologies 

The agencies have identified a list of technologies that provide 

fuel consumption benefits but are difficult to simulate 

accurately. They are developing feature-based drop-down 

menus that make post-simulation adjustments (percent 

reductions) to the results. It appears that manufacturers have 

not taken much advantage of the Phase 1 advanced technology 

structure to earn credits so it is important to try to include most 

of the technologies in some way. However, drop-down menus 

inherently assume that all the technology variants within a 

technology category provide the same fuel consumption 

benefits. Not all the models and brands of a certain technology 

feature would provide the same fuel consumption benefits. 

There is the risk of giving artificial credits to products that 

Although these values used by GEM are fixed as 

default values, the user does have the option to use 

off-cycle credit proposed by the rule, similar to the 

innovative credits in Phase 1, to quantify the 

additional benefits of individual technology. 

Driver Subsystem 

All the driver model related constants are not 

tunable. We tested these pre-selected PI controller 

related constants against over 130 vehicle variants 

without any noticeable issues. In addition, the 

driver controller constants are scaled by vehicle 

mass and therefore adjust automatically for each 

simulation run. 

Transmission 

The auto-shifting tables for all three types of 

transmissions are different in the form of internal 

constants which are not user-tunable. The 

supporting document, “Vehicle Simulation 

Model”, and HD Phase 2 NPRM Draft RIA 

Chapter 4 includes a table to show the impacts of 

the shift algorithm on overall vehicle performance 

as opposed to using manufacturer-supplied shift 

tables. We agree with the reviewer that we need to 

provide a clearer description of this subject and it 

will be clarified in Draft RIA Chapter 4. 

30
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

perform at a lower level than the value that is selected from the 

drop- down menu, thus rewarding poor performers. Also, 

technology products with better than average levels of 

performance would not get additional credits, which is a 

disincentive to make investments in the development of such 

technologies. The default improvement values (percent 

reductions) developed by the agencies were not shared for this 

peer review but they are of relevance and need to be 

determined with care. Currently, the users have no flexibility to 

enter their own values. Giving the users the flexibility to enter 

their own values (after testing and with proper documentation) 

could offer a way to reward good performers. 

It seems that applying adjustment factors in terms of percent 

reductions rather than applying predefined credits in units of 

go2/ton-mile or gal/ton-mile may punish good performers. 

Assuming that truck A emits 90 go2/ton-mile and truck B emits 

100 gCO2/ton-mile. If a certain technology improvement value 

is set at 5%, and both trucks use such technology, truck A 

would get 4.5 gCO2/ton-mile credit and truck B would get 5 

gCO2/ton-mile credit. This discrepancy of incentives can 

exacerbate if the trucks use more than one drop-down 

technology and the agencies decide that the percent 

improvements are additive. So it would be good for the 

agencies to support whether and why percentage-based (versus 

gCO2/ton-mile based) are most appropriate. Also the agencies 

might address, in such drop-down menus whether such 

technology improvements are indeed additive or not. 

Another issue with drop-down technologies is that there is the 

We fully agree with the reviewer’s comments on 

the powertrain test. As a matter of fact, the 

powertrain test is one of the options that 

manufacturers can use to address benefits GEM is 

unable to fully capture. 

Engine Fuel maps 

The proposed engine fuel mapping procedure is 

detailed in the proposed regulations in 40 CFR part 

1036. 

It is always challenging to use a steady state map 

approach to account for transient operation. While 

there are many ways that the vehicle model can be 

improved for those behaviors, there are always 

trade-offs in terms of computational speed and 

accuracy. Furthermore, including more advanced 

models, such as model based control could 

substantially improve accuracy, but the collection 

of test data plus calibration of the model against 

the data would be beyond the agencies’ 

capabilities, and could be expensive, time 

consuming and error-prone. This kind of advanced 

modeling could take much longer to run as 

opposed to the proposed executable version of 

GEM, which only takes a few seconds to complete 

one certification vehicle. It is very typical for a 

vehicle manufacturer to run thousands of 

31
 
 

 

 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

potential for double counting of technology benefits. As an 

example, an electric coolant pump is listed as a drop-down 

technology. Depending on the engine mapping process, the 

resultant engine fuel map may already capture the benefits from 

that technology. Running a simulation with such a map, and 

later improving the results using a drop-down menu will double 

count the benefits. If EPA could respond to how potential 

double-counting situations are minimal, that would be helpful. 

simulations for certification. It is not practical to 

introduce such complicated modeling processes to 

perform certification at this time. 

We propose a single transient factor in the HD 

Phase 2 NPRM, as the reviewer recommended. 

We are also seeking comment on the transient 

correction factor. 

Driver subsystem 

In vehicle simulation modeling, it would seem that the driver 

ideally would be excluded entirely as a factor that could 

influence the GEM regulatory compliance results. Using the 

same driver model for all the vehicles seems to be an 

appropriate choice. However, additional documentation is 

needed for this subsystem. There are no details about how the 

proportional and integral gains of the PI controller have been 

selected. Are they representative of current drivers? Are they 

tuned to enhance the trace-following capabilities of the model? 

The look- ahead feature also lacks documentation. Is it bringing 

any advantage to the trace-following capabilities of the model? 

How was the time span value for such feature selected? Ideally 

EPA would provide some consideration and discussion of such 

factors to provide greater assurance that no anomalies occur in 

compliance results from company-to-company technology 

strategies as well as tested-versus-real-world results for the 

relative technology benefits. 

Transmission subsystem 

Modeling of idle cycle 

The HD Phase 2 NPRM described in Chapter 2 of 

the Draft RIA and Preamble Section V provides

more detailed description on modeling of the 

idle cycle. 

Regarding "trace following” and the idle 

calculation, for tractor-trailers the idle weight is 

zero and the simulation grams/mile are 

multiplied by target mph and also divided by

target mph so what remains is simulation 

grams/mile which will reflect the modeled

performance (or under-performance) of the 

vehicle. 

For vocational vehicles the same is true with 

regards to the simulation grams/mile over the drive 

cycles. Idle consumption takes places at zero 

speed and is measured in grams/hour so there is a 

32
 
 

 

 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

There are some transmission-related features that are confusing 

and need to be clarified. The report mentions that the different 

transmission models: manual (MT), automated manual (AMT), 

and torque converter automatic (AT) are built of similar 

components, but each features a unique control algorithm. 

However, the model seems to use the same "auto shift 

algorithm" to determine the operating gear for any transmission 

type. The differences in the control algorithm of the three 

different transmissions are not clear and need to be provided. 

Since transmissions are an important new addition for Phase 2 

GEM, it is important to let the reader know that the control 

strategy (e.g. shift points) or the selection of predefined 

transmission parameters (e.g. efficiencies and inertias at 

different gears) are not creating any artificial advantage of one 

technology type over the others. I suggest presenting a 

comparison of the same simulated truck with different 

transmission types. It is also important to highlight in the report 

that the new transmission controller is based on both speed and 

throttle position, and differs from the Phase 

1 transmission controller, which was solely based on vehicle 

speed. The rule-based approach of the "auto shift algorithm" 

would ideally be documented. 

It would be appropriate for the agencies to acknowledge that 

Phase 2 GEM simulations can capture some but not all of the 

benefits of powertrain integration. The simulation would 

adequately capture engine down speeding since the users have 

to input specific transmission gear ratios, final drive ratio, and 

tire radius. However, there are many complexities in the control 

conversion factor required to obtain grams/mile. 

The target weighted average speed represents that 

conversion factor and does not alter the modeled 

vehicle performance (or under-performance) over 

the drive cycles. 

Trailer 

The HD Phase 2 NPRM described in Chapter 2 of

the Draft RIA and Preamble Section VI provides

more detailed description on how trailers are 

handled. Tractor manufacturers determine the 

coefficient of drag area for a tractor-trailer

combination. The trailer used in this 

determination is a “reference trailer” that is 

specified in the regulations (40 CFR part 1037).

Details of the test procedures for the tractors

are included in the HD Phase 2 NPRM Section III. 

Accessories 

The agencies chose the same approach as Phase 1 

to model accessories, mainly because it is not an 

easy task to model accessory improvements, which 

requires time consuming and expensive testing and 

validation of the model. Allowing user input of 

accessory loads would require each user to know 

ahead of time the expected load for each vehicle in 

use and while potentially providing more accurate 

33
 
 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

strategy when it comes to integrating engine and transmission. 

Integrated engine-transmission powertrain approaches with 

advanced controls and shifting algorithms that many companies 

are developing could result in significantly more (or less) 

benefit than the agencies determine as the appropriate default 

emission-reduction effect. 

As an example, if two different vehicles have the same 

driveline parameters (tire radius, final drive ratio, transmission 

gear ratios, transmission inertias, and transmission efficiencies) 

and AMT transmissions from different manufacturers, they will 

obtain the same simulation results in GEM but, due to differing 

control strategies and other design characteristics, they will 

show different fuel consumption benefits in reality. It cannot be 

expected that all the AMT transmissions bring the same fuel 

consumption benefits. The drop-down menu option won't 

handle these differences unless there is an option to choose 

manufacturer-specific transmissions or otherwise input such 

data. 

As a result, there is an opportunity here to leverage the 

powertrain testing and provide the option for manufacturers to 

better capture the fuel efficiency gains coming from the control 

strategies and other complexities that are not adequately 

captured in GEM. Another advantage of powertrain testing is 

that the manufacturers would not need to disclose confidential 

information. The results from powertrain testing can then be 

implemented as correction factors for the GEM results. Using 

correction factors, GEM results could be multiplied by a fixed 

results would place an unreasonable burden on the 

user and manufacturers. If the accessory is 

normally part of the engine, the engine mapping 

conducted on the dynamometer should be able to 

account for some of those losses, thus being 

modeled through the engine fuel map. If accessory 

improvement comes from the vehicle, and GEM is 

unable to model it, manufacturers can either use 

pull-down technology or use innovative credit to 

recognize these accessories. 

34
 
 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

percent improvement obtained by comparing the results of 

powertrain test and GEM simulations under the same torquespeed trace.4 The default benefits for transmission 

improvements would ideally be set to be appropriately 

conservative (i.e., lowest expected value based on various 

industry results) in GEM. The drop-down menu could still then 

be offered as a default, for the manufacturers that decide not to 

use the powertrain testing. Then, for the powertrain option, 

companies would ideally be provided clear testing procedures 

and guidance to demonstrate the emission-reduction impact of 

their advanced powertrain approaches with physical vehicle 

testing in simulated real-world conditions. 

Engine fueling maps 

The inclusion of manufacturer-specific engine maps is a critical 

feature to reflect company differences and detailed enginespecific characteristics that reflect real-world fuel consumption 

and emissions. This is an important addition to GEM, but there 

is lack of documentation of the engine mapping procedure. I 

imagine that a fairly prescriptive procedure (including number 

of points, preconditioning and warming procedures, fuel 

properties, etc.) is described somewhere else in the larger 

regulatory development document but this chapter would 

ideally include a brief description of the procedure so the 

reader knows which engine accessories are included or 

excluded during the engine mapping procedure. 

It is noted that there are many advanced features that may 

affect fueling but are not captured by using a steady-state fuel 

35
 
 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

map. Manufacturers are going away from traditional map-based 

strategies and are going towards model-based controls. Diverse 

thermal management strategies are utilized, and some engines 

use dual torque curves. Have the agencies considered how to 

handle these technologies? This could have important 

implications for how tested steady-state engine maps, and GEM 

modeling, and real-world emissions characteristics could differ. 

As a result, we recommend that the agencies discuss such 

industry approaches in the rulemaking and investigate ways to 

ensure that tested results are aligned with real-world engine and 

vehicle operation the results in fuel consumption and 

emissions. 

The approach used to quantify the transient correction factor 

(run GEM with the engine map, then use the torque-speed 

points in the engine dynamometer and compare measured 

versus simulated results) is appropriate. Ideally the transient 

correction factor may be obtained for each individual engine. 

However, since there is a need for selection of a vehicle in 

GEM in order to get the torque-speed trace. It would become a 

hard task for the agencies to try and run a transient correction 

factor for each vehicle-engine configuration. For practicality, I 

recommend provisionally using a single correction factor and 

maintaining the option to refine it over the years with 

additional testing. 

Modeling of idle cycle 

The idle cycle modeling would gain from increased 

documentation. Using a gCO2/mile value for an idle cycle at 

36
 
 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

first seems counterintuitive (i.e., there are no miles traveled) so 

a complete description of the calculation method would clarify. 

It would be desirable to present some validation results for the 

idle cycle modeled in GEM compared to experimental results. 

Some of the engine auxiliaries may not be enabled while doing 

the test, and the map could be underestimating actual idle speed 

fueling rates. There are also engine thermal management 

strategies that are used to keep appropriate after treatment 

system temperatures. These strategies vary from manufacturer 

to manufacturer and could increase idle fueling substantially. 

The "trace following" issue discussed above also has 

implications in the calculation of idle cycle g/mile value. For 

this calculation the fuel rate in units of grams per hour [g/h] is 

converted to units of grams per mile [g/mile] using the 

weighted average speed over the three non-idle cycles. The 

target speed is used for this calculation and not the actual 

simulated speed, which may penalize smaller engines. I suggest 

EPA to consider if this issue might be significant. 

Trailers 

Although there is a parameter in GEM for trailer tires' rolling 

resistance, it is not clear how trailer aerodynamics is going to 

be modeled in GEM. Trailer aerodynamics can bring about 

two-thirds of tractor-trailer aerodynamic benefits, so this is a 

critical area that requires documentation and specification of 

the procedures for the vetting, binning, and including the input 

data. My understanding is that the Coda input parameter is for 

the tractor only (mid-roof and low roof tractors are tested in its 

37
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

bobtail configuration), or for the tractor using a "reference" 53­

ft dry van trailer (for high-roof tractors coast-down test). 

Trailer aerodynamic devices can reduce the overall tractortrailer combination aerodynamic drag and ideally the Coda 

used in simulation should represent the combination. It seems 

that there is no current provision to include the effect of trailer 

aerodynamics as an input in GEM. The report needs to clarify 

how the GEM model is handling trailer parameters (including 

aerodynamics, tires rolling resistance, and weight reduction) 

and if the model is going to use a predefined "reference" trailer 

for all the tractors. Ideally agencies would give credit to tractortrailer integrated designs although it would be difficult for the 

agencies to ensure in-use compliance of matching of tractors 

and trailers. 

Accessories 

There are opportunities for fuel savings from mechanical 

accessories and electric accessories but the agencies decided to 

keep with the Phase 1 approach of having pre-defined and not 

customizable power from accessories. If these parameters are 

assigned default values, there are no incentives to implement 

new technologies that could have greater impact. Allowing 

accessories power consumption to be user-defined inputs can 

be used to promote developments in technologies that reduce 

the power requirements of accessories such as the alternator, 

air-conditioning compressor, power steering pump, or cooling 

fan. There are other opportunities for engine accessories such 

as oil, coolant, and fuel pumps, but is not clear at this point if 

all those savings are going to be captured by the engine 

38
 
 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

mapping process. 

References: 

4 See Sharpe, Delgado, Muncrief (2015) Comparative 

assessment of heavy-duty vehicle regulatory design options 

for U.S. greenhouse gas and efficiency regulation. 

http://www.theicct.org/us-phase2-hdv- regulation-designoptions 

Reviewer 3 The elements in each of the systems (engine, transmission, 

axle, vehicle attributes etc.) seem appropriate and complete. 

The specific selection of the engines and transmissions chosen 

will cover a large portion of the current heavy-duty vehicle 

fleet, although of course any specific, single selection of 

powertrain hardware or powertrain hardware attributes 

necessarily limits the range of vehicles that can be simulated 

with that same selection. 

Non-conventional or alternative powertrains can be 

certified through powertrain testing. 

Reviewer 4 The three main powertrain components that can affect fuel 

economy and greenhouse gas emissions in a vehicle are: engine 

fuel map, transmission type and efficiency map, and vehicle 

aerodynamic improvements (including tire rolling friction 

improvements and weight reduction technologies). In this 

regard, GEM-II addresses all the aforementioned components 

by providing steady state maps for each powertrain component, 

which an informed user can change to represent specific 

technology improvements. GEM-II comes with certain standard 

transmission models, namely: manual, automatic, and 

automated manual transmissions. The user would select the 

appropriate transmission and GEM-II would automatically 

select the user-specified transmission. 

The proposed Phase 2 version of GEM for 

certification is an executable version code, which 

does not require Matlab/Simulink license. In 

additional, a plain text formatted file will be used 

for user inputs. There is no need for user to 

understand the coding structure of GEM in a 

Matlab/Simulink format. Neither manufacturers 

nor users will be able to modify the structure of 

GEM in any way. The Phase 2 GEM User Guide, 

provided with the NPRM, will provide details on 

how to use GEM. 

A technology improvement such as a proprietary 

39
 
 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

Recommendation: It is recommended that additional 

instructions are provided if the user wants to change the engine 

map. Ideally, this would be done from a user specified 

spreadsheet in a GEM-II compatible format, since the user may 

not be fluent in Matlab. In this regard, a clear explanation of all 

the variables used in GEM-II would also help significantly. For 

example, it was not clear how to change the transmission shift 

schedule if an OEM chose to do so. Further, since GEM-II is 

modular with hierarchical layout of component layers, it is 

challenging for an OEM user to insert a technology 

improvement deep within one layer and not affect the layers 

above or the execution of GEM-II. It is not clear, from this 

initial review, how a technology improvement such as a 

proprietary transmission shift schedule can be evaluated in 

terms of gains in fuel economy and greenhouse gases. This 

comment applies to other technology improvements as well, 

such as partial engine cylinder deactivation (power on demand) 

or electrification of certain mechanical accessories. 

The vehicle categories that GEM-II addresses range from Class 

2B to Class 8 HD conventional vehicle powertrains. This is 

achieved by four root-level systems in GEM-II at the root level, 

namely: the ambient, driver, vehicle, and powertrain modules. 

Each of the aforementioned modules consists of several submodules organized in a hierarchical manner. Each root-level 

module outputs a data bus that is mixed into a single data bus. 

The aforementioned four main systems of GEM-II correspond 

to the four main components of a HD vehicle, namely: driver, 

transmission shift schedule would not be 

considered under the current GEM. Rather, the 

agencies encourage the user to use the powertrain 

option described in Chapter 3 of the HD Phase 2 

NPRM RIA to address any benefits associated with 

the transmission and its integration with the engine 

that GEM is unable to model. 

40
 
 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

ambient conditions, vehicle chassis and powertrain modules. 

This one-to-one correspondence between the root-level GEM-II 

models and an actual HD vehicle makes for an easily 

understandable structure. Further, the modular organization of 

the GEM-II contributes to easier debugging and isolation of a 

numerical problem during simulation. 

The powertrain module is the most populated module in GEMII. It contains the engine, transmission and driveline submodules and accessories (mechanical and electrical). The flow 

of data information corresponds to an actual vehicle 

powertrain, with the engine output driving the transmission, 

which in turn drives the driveline components. 

The modular layout of GEM-II, its correspondence with a real 

conventional vehicle is therefore appropriate and complete for 

the reasons stated above. The modular structure and the 

hierarchical arrangement of modules to mimic a real vehicle 

system makes the integration of additional modules and 

capabilities easier to implement. The signals are clearly marked 

and follow a logical naming convention that facilitates the 

addition of additional modules and capabilities into GEM-II. 

b) Performance of each component model including the reviewer’s assessment of the underlying equations and/or physical principles 

coded into that component; 

Reviewer 1 MATLAB/Simulink remains an excellent basis for the GEM 

model. It is well suited for the exploratory and development 

framework, as well as the production of a more limited 

executable model. 

The agencies use their own auto-shift algorithm for 

all transmissions for many reasons as described by 

the supporting document – “Vehicle Simulation 

Model”. We recognize that this is not an ideal 

modeling approach, but we do offer the powertrain 

41
 
 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

GEM may be viewed on three levels. At the highest level, the 

MATLAB/Simulink platform allows GEM to be anything it 

chooses, with the addition or alteration of modules and 

component models. At the second level, there is the model 

provided for review, which has the innate ability to deal with a 

wide range of cycles and truck configurations. At the lowest 

level will be the final executable version, where certain 

parameters are fixed, and where the duty cycles are chosen for 

determination of compliance. Only the second and lowest 

levels can be considered in this review. 

This GEM model is being produced at a time where engine 

control strategy development and integrated powertrain 

controls are advancing rapidly. Also, transmission options are 

now far wider than in the earlier GEM model, where 

unsynchronized manual, synchronized manual and traditional 

automatic transmissions dominated the marketplace. GEM is 

challenged in modeling and giving credit for the technology 

subtleties that will emerge in the marketplace over the next five 

years. 

The use of distance, rather than time, as a basis for the test 

cycles represents a great and important advance. It was widely 

recognized two decades ago that light duty automobiles were 

capable of far more aggressive performance than was embodied 

in the FTP-75, although the FTP-75 was used as the norm, and 

still embodied allowances for vehicles that could not follow its 

modest accelerations. In the heavy-duty arena sustained use of 

full engine power both on grades and during acceleration is the 

norm. All else being equal, a more powerful truck will 

testing approach that allows manufacturers to 

quantify the benefits associated with their own 

more advanced shifting technologies and 

integration benefits with the engine. 

We are fully aware of the limitations of the steady 

state engine fuel maps that are proposed for GEM. 

We proposed the concept of the transient correction 

factor for the transient cycle to minimize the 

deficiency of the steady state map. We are also 

aware that this transient correction factor is derived 

from the diesel engine test, where gasoline and 

natural gas engines may behave differently. We 

are currently asking for comments on this 

approach. We will make refinements in our final 

rulemaking, as needed based on the comments we 

receive. In addition, manufacturers have the option 

to conduct powertrain testing to demonstrate their 

engine’s transient performance. 

At this time, we are proposing a single value for 

axle mechanical efficiency, and ask for comments 

of whether we should use a look-up table to model 

axle efficiency based on axle efficiency test results. 

The agencies will make appropriate adjustments in 

the final rule based on the comments received. 

It is not straight forward to model tire rolling 

resistance as function of speed without 

42
 
 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

complete its duties in less time than an underpowered vehicle, 

and often the more powerful choice represents the overall 

economic optimum. However, the more powerful truck will 

spend less time at full power, and will enjoy a reduced average 

“%load” in revenue service. The adoption of the distance-based 

approach is an important step toward matching the GEM model 

to real-would use. However, as standards are finalized, the 

accelerations and grades of cycles embodied in the GEM 

execution must represent real life as well. If the grades and 

acceleration values are not appropriately challenging, the 

distance-based approach will look more like a time-based 

approach, because underpowered trucks will be able to follow 

the trace in the minimum time allowed. This would divorce the 

market incentives from the environmental incentives and create 

a false impression of fuel efficiency capability at the expense of 

economic reality. It is important that the grades and test 

weights used are realistic and representative. Further, the 

indication of the ratio (actual / minimum time for cycle 

completion) is a very beneficial output value. 

A driver’s habits are known to have a measurable impact on 

truck fuel efficiency. This is in part due to gear selection that 

influences the engine operating envelope, and in part due to 

transient pedal demand (driver PI controller), that may cause an 

engine to depart from steady-state mode to a greater or lesser 

degree. The GEM load demand controller and GEM gear 

selection algorithms can be configured to reflect different 

driving habits. If the chosen GEM driver yields a better fuel 

efficiency than would be expected of the national average 

comprehensive tire data. Besides, just like the 

comments made by this reviewer, detailed tire data 

of this kind are not in the public domain and test 

methods are not universally defined. It is 

challenging for the agencies to develop a more 

advanced tire model at this time. 

The agencies present details of the proposed road 

grade cycles in the HD Phase 2 NPRM preamble 

and welcome comment on the representativeness of 

these and other road grade profiles developed. The 

agencies will reflect the final road grade profiles in 

the final version of the HD Phase 2 GEM. 

43
 
 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

driver, then GEM will fail to grant auto-shifting technology and 

certain engine control strategies their full potential contribution 

to efficiency gain. It is recommended that this issue is at least 

explored to provide driver sensitivity results to the 

accompanying document. 

The engine model in the new GEM is still a steady-state map. 

The documentation acknowledges that transient fuel efficiency 

will differ from steady-state efficiency at the same speed and 

load in time. A transient adjustment factor (TAF) seems likely 

for the final version, but the use of a steady-state map with a 

TAF does not encourage manufacturers to improve transient 

fuel efficiency if a generic TAF is assigned. This reviewer 

appreciates that manufacturers are unwilling to reveal strategies 

that represent a substantial fraction of product value, yet they 

cannot take advantage of their improvements in the model 

without this information. Two solutions are possible: 

(i) Determine a manufacturer-specific TAF rather than an 

agency-specified TAF, or 

(ii) Determine an alternate fuel efficiency map for transient 

(e.g. Heavy-Duty FTP) operation, and use that map or 

both steady state and transient maps for the transient 

cycle. 

In addition, TAF will need to be considered carefully for 

gasoline and natural gas engines, where enrichment 

management has an important effect on fuel efficiency. In a 

similar way, cylinder deactivation strategies may be difficult to 

44
 
 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

characterize for throttled engines, because the deactivation 

strategy is not well represented by a steady-state map. It is 

important to have a TAF strategy that acknowledges successes 

of manufacturers in lowering transient operation disadvantages. 

The EPA developers have sought comment on the issue of axle 

efficiency. It can be dangerous to employ the overall fuel 

economy computation to compare two approaches to modeling 

a single component, particularly if that component represents a 

small loss. In one case, the overall fuel economy differed by 

1.67% when a simplified efficiency was compared with a 

lookup table for rear axle efficiency. This 1.67% represented 

more than a third of the loss associated with that component. 

To place this in further perspective, the 1.67% can be compared 

to the 3-5% contributions of a major component, such as side 

skirts on a semi-trailer at freeway speeds. Generically, if a 

component model with higher fidelity is available, in the 

opinion of this reviewer, it is worth including the detail in 

GEM, even if the component model is fixed in GEM. 

Furthermore, the existence of such a model may provide a 

clearer pathway for entering technology advances by a 

manufacturer who improves that component in the future. 

The tires in GEM are simply characterized by a rolling 

resistance coefficient and an effective loaded radius. It is 

known that the coefficient varies with vehicle speed and 

contact area, while longitudinal slip can change the revolutions 

per mile by a few percent under driving torque and braking, 

which could bias results more substantially when grade is 

45
 
 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

present. This could be coded into GEM, but it is probably more 

appropriate to treat it as a comment, since detailed tire data of 

this kind are not in the public domain and test methods are not 

universally defined. 

Reviewer 2 See response for part A. 

Reviewer 3 One concern with the structure and form of the model is that a 

steady-state engine fueling map is used in each case to simulate 

transient engine operation and hence dynamic vehicle 

operation. This is in addition to the simulation of operation 

under nominally steady vehicle speeds or cruise operation. In 

the case of nominally steady operation, the use of a steady-state 

fueling map is well-justified, but the quasi-steady assumption 

required to allow the extension of the use of such a map to 

transient operation requires additional justification. Heavy duty 

compression ignition engines have high rotational inertias (due 

to the relatively high mass components required to survive the 

high combustion pressures), high mechanical friction (due to 

high effective compression ratios) and relatively slow air and 

exhaust transfer processes (due to the excess air flow rates 

accompanying their lean, un-throttled operation). In addition 

they have relatively high thermal mass due to their large 

physical mass required to withstand the stresses and strains 

resulting from high combustion pressures. All of these features 

conspire to result in deleterious combustion effects under 

highly transient engine operation. In most cases the end effect 

of these phenomena is to reduce the engine brake thermal 

efficiency under transient modes, beyond that which would be 

expected under steady or quasi-steady fueling operation. In 

most cases the additional fuel that is required to undertake a 

We are fully aware of the limitations of the steady 

state engine fuel maps that are used for GEM. We 

introduce the concept of the transient correction 

factor for the transient cycle to minimize the 

deficiency of the steady state map. We are also 

aware that this transient correction factor is derived 

from the diesel engine test, where gasoline and 

natural gas engines may behave differently. We 

are currently asking for comments on this 

approach. We will make refinements in our final 

rulemaking. 

46
 
 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

specific engine transient torque trajectory, beyond that 

estimated using a quasi-steady fueling assumption, would 

typically be less than 10% of the total integrated fueling, but in 

most cases the effect on integrated fuel efficiency over transient 

duty cycles is non-negligible. 

In general, incorporating an additional component into the full 

accounting of the vehicle load by over-accounting for the actual 

total rotational inertia (in the form of an effective or “added” 

mass or inertia) of the drivetrain and driveline system does 

allow for the quasi-steady assumption to hold. However in 

general a quasi-steady, forward-looking simulation such as is 

used in this model, tends to under-predict the actual vehicle 

energy usage under transient duty cycle operation. I notice that 

this issue is addressed in Chapter 1.4.1.8 Transient Adjustment 

Factor, but the designation of a single correction factor for a 

specific engine or powertrain configuration is likely to be 

unsuitable in some cases, and has the potential to cause 

prediction inconsistencies. Note further that the required 

correction factor might not be uniquely engine-specific, but 

might vary for the same engine in different vehicle and 

powertrain configurations. 

Reviewer 4 GEM-II follows the model of a single wheel with a 

concentrated mass at the center of the wheel. The physics 

coded into the modules are based on Newton’s second law of 

motion for this concentrated mass. At the time of this review, 

no other dynamic equations were found in GEM-II, except in 

the clutch and torque converter. The engine, accessory, 

transmission and driveline components are characterized by 

The model physics are Newtonian, as noted, and 

follow textbook equations for Newton’s laws and 

conservation of energy. 

47
 
 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

steady state maps. The equivalent mass of rotating inertia 

components are also correctly included in the vehicle module 

of GEM-II. Rotating inertias are correctly reflected 

downstream to the tire. The inertia is converted to a virtual 

mass which is added to the entire vehicle mass. The wide 

validation of GEM-II against real vehicle data indicates that the 

physics has been correctly implemented in GEM-II. 

c) Input and output structures and how they interact with the model to obtain the expected result, i.e., fuel consumption and CO2 over 

the given driving cycles; 

Reviewer 1 The accompanying explanatory document emphasizes that the 

input and output structure has not been finalized. A comment, 

intended as guidance, is that manufacturers will be obliged to 

use the executable version of GEM a large number of times to 

cover each order or each truck technology change over the 

year. This is needed to compute an average value for 

compliance. The EPA should make every effort to insure that 

the final version can be interfaced with the manufacturers’ 

software to insure that the process is efficient and reasonably 

inexpensive, while keeping that version of the model locked to 

insure compliance. 

The .csv output files, viewed in Excel, provide a representation 

of likely input and output files. These summaries are very 

useful and appropriate. 

The agencies are talking to various manufacturers 

to make sure that our input and output structure can 

be integrated with their software. The HD Phase 2 

NPRM preamble seeks comments from 

stakeholders on suggestions to minimize the 

compliance burden associated with GEM. 

Reviewer 2 See response for part A. 

Reviewer 3 A further concern that is not discussed in the documentation is 

whether any model fitting parameters were employed to obtain 

the fits observed, between the GEM-derived fuel efficiency and 

CO2 emissions values and the dynamometer-measured results. 

Some model constants were adjusted to match the 

individual vehicles, however all simulations for a 

particular vehicle are run with the same 

configuration. 

48
 
 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

In other words, beyond the parameters described and the 

accompanying constants used in the dynamic force and energy 

equations, were any other fitting techniques (or fitting 

parameters) used to obtain the observed correlations between 

the simulated cycle-averaged results and the SwRI chassis 

dynamometer results? Presumably there were dynamometer 

parameters and coefficients fitted using vehicle coast-down 

data (and dynamometer operational parameters), but beyond 

these, are there any other fitting parameters used to obtain the 

correlations shown? Discrepancies between simulated and 

measured results of less than 2-3% are probably not significant, 

except in the presence of a consistent bias between the 

measured and predicted, for any one vehicle, cycle or 

technology considered. 

Examples of adjusted model constants are 

transmission shift delays, rpm limits, up and down 

shifting constraints, first gear skip, etc. However 

once these model constants are tuned, they are not 

adjusted for individual drive cycles or tests. In 

other words, vehicle-specific constants are set up to 

match the behavior of the vehicle but are not tuned 

for individual results. Input values directly from 

experiment, such as coast down data related to aero 

drag coefficient and tire rolling resistance 

coefficients are taken as inputs and not further 

adjusted. 

Reviewer 4 Input for GEM-II: 

A structure format is used to store the inputs to create the input 

data for the execution of GEM-II. The structure format is 

organized as follows: component.variable.units. For example, 

the input variable “engine.idle_fuel_map_speed_radps” 

identifies the engine speed vector of the engine idle fuel map 

expressed in rad per sec. Similarly, the input variable 

“transmission.clutch.input_inertia_kgm2 refers to the clutch 

inertia of the transmission, expressed in kgm2. This format 

follows good coding standards, making the inputs easy to pair 

to the appropriate component it refers to, the particular variable 

name, and the units used. Further, a modular approach is used 

to store the input data for each component in separate easily 

identified files in the “param_files” folder. 

Although this reviewer makes excellent comments 

on the model data structures based on 

Matlab/Simulink, the actual code used for 

certification is only an executable version of the 

code, meaning that it will not require a 

Matlab/Simulink license and the user would not 

touch the source code, and therefore, these 

comments are not relevant to the certification tool. 

49
 
 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

Output for GEM-II: 

When the workspace has been populated with the input data, 

the simulation model “REVS_VM” vehicle model is executed 

over the user-selected drive cycle. Each major component 

model (GEM_CVM, vehicle, driver, ambient) has a bus_out 

output port which contains a structure of component output 

data, which is used within other components. In addition, 

GEM-II uses a datalog structure to store simulation output data 

for later post processing to calculate emissions and fuel 

economy. All the simulation output is stored in a single datalog 

structure with multiple fields, each describing the component 

that the data pertains to. For example, 

datalog.vehicle.speed_mps refers to data log from the vehicle 

component of the variable vehicle speed in m/s. This format is 

an accepted coding standard within other vehicle simulation 

packages (such as PSAT from ANL, RAPTOR from SwRI) as 

well, making the output easy to pair to the appropriate 

component it refers to, the particular variable name, and the 

units used. Similarly, all variables that are used to perform an 

energy balance are prefixed by “audit”. 

Interaction with the model to obtain the expected results: 

The bus_out structure from the various components are stored 

in “goto” blocks which are paired with “from” blocks to 

distribute data from one block to another. The use of paired 

“goto” and “from” blocks is an accepted method of decluttering 

the simulation model and avoiding crisscrossing signal lines, 

thereby significantly facilitating the understanding of 

50
 
 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

information flow from one component to another. 

d) Default values used for the input file, as shown in “Vehicle Simulation Model” document. 

Reviewer 1 The default values are not particularly important at this stage of 

development. They are sufficiently representative of recent or 

current technology to provide reasonable inputs and to assess 

the ability to predict real-world values. However, this is an 

appropriate point to acknowledge and discuss the comparison 

of GEM output with real-world measurements, as described in 

the supporting material. 

The real-world data serve to verify the ability of GEM to model 

a variety of trucks. These data do not extend to the validation of 

truck tire rolling resistance or aerodynamic drag value 

selections because the validation was conducted using roller 

and powertrain dynamometers, where these values were 

entered and were the same values used in GEM. Generally 

GEM matched the measured fuel efficiency values to within 

5%, and the deviation may be attributed both to measurement 

error and to the inherent simplifications in modeling. There are 

some systematic errors evident in the comparison. For example, 

the T700 truck efficiency is underpredicted (GEM vs. 

measured) on the high speed tests and overpredicted on the low 

speed tests. This trend differed for the T270 and F650 trucks. 

The refuse truck fuel efficiency was uniformly overpredicted. 

This leads to the conclusion that GEM may be capable of 

predicting overall fuel efficiency accurately (at the 5% 

difference level), but that one should still be cautious of 

comparing the performance of very different technologies using 

the GEM tool. 

The agencies agree with this reviewer’s comments. 

It is a daunting task to verify every GEM submodel, which would require significant investment 

to collect data and then validate each sub-model. 

Just as this reviewer pointed out, the single overall 

predicted efficiency is of interest to the 

manufacturer because it predicates compliance. 

GEM works reasonably well to predict this single 

value, namely, fuel economy over 130 vehicle 

variants. 

The agencies have made significant improvements 

on the driving cycle. The addition of road grade to 

55 and 65 mph cruise cycles is just one example. 

The agencies are seeking comment on the proposed 

drive cycles and road grades in the HD Phase 2 

NPRM. We will refine GEM as necessary based 

on the comments for the final rulemaking. 

51
 
 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

The narrative states that “While it is encouraging that GEM 

accurately simulates overall vehicle performance in an absolute 

sense, it is actually more important that GEM is accurate in 

relative comparisons.” This is true in the sense that GEM 

should encourage the best technology pathways through 

comparison, but it is nevertheless the single overall predicted 

efficiency that is of interest to the manufacturer because it 

predicates compliance. As an example, when the axle ratios 

were adjusted for a vocational truck from the chosen value of 

3.76 to high (4.06) and low (3.46) values, the predicted 

transient fuel economy values were 5.55, 5.49 and 5.6 

respectively. In contrast to this small variation, the fuel 

economy values for the 65mph operation were 7.14, 6.88 and 

7.37 respectively, attributable to the 9% difference in engine 

speed between the high and low ratios. This reviewer has 

confidence in these relative values where a variable input is 

changed. However, a comparison between two vehicles with 

identical chassis and bodies, but with different engines, 

transmission types and tire rolling resistance challenges several 

parts of GEM in a differential sense, and a greater comparative 

error must be anticipated. One cannot argue that the overall 

agreement with the measured data verifies each sub-model 

within GEM. 

The use of single variables to represent a more complex reality 

is discussed elsewhere in this review. 

The cycles chosen for evaluating vehicle performance can be 

52
 
 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

changed readily in GEM. Although incorporation of grades 

represents a substantial advance, the current choice of fixed 

55mph and 65mph steady speeds may cause designers to “teach 

to the test.” [The CBD cycle, used in a previous age to quantify 

transit bus performance, suffered from problems of this kind 

because all steady state operation was at 20mph.] The output 

data for the tractor (through engine speed / vehicle speed ratio) 

show that the highest gear was used for both fixed speeds. Use 

of a test cycle where speeds varied slowly through the 50 to 70 

mph range could avoid pitting real world optima against model 

optima, and would encourage engine downspeeding strategies 

that are successful in revenue service where speed limits are 

not necessarily 55 and 65mph. 

Reviewer 2 See response for part A. 

Reviewer 3 The default values as defined in the “Vehicle Simulation 

Model” are reasonable and currently fall within the ranges of 

expected vehicle values. It is not clear however under what 

circumstances the user will be able or allowed to make 

modifications in the final model implementation. For instance, 

it is conceivable that the interplay between future auxiliary 

mechanical or electrical loads on an engine might be 

significantly modified through conversion of mechanical 

auxiliaries to electrical or electronic devices. In that case, that 

will shift the relative balance in those loads. Moreover it is not 

clear that engine cooling fan loads have been adequately 

accounted for in the model, as these are typically not 

considered in the engine dynamometer testing from which 

engine fueling maps are normally derived. This exclusion alone 

can modify observed fueling rates by 10% or more under 

The example mentioned by this reviewer of the 

coolant fan is an example of a technology that 

GEM cannot directly model at this time due to lack 

of data and the extra burden of testing that would 

be required to calibrate such a model. In general, 

GEM will recognize all technologies that can be 

measured during dynamometer cell testing through 

the engine fuel mapping procedure. Those that 

cannot be measured or cannot be modeled through 

GEM will be accounted for in different ways 

through 

(1) the pull-down technologies item or 

technical improvement input values 

(2) Powertrain test options 

(3) Innovative credit 

53
 
 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 3. Charge Question 2 

Charge Question 2: Please comment on the appropriateness and completeness of the contents of the overall model structure and its 

individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the 

following: 

specific engine operating conditions. 

Other default values including transmission gear ratios, 

transmission efficiencies, axle efficiencies, tire rolling 

resistance, and vehicle aerodynamic drag product seem 

reasonable. 

Reviewer 4 The default data used in GEM-II is complete and appropriate to 

execute a simulation of HD vehicle powertrain over one of the 

drive cycles available in the GEM-II default drive cycle library. 

The default ambient conditions summarized in 

ambient_param.m are appropriate. The default driver 

parameters, summarized in driver_param.m, contain driver 

gains as well as the time that the driver can look ahead in the 

drive cycle. The driver gains represent an average driver, which 

the user can change to emulate an aggressive driving pattern 

versus a calmer driver. 

The default engine maps of 270 kW, 345 kW, and 455 kW 

power ratings includes inertia, idle speed. Default transmission 

maps for the manual, automatic, auto-manual are also available. 

Default tire radius, axle ratios, rolling resistance of the tires of 

the steering axles and drive axles are also included. 

The certification tool is an executable version, and 

the user will not be able to access the source code 

for certification. Therefore, the user will not have 

flexibility to change model constants, such as 

driver gain. 

Table 4. Charge Question 3 

Charge Question 3: When using the standard of good engineering judgment, is the program execution optimized by the chosen 

methodologies? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

54
 
 

 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 4. Charge Question 3 

Charge Question 3: When using the standard of good engineering judgment, is the program execution optimized by the chosen 

methodologies? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

Reviewer 1 The GEM tool as presented to the reviewers provided a 

workable compromise between accuracy and simplicity. It is 

evident that GEM may be improved in accuracy by increasing 

input data, in particular the substitution of data tables for single 

values. However, these tables would need to be created for each 

component at substantial expense. Also, it would be better to use 

real values or tables or strategies from manufacturers, but each 

of these might require audit and prescribed measurement 

methods, and in many cases the manufacturer considers them to 

be proprietary. The present GEM is close to being optimized: 

clearly development is still taking place. 

As a general observation, the engine and transmission receive 

substantial attention in GEM and in much work on truck 

efficiency improvement. They seem to be of interest at the 

single percentage level. However, tire rolling resistance is a 

major influence for vocational trucks, and drag coefficient 

controls the dominant loss for freeway tractors. Yet these two 

components are each represented by a single parameter. Beyond 

just GEM, a more detailed consideration of these components 

(e.g. longitudinal slip of tires, rolling resistance during 

crosswind correction, effects of yaw on drag) would assist in 

raising modeling accuracy. If that cannot be considered 

expediently for this version of GEM, it should be considered in 

the future, or even embedded in the tables so that it can be 

applied without altering the code. 

We fully agree with this reviewer’s comments. The 

current version of GEM is a balance of model 

fidelity and simplicity. The agencies could develop 

more advanced features, but at higher cost of 

development and longer duration, which would not 

be able to meet the timeline of this rulemaking. In 

the future, many advanced technical features 

including the tire model mentioned here could be 

considered. 

The agencies are proposing to account for the effects 

of yaw on drag in Phase 2 in the CdA input to GEM. 

The HD Phase 2 NPRM preamble Section III 

describes the test procedures to determine the wind 

average yaw coefficient of drag value and we seek 

comment on the proposed approach. 

Reviewer 2 The chosen methods and execution of the model shows strong 

engineering judgment throughout. A good indication of proper 

We appreciate the comments made by this reviewer. 

55
 
 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 4. Charge Question 3 

Charge Question 3: When using the standard of good engineering judgment, is the program execution optimized by the chosen 

methodologies? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

execution is the overall good agreement between the Phase 2 

GEM simulations and testing data obtained with chassis and 

power train dynamometers. The errors shown are well within +/­

5%, which is within the test-to-test variability of chassis 

dynamometer testing. Execution at this level of fidelity meets 

our own criteria that we have utilized to validate tractor-trailer 

simulation results.5 the validation results show that the balance 

between model accuracy and simplicity is adequate. As a result, 

the program would be effective to model a diverse set of 

technology changes and be used in regulatory applications. 

References: 

5 See Delgado and Lutsey (2015). Advanced tractor-trailer 

efficiency technology potential in the 2020-2030 timeframe 

http://www.theicct.org/us-tractor-trailer-efficiency-technology 

Reviewer 3 This issue is difficult to address through the level of observation 

afforded to the reviewer at this stage of development of the 

model. It is not obvious that the program execution is optimized, 

but the results, computational time and outputs displayed 

indicate that the chosen methodologies are suitable for this 

purpose. 

We appreciate the comments made by this reviewer. 

Reviewer 4 Overall, GEM-II uses industry accepted coding practices 

throughout the software modules. The following is a partial list 

of these accepted practices: 

• Valid variable naming structure used – 

• Data bus used for each component – 

• Modular components with no signals crossing – 

• Useful comments to assist the user with following the 

The comments made by this review are well taken in 

terms of improvement of the Matlab/Simulink 

version of the source code. We should point out that 

the certification tool is an executable version of 

GEM, and the user would not be allowed to use the 

Matlab/Simulink version of the source code to 

perform certification. 

56
 
 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 4. Charge Question 3 

Charge Question 3: When using the standard of good engineering judgment, is the program execution optimized by the chosen 

methodologies? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

code – 

• Energy audit adds to the confidence level of the results 

of the simulation. 

• File name that is executed is echoed back to the user. If 

there is a simulation abort, the debug is easier 

• Data that is being loaded is echoed back to the user so 

the user knows what data is being used. 

• Component modules are linked to libraries. A change in 

the library module propagates to all vehicle models 

during execution. 

At this point in the review, I do not have adequate data to 

comment on the execution optimization of GEM-II. Linear 

interpolation modules from the standard Simulink library are 

used within GEM-II, thereby optimizing execution. If there are 

any non-standard user defined functions used within the GEM-II 

simulation model, the execution can be made considerably faster 

through the use of s-functions within Simulink. At the time of 

this review, no S-function were found in the model. 

Table 5. Charge Question 4 

Charge Question 4: Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel 

efficiency output file). 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

Reviewer 1 The .csv output results are sufficiently comprehensive for the 

user who is not executing the program in MATLAB for research 

Yes, a succinct report with .csv format will be used 

as output. 

57
 
 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 5. Charge Question 4 

Charge Question 4: Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel 

efficiency output file). 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

and design purposes. Presumably a report similar to the .csv is 

anticipated as the executable version output. In fact, to the 

manufacturer, who is executing this at time of sale within a 

larger accounting loop, a very succinct output would be 

sufficient. 

Reviewer 2 The data reports did not appear to be fully complete, but the 

accuracy of the output/results appears to meet reasonable 

expectations. The input and output structure of GEM was not 

finalized when released for peer review, however some samples 

of the output files were provided to give the reviewer a flavor of 

the potential structure. In my opinion, for completeness, the 

output file needs to include results for each different cycle and 

not only for the weighted aggregation of cycles. Some metrics 

can be added to the output file to facilitate troubleshooting and 

give the user a better perspective. As mentioned before, actual 

simulated speeds and a measure of deviation from the speeddistance trace would ideally also be provided for transparency of 

the results. Based on the validation results, accuracy with respect 

to measured data was provided and seems to be within 5%, 

which is acceptable output accuracy based on comparable 

modeling as well as real-world testing. 

Phase 2 GEM will use the same output information 

to report certification as Phase 1 GEM, meaning 

that output file would only include the weighted 

aggregation of cycles for the sake of certification. 

However, the user does have the option to access 

the source code to find out more for those 

intermediate results, although the results from 

source code would not be allowed for certification. 

Reviewer 3 The model outputs and results seem clear, complete and 

accurate. One caveat with interpreting or using the freight 

efficiency or load efficiency-based results lies in the use, further 

interpretation or extension of these results. Users might be 

tempted to “scale” the load-based results in an inappropriate 

fashion – for example, if the returned result for the computed 

carbon dioxide emissions is 100 gCO2ptm (grams CO2 per tonFor certification, GEM uses default payloads for 

each regulatory subcategory, meaning that the user 

would not have option to make any change on the 

payload, thus avoiding the issue mentioned by this 

reviewer. 

58
 
 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 5. Charge Question 4 

Charge Question 4: Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel 

efficiency output file). 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

mile) for say a 30 ton vehicle over a specific cycle, there might 

be the temptation on the part of users to employ that same 

numerical result to predict the CO2 emissions for the same 

vehicle loaded to 40 tons over the same cycle. However this 

assumption is not correct, as the vehicle fuel consumption is a 

function not just of load or weight-related terms (rolling 

resistance, grade, acceleration etc.) but also terms that are 

invariant with load or weight (such as aerodynamic drag), and 

this is not reflected in an emissions per ton-mile result. 

Reviewer 4 The output data from a simulation execution is summarized in a 

spreadsheet, which is date and time stamped, allowing the user to 

verify that the output data corresponds to the simulation 

executed. The output data contains data on which technology 

improvement (weight reduction, vehicle speed limiter, single 

drive axle, par time single drive axle, low friction axle 

lubrication, predictive cruise control, high efficiency AC 

compressor, electrified engine cooling pump, extended engine 

idle reduction, automatic tire inflation ) was assessed, engine, 

transmission type, fuel economy and CO2 emissions. 

The output data, summarized above, serves the original purpose 

of GEM-II, which is to enable users to demonstrate compliance 

with regulatory standards either without any modifications to the 

HD vehicle, or analyze the fuel economy and CO2 emissions, 

when one or more technology improvements are employed. 

However, information on the drive cycle is missing or not clearly 

identified. In addition, key plots of vehicle tracking the drive 

cycle, engine operating speed-torque points over the drive cycle, 

GEM is a certification tool, and as such produces 

simplified results, which can not only be easily 

connected to the agencies’ certification tool box for 

compliance, but also can be directly linked to the 

manufacturer’s information technology system. For 

more comprehensive outputs and plots, the user has 

the option to use the Matlab/Simulink version of the 

source code to provide a better understanding of the 

results. GEM as a certification tool is not meant to 

be used as a development aid. Again, the results 

from source code would not be allowed for 

certification. 

59
 
 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 5. Charge Question 4 

Charge Question 4: Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel 

efficiency output file). 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

engine efficiency contour plots, transmission operating points, 

and other plots that assist OEMS to further fine tune the 

powertrain and improve fuel economy/ CO2 emissions in case of 

non-compliance. It would be desirable to have the results of the 

energy audit summarized in the output file. The date stamp 

column is appropriate for the user to cross check simulation runs. 

Table 6. Charge Question 5 

Charge Question 5: In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? 

Any recommendations for specific improvements to the functioning of the outputs of the model? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

Reviewer 1 Words of caution may help in presenting GEM to the user and to 

the public. It is important to state that GEM has acceptable 

accuracy in predicting the fuel efficiency of a specific vehicle 

under specific circumstances. However, it is equally important to 

state that if GEM is used to compare two competing, but very 

different, technology packages, it may not have the fidelity or 

granularity to evaluate which is better. GEM may not determine 

the relative difference between the two with high fidelity, and 

that relative difference will depend on the vehicle vocation or test 

cycle used. 

Although modeling test weights were provided for the example 

vehicles, there was no quantitative discussion of choice of test 

weight for GEM. Test weights receive only brief mention in the 

supporting documentation. It is possible that within vehicle 

classes, or across regions with different topography, engine size 

Test weight is set to a default value for each 

regulatory subcategory, which means that the user 

would not have option to make changes. This is 

necessary, because allowance of different test 

weights per vehicle can result in numerous standards 

for the same class vehicle, which would be 

challenging for the purpose of compliance. The 

agencies provide details regarding the proposed 

payloads and test weights in Chapter 3 of the HD 

Phase 2 Draft RIA and seek comments regarding the 

weights in the preamble. 

60
 
 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 6. Charge Question 5 

Charge Question 5: In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? 

Any recommendations for specific improvements to the functioning of the outputs of the model? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

may be selected based on the anticipated load. The distance 

based strategy shows an appreciation for this issue, but some 

compensation with test weight for engine size could be 

considered. Perhaps test weights could be selected so that the 

time to complete the route remains within reasonable bounds for 

more lightly powered vehicles, but at least that highly powered 

vehicles are acknowledged to be appropriate for some 

occupations, loads or regions. The vocational tractor option in 

Phase I is not a comprehensive solution. 

Reviewer 2 Phase 2 GEM could generate two different output reports. One 

that only includes the most relevant information on an aggregated 

format and is used only for compliance purposes, and a second 

one, that is very detailed and includes results disaggregated by 

cycle and other relevant information that may help the users to 

troubleshoot their results, learn the inner workings of the model 

and potentially suggests enhancements to it. I suggest including a 

summary of the energy audit in the output. Also, provide the 

average engine efficiency over the cycle for the different test 

cycles, as well as the ratio of average engine efficiency to 

maximum engine efficiency, which is an indication of how well 

the transmission parameters are matched to keep the engine 

operating near its peak efficiency range. 

The output file provides some basic “sanity checks” such as 

number of shifts, ratio of number of shifts to number of gears in 

the transmission, distance traveled, and ratio of actual time to 

target time. Please also provide ranges of valid or acceptable 

values for these parameters so the user can be aware of any 

GEM is a certification tool, and as such produces 

simplified results, which can not only be easily 

connected to the agencies’ certification tool box for 

compliance, but also can be directly linked to the 

manufacturer information technology system. For 

more comprehensive outputs and plots, the user has 

the option to use the Matlab/Simulink version of the 

source code to provide a better understanding of the 

results. GEM as a certification tool is not meant to 

be used as a development aid. Again, the results 

from source code would not be allowed for 

certification. 

61
 
 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 6. Charge Question 5 

Charge Question 5: In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? 

Any recommendations for specific improvements to the functioning of the outputs of the model? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

potential issues with the simulation. 

A further step that could allow the tool to be much more useful 

would be to allow users to input their own cycles as is currently 

done with VECTO6 (Vehicle Energy Consumption calculation 

Tool) model in Europe. The VECTO tool has a “declaration 

mode” for compliance, and an “engineering mode” which offers 

the ability to edit inputs and allow users to explore what the tool 

can do. This would be critical for transparency and follow the 

best practice as seen in the Europe situation. It would also be 

highly useful for individuals in the heavy-duty vehicle supply 

chain to explore the variation of the results with respect to realworld duty cycle factors. Especially considering the very diverse 

use of heavy-duty vehicles in local, regional, and long- distance 

conditions, this capability would allow dealers and fleet 

managers to gauge how fuel consumptions for particular relevant 

driving patterns differs from the cycle. This would help ensure 

the technologies that are more suited to particular duty cycles are 

being selected in the market place, and it would also help 

overcome the prevailing market barrier, whereby knowledge, 

data, and confidence on truck efficiency has been limited.7 

References: 

6 See Luz et al (2014) 

http://ec.europa.eu/clima/policies/transport/vehicles/heavy/docs/f 

inal_report_co2_hdv_en.pdf

7 See Roeth et al (2015) http://www.theicct.org/hdv-technologymarket-barriers-north-america 

62
 
 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 6. Charge Question 5 

Charge Question 5: In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? 

Any recommendations for specific improvements to the functioning of the outputs of the model? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

Reviewer 3 The version reviewed here does not include the graphical user 

interface (with “pull-down menus”) described in the instructions. 

The ability to modify input parameters and vehicle attributes will 

improve the user experience, while obviously presumably not 

impacting the model outputs. 

Due care and attention should be paid to the number of 

significant digits presented in the output results. For example, in 

the results presented from a single specific simulation (shown 

below): 

>> GEM_Phase2_Idle_55_65_CARB_HHDDT_Transient 

Distance = 32.414 mi 

Fuel Consumption = 5.4059 gallons 

Fuel Consumption = 17184.1217 grams 

Fuel Economy = 5.996 mpg 

Fuel Consumption = 530.140 g/mile 

CO2 Emission = 1697.77 g/mile 

The number of significant digits in the model simulation outputs 

presented above (some of which are directly related through 

derivation or calculation) varies from 4 to 9. This does not meet 

recommended practices in the presentation of results and data. 

Moreover, industry experience in the measurement of real-world 

fuel efficiency during over the road truck testing dictates that 

measured fuel consumption variations of less than 1-2% should 

not be considered significant or compelling, and this level of 

variation could correspond to variations in the 2nd or 3rd 

significant figures in fuel consumption in most cases. 

The agencies have consulted with all major 

manufactures on whether a graphic user interface 

(GUI) needs to be developed. At this time, none of 

them support this idea. The reason is that a GUI 

would prevent the GEM output from being 

integrated with their internal information technology 

system. At the same time, a GUI would provide 

convenience to those individual user or small 

entities for use. In order to compromise this issue, 

the agencies decide not to propose a GUI. Rather, 

the input file is designed in such a simple way that 

the individual users can easily use it for their own 

purpose, and an interactive Excel spreadsheet will 

be made available as mentioned previously. 

The number of the significant digits shown in the 

output screen is not the same as those in certification 

output file (.csv). It should also be noted that the 

same output format is used for light duty vehicles 

where the magnitude of the numbers is much 

smaller and therefore the significant digits are fewer. 

No attempt was made to tune this output, which is 

not part of the certification process, for heavy duty 

test results. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 6. Charge Question 5 

Charge Question 5: In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? 

Any recommendations for specific improvements to the functioning of the outputs of the model? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

Reviewer 4 The following modules will enhance GEM-II: 

• A module that is able to create the input data for a GEMII execution from a user provided spreadsheet with predefined tabs for the engine, transmission, drive cycle, 

vehicle parameters, and technology improvement. Users 

are more familiar with spreadsheets than the Matlab 

environment. 

• A GUI module that guides the user to create a HD vehicle 

model. 

• A module that allows users to select plots of key 

component performance. These plots may be summarized 

in the output spreadsheet data file. 

• A more detailed explanation of all the user provided data 

“target.X” and the various choices available for each of 

the user provided data. For example, what are the choices 

that the user has for the variable target.veh_style ? 

• GEM-II execution takes place within the Simulink 

environment. During execution, no feedback is provided 

to the user on the status of the simulation. The user is 

waiting on a blank screen – Percent complete of the 

simulation and which drive cycle is being executed would 

be useful feedback for the user. 

• Predefined sample input data for all class of vehicles to 

assist users to easily modify them if necessary, since 

some users may not be familiar with Matlab. 

• The ability to turn on the feed forward term for the driver 

model in case of tracking problems in drive cycles with 

grade. 

Many comments made by this reviewer are very 

helpful in terms of the Matlab/Simulink version of 

GEM. As pointed out earlier, only the executable 

version of GEM is allowed for certification where 

the Matlab/Simulink environment is not needed. 

Because of that, the user has no option to make any 

model constant modifications. 

A GUI is helpful for individual users. However, it 

may not be helpful for large vehicle manufacturers 

where they need to connect their information 

technology system with the output of GEM. The 

agencies attempt to balance the needs of individual 

users and large organizations. The combination of 

the proposed input file and GEM User Guide should 

be as user friendly as a GUI. 

64
 
 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 6. Charge Question 5 

Charge Question 5: In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? 

Any recommendations for specific improvements to the functioning of the outputs of the model? 

Reviewer 

Name 

Reviewer Comment EPA Response to Comment 

• The ability to model accessory power draw as a function 

of engine speed and engine temperature. The engine 

cooling fan power cycle will affect fuel economy and 

CO2 emissions. 

Table 7. Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Reviewer 

Name 

Page Paragraph Reviewer Comment EPA Response to Comment 

Reviewer 1 8 1 

Axle lookup table is a better approach 

The agencies note the comment but 

determined no revisions are required to

the documentation 

8 2 “Brakes” Addition of the inertia component to axle 

is curious/ a curious description. This is rather a 

retarding torque. Perhaps the inertia becomes a force 

if MATLAB is viewed over time steps. I was 

confused by this language. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM. 

10 2 It would be good to see (as well) the equivalent to 

Figure 1-3 with the proposed locked shifting 

strategies in GEM, rather than actual strategies as 

discussed on p. 10. 

Some of the comparisons are shown in 

Table 4. 

16 2 Need to be cautious about claims in modeling 

changes. Effect of change in Crr is clear, but GEM 

may have difficulty with relative accuracy in 

changing transmission type. 

The agencies note the comment but 

determined no revisions are required to

the documentation 

16 2 Note in presenting these agreements that Crr or Cd 

changes are entered as dynamometer A-B-C 

coefficients, and these are not real world 

The agencies note the comment but 

determined no revisions are required to

the documentation 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 7. Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Reviewer 

Name 

Page Paragraph Reviewer Comment EPA Response to Comment 

measurements. Essentially the dynamometer is 

partially modeling these effects. 

17 Table 1-3 And the figure. Note that the 1.8% error represents a 

17% error based on the difference, if this figure is 

intended to show the accuracy of predicting 

differences rather than absolutes. 

The agencies note the comment but 

determined no revisions are required to 

the documentation 

18 2 GEM is using automated shifting, essentially, for 

both MT and AMT, and this will be used (with PI 

control pedal) for impact assessment. Yet this 

paragraph brings human drivers to the fore. 

Philosophically, that the human drivers are the truth 

and the accuracy of revenue service, more than the 

model or powertrain cell. 

The agencies note the comment but 

determined no revisions are required to

the documentation 

19 Fig 1-9 to 

1-13 Are these with default or manufacturer’s shift tables? 

Yes. 

22 Table 1-4 

Little or no shifting occurs in the 55 and 65 cycles. 

That should be stated. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

23 End of 

page Text should explain in a little more detail how these 

powertrain tests may be inserted into GEM 

The agencies note the comment but 

determined no revisions are required to

the documentation 

Reviewer 2 2 2 The list of key technical features may include the 

fact that the new model uses distance-based cycles 

instead of time-based cycles, and the fact that test 

cycles now include road grade. 

It is a distance-base model 

2 2 The claim "more stable engine idle speed controller" 

is not discussed in the text. Some metric or 

quantification of what is meant by "more stable" 

needs to be provided. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

2 3 Regarding “substantial effort has been put forth to It is mainly used for internal use. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 7. Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Reviewer 

Name 

Page Paragraph Reviewer Comment EPA Response to Comment 

accurately track and audit power flows through the 

model to ensure conservation of energy" The report 

lack details about the energy audit. Was the energy 

audit developed just for internal quality control or is 

it going to be provided to the end users in an output 

file? 

3 1 Regarding "the road gradient has been modified to 

accept a road grade that varies as a function of 

distance traveled" Please introduce the concept of 

distance-based versus any pros/cons of the new 

method and why did you change the approach. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

3 2 Driver subsystem. This section (1.2.2.2) is not clear 

to the reader and, in my opinion, needs rewriting. 

There are various confusing statements such as "the 

feed forward calculations using drive cycle 

accelerations and vehicle mass have been removed". 

The section also mentions (page 4, paragraph 1) that 

a ratio of speeds (which is non-dimensional) is 

integrated to produce the current cycle position 

(which has units of distance), which is dimensionally 

incorrect. I recommend showing the equations to 

avoid confusing the reader. Regarding the statement 

"the addition of distance compensation allows all 

simulated vehicles to complete an equivalent trip 

such as traveling from point A to point B" Does that 

mean that without distance compensation the 

vehicles would not complete the trip? 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

3 2 How were the proportional and integral constants of 

the PI controller estimated? Is the same driver 

subsystem used independently of transmission 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD 

Phase 2 NPRM 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Reviewer 

Name 

T

Page Paragraph 

able 7. Specifi

Reviewer Comment 

c Observations on Tool Description Entitled, “Vehi

EPA Response to Comment 

cle Simulation Model” 

choice? How was the look-ahead feed-forward 

control implemented? 

4 2 Consider removing the mention to the "variant 

power train architecture" since it is not mentioned 

anywhere else in the report. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

5 1 Please clarify that the engine map is not a predetermined parameter as in Phase 1 GEM, but a 

user-defined input. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

5 3 For consistency with previous section, please 

show the proposed constant power loss magnitude 

of electric subsystem. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

5 4 Please change "four different variants” for "three 

different variants” (MT, AMT, AT). 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

11 There is an apparent incongruence in Page 5, 

paragraph 4, which mentions that each transmission 

"features a unique control algorithm matching 

behaviors observed during vehicle testing" 

however, in Page 5, paragraph 5 it is mentioned 

that "all of the transmission models use an auto 

shift algorithm to determine the operating gear over 

the cycle". Are the auto shift algorithm parameters 

changed based on transmission type? Is there 

really a unique control algorithm for each 

transmission type? 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

5 5 The "auto shifting optimizer" needs proper 

documentation. How does it work? 

A reference paper (Newman, K., Kargul, J., 

and Barba, D., "Development and Testing

of an Automatic Transmission Shift 

Schedule Algorithm for Vehicle 

Simulation," SAE Int. J. Engines 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 7. Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Reviewer 

Name 

Page Paragraph Reviewer Comment EPA Response to Comment 

8(3):2015, 2015, doi:10.4271/2015-01-

1142.) 

has been added into Draft RIA chapter 4 for 

more information 

6 1 The clutch model is a key new addition and lacks 

proper documentation. 

Please support claims such as "realistic actuation 

durations and more accurate physics of torque 

conservation and lockup behavior" with data. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

6 2 Please clarify what you mean by “This layout is 

more similar to a manual transmission, but the 

application for a planetary gearbox is a 

reasonable approximation as this type of gearbox 

can utilize a variety of topologies" i s confusing to 

me. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

8 2 The statement "The brake model also adds a 

rotational inertia component to the axle" is 

misleading since the inertia of brakes is set to zero 

in GEM. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

9 2 Please provide a table with a complete list of predefined and user-defined parameters. There is no 

need for specific values, just the list of parameters. 

It is included in the NPRM 

12 1 Description of test condition number 6 reads, 

"Run a new set of road load coefficients to 

represent a vehicle configuration optimized for 

fuel efficiency for each vehicle that was tested." 

To be consistent with the other test conditions 

described please quantify the reductions in rolling 

resistance, aerodynamic drag, and mass for this 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Reviewer 

Name 

T

Page Paragraph 

able 7. Specifi

Reviewer Comment 

c Observations on Tool Description Entitled, “Vehi

EPA Response to Comment 

cle Simulation Model” 

particular "optimized package" case. 

13 Figure 1-3 

to 1-6 

In the legend, it is not clear if the 55mph and 65 

mph tests contain grade or not. Also, the "utility" 

cycle is not described in the text. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

15 Figure 1-6 Although is mentioned in the text, it seems that 

the refuse truck was not tested under the refuse 

cycle. Also, it seems that it was not tested under 

different test conditions as the remaining vehicles. 

Any reason for this? Please explain. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

16 1 Change "numerically" for "numerical.” The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

18 2 The statement "In some cases, it is hard to 

quantify which method, vehicle simulation or 

chassis dynamometer test, is more accurate" is very 

misleading. The chassis dynamometer test 

although imperfect, is a measurement and it was 

treated as a "true" value in the validation process 

(Figures 1-3, 1-5, and 1-6). Accuracy can only be 

measured in reference to a true value. The chassis 

dynamometer test was selected as such and the 

model cannot hope to have better accuracy than 

the test. 

Added SwRI technical research workshop 

as one of the references to Draft RIA 

Chapter 4. (US EPA, “Technical Research

Workshop supporting EPA and NHTSA

Phase 2 Standards for MD/HD

Greenhouse Gas and Fuel Efficiency —

December 10 and 11, 2014,”

http://www.epa.gov/otaq/climate/regsheavy-duty.htm) 

18 3 In the statement "GEM is capable of capturing the 

impact on the total vehicle CO2 emissions and 

fuel consumption due to any technology 

improvement" the word "any" is misleading since 

the validation effort was only done over 

aerodynamic, rolling resistance and mass 

parameters. Moreover, there is certainly a set of 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 7. Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Reviewer 

Name 

Page Paragraph Reviewer Comment EPA Response to Comment 

technologies that GEM is incapable of model. 

17 Table 1-3 Correct the numbers on the "Delta" column. Due 

to rounding it is not evident that the column 

represents the difference between the two previous 

columns. For example in the fourth row we have 

3.9% - 4.9% = -0.9%. In the same Table, please 

calculate the relative error (consistent with Figure 

1-8). Is this relative error more relevant than the 

“delta”? What is the maximum acceptable relative 

error? 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

22 Please add a table that summarizes the 

technologies captured by the simulation and the 

technologies that are not captured but are 

accounted for via drop-down menus. A third 

(optional) column may include technologies that 

currently are not either simulated, nor recognized 

by drop-down menus but potentially may be 

included in future regulations. 

We have detailed the technologies included 

as inputs to GEM and technology 

improvement inputs (drop-down) in the HD 

Phase 2 NPRM preamble. We welcome 

comment on other technologies that would 

only be considered as part of the innovative 

technology credit program and therefore not 

simulated or recognized by the drop-down 

menu. 

22 Section 

1.4.1.1 

Regarding "As described in Chapter 1.2.2, one of 

the major changes in the HD Phase 2 version of 

GEM is to allow manufacturers to enter their 

transmission gear number versus gear ratio" 

Chapter 1.2.2 does not mention that fact. Please 

check throughout the report to avoid issues with 

these self-references. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

23 1 Regarding the statement "Manufacturers also have 

an option to select the type of transmission, which 

is either manual or automatic" It is not clear if 

transmission type is a required input or an 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 7. Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Reviewer 

Name 

Page Paragraph Reviewer Comment EPA Response to Comment 

optional input. Also, the user should have three 

options (AT, MT, and AMT), not just two. 

23 Table 1-4 Table heading should mention that the results are 

from simulations in GEM, not measurements. Also, 

it is not clear if the 55mph and 65mph cruise contain 

grade. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

23 4 The report mentions that due to lack of data, DCT, 

DCT with TC and Allison TC-10 AT transmissions 

were not validated. That assertion implies that MT, 

AMT and AT were validated. Since transmission 

technologies were not tested at the same level of 

detail as road load reduction technologies, it is 

important to acknowledge the different level of 

validation between transmissions and road-load 

reduction technologies. 

The agencies note the comment but 

determined no revisions are required to

the documentation 

23 Last 

Paragraph 

Regarding DCT and other transmission types not 

included in the model, the report says, "The 

manufacturers still have the options to use 

powertrain dyno tests to quantify the benefits of 

these or any other special transmissions". It is not 

clear if the results of the power train tests are going 

to be used to correct the GEM simulation results or 

are going to replace the GEM simulation results 

altogether. Please clarify. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

24 1 Regarding OEM overriding the axle efficiency 

input, "the inputs would be determined by using 

the prescribed test procedure” It is not clear 

which test procedure is the report referring to. 

Please add a reference to such procedure. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

24 Last Rolling resistance coefficients are usually expressed The text has been corrected (or clarified) 

72
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 7. Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Reviewer 

Name 

Page Paragraph Reviewer Comment EPA Response to Comment 

Paragraph in units of kilograms per metric ton (1 t = 1,000 kg). 

The units used (kg/ton) may imply short ton (1 ton = 

2,000 lbs.). Please correct and be consistent 

throughout the document. 

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

25 1 The "Regional", “Multi-purpose", and "Urban" 

composite duty cycles are not described in the 

document. 

More can be seen in Chapter 3.4.2.3 about 

idle cycle as stated in the same paragraph 

25 3 Please support your statement, "We concluded that 

for the 55 mph and 65 mph duty cycles, GEM's 

interpolation of steady-state data tables was 

sufficiently accurate versus the measured results" 

What was the observed accuracy of using steadystate maps for the 55 and 65mph cruise cycles? 

How much accuracy is sufficient? 

This statement is based on the engineering 

judgment. 

25 3 The 55mph cruise is named "urban highway with 

road grade", the 65mph cruise is named "rural 

highway with road grade, and the ARB transient 

cycle is named "urban local". Please try to use 

consistent names throughout. Also, since the 

cruise cycles in Phase 1 were time-based and did 

not include road grade, the Phase 2 cruise routes 

(distance-based with grade) are not equivalent to 

them and using the same name is misleading. I 

think a distinction can be made by using the term 

"route" for the distance-based tests and "cycle" 

for the time-based, or simply name them "55mph 

cruise with grade" and "65mph cruise with grade". 

The agencies note the comment but 

determined no revisions are required to

the documentation 

29­

30 

Table 1-6 

& 1-7 

Automatic transmissions have the same efficiency 

for all gears (98%), and such efficiency is 

equivalent to that of manual and automated manual 

We chose this based on the comments from 

manufacturers’ input plus our engineering 

judgment. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Reviewer 

Name 

T

Page Paragraph 

able 7. Specifi

Reviewer Comment 

c Observations on Tool Description Entitled, “Vehi

EPA Response to Comment 

cle Simulation Model” 

transmissions in direct drive. Was this advantage 

observed during testing? If possible, please 

document with measured data showing the benefits 

of AT over MT in terms of gearbox efficiency. 

Reviewer 3 1 

Use “dynamometer” and not “dyno” 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD 

Phase 2 NPRM 

Et 

seq. 

Use “Phase 2” and not “Phase II” 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

5 1.2.2.3.1 

Use “watts” or “W” and not “Watts” 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

5 1.2.2.3.1 

“it may o make use” requires clarification 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

7 1.2.2.3.3.7 “With the new gear engaged the clutch is reengaged 

and the engine is again allowed to operate at full 

load.” This statement presupposes that the 

transmission was shifting under full engine load, 

which is not necessarily the case for high power 

engines under benign operating cycles. 

The agencies note the comment but 

determined no revisions are required to

the documentation 

7 1.2.2.3.4 “This includes drive shafts as well as driven and 

passive axles, consisting of a differential, brakes and 

tires.” Passive axles will not ordinarily include a 

differential, only driven axles will. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

8 1.2.2.4 “The vehicle system consists of the chassis, its mass 

and forces associated with aerodynamic drag and 

changes in road grade”. Why “changes in road 

grade”? Any constant road grade (other than zero) 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD 

Phase 2 NPRM 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Reviewer 

Name 

T

Page Paragraph 

able 7. Specifi

Reviewer Comment 

c Observations on Tool Description Entitled, “Vehi

EPA Response to Comment 

cle Simulation Model” 

will have an effect on the apparent vehicle load, and 

not just changes in grade. 

9 1.2.2.4 “computes acceleration [not accelerations] from the 

input force and equivalent mass which is integrated 

to generate vehicle speed and distance traveled” 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD 

Phase 2 NPRM 

9 1.2.3.2 

Use “Matlab” or “MATLAB” and not both. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

10 1.3 

“Validations use all actual vehicle variables 

conducted at Chassis dyno cell,” needs editing. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

11 Ref. 3 is not the SwRI report as stated. It is an 

ASME Technical Paper. 

The Technical Paper is the report 

12 A +-15% variation in aerodynamic drag, for 

example, is unlikely to span the full range of 

expected values in the future for HD vehicles. 

Presumably aerodynamic modifications to Class 8 

vehicles may result in significantly lower drag 

coefficients, or drag products (CdA) 

This was just for the purposes of the tech 

study, these are not GEM limitations 

13 1.3.2 For the Class 8 T700 tests, at high fuel efficiency, 

the GEM model appears to consistently underpredict the actual measured vehicle fuel economy. 

This consistent offset is of concern. The reverse is 

observed for the Class 6 truck tests. 

In the technical research workshop held at 

SwRI in December, 2015, the testing 

variability is discussed in details. It is very 

challenging to validate GEM for those 

highly transient cycles for a heavy truck. 

20 Fig 1-11 

Caption is incorrect. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

21 Fig 1-13 Vertical axis incorrect unit designation. It is NM for torque 

22 Do not use the term “aero drag”. It should be 

“aerodynamic drag”. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Reviewer 

Name 

T

Page Paragraph 

able 7. Specifi

Reviewer Comment 

c Observations on Tool Description Entitled, “Vehi

EPA Response to Comment 

cle Simulation Model” 

Phase 2 NPRM 

22 

“tire radius” should be “tire rolling radius” or 

‘effective radius’. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

Reviewer 4 5 2 The last sentence reads “If a manufacturer uses a 

hybrid powertrain for the power take-off devices, it 

may o make use of ....”. The “o” after may is a typo. 

The text has been corrected (or clarified)

in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM 

3 2 Distance compensation is critical for all vehicle 

simulations – Therefore, this is a good feature that 

has been implemented in GEM-II 

The agencies note the comment but 

determined no revisions are required to

the documentation 

6 4 

Please explain what is included in spin losses, since 

this may not be clear to all OEM users. 

The agencies note the comment but 

determined no revisions are required to

the documentation 

9 3 The GEM-II executable is very appropriate for users 

who are not fluent in the Matlab/Simulink 

environment. Further, the executable prevents users 

from making any changes to GEM-II to support 

compliance. 

The agencies note the comment but

determined no revisions are required to

the documentation 

Reviewer 

Name 

Input 

Table 8. 

Variable 

Specific Observations on Electronic Model Entitled, “GEM Tool” 

Reviewer Comment EPA Response to Comment 

Reviewer 1 No Specific Comments or Observations 

Provided. 

Reviewer 2 File: “GEM_run_postproc.m” Lines: 104 to 

108. Potential issue: It seems to me that the 

equation is not dimensionally correct (I 

might be wrong). Additive terms should 

have the same units and the equation seems 

The equation, while lengthy, is correct. Simplified, 

the equation amounts to grams/hour * hour/mile 

which equates to grams/mile. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 8. Specific Observations on Electronic Model Entitled, “GEM Tool” 

Reviewer 

Name 

Input Variable Reviewer Comment EPA Response to Comment 

to be adding gCO2/h terms with gCO2/mile 

terms. Please check for missing terms 

and/or appropriate use of parenthesis. 

File: “GEM_run_postproc.m” Line: 101. 

The calculation performed for case 4 is 

identical to the calculation performed for 

case 3, making it redundant. Please 

eliminate case 4 (neutral idle with 

start/stop), or correct the equation to 

account for a 90% reduction in neutral idle 

emissions (not drive idle emissions). 

This is correct, for certification neutral idle and 

start/stop will not be credited simultaneously, only 

the start/stop credit is available. This code is from 

the evaluation phase of GEM development. 

“vehicle.chas 

sis. 

frontal_area_ 

m2” 

The name is misleading. Please rename to 

“drag_area”. Drag area is CdA, 

aerodynamic drag coefficient is Cd and 

frontal area is A. 

The model supports separate variables for Cd and 

Area. For certification, we set the Cd to 1.0 and 

apply the Cd*A to the area variable. This does not 

affect simulation results. 

File: “load_GEM_params.m” Lines: 76 to 

85. These equations set weight reduction 

penalties for spark-ignited CNG (525 lbs), 

compression-ignited CNG (900 lbs), and 

compression-ignited LNG (600 lbs). Please 

set a weight reduction penalty for the 

missing case: spark-ignited LNG. 

We are seeking comment on the weight penalties 

associated with natural gas vehicles in the preamble 

to the HD Phase 2 NPRM. We will adjust the 

values accordingly for the final version of GEM, 

based on the comments received. 

File: “load_GEM_params.m” Line: 94. I 

am confused about the variable 

“vehicle.chassis.mass_dynamic_kg” as 

defined here is a constant. However, during 

the simulation (variable: 

datalog.vehicle.dynamic_mass_kg) the 

equivalent mass of the rotational 

components vary depending on the active 

The chassis.dynamic_mass_kg represents the weight 

of the chassis (“static_mass_kg”) plus the effective 

mass of the rotating inertia of the tires/wheels (125 

lbs mass per wheel as consistent with other EPA test 

procedures). The upstream inertias are calculated 

dynamically during model execution, as noted, and 

added to the chassis.dynamic_mass_kg to determine 

the vehicle’s total effective inertia. The datalog 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 8. Specific Observations on Electronic Model Entitled, “GEM Tool” 

Reviewer 

Name 

Input Variable Reviewer Comment EPA Response to Comment 

gear. variable represents the total vehicle inertia during 

simulation, not just the inertia of the chassis. 

File: “load_GEM_params.m” Lines: 117 

and 143. It is not clear what exactly the 

variables 

“transmission.autoshift.cost_map” and 

transmission.autoshift.required_cost_ben 

efit_ratio” represent, and how are they 

used in the model. Other features such as 

“restrict skip shifts”, restrict shift parity”, 

“disable coast saving downshifts” are not 

well documented in the .m files or in the 

report. 

These features are not user inputs but are described 

in a technical paper, SAE 2015-01-1142. 

File: “load_GEM_params.m” L i n e : 131. 

The c a l c u l a t i o n of 

“ Transmission.gear.inertia_kgm2” 

involves a multiplication by 0. Therefore 

it would produce an array of zeroes. Also, 

assuming that the value of 0 is changed 

to a finite constant, it seems that the 

model is assuming the same inertia value 

for all the different gears. Is that 

simplification accurate? 

For the transmission in question, the total inertia is 

represented by the common input and common 

output inertia, the inertias referred to are the “gear 

specific” inertias which for an AMT or MT are set 

to zero since all gears always spin with the input or 

output. Since this is not a user input the default 

value makes little difference for certification 

purposes since all users will use the same value. 

File: “load_GEM_params.m” Line: 134. 

The calculation of 

“transmission.gear.spin_loss_torque_Nm” 

involves a division by a factor of 3.73 for 

all the transmissions that are not 

C78_AMT. I am wondering what that 

factor represents. Also, if that factor is still 

The 3.73 is a scale factor which scales the default 

Class 8 spin losses down to a level comparable to 

the automatic transmission while maintaining the 

same loss trend as the Class 8 AMT with respect to 

speed. The default transmission losses will receive 

additional scrutiny between now and the final rule. 

In addition the peer review does not necessarily 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 8. Specific Observations on Electronic Model Entitled, “GEM Tool” 

Reviewer 

Name 

Input Variable Reviewer Comment EPA Response to Comment 

valid for a potential C78_MT transmission. have specific default values for every transmission 

type by capacity (LD versus HHD, etc). 

Energy Audit. Net system kinetic energy 

change is 0 kJ, which is the result of the 

test cycle starting and ending at 0 mph 

speed. The test cycle seems to start and end 

at the same altitude (symmetric grade 

profile traveled at constant speed), so one 

can expect the net system potential energy 

change to be 0kJ as well. Since both kinetic 

and potential energy are conservative and 

not dissipative forms of energy, I was 

confused about the energy audit accounting 

for energy “consumed” by gradient at about 

17% of the losses for a tractor-trailer. 

Checking the equations, it seems that the 

energy audit is performed only for positive 

tractive loads. If that is the case I am 

confused about the energy consumed by the 

brakes at about 7% of the losses for a 

tractor-trailer. They should be really low if 

one is only considering positive tractive 

loads. The brakes are mostly applied for 

negative tractive loads (e.g. driving 

downhill). Am I missing something here? 

For auditing purposes, the potential energy changes 

are split between “Energy Consumed” (going uphill) 

and “Energy Provided” (going downhill). In the 

case of a driving cycle which starts and ends at the 

same altitude but has some gradient in-between you 

will see equal (within model tolerances) entries in 

both of these audit categories. 

All of the “Energy Consumed” audit values 

represent energy sinks, the brakes are included 

among these since they dissipate kinetic energy. 

In any case, the audit report is for internal use only 

and does not represent a user or certification output. 

Why the weighted average speed For tractor-trailers the idle weight is zero and the 

(weighted_avg_speed_mph) used in post simulation grams/mile are multiplied by target mph 

processing (file: “GEM_run_postproc.m”) and also divided by target mph so what remains is 

is based on the target speed-distance trace simulation grams/mile which will reflect the 

and not in the actual simulated speed- modeled performance (or under-performance) of the 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 8. Specific Observations on Electronic Model Entitled, “GEM Tool” 

Reviewer 

Name 

Input Variable Reviewer Comment EPA Response to Comment 

distance trace? This decision has 

implications for underpowered vehicles 

that deviate substantially from the target 

trace since their actual average speed may 

differ substantially from the target speed. 

This also has implications for the 

calculation of idle fuel rates for vocational 

vehicles since the conversion factor from 

idle fuel rate in [kg/h] to [kg/mile] is the 

weighted average speed. 

vehicle. 

For vocational vehicles the same is true with regard 

to the simulation grams/mile over the drive cycles. 

Idle consumption takes places at zero speed and is 

measured in grams/hour so there is a conversion 

factor required to obtain grams/mile. The target 

weighted average speed represents that conversion 

factor and does not alter the modeled vehicle 

performance (or under-performance) over the drive 

cycles. 

Reviewer 3 

Aerodynamic 

drag 

-- Audit data for 

GEM_Phase2_Idle_55_65_CARB_HHDD 

T_Transient drive cycle – 

“Energy Consumed by Cd” should refer to 

“CdA” and not “Cd” alone. 

True, but the audit report is for internal use only and 

does not represent a user or certification output so 

the shorthand here is of little importance. 

Engine 

Accessories 

Engine Accessories = 846.16 kJ 0.23% 

It seems as though engine accessory loads 

are under-accounted for in this 

implementation of the model – a 0.23% 

loss for a full transient cycle seems 

inappropriately low. 

For peer review, the accessory load is set to 1300 W 

combined mechanical and electric load for all 

vehicle classes. The agencies are seeking comment 

on the predefined values in GEM in the HD Phase 2 

NPRM preamble and will make the necessary 

adjustments for the final version of GEM. 

Usable System Energy Provided = 

373988.49 kJ 

Engine Energy = 309402.35 kJ 

Engine Efficiency = 42.08 % 

The maps provided were mathematically generated 

and do not necessarily represent actual fuel maps. 

In any case this would represent the total efficiency 

over the drive cycle. These audit results are not user 

or certification outputs and will not be available 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Table 8. Specific Observations on Electronic Model Entitled, “GEM Tool” 

Reviewer 

Name 

Input Variable Reviewer Comment EPA Response to Comment 

This integrated “engine efficiency” is high 

for the average efficiency expected across a 

fully transient cycle – does this refer to the 

peak engine efficiency encountered? 

during certification. 

Reviewer 4 Avoid taking the derivative in the Simulink 

models. This can cause instabilities if the 

signal fluctuates rapidly 

Point taken, the use of derivative blocks is 

minimized in GEM. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

E. INDIVIDUAL PEER REVIEWER COMMENTS
 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Peer Reviewer # 1
 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Peer Review Comments on EPA’s Heavy-Duty Greenhouse Gas Emission 

Model (GEM): Phase II and Supporting Documentation 

I. GENERAL IMPRESSIONS 

The purpose of GEM in determining standards, providing a compliance tool, and estimating realworld benefits is clearly articulated. The proposed Phase II GEM tool has evolved substantially 

from the Phase I version, particularly by allowing additional user inputs that are necessary to 

acknowledge fuel efficiency design improvements. As a compliance tool GEM should seek to 

account for all technology advances and differences, yet remain simple to execute and employ 

readily-measured and well-defined input variables. The Phase II GEM model has reached a 

reasonable compromise between these conflicting goals, and this made clear in the narrative. The 

overall architecture is sound, the present component models are appropriate to the task in nearly 

all cases, and they are clearly described. The model yields credible results and credible responses 

to input variable changes. The overall model predicts fuel efficiency to within 5% of 

experimental measurements, and a clear summary of these comparisons is presented. However, 

the material does not address quantitatively the experimental error that is likely in these 

comparisons, and measurement errors associated with rolling resistance and drag are not 

included in the data comparison. Overall agreement with experimental data (as vehicle fuel 

economy) does not validate each component model to the same degree, and this should be 

acknowledged more clearly. As one example, overall fuel economy data are used to compare a 

component model with a fixed efficiency value. The difference overall was only 1.67%, but this 

represented more than a third of the losses for that component. The move to a distance-based 

strategy is justified and well-described, and represents a laudable advance. Addition of several 

transmission models is presented, as are thoughts on the addition of transient adjustment factors. 

Little is said of the “powertrain variant architecture,” although this may prove important for 

integrated powertrains with or without a hybrid component. Transient Adjustment Factors are 

not yet finalized, and transient operation may warrant more than a single correction factor 

approach. 

II. RESPONSE TO CHARGE QUESTIONS 

1. Please comment on EPA’s overall approach to the stated purpose of the model (meet 

agencies’ compliance requirements) and whether the particular attributes found in the 

resulting model embodies that purpose. Were there critical results or issues that were not 

discussed or addressed by the GEM tool or its component sections? 

Throughout his review, except where different fuels are mentioned, fuel efficiency improvement 

and GHG reduction are considered to be synonymous. 

Beyond the need for assurance of compliance is the need to reduce fuel use and climate change 

emissions from heavy-duty vehicles in revenue use. A successful EPA approach must be 

examined from two perspectives. First, it is necessary that the approach yields well-defined, 

unambiguous results to allow a manufacturer to compare against a standard without the process 

being unreasonably onerous. Second, it is necessary that that the vehicle attributes and behaviors 

embodied in the certification process are substantially representative of real world circumstances. 

These two necessities are often in conflict, because the real world scenario is complex, variable, 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

and long in duration, whereas the standard must be concise and precise. The conflict is far 

greater in the heavy duty trucking arena than for light-duty vehicles or rail because truck 

architectures vary widely, and are used in an even wider fashion. 

Employing a model such as GEM to assure compliance provides some relief in the conflict 

described above because the model can be executed for a variety of activities and scenarios 

without excessive cost of time and resources. However, as the model is challenged to predict 

these varied (and emerging) scenarios with fidelity, the model complexity rises. As a result, the 

empirical tables or computational sub-models needed within the model grow in number and 

demand substantial engineering time to prepare and verify. One might argue that “the more one 

models, the more one measures,” recognizing too that precise test protocols must accompany 

each measurement. 

Compromise is necessary between four fundamental needs: 

1) Relevance of the model to real world truck operation. 

Else the real world improvements will not match the changes in standards. 

2) Accuracy of the model in predicting measured fuel efficiency (and GHG production). 

Else confidence in the model will be lost and the compliance will become artificial. 

3) Accuracy of the model in predicting differential effects of technology changes on fuel 

efficiency (and GHG production). 

Else the drivers for technology advancement will be lost 

4) Control complexity and cost of modeling and compliance. 

Else the cost transferred to the consumers will be inappropriate. 

The overall new GEM approach shows awareness of these necessities, and reaches a reasonable 

compromise. However, when some parameters are fixed by the agency, manufacturers may be 

discouraged from pursuing certain development opportunities in the following way. Both future 

fuel pricing and future fuel efficiency standards are unknown. If high fuel prices transcend the 

standards, then manufacturers will pursue every cost-effective tool to reduce fuel use. However, 

if fuel prices are low and are not the driving force, and the GEM approach offers default values 

for factors such as engine transient adjustment factors or transmission efficiencies, some 

opportunities for real world reduction may be left on the table. GEM cannot rely on economic 

drivers to address technology advances that are not modeled. 

GEM is a vehicle-based tool that is geared towards road-load demands rather than enginespecific (“%load” and “%speed”) demands. Only the new distance-based cycles give a nod 

toward engine power. Criteria pollutants are still characterized using a paradigm based on engine 

rated output. Allowing different measurement methodologies for efficiency and criteria pollutant 

production will open a window for separate hardware and software optimization for each test. 

This may demean the benefits of the separate standards to some degree: in-use compliance for 

criteria pollutant measurement will not close this gap because measurement allowance for 

criteria pollutants reduces stringency for criteria pollutants. 

2. Please comment on the appropriateness and completeness of the contents of the overall 

model structure and its individual systems and their component models (i.e., using the 

MATLAB/Simulink version), if applicable, and considering the following: 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

a)	 Elements in each system used to describe different vehicle categories; 

The proposed GEM Phase II model represents a substantial advance over the model used to 

implement the first phase of truck efficiency legislation, and encourages more technology 

advances from manufacturers in consequence. Improvements in truck efficiency are based 

primarily on reductions in aerodynamic drag, tire rolling resistance and engine brake specific 

fuel consumption, and this was recognized in the first GEM model. Practically, there is less to be 

gained from aerodynamic improvements in most vocational truck operation than in long haul 

trucking and the GEM model as presented neglects vocational truck aerodynamics, and the 

modelers are right to exclude aerodynamic parameter entries for low speed trucks. However, the 

overall GEM structure is capable of modeling aerodynamic improvements for niche vocational 

designs, and has the flexibility to extend beyond the present exclusion of the drag coefficient. In 

this way, the capabilities of the model, as received, will be far greater than the executable version 

that is finally used for compliance. 

A major theme in the industry is that efficiency gains are significant from design integration, 

particularly powertrain integration. But it is understood that combined powertrain control is 

proprietary. The supporting language might address this more clearly, noting that the GEM 

model employs just steady-state maps and a defined set of gear ratios, and cannot predict the 

benefits of more sophisticated integration. In a similar fashion GEM cannot predict the benefits 

of learning algorithms, look-ahead strategies and intelligent vehicle systems for the optimization 

of powertrain efficiency on specific routes. These are emerging approaches, but it is 

acknowledged that it would take great effort to configure GEM to deal with these details and it 

would be difficult to assure their generic benefit in revenue service. GEM has some check-a-box 

options proposed for features that cannot be modeled. 

The model, as provided, was oriented to diesel engines. The shift strategies also considered the 

engine torque curve for execution. Naturally aspirated gasoline, boosted gasoline and natural gas 

engines are likely players in the next five years and may warrant separate and careful 

consideration because their characteristics, torque curves and efficiency maps differ substantially 

from the diesel engine properties. 

b)	 Performance of each component model including the reviewer’s assessment of the 

underlying equations and/or physical principles coded into that component; 

MATLAB/Simulink remains an excellent basis for the GEM model. It is well suited for the 

exploratory and development framework, as well as the production of a more limited executable 

model. 

GEM may be viewed on three levels. At the highest level, the MATLAB/Simulink platform 

allows GEM to be anything it chooses, with the addition or alteration of modules and component 

models. At the second level, there is the model provided for review, which has the innate ability 

to deal with a wide range of cycles and truck configurations. At the lowest level will be the final 

executable version, where certain parameters are fixed, and where the duty cycles are chosen for 

determination of compliance. Only the second and lowest levels can be considered in this review. 

This GEM model is being produced at a time where engine control strategy development and 

integrated powertrain controls are advancing rapidly. Also, transmission options are now far 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

wider than in the earlier GEM model, where unsynchronized manual, synchronized manual and 

traditional automatic transmissions dominated the marketplace. GEM is challenged in modeling 

and giving credit for the technology subtleties that will emerge in the marketplace over the next 

five years. 

The use of distance, rather than time, as a basis for the test cycles represents a great and 

important advance. It was widely recognized two decades ago that light duty automobiles were 

capable of far more aggressive performance than was embodied in the FTP-75, although the 

FTP-75 was used as the norm, and still embodied allowances for vehicles that could not follow 

its modest accelerations. In the heavy-duty arena sustained use of full engine power both on 

grades and during acceleration is the norm. All else being equal, a more powerful truck will 

complete its duties in less time than an underpowered vehicle, and often the more powerful 

choice represents the overall economic optimum. However, the more powerful truck will spend 

less time at full power, and will enjoy a reduced average “%load” in revenue service. The 

adoption of the distance-based approach is an important step toward matching the GEM model to 

real-would use. However, as standards are finalized, the accelerations and grades of cycles 

embodied in the GEM execution must represent real life as well. If the grades and acceleration 

values are not appropriately challenging, the distance-based approach will look more like a timebased approach, because underpowered trucks will be able to follow the trace in the minimum 

time allowed. This would divorce the market incentives from the environmental incentives and 

create a false impression of fuel efficiency capability at the expense of economic reality. It is 

important that the grades and test weights used are realistic and representative. Further, the 

indication of the ratio (actual / minimum time for cycle completion) is a very beneficial output 

value. 

A driver’s habits are known to have a measurable impact on truck fuel efficiency. This is in part 

due to gear selection that influences the engine operating envelope, and in part due to transient 

pedal demand (driver PI controller), that may cause an engine to depart from steady-state mode 

to a greater or lesser degree. The GEM load demand controller and GEM gear selection 

algorithms can be configured to reflect different driving habits. If the chosen GEM driver yields 

a better fuel efficiency than would be expected of the national average driver, then GEM will fail 

to grant auto-shifting technology and certain engine control strategies their full potential 

contribution to efficiency gain. It is recommended that this issue is at least explored to provide 

driver sensitivity results to the accompanying document. 

The engine model in the new GEM is still a steady-state map. The documentation acknowledges 

that transient fuel efficiency will differ from steady-state efficiency at the same speed and load in 

time. A transient adjustment factor (TAF) seems likely for the final version, but the use of a 

steady-state map with a TAF does not encourage manufacturers to improve transient fuel 

efficiency if a generic TAF is assigned. This reviewer appreciates that manufacturers are 

unwilling to reveal strategies that represent a substantial fraction of product value, yet they 

cannot take advantage of their improvements in the model without this information. Two 

solutions are possible: 

(i) Determine a manufacturer-specific TAF rather than an agency-specified TAF, or 

(ii) Determine an alternate fuel efficiency map for transient (e.g. Heavy-Duty FTP) 

operation, and use that map or both steady state and transient maps for the transient cycle. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

In addition, TAF will need to be considered carefully for gasoline and natural gas engines, where 

enrichment management has an important effect on fuel efficiency. In a similar way, cylinder 

deactivation strategies may be difficult to characterize for throttled engines, because the 

deactivation strategy is not well represented by a steady-state map. It is important to have a TAF 

strategy that acknowledges successes of manufacturers in lowering transient operation 

disadvantages. 

The EPA developers have sought comment on the issue of axle efficiency. It can be dangerous to 

employ the overall fuel economy computation to compare two approaches to modeling a single 

component, particularly if that component represents a small loss. In one case, the overall fuel 

economy differed by 1.67% when a simplified efficiency was compared with a lookup table for 

rear axle efficiency. This 1.67% represented more than a third of the loss associated with that 

component. To place this in further perspective, the 1.67% can be compared to the 3-5% 

contributions of a major component, such as side skirts on a semi-trailer at freeway speeds. 

Generically, if a component model with higher fidelity is available, in the opinion of this 

reviewer, it is worth including the detail in GEM, even if the component model is fixed in GEM. 

Furthermore, the existence of such a model may provide a clearer pathway for entering 

technology advances by a manufacturer who improves that component in the future. 

The tires in GEM are simply characterized by a rolling resistance coefficient and an effective 

loaded radius. It is known that the coefficient varies with vehicle speed and contact area, while 

longitudinal slip can change the revolutions per mile by a few percent under driving torque and 

braking, which could bias results more substantially when grade is present. This could be coded 

into GEM, but it is probably more appropriate to treat it as a comment, since detailed tire data of 

this kind are not in the public domain and test methods are not universally defined. 

c)	 Input and output structures and how they interact with the model to obtain the expected 

result, i.e., fuel consumption and CO2 over the given driving cycles; 

The accompanying explanatory document emphasizes that the input and output structure has not 

been finalized. A comment, intended as guidance, is that manufacturers will be obliged to use the 

executable version of GEM a large number of times to cover each order or each truck technology 

change over the year. This is needed to compute an average value for compliance. The EPA 

should make every effort to insure that the final version can be interfaced with the 

manufacturers’ software to insure that the process is efficient and reasonably inexpensive, while 

keeping that version of the model locked to insure compliance. 

The .csv output files, viewed in Excel, provide a representation of likely input and output files. 

These summaries are very useful and appropriate. 

d)	 Default values used for the input file, as shown in “Vehicle Simulation Model” document. 

The default values are not particularly important at this stage of development. They are 

sufficiently representative of recent or current technology to provide reasonable inputs and to 

assess the ability to predict real-world values. However, this is an appropriate point to 

acknowledge and discuss the comparison of GEM output with real-world measurements, as 

described in the supporting material. 

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The real-world data serve to verify the ability of GEM to model a variety of trucks. These data 

do not extend to the validation of truck tire rolling resistance or aerodynamic drag value 

selections because the validation was conducted using roller and powertrain dynamometers, 

where these values were entered and were the same values used in GEM. Generally GEM 

matched the measured fuel efficiency values to within 5%, and the deviation may be attributed 

both to measurement error and to the inherent simplifications in modeling. There are some 

systematic errors evident in the comparison. For example, the T700 truck efficiency is 

underpredicted (GEM vs. measured) on the high speed tests and overpredicted on the low speed 

tests. This trend differed for the T270 and F650 trucks. The refuse truck fuel efficiency was 

uniformly overpredicted. This leads to the conclusion that GEM may be capable of predicting 

overall fuel efficiency accurately (at the 5% difference level), but that one should still be 

cautious of comparing the performance of very different technologies using the GEM tool. 

The narrative states that “While it is encouraging that GEM accurately simulates overall vehicle 

performance in an absolute sense, it is actually more important that GEM is accurate in relative 

comparisons.” This is true in the sense that GEM should encourage the best technology pathways 

through comparison, but it is nevertheless the single overall predicted efficiency that is of 

interest to the manufacturer because it predicates compliance. As an example, when the axle 

ratios were adjusted for a vocational truck from the chosen value of 3.76 to high (4.06) and low 

(3.46) values, the predicted transient fuel economy values were 5.55, 5.49 and 5.6 respectively. 

In contrast to this small variation, the fuel economy values for the 65mph operation were 7.14, 

6.88 and 7.37 respectively, attributable to the 9% difference in engine speed between the high 

and low ratios. This reviewer has confidence in these relative values where a variable input is 

changed. However, a comparison between two vehicles with identical chassis and bodies, but 

with different engines, transmission types and tire rolling resistance challenges several parts of 

GEM in a differential sense, and a greater comparative error must be anticipated. One cannot 

argue that the overall agreement with the measured data verifies each sub-model within GEM. 

The use of single variables to represent a more complex reality is discussed elsewhere in this 

review. 

The cycles chosen for evaluating vehicle performance can be changed readily in GEM. Although 

incorporation of grades represents a substantial advance, the current choice of fixed 55mph and 

65mph steady speeds may cause designers to “teach to the test.” [The CBD cycle, used in a 

previous age to quantify transit bus performance, suffered from problems of this kind because all 

steady state operation was at 20mph.] The output data for the tractor (through engine speed / 

vehicle speed ratio) show that the highest gear was used for both fixed speeds. Use of a test cycle 

where speeds varied slowly through the 50 to 70 mph range could avoid pitting real world 

optima against model optima, and would encourage engine downspeeding strategies that are 

successful in revenue service where speed limits are not necessarily 55 and 65mph. 

3. When using the standard of good engineering judgment, is the program execution optimized 

by the chosen methodologies? 

The GEM tool as presented to the reviewers provided a workable compromise between accuracy 

and simplicity. It is evident that GEM may be improved in accuracy by increasing input data, in 

particular the substitution of data tables for single values. However, these tables would need to 

be created for each component at substantial expense. Also, it would be better to use real values 

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or tables or strategies from manufacturers, but each of these might require audit and prescribed 

measurement methods, and in many cases the manufacturer considers them to be proprietary. 

The present GEM is close to being optimized: clearly development is still taking place. 

As a general observation, the engine and transmission receive substantial attention in GEM and 

in much work on truck efficiency improvement. They seem to be of interest at the single 

percentage level. However, tire rolling resistance is a major influence for vocational trucks, and 

drag coefficient controls the dominant loss for freeway tractors. Yet these two components are 

each represented by a single parameter. Beyond just GEM, a more detailed consideration of these 

components (e.g. longitudinal slip of tires, rolling resistance during crosswind correction, effects 

of yaw on drag) would assist in raising modeling accuracy. If that cannot be considered 

expediently for this version of GEM, it should be considered in the future, or even embedded in 

the tables so that it can be applied without altering the code. 

4. Please comment on the clarity, completeness and accuracy of the intended output/results 

(CO2 emissions or fuel efficiency output file). 

The .csv output results are sufficiently comprehensive for the user who is not executing the 

program in MATLAB for research and design purposes. Presumably a report similar to the .csv 

is anticipated as the executable version output. In fact, to the manufacturer, who is executing this 

at time of sale within a larger accounting loop, a very succinct output would be sufficient. 

5. In your opinion, are there any procedures or observations that would have added to the 

quality of the GEM tool? Any recommendations for specific improvements to the functioning 

of the outputs of the model? 

Words of caution may help in presenting GEM to the user and to the public. It is important to 

state that GEM has acceptable accuracy in predicting the fuel efficiency of a specific vehicle 

under specific circumstances. However, it is equally important to state that if GEM is used to 

compare two competing, but very different, technology packages, it may not have the fidelity or 

granularity to evaluate which is better. GEM may not determine the relative difference between 

the two with high fidelity, and that relative difference will depend on the vehicle vocation or test 

cycle used. 

Although modeling test weights were provided for the example vehicles, there was no 

quantitative discussion of choice of test weight for GEM. Test weights receive only brief 

mention in the supporting documentation. It is possible that within vehicle classes, or across 

regions with different topography, engine size may be selected based on the anticipated load. The 

distance based strategy shows an appreciation for this issue, but some compensation with test 

weight for engine size could be considered. Perhaps test weights could be selected so that the 

time to complete the route remains within reasonable bounds for more lightly powered vehicles, 

but at least that highly powered vehicles are acknowledged to be appropriate for some 

occupations, loads or regions. The vocational tractor option in Phase I is not a comprehensive 

solution. 

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III. SPECIFIC OBSERVATIONS
 

Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Page Paragraph Comment or Question 

8 1 Axle lookup table is a better approach 

8 2 “Brakes” Addition of the inertia component to axle is curious/ a 

curious description. This is rather a retarding torque. Perhaps the 

inertia becomes a force if MATLAB is viewed over time steps. I was 

confused by this language. 

10 2 It would be good to see (as well) the equivalent to Figure 1-3 with 

the proposed locked shifting strategies in GEM, rather than actual 

strategies as discussed on p. 10. 

16 2 Need to be cautious about claims in modeling changes. Effect of 

change in Crr is clear, bur GEM may have difficulty with relative 

accuracy in changing transmission type. 

16 2 Note in presenting these agreements that Crr or Cd changes are 

entered as dynamometer A-B-C coefficients, and these are not real 

world measurements. Essentially the dynamometer is partially 

modeling these effects. 

17 Table 1-3 And the figure. Note that the 1.8% error represents a 17% error based 

on the difference, if this figure is intended to show the accuracy of 

predicting differences rather than absolutes. 

18 2 GEM is using automated shifting, essentially, for both MT and AMT, 

and this will be used (with PI control pedal) for impact assessment. 

Yet this paragraph brings human drivers to the fore. Philosophically, 

that the human drivers are the truth and the accuracy of revenue 

service, more than the model or powertrain cell. 

19 Fig 1-9 to 1­

13 

Are these with default or manufacturer’s shift tables? 

22 Table 1-4 Little or no shifting occurs in the 55 and 65 cycles. That should be 

stated. 

23 End of page Text should explain in a little more detail how these powertrain tests 

may be inserted into GEM 

Specific Observations on Electronic Model Entitled, “GEM Tool” 

Input Variable Comment or Question 

No Specific Comments or Observations Provided. 

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Peer Reviewer # 2
 

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Peer Review Comments on EPA’s Heavy-Duty Greenhouse Gas Emission 

Model (GEM): Phase II and Supporting Documentation 

I. GENERAL IMPRESSIONS 

This document summarizes the findings of the review of the US EPA's Heavy-Duty Greenhouse 

Gas Emission Model (Phase 2 GEM) and supporting documentation ("Vehicle 

Simulation Model"). The tool will serve as the principal support for the second round of HeavyDuty GHG emissions regulations, which are under development by NHTSA and EPA. The 

agencies are considering recognizing the efficiency of various vehicle, engine, and transmission 

technologies and they consider critical to develop methods that assess the expected real world 

performance of those technologies. The main purpose of this review is to evaluate how well the 

developed model can serve as a regulatory and compliance tool. The following represent my 

review of the tool and accompanying report based on my experience in modeling heavy-duty 

vehicles with full-vehicle simulation tools, as well as from our assessment at the International 

Council on Clean Transportation (ICCT) of other heavy-duty vehicle regulatory models used 

around the world. 

After reviewing the Matlab/Simulink model and the accompanying report, my general 

impression is that the "Phase 2 GEM" constitutes a valuable development effort by EPA to 

develop a rigorous tool that represents the relative efficiency and emissions of vehicles. The new 

modeling tools’ comprehensiveness, quality and amount of data inputs, and modeling structure 

reflect state-of-the-art modeling techniques and accurately represent relative efficiency 

differences of vehicles in real-world conditions. 

The model architecture is clear and easy to follow and has incorporated some key features that 

will enhance its overall accuracy with respect to real world performance of technologies, and 

will allow the model to capture fuel consumption reductions from a broader range of 

technologies. Overall, the tool offers a rigorous and comprehensive simulation accounting of 

both engine-specific and full-vehicle effects in a manner that is suitable for the regulatory 

compliance purposes as indicated. The model will be capable of performing its intended purpose 

of reflecting technology benefits for compliance purposes of most of the technologies that the 

agencies are considering. 

Some new vehicle modeling features are especially important, namely the ability of the model to 

incorporate user-defined engine fueling maps and driveline parameters, the development of 

different transmission options, the enhanced transmission gear-shifting strategy, the inclusion of 

a distance-based routes with road grade, and the more comprehensive treatment of vocational 

truck technologies. The accompanying testing effort that was undertaken to validate the model is 

impressive and thorough, as capturing the effect of combinations of technologies in such close 

agreement with powertrain and chassis dynamometer testing is a difficult task. The model 

development demonstrates a thorough development process, and also shows a strong 

commitment to transparently presenting the data and methodology that were involved. 

The comments below provide additional details, as well as some suggestions that could also be 

considered by the agencies in the final model development. 

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Although the tool itself offers a suitable modeling platform, the document that describes 

modeling approach could provide further details in a number of areas. It appears as though the 

documentation available for this peer review was at an early draft stage. There is an overall lack 

of detail on key technical features that are new in the model. Interested readers would gain from 

better descriptions of such features, how they were developed, and perhaps, more quantitative 

results in several areas. Also, the quality of the report may be enhanced with more consistent use 

of terminology and a reduction in the number of self-references. Further details regarding areas 

where such documentation and enhanced information would be helpful are described below. 

II. RESPONSE TO CHARGE QUESTIONS 

1. Please comment on EPA’s overall approach to the stated purpose of the model (meet 

agencies’ compliance requirements) and whether the particular attributes found in the 

resulting model embodies that purpose. Were there critical results or issues that were not 

discussed or addressed by the GEM tool or its component sections? 

The proposed Phase 2 standards are predicated on the performance of a broader range of 

technological improvements than Phase 1, including changes to transmissions and better 

integration of engines and transmissions, so a more comprehensive model is required. The model 

in its current form will be capable of performing its intended purpose of reflecting technology 

benefits for compliance purposes of most of the technologies that the agencies are considering. 

The model is enhanced in various aspects with respect to its previous Phase 1 version. Fuel maps 

are one of the most important elements in simulation-based models and the new feature of using 

actual maps and drivetrain parameters would make the results more realistic, allow the model to 

capture the effects of matching engine and driveline, and ideally promote right sizing of the 

engines to application. Different transmission options are included in the model. The shifting 

behavior is now more realistic since is based on both throttle and speed inputs, and includes the 

effects of a clutch friction model. Phase 1 GEM shifting strategy was based only on vehicle 

speed and there was no torque interruption during shifting. Road grade has a major impact on 

fuel consumption and its addition to the tests cycles would also make the results more realistic. 

The treatment of vocational technologies, which were limited to the tires in Phase 1, is 

considerably enhanced. The approach followed by EPA to tackle the diversity of vocational truck 

applications is appropriate. A few drive cycles are simulated (ARB transient, 55 mph and 

65 mph cruise with grade, and a new idle cycle) and weighted differently based on specific 

application. 

EPA’s approach involved a good amount of testing and validation. It must be said that most of 

these validation efforts only covered fuel consumption results from reduced weight, better 

aerodynamics, and better tires. The validation effort for transmission types and enginetransmission-vehicle interaction was less comprehensive. However, based on the results 

presented, Phase 2 GEM model would be accurate enough to support regulation and drive 

technology adoption. 

More broadly, I make one final comment on how the overall modeling approach may meet 

EPA’s overall goals for the regulation, related to the public release of the GEM input and output 

data. The existing and Phase 2 heavy-duty vehicle regulation approach relies on the GEM inputs 

and outputs to determine compliance. The GEM data are analogous to the light-duty vehicle 

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gram/mile1, heavy-duty vehicle gram/brake-horsepower2, and light-duty vehicle mile-pergallon3 compliance values. For the heavy-duty use of the GEM in the greenhouse gas emission 

regulatory program to meet the agency’s own standard, the input and output data from GEM 

would ideally be made publicly available just as the regulatory data for the other regulations for 

each engine and vehicle. For the public to have confidence in the regulatory program that is built 

on a mix of engine- and vehicle-model-specific inputs and modeled GEM outputs, the underlying 

data would be presented in full in downloadable data files (e.g., in Excel) as in other EPA 

regulations. 

References: 

1 EPA http://www.epa.gov/otaq/crttst.htm 

2 EPA http://www.epa.gov/otaq/certdata.htm 

3 EPA http://www.epa.gov/otaq/tcldata.htm, http://www.fueleconomy.gov/feg/download.shtml 

2. Please comment on the appropriateness and completeness of the contents of the overall 

model structure and its individual systems and their component models (i.e., using the 

MATLAB/Simulink version), if applicable, and considering the following: 

a) Elements in each system used to describe different vehicle categories; 

b) Performance of each component model including the reviewer’s assessment of the 

underlying equations and/or physical principles coded into that component; 

c) Input and output structures and how they interact with the model to obtain the expected 

result, i.e., fuel consumption and CO2 over the given driving cycles; 

d) Default values used for the input file, as shown in “Vehicle Simulation Model” document. 

Overall the model structure and its systems are appropriate and, in large part, complete. 

Generally, the performance of each component model and the underlying equations and physical 

principles are valid throughout (see some finer details below). The input and output structures 

interact with the model to obtain the expected result in a way that is sound. The following subsections comment on specific issues regarding model structure, individual systems, as well as 

default values, in no particular order of importance. 

Fixed payloads 

Phase 1 GEM had predefined engines, driveline parameters, and payloads for every category. An 

issue that may arise when using user-defined engine fueling maps in combination with 

predefined payloads is that some simulated vehicles, with lower power-to-weight ratios, will 

show higher deviations from the target speed-distance trace. This affects the simulation results 

since these underpowered vehicles will take more time to complete the assigned route and will 

show a lower average speed. This could lead to underpowered vehicles being improperly 

credited. 

Appropriate matching of engine, transmission gear ratios, axle ratios, and tire radius is only 

going to be promoted if the GEM payloads closely match actual vehicle operation. Right sizing 

of powertrains to application does not seem to be promoted when payloads are predefined for a 

particular vehicle category. In order to recognize engine power matching to vehicle road load, 

payload needs to be a user input rather than a predefined parameter. The regulatory approach and 

modeling would ideally recognize and promote market diversity and identify potential 

discrepancies between actual payloads and GEM payloads. There is an existing trend towards 

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smaller engines, but also some applications require larger engines. On the other hand, if the truck 

manufacturer is allowed to input vehicle-specific payloads, some issues may arise in terms of 

enforceability (How do the regulatory agencies ensure that the vehicles are operated close to the 

payload values at which they were certified?), that may also open the door for the manufacturers 

to report numbers for their own benefit, and adds complexity. 

An option could be to adjust the payload on a few pre-defined bins based on certain parameters 

that are indicative of vehicle road load (e.g. engine displacement, engine power, final drive 

ratio). Under this option, a performance criterion that captures the trace-following capabilities of 

the simulated truck (e.g. a set threshold of percent difference between target speed and simulated 

speed) can be used to force certain engine-vehicle combinations to switch to a lower payload bin 

if they don’t follow the trace according to the specified criterion. Another option would be to 

impose a CO2 penalty based on the ratio of simulated average speed to target average speed. 

Ideally, the allowed deviations from the target trace should be minimized for the simulations to 

be considered valid and allow comparisons between them. 

Drop-down technologies 

The agencies have identified a list of technologies that provide fuel consumption benefits but are 

difficult to simulate accurately. They are developing feature-based drop-down menus that make 

post-simulation adjustments (percent reductions) to the results. It appears that manufacturers 

have not taken much advantage of the Phase 1 advanced technology structure to earn credits so it 

is important to try to include most of the technologies in some way. However, drop-down menus 

inherently assume that all the technology variants within a technology category provide the same 

fuel consumption benefits. Not all the models and brands of a certain technology feature would 

provide the same fuel consumption benefits. There is the risk of giving artificial credits to 

products that perform at a lower level than the value that is selected from the drop- down menu, 

thus rewarding poor performers. Also, technology products with better than average levels of 

performance would not get additional credits, which is a disincentive to make investments in the 

development of such technologies. The default improvement values (percent reductions) 

developed by the agencies were not shared for this peer review but they are of relevance and 

need to be determined with care. Currently, the users have no flexibility to enter their own 

values. Giving the users the flexibility to enter their own values (after testing and with proper 

documentation) could offer a way to reward good performers. 

It seems that applying adjustment factors in terms of percent reductions rather than applying 

predefined credits in units of go2/ton-mile or gal/ton-mile may punish good performers. 

Assuming that truck A emits 90 go2/ton-mile and truck B emits 100 gCO2/ton-mile. If a certain 

technology improvement value is set at 5%, and both trucks use such technology, truck A would 

get 4.5 gCO2/ton-mile credit and truck B would get 5 gCO2/ton-mile credit. This discrepancy of 

incentives can exacerbate if the trucks use more than one drop-down technology and the agencies 

decide that the percent improvements are additive. So it would be good for the agencies to 

support whether and why percentage-based (versus gCO2/ton-mile based) are most appropriate. 

Also the agencies might address, in such drop-down menus whether such technology 

improvements are indeed additive or not. 

Another issue with drop-down technologies is that there is the potential for double counting of 

technology benefits. As an example, an electric coolant pump is listed as a drop-down 

technology. Depending on the engine mapping process, the resultant engine fuel map may 

already capture the benefits from that technology. Running a simulation with such a map, and 

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later improving the results using a drop-down menu will double count the benefits. If EPA could 

respond to how potential double-counting situations are minimal, that would be helpful. 

Driver subsystem 

In vehicle simulation modeling, it would seem that the driver ideally would be excluded entirely 

as a factor that could influence the GEM regulatory compliance results. Using the same driver 

model for all the vehicles seems to be an appropriate choice. However, additional documentation 

is needed for this subsystem. There are no details about how the proportional and integral gains 

of the PI controller have been selected. Are they representative of current drivers? Are they tuned 

to enhance the trace-following capabilities of the model? The look- ahead feature also lacks 

documentation. Is it bringing any advantage to the trace-following capabilities of the model? 

How was the time span value for such feature selected? Ideally EPA would provide some 

consideration and discussion of such factors to provide greater assurance that no anomalies occur 

in compliance results from company-to-company technology strategies as well as tested-versusreal-world results for the relative technology benefits. 

Transmission subsystem 

There are some transmission-related features that are confusing and need to be clarified. The 

report mentions that the different transmission models: manual (MT), automated manual (AMT), 

and torque converter automatic (AT) are built of similar components, but each features a unique 

control algorithm. However, the model seems to use the same "auto shift algorithm" to determine 

the operating gear for any transmission type. The differences in the control algorithm of the three 

different transmissions are not clear and need to be provided. Since transmissions are an 

important new addition for Phase 2 GEM, it is important to let the reader know that the control 

strategy (e.g. shift points) or the selection of predefined transmission parameters (e.g. 

efficiencies and inertias at different gears) are not creating any artificial advantage of one 

technology type over the others. I suggest presenting a comparison of the same simulated truck 

with different transmission types. It is also important to highlight in the report that the new 

transmission controller is based on both speed and throttle position, and differs from the Phase 

1 transmission controller, which was solely based on vehicle speed. The rule-based approach of 

the "auto shift algorithm" would ideally be documented. 

It would be appropriate for the agencies to acknowledge that Phase 2 GEM simulations can 

capture some but not all of the benefits of powertrain integration. The simulation would 

adequately capture engine down speeding since the users have to input specific transmission gear 

ratios, final drive ratio, and tire radius. However, there are many complexities in the control 

strategy when it comes to integrating engine and transmission. Integrated engine-transmission 

powertrain approaches with advanced controls and shifting algorithms that many companies are 

developing could result in significantly more (or less) benefit than the agencies determine as the 

Appropriate default emission-reduction effect. 

As an example, if two different vehicles have the same driveline parameters (tire radius, final 

drive ratio, transmission gear ratios, transmission inertias, and transmission efficiencies) and 

AMT transmissions from different manufacturers, they will obtain the same simulation results in 

GEM but, due to differing control strategies and other design characteristics, they will show 

different fuel consumption benefits in reality. It cannot be expected that all the AMT 

transmissions bring the same fuel consumption benefits. The drop-down menu option won't 

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handle these differences unless there is an option to choose manufacturer-specific transmissions 

or otherwise input such data. 

As a result, there is an opportunity here to leverage the powertrain testing and provide the option 

for manufacturers to better capture the fuel efficiency gains coming from the control strategies 

and other complexities that are not adequately captured in GEM. Another advantage of 

powertrain testing is that the manufacturers would not need to disclose confidential information. 

The results from powertrain testing can then be implemented as correction factors for the GEM 

results. Using correction factors, GEM results could be multiplied by a fixed percent 

improvement obtained by comparing the results of powertrain test and GEM simulations under 

the same torque-speed trace.4 The default benefits for transmission improvements would ideally 

be set to be appropriately conservative (i.e., lowest expected value based on various industry 

results) in GEM. The drop-down menu could still then be offered as a default, for the 

manufacturers that decide not to use the powertrain testing. Then, for the powertrain option, 

companies would ideally be provided clear testing procedures and guidance to demonstrate the 

emission-reduction impact of their advanced powertrain approaches with physical vehicle testing 

in simulated real-world conditions. 

Engine fueling maps 

The inclusion of manufacturer-specific engine maps is a critical feature to reflect company 

differences and detailed engine-specific characteristics that reflect real-world fuel consumption 

and emissions. This is an important addition to GEM, but there is lack of documentation of the 

engine mapping procedure. I imagine that a fairly prescriptive procedure (including number of 

points, preconditioning and warming procedures, fuel properties, etc.) is described somewhere 

else in the larger regulatory development document but this chapter would ideally include a brief 

description of the procedure so the reader knows which engine accessories are included or 

excluded during the engine mapping procedure. 

It is noted that there are many advanced features that may affect fueling but are not captured by 

using a steady-state fuel map. Manufacturers are going away from traditional map-based 

strategies and are going towards model-based controls. Diverse thermal management strategies 

are utilized, and some engines use dual torque curves. Have the agencies considered how to 

handle these technologies? This could have important implications for how tested steady-state 

engine maps, and GEM modeling, and real-world emissions characteristics could differ. As a 

result, we recommend that the agencies discuss such industry approaches in the rulemaking and 

investigate ways to ensure that tested results are aligned with real-world engine and vehicle 

operation the results in fuel consumption and emissions. 

The approach used to quantify the transient correction factor (run GEM with the engine map, 

then use the torque-speed points in the engine dynamometer and compare measured versus 

simulated results) is appropriate. Ideally the transient correction factor may be obtained for each 

individual engine. However, since there is a need for selection of a vehicle in GEM in order to 

get the torque-speed trace. It would become a hard task for the agencies to try and run a transient 

correction factor for each vehicle-engine configuration. For practicality, I recommend 

provisionally using a single correction factor and maintaining the option to refine it over the 

years with additional testing. 

Modeling of idle cycle 

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The idle cycle modeling would gain from increased documentation. Using a gCO2/mile value for 

an idle cycle at first seems counterintuitive (i.e., there are no miles traveled) so a complete 

description of the calculation method would clarify. It would be desirable to present some 

validation results for the idle cycle modeled in GEM compared to experimental results. Some of 

the engine auxiliaries may not be enabled while doing the test, and the map could be 

underestimating actual idle speed fueling rates. There are also engine thermal management 

strategies that are used to keep appropriate after treatment system temperatures. These strategies 

vary from manufacturer to manufacturer and could increase idle fueling substantially. 

The "trace following" issue discussed above also has implications in the calculation of idle cycle 

g/mile value. For this calculation the fuel rate in units of grams per hour [g/h] is converted to 

units of grams per mile [g/mile] using the weighted average speed over the three non-idle cycles. 

The target speed is used for this calculation and not the actual simulated speed, which may 

penalize smaller engines. I suggest EPA to consider if this issue might be significant. 

Trailers 

Although there is a parameter in GEM for trailer tires' rolling resistance, it is not clear how 

trailer aerodynamics is going to be modeled in GEM. Trailer aerodynamics can bring about twothirds of tractor-trailer aerodynamic benefits, so this is a critical area that requires documentation 

and specification of the procedures for the vetting, binning, and including the input data. My 

understanding is that the Coda input parameter is for the tractor only (mid-roof and low roof 

tractors are tested in its bobtail configuration), or for the tractor using a "reference" 53-ft dry van 

trailer (for high-roof tractors coast-down test). Trailer aerodynamic devices can reduce the 

overall tractor-trailer combination aerodynamic drag and ideally the Coda used in simulation 

should represent the combination. It seems that there is no current provision to include the effect 

of trailer aerodynamics as an input in GEM. The report needs to clarify how the GEM model is 

handling trailer parameters (including aerodynamics, tires rolling resistance, and weight 

reduction) and if the model is going to use a predefined "reference" trailer for all the tractors. 

Ideally agencies would give credit to tractor-trailer integrated designs although it would be 

difficult for the agencies to ensure in-use compliance of matching of tractors and trailers. 

Accessories 

There are opportunities for fuel savings from mechanical accessories and electric accessories but 

the agencies decided to keep with the Phase 1 approach of having pre-defined and not 

customizable power from accessories. If these parameters are assigned default values, there are 

no incentives to implement new technologies that could have greater impact. Allowing 

accessories power consumption to be user-defined inputs can be used to promote developments 

in technologies that reduce the power requirements of accessories such as the alternator, airconditioning compressor, power steering pump, or cooling fan. There are other opportunities for 

engine accessories such as oil, coolant, and fuel pumps, but is not clear at this point if all those 

savings are going to be captured by the engine mapping process. 

References:
 4 See Sharpe, Delgado, Muncrief (2015) Comparative assessment of heavy-duty vehicle
 

regulatory design options for U.S. greenhouse gas and efficiency regulation.
 

http://www.theicct.org/us-phase2-hdv- regulation-design-options
 

3. When using the standard of good engineering judgment, is the program execution optimized 

by the chosen methodologies? 

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The chosen methods and execution of the model shows strong engineering judgment throughout. 

A good indication of proper execution is the overall good agreement between the Phase 2 GEM 

simulations and testing data obtained with chassis and power train dynamometers. The errors 

shown are well within +/-5%, which is within the test-to-test variability of chassis dynamometer 

testing. Execution at this level of fidelity meets our own criteria that we have utilized to validate 

tractor-trailer simulation results.5 the validation results show that the balance between model 

accuracy and simplicity is adequate. As a result, the program would be effective to model a 

diverse set of technology changes and be used in regulatory applications. 

References: 

5 See Delgado and Lutsey (2015). Advanced tractor-trailer efficiency technology potential in the 

2020-2030 timeframe http://www.theicct.org/us-tractor-trailer-efficiency-technology 

4. Please comment on the clarity, completeness and accuracy of the intended output/results 

(CO2 emissions or fuel efficiency output file). 

The data reports did not appear to be fully complete, but the accuracy of the output/results 

appears to meet reasonable expectations. The input and output structure of GEM was not 

finalized when released for peer review, however some samples of the output files were provided 

to give the reviewer a flavor of the potential structure. In my opinion, for completeness, the 

output file needs to include results for each different cycle and not only for the weighted 

aggregation of cycles. Some metrics can be added to the output file to facilitate troubleshooting 

and give the user a better perspective. As mentioned before, actual simulated speeds and a 

measure of deviation from the speed-distance trace would ideally also be provided for 

transparency of the results. Based on the validation results, accuracy with respect to measured 

data was provided and seems to be within 5%, which is acceptable output accuracy based on 

comparable modeling as well as real-world testing. 

5. In your opinion, are there any procedures or observations that would have added to the 

quality of the GEM tool? Any recommendations for specific improvements to the functioning 

of the outputs of the model? 

Phase 2 GEM could generate two different output reports. One that only includes the most 

relevant information on an aggregated format and is used only for compliance purposes, and a 

second one, that is very detailed and includes results disaggregated by cycle and other relevant 

information that may help the users to troubleshoot their results, learn the inner workings of the 

model and potentially suggests enhancements to it. I suggest including a summary of the energy 

audit in the output. Also, provide the average engine efficiency over the cycle for the different 

test cycles, as well as the ratio of average engine efficiency to maximum engine efficiency, 

which is an indication of how well the transmission parameters are matched to keep the engine 

operating near its peak efficiency range. 

The output file provides some basic “sanity checks” such as number of shifts, ratio of number of 

shifts to number of gears in the transmission, distance traveled, and ratio of actual time to target 

time. Please also provide ranges of valid or acceptable values for these parameters so the user 

can be aware of any potential issues with the simulation. 

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A further step that could allow the tool to be much more useful would be to allow users to input
 

their own cycles as is currently done with VECTO6 (Vehicle Energy Consumption calculation 

Tool) model in Europe. The VECTO tool has a “declaration mode” for compliance, and an 

“engineering mode” which offers the ability to edit inputs and allow users to explore what the 

tool can do. This would be critical for transparency and follow the best practice as seen in the
 

Europe situation. It would also be highly useful for individuals in the heavy-duty vehicle supply
 

chain to explore the variation of the results with respect to real-world duty cycle factors.
 

Especially considering the very diverse use of heavy-duty vehicles in local, regional, and longdistance conditions, this capability would allow dealers and fleet managers to gauge how fuel
 

consumptions for particular relevant driving patterns differs from the cycle. This would help 

ensure the technologies that are more suited to particular duty cycles are being selected in the 

market place, and it would also help overcome the prevailing market barrier, whereby 

knowledge, data, and confidence on truck efficiency has been limited.7
 

References:
 6 See Luz et al (2014)
 

http://ec.europa.eu/clima/policies/transport/vehicles/heavy/docs/final_report_co2_hdv_en.pdf

7 See Roeth et al (2015) http://www.theicct.org/hdv-technology-market-barriers-north-america
 

III. SPECIFIC OBSERVATIONS 

Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Page Paragraph Comment or Question 

2 2 The list of key technical features may include the fact that the new 

model uses distance-based cycles instead of time-based cycles, 

and the fact that test cycles now include road grade. 

2 2 The claim "more stable engine idle speed controller" is not discussed 

in the text. Some metric or quantification of what is meant by "more 

stable" needs to be provided. 

2 3 Regarding “substantial effort has been put forth to accurately track 

and audit power flows through the model to ensure conservation of 

energy" The report lack details about the energy audit. Was the 

energy audit developed just for internal quality control or is it going 

to be provided to the end users in an output file? 

3 1 Regarding "the road gradient has been modified to accept a road 

grade that varies as a function of distance traveled" Please 

introduce the concept of distance-based versus any pros/cons of 

the new method and why did you change the approach. 

3 2 Driver subsystem. This section (1.2.2.2) is not clear to the reader and, 

in my opinion, needs rewriting. There are various confusing 

statements such as "the feed forward calculations using drive cycle 

accelerations and vehicle mass have been removed". The section also 

mentions (page 4, paragraph 1) that a ratio of speeds (which is nondimensional) is integrated to produce the current cycle position 

(which has units of distance), which is dimensionally incorrect. I 

recommend showing the equations to avoid confusing the reader. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Page Paragraph Comment or Question 

Regarding the statement "the addition of distance compensation 

allows all simulated vehicles to complete an equivalent trip such as 

traveling from point A to point B" Does that mean that without 

distance compensation the vehicles would not complete the trip? 

3 2 How were the proportional and integral constants of the PI 

controller estimated? Is the same driver subsystem used 

independently of transmission choice? How was the look-ahead 

feed-forward control implemented? 

4 2 Consider removing the mention to the "variant power train 

architecture" since it is not mentioned anywhere else in the report. 

5 1 Please clarify that the engine map is not a pre-determined 

parameter as in Phase 1 GEM, but a user-defined input. 

5 3 For consistency with previous section, please show the proposed 

constant power loss magnitude of electric subsystem. 

5 4 Please change "four different variants” for "three different variants” 

(MT, AMT, AT). 

11 There is an apparent incongruence in Page 5, paragraph 4, which 

mentions that each transmission "features a unique control 

algorithm matching behaviors observed during vehicle testing" 

however, in Page 5, paragraph 5 it is mentioned that "all of the 

transmission models use an auto shift algorithm to determine the 

operating gear over the cycle". Are the auto shift algorithm 

parameters changed based on transmission type? Is there really a 

unique control algorithm for each transmission type? 

5 5 The "auto shifting optimizer" needs proper documentation. How 

does it work? 

6 1 The clutch model is a key new addition and lacks proper 

documentation. 

Please support claims such as "realistic actuation durations and 

more accurate physics of torque conservation and lockup 

behavior" with data. 

6 2 Please clarify what you mean by “This layout is more similar to a 

manual transmission, but the application for a planetary gearbox 

is a reasonable approximation as this type of gearbox can utilize a 

variety of topologies" i s confusing to me. 

8 2 The statement "The brake model also adds a rotational inertia 

component to the axle" is misleading since the inertia of brakes is 

set to zero in GEM. 

9 2 Please provide a table with a complete list of pre-defined and 

user-defined parameters. There is no need for specific values, just 

the list of parameters. 

12 1 Description of test condition number 6 reads, "Run a new set of 

road load coefficients to represent a vehicle configuration 

optimized for fuel efficiency for each vehicle that was tested." 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Page Paragraph Comment or Question 

To be consistent with the other test conditions described please 

quantify the reductions in rolling resistance, aerodynamic drag, and 

mass for this particular "optimized package" case. 

13 Figure 1-3 to 

1-6 

In the legend, it is not clear if the 55mph and 65 mph tests 

contain grade or not. Also, the "utility" cycle is not described in 

the text. 

15 Figure 1-6 Although is mentioned in the text, it seems that the refuse truck 

was not tested under the refuse cycle. Also, it seems that it was 

not tested under different test conditions as the remaining 

vehicles. Any reason for this? Please explain. 

16 1 Change "numerically" for "numerical.” 

18 2 The statement "In some cases, it is hard to quantify which method, 

vehicle simulation or chassis dynamometer test, is more accurate" 

is very misleading. The chassis dynamometer test although 

imperfect, is a measurement and it was treated as a "true" value 

in the validation process (Figures 1-3, 1-5, and 1-6). Accuracy can 

only be measured in reference to a true value. The chassis 

dynamometer test was selected as such and the model cannot 

hope to have better accuracy than the test. 

18 3 In the statement "GEM is capable of capturing the impact on the 

total vehicle CO2 emissions and fuel consumption due to any 

technology improvement" the word "any" is misleading since the 

validation effort was only done over aerodynamic, rolling 

resistance and mass parameters. Moreover, there is certainly a set 

of technologies that GEM is incapable of model. 

17 Table 1-3 Correct the numbers on the "Delta" column. Due to rounding it is 

not evident that the column represents the difference between the 

two previous columns. For example in the fourth row we have 

3.9% - 4.9% = -0.9%. In the same Table, please calculate the 

relative error (consistent with Figure 1-8). Is this relative error 

more relevant than the “delta”? What is the maximum acceptable 

relative error? 

22 Please add a table that summarizes the technologies captured by 

the simulation and the technologies that are not captured but are 

accounted for via drop-down menus. A third (optional) column 

may include technologies that currently are not either simulated, 

nor recognized by drop-down menus but potentially may be 

included in future regulations. 

22 Section 

1.4.1.1 

Regarding "As described in Chapter 1.2.2, one of the major 

changes in the HD Phase 2 version of GEM is to allow 

manufacturers to enter their transmission gear number versus gear 

ratio" Chapter 1.2.2 does not mention that fact. Please check 

throughout the report to avoid issues with these self-references. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Page Paragraph Comment or Question 

23 1 Regarding the statement "Manufacturers also have an option to 

select the type of transmission, which is either manual or 

automatic" It is not clear if transmission type is a required input 

or an optional input. Also, the user should have three options 

(AT, MT, and AMT), not just two. 

23 Table 1-4 Table heading should mention that the results are from simulations in 

GEM, not measurements. Also, it is not clear if the 55mph and 

65mph cruise contain grade. 

23 4 The report mentions that due to lack of data, DCT, DCT with TC and 

Allison TC-10 AT transmissions were not validated. That assertion 

implies that MT, AMT and AT were validated. Since transmission 

technologies were not tested at the same level of detail as road load 

reduction technologies, it is important to acknowledge the different 

level of validation between transmissions and road-load reduction 

technologies. 

23 Last 

Paragraph 

Regarding DCT and other transmission types not included in the 

model, the report says, "The manufacturers still have the options to 

use powertrain dyno tests to quantify the benefits of these or any 

other special transmissions". It is not clear if the results of the power 

train tests are going to be used to correct the GEM simulation results 

or are going to replace the GEM simulation results altogether. Please 

clarify. 

24 1 Regarding OEM overriding the axle efficiency input, "the inputs 

would be determined by using the prescribed test procedure” It is 

not clear which test procedure is the report referring to. Please 

add a reference to such procedure. 

24 Last 

Paragraph 

Rolling resistance coefficients are usually expressed in units of 

kilograms per metric ton (1 t = 1,000 kg). The units used (kg/ton) 

may imply short ton (1 ton = 2,000 lbs.). Please correct and be 

consistent throughout the document. 

25 1 The "Regional", “Multi-purpose", and "Urban" composite duty 

cycles are not described in the document. 

25 3 Please support your statement, "We concluded that for the 55 mph 

and 65 mph duty cycles, GEM's interpolation of steady-state data 

tables was sufficiently accurate versus the measured results" What 

was the observed accuracy of using steady-state maps for the 55 

and 65mph cruise cycles? How much accuracy is sufficient? 

25 3 The 55mph cruise is named "urban highway with road grade", the 

65mph cruise is named "rural highway with road grade, and the 

ARB transient cycle is named "urban local". Please try to use 

consistent names throughout. Also, since the cruise cycles in 

Phase 1 were time-based and did not include road grade, the 

Phase 2 cruise routes (distance-based with grade) are not 

equivalent to them and using the same name is misleading. I think a 

distinction can be made by using the term "route" for the 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Page Paragraph Comment or Question 

distance-based tests and "cycle" for the time-based, or simply 

name them "55mph cruise with grade" and "65mph cruise with 

grade". 

29-30 Table 1-6 & 

1-7 

Automatic transmissions have the same efficiency for all gears 

(98%), and such efficiency is equivalent to that of manual and 

automated manual transmissions in direct drive. Was this 

advantage observed during testing? If possible, please document 

with measured data showing the benefits of AT over MT in terms 

of gearbox efficiency. 

Specific Observations on Electronic Model Entitled, “GEM Tool” 

Input Variable Comment or Question 

File: “GEM_run_postproc.m” Lines: 104 to 108. Potential 

issue: It seems to me that the equation is not dimensionally 

correct (I might be wrong). Additive terms should have the 

same units and the equation seems to be adding gCO2/h 

terms with gCO2/mile terms. Please check for missing 

terms and/or appropriate use of parenthesis. 

File: “GEM_run_postproc.m” Line: 101. The calculation 

performed for case 4 is identical to the calculation 

performed for case 3, making it redundant. Please 

eliminate case 4 (neutral idle with start/stop), or correct the 

equation to account for a 90% reduction in neutral idle 

emissions (not drive idle emissions). 

“vehicle.chassis.frontal 

_area_m2” 

The name is misleading. Please rename to “drag area”. 

Drag area is Coda, aerodynamic drag coefficient is Cd and 

frontal area is A. 

File: “load_GEM_params.m” Lines: 76 to 85. These 

equations set weight reduction penalties for spark-ignited 

CNG (525 lbs.), compression-ignited CNG (900 lbs.), and 

compression-ignited LNG (600 lbs.). Please set a weight 

reduction penalty for the missing case: spark-ignited LNG. 

File: “load_GEM_params.m” Line: 94. I am confused 

about the variable “vehicle.chassis.mass_dynamic_kg” as 

defined here is a constant. However, during the simulation 

(variable: datalog.vehicle.dynamic_mass_kg) the 

equivalent mass of the rotational components vary 

depending on the active gear. 

File: “load_GEM_params.m” Lines: 117 and 143. It is 

not clear what exactly the variables 

“transmission.autoshift.cost_map” and 

transmission.autoshift.required_cost_benefit_ratio” 

represent, and how are they used in the model. Other 

features such as “restrict skip shifts”, restrict shift 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Specific Observations on Electronic Model Entitled, “GEM Tool” 

Input Variable Comment or Question 

parity”, “disable coast saving downshifts” are not well 

documented in the .m files or in the report. 

File: “load_GEM_params.m” L i n e : 131. The 

c a l c u l a t i o n of “ Transmission.gear.inertia_kgm2” 

involves a multiplication by 0. Therefore it would 

produce an array of zeroes. Also, assuming that the 

value of 0 is changed to a finite constant, it seems that 

the model is assuming the same inertia value for all the 

different gears. Is that simplification accurate? 

File: “load_GEM_params.m” Line: 134. The calculation 

of “transmission.gear.spin_loss_torque_Nm” involves a 

division by a factor of 3.73 for all the transmissions that 

are not C78_AMT. I am wondering what that factor 

represents. Also, if that factor is still valid for a potential 

C78_MT transmission. 

Energy Audit. Net system kinetic energy change is 0 kJ, 

which is the result of the test cycle starting and ending at 0 

mph speed. The test cycle seems to start and end at the 

same altitude (symmetric grade profile traveled at constant 

speed), so one can expect the net system potential energy 

change to be 0kJ as well. Since both kinetic and potential 

energy are conservative and not dissipative forms of 

energy, I was confused about the energy audit accounting 

for energy “consumed” by gradient at about 17% of the 

losses for a tractor-trailer. Checking the equations, it 

seems that the energy audit is performed only for positive 

tractive loads. If that is the case I am confused about the 

energy consumed by the brakes at about 7% of the losses 

for a tractor-trailer. They should be really low if one is 

only considering positive tractive loads. The brakes are 

mostly applied for negative tractive loads (e.g. driving 

downhill). Am I missing something here? 

Why the weighted average speed 

(weighted_avg_speed_mph) used in post processing (file: 

“GEM_run_postproc.m”) is based on the target speeddistance trace and not in the actual simulated speeddistance trace? This decision has implications for 

underpowered vehicles that deviate substantially from the 

target trace since their actual average speed may differ 

substantially from the target speed. This also has 

implications for the calculation of idle fuel rates for 

vocational vehicles since the conversion factor from idle 

fuel rate in [kg/h] to [kg/mile] is the weighted average 

speed. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Peer Reviewer # 3
 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Peer Review Comments on EPA’s Heavy-Duty Greenhouse Gas Emission 

Model (GEM): Phase II and Supporting Documentation 

I. GENERAL IMPRESSIONS 

The EPA Heavy-Duty Greenhouse Gas Emission Model (GEM) Phase 2 documentation 

accurately represents the structure, format, logic and algorithmic description of the model as 

presented. The supporting documentation is for the most part, clear and self-explanatory. The 

results produced by the GEM model appear to be sound, although each set of results is presented 

as integrated fuel efficiency and carbon dioxide emissions results. As such the results present a 

single-valued, integrated snap-shot of the model prediction, and the time-based instantaneous 

fuel efficiency and carbon dioxide emissions predictions are not available for review. The overall 

dynamic performance of the model prediction is thus difficult to judge in the greater context of 

what is usually fully transient vehicle operation. Furthermore, in the version reviewed, the ability 

to vary input parameters and vehicle and drivetrain attributes is limited to modifying input files 

and not through a graphical user interface as described in the review instructions. 

II. RESPONSE TO CHARGE QUESTIONS 

1. Please comment on EPA’s overall approach to the stated purpose of the model (meet 

agencies’ compliance requirements) and whether the particular attributes found in the 

resulting model embodies that purpose. Were there critical results or issues that were not 

discussed or addressed by the GEM tool or its component sections? 

The model appears to meet the stated purpose for which it was intended, which is the prediction 

of integrated cycle-based vehicle fuel efficiency and carbon dioxide emissions for vehicles with 

preselected physical and drivetrain attributes. While this was the subject of some detailed 

explanation in the model documentation, the assumption of quasi-steady engine fueling and its 

extension to fully transient engine operation is not without complexity in the assessment of its 

validity. A further, acknowledged inadequacy of the model in its current form is the limited 

ability of the user to modify specific vehicle attributes, and component values and efficiencies. 

2. Please comment on the appropriateness and completeness of the contents of the overall 

model structure and its individual systems and their component models (i.e., using the 

MATLAB/Simulink version), if applicable, and considering the following: 

a)	 Elements in each system used to describe different vehicle categories; 

The elements in each of the systems (engine, transmission, axle, vehicle attributes etc.) seem 

appropriate and complete. The specific selection of the engines and transmissions chosen will 

cover a large portion of the current heavy-duty vehicle fleet, although of course any specific, 

single selection of powertrain hardware or powertrain hardware attributes necessarily limits the 

range of vehicles that can be simulated with that same selection. 

b)	 Performance of each component model including the reviewer’s assessment of the 

underlying equations and/or physical principles coded into that component; 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

One concern with the structure and form of the model is that a steady-state engine fueling map is 

used in each case to simulate transient engine operation and hence dynamic vehicle operation. 

This is in addition to the simulation of operation under nominally steady vehicle speeds or cruise 

operation. In the case of nominally steady operation, the use of a steady-state fueling map is 

well-justified, but the quasi-steady assumption required to allow the extension of the use of such 

a map to transient operation requires additional justification. Heavy duty compression ignition 

engines have high rotational inertias (due to the relatively high mass components required to 

survive the high combustion pressures), high mechanical friction (due to high effective 

compression ratios) and relatively slow air and exhaust transfer processes (due to the excess air 

flowrates accompanying their lean, un-throttled operation). In addition they have relatively high 

thermal mass due to their large physical mass required to withstand the stresses and strains 

resulting from high combustion pressures. All of these features conspire to result in deleterious 

combustion effects under highly transient engine operation. In most cases the end effect of these 

phenomena is to reduce the engine brake thermal efficiency under transient modes, beyond that 

which would be expected under steady or quasi-steady fueling operation. In most cases the 

additional fuel that is required to undertake a specific engine transient torque trajectory, beyond 

that estimated using a quasi-steady fueling assumption, would typically be less than 10% of the 

total integrated fueling, but in most cases the effect on integrated fuel efficiency over transient 

duty cycles is non-negligible. 

In general, incorporating an additional component into the full accounting of the vehicle load by 

over-accounting for the actual total rotational inertia (in the form of an effective or “added” mass 

or inertia) of the drivetrain and driveline system does allow for the quasi-steady assumption to 

hold. However in general a quasi-steady, forward-looking simulation such as is used in this 

model, tends to under-predict the actual vehicle energy usage under transient duty cycle 

operation. I notice that this issue is addressed in Chapter 1.4.1.8 Transient Adjustment Factor, 

but the designation of a single correction factor for a specific engine or powertrain configuration 

is likely to be unsuitable in some cases, and has the potential to cause prediction inconsistencies. 

Note further that the required correction factor might not be uniquely engine-specific, but might 

vary for the same engine in different vehicle and powertrain configurations. 

c)	 Input and output structures and how they interact with the model to obtain the expected 

result, i.e., fuel consumption and CO2 over the given driving cycles; 

A further concern that is not discussed in the documentation is whether any model fitting 

parameters were employed to obtain the fits observed, between the GEM-derived fuel efficiency 

and CO2 emissions values and the dynamometer-measured results. In other words, beyond the 

parameters described and the accompanying constants used in the dynamic force and energy 

equations, were any other fitting techniques (or fitting parameters) used to obtain the observed 

correlations between the simulated cycle-averaged results and the SwRi chassis dynamometer 

results? Presumably there were dynamometer parameters and coefficients fitted using vehicle 

coast-down data (and dynamometer operational parameters), but beyond these, are there any 

other fitting parameters used to obtain the correlations shown? Discrepancies between simulated 

and measured results of less than 2-3% are probably not significant, except in the presence of a 

consistent bias between the measured and predicted, for any one vehicle, cycle or technology 

considered. 

d)	 Default values used for the input file, as shown in “Vehicle Simulation Model” document. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

The default values as defined in the “Vehicle Simulation Model” are reasonable and currently 

fall within the ranges of expected vehicle values. It is not clear however under what 

circumstances the user will be able or allowed to make modifications in the final model 

implementation. For instance, it is conceivable that the interplay between future auxiliary 

mechanical or electrical loads on an engine might be significantly modified through conversion 

of mechanical auxiliaries to electrical or electronic devices. In that case, that will shift the 

relative balance in those loads. Moreover it is not clear that engine cooling fan loads have been 

adequately accounted for in the model, as these are typically not considered in the engine 

dynamometer testing from which engine fueling maps are normally derived. This exclusion 

alone can modify observed fueling rates by 10% or more under specific engine operating 

conditions. 

Other default values including transmission gear ratios, transmission efficiencies, axle 

efficiencies, tire rolling resistance, and vehicle aerodynamic drag product seem reasonable. 

3. When using the standard of good engineering judgment, is the program execution optimized 

by the chosen methodologies? 

This issue is difficult to address through the level of observation afforded to the reviewer at this 

stage of development of the model. It is not obvious that the program execution is optimized, but 

the results, computational time and outputs displayed indicate that the chosen methodologies are 

suitable for this purpose. 

4. Please comment on the clarity, completeness and accuracy of the intended output/results 

(CO2 emissions or fuel efficiency output file). 

The model outputs and results seem clear, complete and accurate. One caveat with interpreting or 

using the freight efficiency or load efficiency-based results lies in the use, further interpretation 

or extension of these results. Users might be tempted to “scale” the load-based results in an 

inappropriate fashion – for example, if the returned result for the computed carbon dioxide 

emissions is 100 gCO2ptm (grams CO2 per ton-mile) for say a 30 ton vehicle over a specific 

cycle, there might be the temptation on the part of users to employ that same numerical result to 

predict the CO2 emissions for the same vehicle loaded to 40 tons over the same cycle. However 

this assumption is not correct, as the vehicle fuel consumption is a function not just of load or 

weight-related terms (rolling resistance, grade, acceleration etc.) but also terms that are invariant 

with load or weight (such as aerodynamic drag), and this is not reflected in an emissions per tonmile result. 

5. In your opinion, are there any procedures or observations that would have added to the 

quality of the GEM tool? Any recommendations for specific improvements to the functioning 

of the outputs of the model? 

The version reviewed here does not include the graphical user interface (with “pull-down 

menus”) described in the instructions. The ability to modify input parameters and vehicle 

attributes will improve the user experience, while obviously presumably not impacting the model 

outputs. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Due care and attention should be paid to the number of significant digits presented in the output 

results. For example, in the results presented from a single specific simulation (shown below): 

>> GEM_Phase2_Idle_55_65_CARB_HHDDT_Transient 

Distance = 32.414 mi 

Fuel Consumption = 5.4059 gallons 

Fuel Consumption = 17184.1217 grams 

Fuel Economy = 5.996 mpg 

Fuel Consumption = 530.140 g/mile 

CO2 Emission = 1697.77 g/mile 

The number of significant digits in the model simulation outputs presented above (some of which 

are directly related through derivation or calculation) varies from 4 to 9. This does not meet 

recommended practices in the presentation of results and data. Moreover, industry experience in 

the measurement of real-world fuel efficiency during over the road truck testing dictates that 

measured fuel consumption variations of less than 1-2% should not be considered significant or 

compelling, and this level of variation could correspond to variations in the 2nd or 3rd significant 

figures in fuel consumption in most cases. 

III. SPECIFIC OBSERVATIONS 

Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Page Paragraph Comment or Question 

1 Use “dynamometer” and not “dyno” 

Et seq. Use “Phase 2” and not “Phase II” 

5 1.2.2.3.1 Use “watts” or “W” and not “Watts” 

5 1.2.2.3.1 “it may o make use” requires clarification 

7 1.2.2.3.3.7 “With the new gear engaged the clutch is reengaged and the engine is 

again allowed to operate at full load.” This statement presupposes that 

the transmission was shifting under full engine load, which is not 

necessarily the case for high power engines under benign operating 

cycles. 

7 1.2.2.3.4 “This includes drive shafts as well as driven and passive axles, 

consisting of a differential, brakes and tires.” Passive axles will not 

ordinarily include a differential, only driven axles will. 

8 1.2.2.4 “The vehicle system consists of the chassis, its mass and forces 

associated with aerodynamic drag and changes in road grade”. Why 

“changes in road grade”? Any constant road grade (other than zero) will 

have an effect on the apparent vehicle load, and not just changes in 

grade. 

9 1.2.2.4 “computes acceleration [not accelerations] from the input force and 

equivalent mass which is integrated to generate vehicle speed and 

distance traveled” 

9 1.2.3.2 Use “Matlab” or “MATLAB” and not both. 

10 1.3 “Validations use all actual vehicle variables conducted at Chassis dyno 

cell,” needs editing. 

11 Ref. 3 is not the SwRI report as stated. It is an ASME Technical 

Paper. 

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Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Page Paragraph Comment or Question 

12 A +-15% variation in aerodynamic drag, for example, is unlikely to 

span the full range of expected values in the future for HD vehicles. 

Presumably aerodynamic modifications to Class 8 vehicles may 

result in significantly lower drag coefficients, or drag products (CdA) 

13 1.3.2 For the Class 8 T700 tests, at high fuel efficiency, the GEM model 

appears to consistently under-predict the actual measured vehicle fuel 

economy. This consistent offset is of concern. The reverse is 

observed for the Class 6 truck tests. 

20 Fig 1-11 Caption is incorrect. 

21 Fig 1-13 Vertical axis incorrect unit designation. 

22 Do not use the term “aero drag”. It should be “aerodynamic drag”. 

22 “tire radius” should be “tire rolling radius” or ‘effective radius’. 

23 “Lack of testing data for other types of transmission, GEM would not be 

able to be validated in time against those three cases” requires editing. 

Specific Observations on Electronic Model Entitled, “GEM Tool” 

Input Variable Comment or Question 

-- Audit data for 

GEM_Phase2_Idle_55_65_CARB_HHDDT_Transient drive 

cycle -­

Aerodynamic 

drag 

“Energy Consumed by Cd” should refer to “CdA” and not “Cd” 

alone. 

Engine 

Accessories Engine Accessories = 846.16 kJ 0.23% 

It seems as though engine accessory loads are under-accounted 

for in this implementation of the model – a 0.23% loss for a full 

transient cycle seems inappropriately low. 

Usable System Energy Provided = 373988.49 kJ 

Engine Energy = 309402.35 kJ 

Engine Efficiency = 42.08 % 

This integrated “engine efficiency” is high for the average 

efficiency expected across a fully transient cycle – does this refer 

to the peak engine efficiency encountered? 

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Peer Reviewer # 4
 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

Peer Review Comments on EPA’s Heavy-Duty Greenhouse Gas Emission 

Model (GEM): Phase II and Supporting Documentation 

I. GENERAL IMPRESSIONS 

Accuracy of information: 

The document provided, “Vehicle Simulation Model” provides a good background on GEM-II, 

its differences from GEM-I, and the Phase I certification process. Section 1.2, “Model Code 

Description” describes the model components and sub-components, in adequate detail for the 

user to understand the depth and breadth of GEM-II. No underlying equations are provided. The 

section on Model validation is an important section for GEM-II. The extent of the validation and 

the comparisons with dynamometer testing is impressive. This gives the reader additional 

confidence in the results produced by GEM-II. The validation process is well documented, 

concluding with the graph that summarizes all the 130 vehicle validations performed. The 

validation also includes graphs of component performance (engine speed, engine fuel rate, and 

transmission gear number) as a function of time 

The document does not explain the variable target.veh_sytyle. The structure format used for the 

user input data is useful in collecting all user-provided data. 

A final conclusions section is missing in the document provided. 

II. RESPONSE TO CHARGE QUESTIONS 

1. Please comment on EPA’s overall approach to the stated purpose of the model (meet 

agencies’ compliance requirements) and whether the particular attributes found in the 

resulting model embodies that purpose. Were there critical results or issues that were not 

discussed or addressed by the GEM tool or its component sections? 

EPA’s overall approach to meet the agency’s compliance requirements consists of making a 

validated simulation model (GEM –II) available to OEMs so that they can check the compliance 

of their vehicles against the agency’s guidelines. The extensive validation of GEM – II against 

dynamometer testing of the actual vehicle shows a good correlation between simulation and 

hardware to within ±5%. Most validations are well within ±3%. This provides the user with a 

high level of confidence that the physics has been correctly implemented and there are no 

unresolved “bugs” in GEM-II. 

Further, an additional level of confidence is achieved, with select validation from four 

representative vehicle classes, namely: Class 8 Kenworth T700 truck, the Class 6 Ford F650 tow 

truck, the Class 6 box truck, and the New Flyer Refuse truck. There is a very good correlation 

between GEM-II predicted engine speeds and transmission gear shifting versus the same on the 

actual vehicle. 

Recommendation: It is recommended that representative vehicles from each of the classes be 

modeled in GEM-II and validation results presented similar to 1.3.1 of the GEM-II Manual. It is 

the understanding of the reviewer, based on the provided manual that the following trucks were 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

tested on a vehicle chassis: Class 6 Kenworth T270, Class 6 Ford F650, Class 8 Kenworth T700, 

Class 8 Cascadia Line Haul truck, and Class 8 New Flyer refuse truck.
 

Issues/Results that were not addressed by GEM-II:
 

During this review, the following unaddressed issues were identified for GEM-II:
 

•	 GEM-II includes several PID controllers within its overall structure. For example, the 

engine idle speed controller of the engine is implemented as a PID with three gains. The 

unaddressed issue in this regard is stability feedback to the user caused by unrealistic 

hunting for the idle speed. What safe-guards are in place within GEM to inform the user 

of clutch chattering since GEM does not model second order inertial effects caused 

during clutch engagement. 

•	 It is possible for the vehicle not to meet the driving cycle as a result of excessive grade or 

weight or other issues with the transmission/engine. The unaddressed issue in this regard 

is a feedback alert to the user during the time instances when the vehicle is significantly 

slowed down and does not meet the desired driving cycle. The output file does not alert 

the user on the number of time instances when vehicle tracking was compromised. 

•	 GEM-II does not address thermal characteristics of the engine cooling system or the heat 

rejection of the transmission fluids. These thermal issues affect the operational duty-cycle 

of the engine fan, which will affect the fuel economy. At present, GEM-II models the 

parasitic loads as a constant average number. 

Recommendation: Allow the user the ability to introduce an engine load dependent 

mechanical accessory curve which is more realistic than a constant average number. A 

simple heat model may be used to capture the effect of thermal characteristics of the 

multiple radiators in a typical MD and HD engine. 

•	 Although GEM-II does not model tire slip/lockup during a hard deceleration, the effect of 

ignoring this on fuel economy is negligible. 

•	 The validation results included kinematic comparisons (speeds, gear number) between 

GEM-II and the actual vehicle on a chassis dynamometer. While, the kinematic 

comparisons look very favorable, the dynamic comparisons (engine load and engine 

fueling) are missing in the results section of GEM-II. 

•	 The transmission shift strategy can affect fuel economy and emissions. GEM-II allows 

the user to preselect different transmission types (manual, automatic or automatedmanual). However, it was not clear how to modify the GEM-II default shift strategy with 

an OEM proprietary shift strategy. 

•	 Although GEM-II results have been extensively validated against dynamometer test data 

in a controlled lab environment, it is unclear how well GEM-II will compare against real 

world road testing, especially with temperature fluctuations. For example, the lack of a 

thermal model in the engine model may cause GEM-II results to deviate from on-theroad test data, where the engine fan is cycled on and off based on thermal loads on the 

engine. Each time, the engine fan turns on, fuel economy is affected. 

2. Please comment on the appropriateness and completeness of the contents of the overall 

model structure and its individual systems and their component models (i.e., using the 

MATLAB/Simulink version), if applicable, and considering the following: 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

The three main powertrain components that can affect fuel economy and greenhouse gas 

emissions in a vehicle are: engine fuel map, transmission type and efficiency map, and vehicle 

aerodynamic improvements (including tire rolling friction improvements and weight reduction 

technologies). In this regard, GEM-II addresses all the aforementioned components by providing 

steady state maps for each powertrain component, which an informed user can change to 

represent specific technology improvements. GEM-II comes with certain standard transmission 

models, namely: manual, automatic, and automated manual transmissions. The user would select 

the appropriate transmission and GEM-II would automatically select the user-specified 

transmission. 

Recommendation: It is recommended that additional instructions are provided if the user wants 

to change the engine map. Ideally, this would be done from a user specified spreadsheet in a 

GEM-II compatible format, since the user may not be fluent in Matlab. In this regard, a clear 

explanation of all the variables used in GEM-II would also help significantly. For example, it 

was not clear how to change the transmission shift schedule if an OEM chose to do so. Further, 

since GEM-II is modular with hierarchical layout of component layers, it is challenging for an 

OEM user to insert a technology improvement deep within one layer and not affect the layers 

above or the execution of GEM-II. It is not clear, from this initial review, how a technology 

improvement such as a proprietary transmission shift schedule can be evaluated in terms of gains 

in fuel economy and greenhouse gases. This comment applies to other technology improvements 

as well, such as partial engine cylinder deactivation (power on demand) or electrification of 

certain mechanical accessories. 

a) Elements in each system used to describe different vehicle categories; 

The vehicle categories that GEM-II addresses range from Class 2B to Class 8 HD conventional 

vehicle powertrains. This is achieved by four root-level systems in GEM-II at the root level, 

namely: the ambient, driver, vehicle, and powertrain modules. Each of the aforementioned 

modules consists of several sub-modules organized in a hierarchical manner. Each root-level 

module outputs a data bus that is muxed into a single data bus. The aforementioned four main 

systems of GEM-II correspond to the four main components of a HD vehicle, namely: driver, 

ambient conditions, vehicle chassis and powertrain modules. This one-to-one correspondence 

between the root-level GEM-II models and an actual HD vehicle makes for an easily 

understandable structure. Further, the modular organization of the GEM-II contributes to easier 

debugging and isolation of a numerical problem during simulation. 

The powertrain module is the most populated module in GEM-II. It contains the engine, 

transmission and driveline sub-modules and accessories (mechanical and electrical). The flow of 

data information corresponds to an actual vehicle powertrain, with the engine output driving the 

transmission, which in turn drives the driveline components. 

The modular layout of GEM-II, its correspondence with a real conventional vehicle is therefore 

appropriate and complete for the reasons stated above. The modular structure and the 

hierarchical arrangement of modules to mimic a real vehicle system makes the integration of 

additional modules and capabilities easier to implement. The signals are clearly marked and 

follow a logical naming convention that facilitates the addition of additional modules and 

capabilities into GEM-II. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

b)	 Performance of each component model including the reviewer’s assessment of the 

underlying equations and/or physical principles coded into that component; 

GEM-II follows the model of a single wheel with a concentrated mass at the center of the wheel. 

The physics coded into the modules are based on Newton’s second of motion for this 

concentrated mass. At the time of this review, no other dynamic equations were found in GEMII, except in the clutch and torque converter. The engine, accessory, transmission and driveline 

components are characterized by steady state maps. The equivalent mass of rotating inertia 

components are also correctly included in the vehicle module of GEM-II. Rotating inertias are 

correctly reflected downstream to the tire. The inertia is converted to a virtual mass which is 

added to the entire vehicle mass. The wide validation of GEM-II against real vehicle data 

indicates that the physics has been correctly implemented in GEM-II. 

c)	 Input and output structures and how they interact with the model to obtain the expected 

result, i.e., fuel consumption and CO2 over the given driving cycles; 

Input for GEM-II: 

A structure format is used to store the inputs to create the input data for the execution of GEM-II. 

The structure format is organized as follows: component.variable.units. For example, the input 

variable “engine.idle_fuel_map_speed_radps” identifies the engine speed vector of the engine 

idle fuel map expressed in rad per sec. Similarly, the input variable 

“transmission.clutch.input_inertia_kgm2 refers to the clutch inertia of the transmission, 

expressed in kgm2. This format follows good coding standards, making the inputs easy to pair to 

the appropriate component it refers to, the particular variable name, and the units used. Further, a 

modular approach is used to store the input data for each component in separate easily identified 

files in the “param_files” folder. 

Output for GEM-II: 

When the workspace has been populated with the input data, the simulation model “REVS_VM 

vehicle model is executed over the user-selected drive cycle. Each major component model 

(GEM_CVM, vehicle, driver, ambient) has a bus_out output port which contains a structure of 

component output data, which is used within other components. In addition, GEM-II uses a 

datalog structure to store simulation output data for later post processing to calculate emissions 

and fuel economy. All the simulation output is stored in a single datalog structure with multiple 

fields, each describing the component that the data pertains to. For example, 

datalog.vehicle.speed_mps refers to data log from the vehicle component of the variable vehicle 

speed in m/s. This format is an accepted coding standard within other vehicle simulation 

packages (such as PSAT from ANL, RAPTOR from SwRI) as well, making the output easy to 

pair to the appropriate component it refers to, the particular variable name, and the units used. 

Similarly, all variables that are used to perform an energy balance are prefixed by “audit”. 

Interaction with the model to obtain the expected results: 

The bus_out structure from the various components are stored in “goto” blocks which are paired 

with “from” blocks to distribute data from one block to another. The use of paired “goto” and 

“from” blocks is an accepted method of decluttering the simulation model and avoiding 

crisscrossing signal lines, thereby significantly facilitating the understanding of information flow 

from one component to another. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

d)	 Default values used for the input file, as shown in “Vehicle Simulation Model” document. 

The default data used in GEM-II is complete and appropriate to execute a simulation of HD 

vehicle powertrain over one of the drive cycles available in the GEM-II default drive cycle 

library. The default ambient conditions summarized in ambient_param.m are appropriate. The 

default driver parameters, summarized in driver_param.m, contain driver gains as well as the 

time that the driver can look ahead in the drive cycle. The driver gains represent an average 

driver, which the user can change to emulate an aggressive driving pattern versus a calmer 

driver. 

The default engine maps of 270 kW, 345 kW, and 455 kW power ratings includes inertia, idle 

speed. Default transmission maps for the manual, automatic, auto-manual are also available. 

Default tire radius, axle ratios, rolling resistance of the tires of the steering axles and drive axles 

are also included. 

3. When using the standard of good engineering judgment, is the program execution optimized 

by the chosen methodologies? 

Overall, GEM-II uses industry accepted coding practices throughout the software modules. The 

following is a partial list of these accepted practices: 

•	 Valid variable naming structure used – 

•	 Data bus used for each component – 

•	 Modular components with no signals crossing – 

•	 Useful comments to assist the user with following the code – 

•	 Energy audit adds to the confidence level of the results of the simulation. 

•	 File name that is executed is echoed back to the user. If there is a simulation abort, the 

debug is easier 

•	 Data that is being loaded is echoed back to the user so the user knows what data is being 

used. 

•	 Component modules are linked to libraries. A change in the library module propagates to 

all vehicle models during execution. 

At this point in the review, I do not have adequate data to comment on the execution 

optimization of GEM-II. Linear interpolation modules from the standard Simulink library are 

used within GEM-II, thereby optimizing execution. If there are any non-standard user defined 

functions used within the GEM-II simulation model, the execution can be made considerably 

faster through the use of s-functions within Simulink. At the time of this review, no S-function 

were found in the model. 

4. Please comment on the clarity, completeness and accuracy of the intended output/results 

(CO2 emissions or fuel efficiency output file). 

The output data from a simulation execution is summarized in a spreadsheet, which is date and 

time stamped, allowing the user to verify that the output data corresponds to the simulation 

executed. The output data contains data on which technology improvement ( weight reduction, 

vehicle speed limiter, single drive axle, par time single drive axle, low friction axle lubrication, 

predictive cruise control, high efficiency AC compressor, electrified engine cooling pump, 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

extended engine idle reduction, automatic tire inflation )was assessed, engine, transmission type, 

fuel economy and CO2 emissions. 

The output data, summarized above, serves the original purpose of GEM-II, which is to enable 

users to demonstrate compliance with regulatory standards either without any modifications to 

the HD vehicle, or analyze the fuel economy and CO2 emissions, when one or more technology 

improvements are employed. However, information on the drive cycle is missing or not clearly 

identified. In addition, key plots of vehicle tracking the drive cycle, engine operating speedtorque points over the drive cycle, engine efficiency contour plots, transmission operating points, 

and other plots that assist OEMS to further fine tune the powertrain and improve fuel economy/ 

CO2 emissions in case of non-compliance. It would be desirable to have the results of the energy 

audit summarized in the output file. The date stamp column is appropriate for the user to cross 

check simulation runs. 

5. In your opinion, are there any procedures or observations that would have added to the 

quality of the GEM tool? Any recommendations for specific improvements to the functioning 

of the outputs of the model? 

The following modules will enhance GEM-II: 

•	 A module that is able to create the input data for a GEM-II execution from a user 

provided spreadsheet with pre-defined tabs for the engine, transmission, drive cycle, 

vehicle parameters, and technology improvement. Users are more familiar with 

spreadsheets than the Matlab environment. 

•	 A GUI module that guides the user to create a HD vehicle model. 

•	 A module that allows users to select plots of key component performance. These plots 

may be summarized in the output spreadsheet data file. 

•	 A more detailed explanation of all the user provided data “target.X” and the various 

choices available for each of the user provided data. For example, what are the choices 

that the user has for the variable target.veh_style ? 

•	 GEM-II execution takes place within the Simulink environment. During execution, no 

feedback is provided to the user on the status of the simulation. The user is waiting on a 

blank screen – Percent complete of the simulation and which drive cycle is being 

executed would be useful feedback for the user. 

•	 Predefined sample input data for all class of vehicles to assist users to easily modify them 

if necessary, since some users may not be familiar with Matlab. 

•	 The ability to turn on the feed forward term for the driver model in case of tracking 

problems in drive cycles with grade. 

•	 The ability to model accessory power draw as a function of engine speed and engine 

temperature. The engine cooling fan power cycle will affect fuel economy and CO2 

emissions. 

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External Peer Review of EPA’s Heavy-Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation 

III. SPECIFIC OBSERVATIONS
 

Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 

Page Paragraph Comment or Question 

5 2 The last sentence reads “If a manufacturer uses a hybrid powertrain 

for the power take-off devices, it may o make use of ....”. The “o” 

after may is a typo 

3 2 Distance compensation is critical for all vehicle simulations – 

Therefore, this is a good feature that has been implemented in GEMII 

6 4 Please explain what is included in spin losses, since this may not be 

clear to all OEM users. 

9 3 The GEM-II executable is very appropriate for users who are not 

fluent in the Matlab/Simulink environment. Further, the executable 

prevents users from making any changes to GEM-II to support 

compliance. 

Specific Observations on Electronic Model Entitled, “GEM Tool” 

Input Variable Comment or Question 

NA NA Avoid taking the derivative in the Simulink models. This can cause 

instabilities if the signal fluctuates rapidly. 

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