Research Progress on CO₂ Emission Simulation for Heavy-Duty Commercial Vehicles

Abstract

Carbon emissions are currently a hot topic in the international community. CO₂ reduction from heavy-duty commercial vehicles plays a significant role in slowing down the global greenhouse effect and promoting sustainable development. To control carbon emissions, many countries have tightened CO₂ emission regulations and policy requirements for heavy-duty commercial vehicles in recent years. Various CO₂ emission simulation models have been developed, such as the Greenhouse Gas Emissions Model (GEM) in the United States and the Vehicle Energy Consumption Calculation Tool (VECTO) in the European Union, to evaluate the real CO₂ emission levels of commercial vehicles and provide a scientific basis for formulating corresponding emission reduction policies and control measures. This paper systematically analyzes the CO₂ emission regulations and policy requirements for heavy-duty commercial vehicles in the United States, the European Union, China, and other developed countries. It also analyzes the GEM software in the United States, the VECTO software used in Europe, and the energy consumption simulation software for commercial vehicles in China. The influencing factors of CO₂ emission simulation are explored in detail. This study found that, although GEM and VECTO software are recognized for their high accuracy, their applications are still dependent on local policies. In other countries and regions, VECTO software has broader applicability. On the other hand, China’s commercial vehicle energy consumption simulation software and other reported studies have only been validated for specific vehicle types. The accuracy and generalizability of these models should be further promoted and verified.

1. Introduction

With the development of the global economy and the increase in human activities, greenhouse gas emissions have become a major issue impacting the sustainable development of humanity. Since 1850, the rising total emissions of greenhouse gases caused by human activities have contributed significantly to the intensification of climate change on the planet [1]. In particular, in 2019, human society emitted a staggering 59 billion tons of greenhouse gases into the atmosphere [2], the highest amount on record. Although the growth rate of global greenhouse gas (GHG) emissions has slowed in recent years, overall emissions continue to rise.

Among all sources of GHG emissions, the transportation sector plays a crucial role, becoming one of the largest contributors to both greenhouse gas and air pollutant emissions worldwide. Emissions from the transportation sector account for 15% of global GHG emissions, and this proportion is growing [3]. Specifically, CO₂ emissions from heavy-duty vehicles (HDVs) represent a significant share of emissions within the transportation sector [4]. To effectively control carbon emissions from HDVs, it is essential to deeply understand and analyze the methods for simulating CO₂ emissions from these vehicles. These methods not only help assess the actual emission levels of HDVs but also provide a scientific foundation for formulating appropriate emission reduction policies and technical measures. Therefore, this paper aims to provide an overview of CO₂ emission simulation methods for heavy-duty commercial vehicles to advance research in this field.

This paper is a Brief Report focusing on the preliminary results of a review of CO₂ emission simulation methods for heavy-duty vehicles. The study provides initial insights into their application and highlights areas for further development. This paper first reviews the current status and trends of CO₂ emissions from HDVs. globally, along with the relevant legal and regulatory requirements in various countries. It then focuses on CO₂ emission simulation methods for HDVs, providing a comprehensive analysis of the advantages and disadvantages of different methods. The paper also summarizes existing research and offers recommendations for further studies. A thorough understanding of CO₂ emission simulation methods for HDVs could help reduce their impact on climate change and contribute to building a more environmentally friendly and sustainable transportation system.

2. Legal and Regulatory Requirements for CO₂ Emissions from HDVs

Globally, CO₂ emissions from HDVs are a growing concern, and many countries have enacted laws and regulations to control and reduce their emission levels. These regulations aim to mitigate greenhouse gas emissions and address environmental challenges such as climate change and air pollution. Understanding the legal and regulatory requirements for CO₂ emissions from HDVs in different countries is crucial for promoting emission reduction measures and encouraging technological innovation.

The sales of commercial vehicles in recent years in the European Union, the United States, and China are shown in Figure 1, which illustrates that the annual sales in these countries and regions have remained relatively stable [5,6]. Although heavy commercial vehicles are moving towards electrification, due to factors such as power capacity and operational requirements, relevant research predicts that, for the foreseeable future, internal combustion engines will remain the primary power source for heavy commercial vehicles [7]. The internal combustion engine, as a more mature technology in the industry, still has significant potential for energy savings through the integration of electrification and intelligent technologies [8].

2.1. Requirements of Relevant U.S. Laws and Regulations

In the United States, CO₂ emissions from human activities account for 79.7% of total GHG emissions, making them the largest contributor to greenhouse gases. These emissions primarily stem from the combustion of fossil fuels in transportation and power generation, with transportation alone contributing over 37% [9]. Although the overall trend of CO₂ emissions from transportation in the U.S. has been declining in recent years, the share of transportation-related emissions in the total CO₂ emissions is still increasing each year [10], as shown in Figure 2.

To control CO₂ emissions from HDVs, the U.S. Environmental Protection Agency (EPA) first issued Phase I GHG emissions regulations in August 2011 and later updated them to Phase III, which continues to tighten carbon emission requirements for HDVs. The EPA recently updated its heavy-duty commercial vehicle emission standards for the 2027 model year. The final regulation imposes stricter requirements on new HDVs, including revised testing processes, regulatory lifetimes, and emission-related warranties, while also modifying key provisions of existing heavy-duty emission controls. The regulation does not restrict the technological pathways for enterprises to meet emissions standards. These include gradually increasing the proportion of zero-emission vehicles such as plug-in hybrids, pure electric vehicles, and other new energy vehicles; improving internal combustion engine efficiency; reducing drag; and using low-carbon fuels. Additionally, it incentivizes the long-term development of new energy vehicles by introducing a new energy accounting factor and increasing the weight of this factor in the calculation of average enterprise emissions [11].

On 29 March 2024, the U.S. Environmental Protection Agency announced the final national GHG pollution standards for HDVs (e.g., freight trucks and buses) for the 2027–2032 model years—Heavy-Duty Vehicle Greenhouse Gas Emission Standards; Phase 3. These standards represent the most stringent GHG regulations ever set for HDVs in the U.S. The new standards require manufacturers to deploy more efficient vehicles starting in model year 2027 for specialty HDVs (e.g., delivery trucks, garbage trucks, utility trucks, buses, shuttles, school buses, etc.) and tractor-trailers. This includes the use of more efficient internal combustion engines and electric driveline systems, bringing the U.S. closer to achieving its domestic and international climate goals. Compared to the previous phase, the emission requirements for each vehicle type will increase by 25% to 60% by 2032, with an overall increase of about 40% [12], as shown in Figure 3.

2.2. European Union Requirements

In the European Union, HDVs accounted for 30% of CO₂ emissions from road transport, despite heavy-duty commercial vehicle ownership representing only 4% of the total vehicle fleet [13]. The EU has regulated CO₂ emissions from rigid trucks and tractor-trailers since 2018, with the regulation extended to buses and other HDV categories in 2022 [14].

On 8 May 2024, the European Parliament and the European Council published the official Euro 7 regulation (EU 2024/1257), which established new emission and battery durability standards for motor vehicles, engines, and related vehicle systems [15]. These new standards replace the existing Euro 6 emission standards for passenger cars and vans (Regulation (EC) 715/2007) and Euro VI emission standards for heavy goods vehicles and buses (Regulation (EC) 595/2009) [16].

On 13 May 2024, the European Council approved the revised CO₂ standards for HDVs, marking the final step in the legislative process. The revised standards maintain the target of a 15% reduction in CO₂ emissions by 2025, raise the reduction target to 45% by 2030, and introduce targets of a 65% reduction by 2035 and a 90% reduction by 2040, as shown in Figure 4. With these updates, the EUs CO₂ standards have become some of the most aggressive and stringent GHG regulations in the global HDV sector [17].

The EU Emissions Trading System (EU ETS) is the cornerstone of the EUs climate change policy and a key tool for cost-effective greenhouse gas reduction. The EU ETS caps CO₂ emissions from industries and creates a market for carbon allowances. The heavy vehicle transport sector is also included in the system and is required to purchase and use emission allowances, known as carbon permits [18]. In addition, the European Union has implemented a new energy incentive mechanism similar to that of the United States. This mechanism increases the accounting factor for zero-emission and low-emission vehicles, gradually adjusting these factors over time to ensure a smooth transition to zero emissions in the transport sector [19].

2.3. Relevant Requirements in China

Since the end of the 20th century, the total CO₂ emissions from China’s transportation sector have continued to rise, and its share of China’s overall CO₂ emissions has grown steadily [20], as shown in Figure 5. In 2019, heavy-duty trucks accounted for 39.7% of CO₂ emissions from the transportation sector, with diesel vehicles representing about 52.5% of these emissions. Heavy-duty trucks are a major source of CO₂ emissions from vehicles in China and need to be controlled [21].

China has been controlling emissions from heavy-duty diesel vehicles since 2001 [22], issuing emission standards for HDVs ranging from Stage I to Stage VI. Currently, the “Limits and Measurement Methods for Emissions from Diesel-Fueled Heavy-Duty Vehicles (China VI)” are in effect, which regulates pollutant emissions from HDVs [23]. The latest standard, GB 30510-2024 “Fuel Consumption Limits for Heavy-Duty Commercial Vehicles”, issued by the National Automobile Standardization Technical Committee in September 2024, will replace GB 30510-2018 in 2025. This new standard tightens fuel consumption limits for various models and adds a reference value for CO₂ emissions based on the current fuel consumption levels of vehicle models and their energy-saving potential. Overall, the fuel consumption limits for the new standard models have been tightened by 12% to 16% compared to the previous version [24,25]. The standard applies to commercial vehicles powered by gasoline or diesel with a maximum design gross mass greater than 3500 kg, including trucks, semi-trailers, buses, dump trucks, and city buses. It specifies emission limits for each model. According to Ge Zihao [26], in real-world operations, the CO₂ emissions of National VI heavy-duty diesel vehicles were about 10% higher than those of National V heavy-duty diesel vehicles, suggesting that China needs to address CO₂ emission limits more effectively in future standards.

The standard GB/T 27840-2021 “Measurement Methods of Fuel Consumption for Heavy-Duty Commercial Vehicles”, outlines the methods for measuring fuel consumption in heavy-duty commercial vehicles [27]. The chassis dynamometer method must be used to determine fuel consumption for basic vehicles, while either the chassis dynamometer method or a simulation method can be used for variant vehicles, depending on the manufacturer’s choice. The standard specifies the measurement conditions for the chassis dynamometer method, test procedures, and data processing methods. It also provides detailed descriptions of the simulation calculation method and process.

2.4. Other Countries

Japan’s Ministry of Land, Infrastructure, and Transport finalized new fuel economy standards for new on-road HDVs in 2019. The Phase 2 regulation applies to model-year 2025 diesel commercial vehicles with a gross vehicle weight of 3.5 tons or more, as well as buses capable of transporting 10 or more passengers [28]. The standards establish CO₂ emission regulations for vehicles of different tonnages, measured in kilometers per liter (km/L). However, the emission requirements for tractor-trailers in Japan have been increased by only about 1% per year from the 2002 baseline. This rate of increase is relatively low compared to requirements in other countries and regions [29].

In 2020, the Korean government introduced a CO₂ monitoring regulation, requiring HDV manufacturers to submit CO₂ emissions data for HDVs sold in Korea between 2021 and 2022 [30]. The purpose of this regulation is to establish a CO₂ emissions baseline for high-intensity transportation in the country. Following this, the Korean government set a voluntary CO₂ reduction period from 2023 to 2025, with reduction targets of 2% in 2023, 4.5% in 2024, and 7.5% in 2025. During this voluntary emissions reduction period, manufacturers who exceed their CO₂ reduction targets will earn credits, while no penalties will be imposed on those who fail to meet the targets. A mandatory emissions reduction policy is expected to be implemented starting in 2026.

In summary, developed countries and regions, such as the United States and the European Union, began addressing HDV carbon emissions earlier than developing countries due to their earlier industrialization and more stable HDV ownership. As a result, they have established a series of policies and regulations aimed at limiting carbon emissions. In contrast, the HDV population in China and other developing countries is still growing rapidly, and carbon emissions from HDVs have not yet received enough attention. Therefore, relevant policies and regulations in these countries need to be improved to effectively control CO₂ emissions from HDVs.

3. CO₂ Emission Simulation Methods for Heavy Commercial Vehicles

3.1. VECTO Software

VECTO software is a tool developed by the European Union for calculating vehicle energy consumption and CO₂ emissions [31]. It models the components of an HDV and simulates CO₂ emissions based on a specified driving cycle. The purpose of VECTO is to provide a standardized method for calculating the fuel consumption and corresponding CO₂ emissions of HDVs in Europe. It is currently used in the EU to calculate and manage carbon emissions from heavy commercial vehicles [19,32]. Özener et al. [33] validated the VECTO model by comparing its simulated results with real driving fuel consumption and CO₂ emissions data from Istanbul. The results showed that the difference between the simulated and actual test results was between 1% and 5%. Broekaert et al. [34] developed a simplified model using VECTO to simulate heavy-duty buses and analyzed energy use and CO₂ emissions for different mission profiles. The results showed that the model accurately captured the general trend of CO₂ emissions, with a model standard deviation of less than 0.4%. Georgios et al. [35] validated the accuracy of VECTO using a 40-ton Euro 6 long-haul truck and an 18-ton Euro 5 rigid truck. The simulation results closely matched those from the dynamometer tests, with the final simulated fuel consumption deviating by about ±2–4% from the measured values. Other researchers have also validated the accuracy of VECTO and conducted in-depth studies of HDV emissions in Ireland using the software [36,37].

VECTO includes both certification and development modes of operation. Both modes calculate vehicle fuel consumption and CO₂ emissions based on input files containing user-defined vehicle parameters and output the related result files simultaneously.

3.1.1. Calculation Logic

VECTO simulates the reverse power transmission chain: the vehicle’s speed in the driving cycle is used as the actual value to calculate the corresponding power demand. This includes the changes in speed and torque from the vehicle body through the tires, gearbox, transmission, and engine output shaft, while also accounting for the additional power loss from relevant accessories, as shown in Figure 6.

3.1.2. VECTO User Input File

The main user interface of VECTO displays the folder path for the entire project, buttons for running calculations, and editing channels for project-related parameter files. Whether in certification mode or development mode, the input files typically required for project calculations include Vehicle, Engine, Gearbox, Auxiliaries, and Cycles. VECTOs vehicle interface is shown in Figure 7.

• Vehicle parameters

The general parameters required include vehicle category (HDV Group; this is only needed in certification mode), vehicle mass, load, air resistance, tire dynamic radius, engine idle speed, drive shaft, and tire-related parameters, among others.

2.

Engine parameters file

Users need to enter parameters such as engine model, idling speed, engine displacement, rated speed, rated power, maximum torque, fuel type, engine inertia (with flywheel), and other relevant details. Additionally, users must provide the engine’s full-load characteristic curve and the reverse drag characteristic curve, which define the engine’s speed and torque boundaries. The engine’s universal performance characteristics map is used to calculate fuel consumption, with values obtained through linear interpolation for the corresponding operating conditions. The influence of relevant correction factors should also be considered when calculating the vehicle’s total fuel consumption.

3.

Gearbox Parameter File

The gearbox parameter file defines all parameters related to the gearbox, such as gear ratios, transmission torque loss map, and more. When adding gear parameters, users must input the corresponding gear ratio, transmission efficiency, or transmission torque loss map. In development mode, for manual gearboxes, parameters such as moment of inertia (common to all gears) and gear shift intervals can also be input. These parameters are used to calculate the vehicle’s total fuel consumption by interpolating the corresponding conditions.

3.1.3. Driving Cycle for Simulation

In the certification mode of the VECTO software, once the user sets the vehicle category, the software automatically generates the corresponding test cycle, which cannot be modified by the user. However, in development mode, the user can select from the test cycles provided by the software to calculate CO₂ emissions and fuel consumption. Additionally, the user can load their own custom-defined test cycle into the model. VECTO also offers the flexibility to use either a time-based or distance-based test cycle, depending on the user’s preference.

3.1.4. VECTO Output File

VECTO generates two result files after individual project calculations:

• A file in vmod format that includes the simulation results of the dynamic response of almost all subcomponents, such as the real-time speed and power of the axle, as well as the speed and power of the vehicle.
• A file in vsum format that includes the average or total values for the entire driving cycle, such as corrected average CO₂ emissions and average fuel consumption.

3.2. GEM Software

The GEM model was first created by the U.S. EPA as part of the Greenhouse Gas Emissions Standards for Heavy Duty Vehicles and Fuel Efficiency Standards for Medium and Heavy Duty Engines [38]. Manufacturers are now using GEM to certify vehicles as compliant with HDV GHG emissions standards of the U.S. [39]. The model was used to fully validate 130 vehicle variants, including several medium- and heavy-duty trucks. The simulation results were in good agreement with the test results, with the accuracy of the model simulations controlled to within an error of less than ±5 percent. This indicates that the model is technically sound and ready for the next stage of GHG emissions certification [40].

The vehicle model categories in the GEM software are divided into three regulatory subcategories: tractor, trailer, and work vehicle. Each subcategory has its own corresponding parameter input file, but all three input files share the same four subfiles: engine system, transmission system, axle system, and powertrain system. While there are differences in the parameters for each subcategory, primarily in the predefined default parameters for each vehicle, the calculation parameter requirements that the user must input remain largely the same. In GEM 3.0, the user interaction interface has been removed, so the software automatically generates the corresponding result files after the vehicle parameter files are inputted [41].

3.2.1. Computational Logic

The GEM uses a forward power transfer chain to simulate the energy flow and powertrain transmission during real driving. The simulation starts from the accelerator pedal to the wheels: the power system submodule receives the acceleration signal from the accelerator pedal, and using the vehicle’s speed in the driving cycle as the target value, it converts this into a torque output request signal. This signal is then fed back to the gas pedal control module, closely mimicking the actual driving situation, as shown in Figure 8.

3.2.2. GEM Software User Input Files

In the latest version of GEM, only a vehicle parameter input file is required; the software will automatically generate the corresponding result file. The input file includes:

• Engine system parameters

The parameters to be input in the engine parameter system include engine idle speed, displacement, full-load characteristic curve, and reverse drag characteristic curve. In addition, GEM requires the input of the engine’s universal performance characteristics MAP, which is used to calculate the vehicle’s fuel consumption and CO₂ emissions. For tractors and vocational vehicles, the manufacturer must provide the cyclic work and average fuel consumption for a specific transient cycle.

2.

Transmission System Parameters

GEMs transmission model offers three alternative transmission types, similar to VECTO: Manual Transmission (MT), Automated Manual Transmission (AMT), and Automatic Transmission (AT). Users are required to enter the ratio, maximum transmission torque, and transmission power loss for each gear separately.

3.

Powertrain and axle parameters

The input files for the powertrain and axle system sections contain fewer parameters. The axle system section requires the input of the output torque and power loss of the driveshaft at different speed ranges. The input file for the powertrain section includes information on the vehicle’s fuel consumption at idle, power, and fuel consumption at constant speeds of 55 mph and 65 mph, as well as the cyclic work and fuel consumption measured under specific transient cycles.

3.2.3. Driving Cycle for Simulation

There are only three default time-based cycle modes in the GEM software: the California Air Resources Board (ARB) Transient Drive Cycle, the GEM 55 mph Drive Cycle, and the GEM 65 mph Drive Cycle. Depending on the vehicle subcategory, the simulation results from these three cycles are weighted differently in the final emissions and fuel consumption results. The user cannot choose between these cycles during the simulation, nor can they customize the test cycle. Only the software’s default settings can be used in GEM.

3.2.4. GEM Software Output Files

After each simulation, the GEM software automatically generates a CSV-format result file. The output file closely mirrors the input file, with additional columns for the calculation results. These added columns include CO₂ emissions, fuel consumption, and the limit values of CO₂ emissions and fuel consumption as required by the regulations.

3.3. Commercial Vehicle Energy Consumption Simulation Software of China

According to the Chinese standard “Measurement Methods of Fuel Consumption for Heavy-Duty Commercial Vehicles” (GB/T 27840-2021), testing with a chassis dynamometer requires a representative vehicle model to be submitted to an inspection agency under specified conditions, which can be both costly and time-consuming. In contrast, the simulation method uses universal characteristic test data for the vehicle’s engine and key parameters inputted into a computer program. This method simulates the driving conditions of the test vehicle and calculates the corresponding fuel consumption and CO₂ emissions.

The energy consumption simulation software for commercial vehicles was developed by the China Automotive Technology Research Center Co., Ltd. (Tianjin, China). The software is based on reverse power transmission chain simulation and driving cycles. It calculates driving resistance and gearshift logic in accordance with GB/T 27840 provisions. The system has undergone model upgrades and algorithmic improvements to meet the research and validation needs of manufacturers. Currently, the simulation system supports the calculation of fuel consumption for traditional power vehicles and energy consumption for hybrid vehicles.

3.3.1. Calculation Logic

The calculation logic of the commercial vehicle energy consumption simulation software is based on the same principles as VECTO, utilizing the reverse power transmission chain for simulation. The software calculates the corresponding working conditions of the engine based on the power demand from the specified driving conditions. This is carried out by simulating the energy flow from the wheels, through the drive shafts, reducer, gearbox, and other components, before calculating the fuel consumption according to the engine parameters.

3.3.2. User Input Files

The simulation follows the data format required by the regulations. Once the file is inputted, the software automatically matches the working conditions based on the model. After completing the calculations, the main interface displays parameters such as the MAP distribution of working condition points, fuel consumption rates under those conditions, gear shifts, engine load rates, and other related details.

• Basic vehicle information

The general parameters required include vehicle type, fuel type, tire specifications, vehicle mass, load, and drive shaft-related parameters, among others.

2.

Driveline Documentation

Users must enter parameters like the main gear ratio of the driveline, the starting gear, the number of main transmission gears, the gear ratios for each gear, the number of sub-transmission gears, and the transmission type.

3.

Engine parameter files

Engine parameter files mainly include the engine reverse drag characteristic file, engine universal performance characteristics file, engine speed file, engine maximum torque file, and other parts. The engine reverse drag characteristic file should list the speed and corresponding anti-trailing torque for each measurement point. The engine universal performance characteristics file should present engine speed, torque, and transient fuel consumption rates in three separate columns. The engine speed file primarily includes parameters such as engine idle speed, rated speed, and maximum speed. Lastly, the engine maximum torque file should detail the maximum torque at various speeds, with corresponding speed values listed in two columns.

4.

Coasting resistance file

This file provides atmospheric temperature and pressure during the road test, along with the intermediate speeds and corresponding deceleration times for each deceleration interval.

3.3.3. Driving Cycle for Simulation

When selecting the test cycle, the commercial vehicle energy consumption simulation software uses the China Heavy-duty Commercial Vehicle Test Cycle (CHTC), in accordance with the requirements of GB/T 27840. This cycle includes six types of working condition cycles, and the software automatically selects the appropriate test conditions based on the input vehicle type during the calculation process. Compared to the previously used China World Transient Vehicle Cycle (C-WTVC), the CHTC cycle is characterized by more idling periods and lower running speeds. This better reflects the high proportion of low-speed and low-load conditions experienced by heavy commercial vehicles in China [42].

3.3.4. Output File

The simulation generates fuel consumption results and displays the gear curve, engine load factor, fuel consumption curve, and other related data in the resulting interface.

3.4. Other Test Methods

In addition to the commercial vehicle energy consumption simulation software, other studies have been conducted on commercial vehicle fuel consumption using various commercial software, such as fuel economy analysis based on tools like Cruise and AVL CRUISE [43,44]. Wang Zhenpo et al. proposed a carbon emission accounting method for HDVs based on remote monitoring data. This method calculates the carbon emissions of large-scale vehicles using monitoring data, a carbon emission determination model, and a carbon emission factor model [45]. Several studies also focus on the localized application of VECTO. Wang et al. conducted a comparative analysis of the fuel consumption of a heavy-duty truck using chassis dynamometer tests, engine-in-the-loop (EIL) tests, and VECTO simulations. The results showed that the largest deviation in speed came from the chassis dynamometer test, while the smallest deviation was from the VECTO simulation. The weighted fuel consumption in the VECTO simulation was higher than that of the chassis dynamometer test and the EIL test [46]. A study on the VECTO test cycle for several commercial vehicles in China showed that when the test cycles better matched the road conditions in China, the simulated fuel consumption and CO₂ emissions of heavy commercial vehicles were closer to real-world values, making the regulations more effective for energy saving and CO₂ reduction [47].

In 2020, the Korean government introduced a CO₂ monitoring regulation requiring HDV manufacturers to submit data on CO₂ calculations using the Heavy Duty Vehicle Emission Simulator (HES), a vehicle dynamics-based system model that estimates fuel consumption and CO₂ emissions [48]. Seo J et al. contributed to the development of the HES program [49]. Validation showed that the average CO₂ emission error between the experimental values and the HES results was 4.6%. Additionally, Tong Liu et al. proposed a data-driven neural network agent model to predict the resistance of a truck platoon system. This model reduced the fuel consumption of truck platoons by 10%, demonstrating higher cost-effectiveness potential [50].

3.5. Comparison of Test Methods

3.5.1. Scope of Application

The GEM is primarily used to assess whether the fuel consumption and GHG emissions of Class 7–8 tractor vehicles and Class 2b–8 operational vehicles comply with EPA and National Highway Traffic Safety Administration (NHTSA) regulations on greenhouse gas emissions and fuel efficiency. The GEM computational model is limited to Class 7–8 tractor vehicles and Class 2b–8 operational vehicles, along with their related vehicle models. It is not capable of simulating other vehicle types.

In contrast, VECTO software does not target specific vehicle types. Its mathematical model is more versatile, allowing users to define the main parameters of the vehicle types in the development mode. The software calculates fuel consumption and CO₂ emissions based on the parameters inputted by users. It can be used for both certification and supervision and is suitable for technical verification of a company’s economic and emission performance.

China’s energy consumption simulation software for commercial vehicles is primarily focused on the variants of vehicle types specified in the China standard GB/T 27840-2021. As the development and application of the software are still in their early stages, it has only been validated for specific vehicle types. However, it is expected to be expanded and popularized in the future.

3.5.2. Calculation Logic and Accuracy

The reverse power transmission chain represented by VECTO differs somewhat from the real driving state of the vehicle. When simulating the corresponding driving cycle, closed-loop control is not required. The models of individual components and the entire vehicle are streamlined, and the calculation accuracy meets the necessary demands. On the other hand, the forward power transmission chain used by GEM is better suited to simulate real driving conditions. However, when calculating the corresponding driving cycle, closed-loop control of driver parameters, such as the gas pedal, needs to be incorporated to ensure a good transient response.

Although the power transfer model, driver model, and gear shift strategies differ between the two software programs, the discrepancies in their calculation accuracy are relatively minor. This has been demonstrated by comparisons of results from a wide range of vehicles in relevant studies. For instance, in an ICCT study, fuel consumption corresponding to engine output and payload was compared for two base models in GEM and VECTO software under three test cycles (ARB transient, 55 mph, and 65 mph). A total of 6000 tests were conducted, with 500 random vehicle configurations tested for each model. A linear regression model was used to assess the agreement between the datasets. The results showed that, despite differences in computational logic and input file formats between the two software programs, the results were very similar, with the maximum computational accuracy difference not exceeding 3% [51]. In a follow-up study on technology validation tools, researchers used both VECTO and GEM to simulate 100 random variants of a reference vehicle in order to assess the fuel-saving effects of aerodynamic devices and low-drag tire technologies on the fleet. In the aerodynamic device simulation, the results from both software programs were nearly identical, with fuel consumption reduction values and standard deviations differing by no more than 0.1%. In a separate set of simulations involving low-drag tires, the differences between the results from the two programs were slightly larger but still within about 1% [52].

3.5.3. Software Functions

The functions of GEM and VECTO software are similar in that both can calculate CO₂ emissions and fuel consumption based on input vehicle parameters. However, GEM is more focused on determining CO₂ emission compliance for vehicle subcategories within regulatory frameworks, positioning it primarily as a certification tool. Consequently, many of the parameters in GEM are set to default values, with users able to modify only a limited number of them. VECTO, on the other hand, offers both certification and development modes. In certification mode, the functions of VECTO and GEM are comparable, with many parameters defaulted to system values. However, in development mode, VECTO offers much greater flexibility, allowing users to input nearly all vehicle component parameters. This mode is particularly useful for vehicle manufacturers during the vehicle development phase to evaluate CO₂ emission performance. As a result, VECTOs functionality is more versatile than that of GEM.

In addition to calculating CO₂ emissions and fuel consumption, the energy consumption simulation software for commercial vehicles also facilitates statistical analysis. This includes examining the frequency of high-gear usage, the distribution of high-frequency gear operating points, and the spread of calculated operating points. These analyses can help manufacturers optimize vehicle designs for better efficiency and performance.

4. Conclusions

HDVs, as a significant contributor to carbon emissions in the transportation sector, have drawn increasing attention from countries worldwide. In recent years, many nations have introduced stringent limits on CO₂ emissions from HDVs, with the latest emission standards in several countries reaching historically tight levels.

This paper focuses on analyzing the GEM software used in the U.S., the VECTO software in Europe, and other related CO₂ simulation methods. The GEM model, widely used in the U.S., can accurately predict fuel efficiency and CO₂ emissions based on various vehicle parameters and driving conditions. The VECTO software, employed in Europe for evaluating CO₂ emissions from heavy-duty commercial vehicles, accounts for a wide range of parameters such as the powertrain, vehicle weight, driving conditions, and fuel efficiency, providing a comprehensive calculation of fuel consumption and CO₂ emissions. In addition to GEM and VECTO, other simulation methods, like the Commercial Vehicle Energy Consumption Simulation Software (1.0) in China, also play a crucial role.

By comprehensively analyzing the advantages and limitations of these measurement methods, the following conclusions can be drawn:

• GEM and VECTO software are recognized as highly accurate softwares in the industry and have been widely adopted with notable success. The accuracy of both software programs in modeling CO₂ emissions is very similar. However, these tools are dependent on local policy norms and may therefore vary in use across different countries and regions, requiring adjustments to suit local conditions. In countries and regions where GEM and VECTO are applicable, validation and research can be conducted using the respective software. In other regions, VECTO has broader applicability due to its flexibility in defining custom driving cycles, offering more parameter input options, and supporting a variety of computational modes.
• Other countries are still in the early stages of CO₂ emission simulation for HDVs. The proposed CO₂ simulation methods have only been validated for specific vehicle types and need to be further developed and expanded to validate their accuracy and generalizability. Relevant research can draw on the calculation logic of GEM and VECTO, integrating it with local policies and regulations to develop more regionally suitable software. Additionally, integrating advanced modeling techniques, such as machine learning and real-time data collection, could improve the accuracy and adaptability of these models. International cooperation should be encouraged in the formulation of HDV emission reduction policies, helping to promote global emission reduction goals.