Search NASA⌕ Search

SEARCH · Search NASA

Results for “powertrain simulation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Vehicle Powertrain Simulation Accuracy for Various Drive Cycle Frequencies and Upsampling Techniques

As connected and automated vehicle technologies emerge and proliferate, lower frequency vehicle trajectory data is becoming more widely available. In some cases, entire fleets are streaming position, speed, and telemetry at sample rates of less than 10 seconds. This presents opportunities to apply powertrain simulators such as the National Renewable Energy Laboratory's Future Automotive Systems Technology Simulator to model how advanced powertrain technologies would perform in the real world. However, connected vehicle data tends to be available at lower temporal frequencies than the 1-10 Hz trajectories that have typically been used for powertrain simulation. Higher frequency data, typically used for simulation, is costly to collect and store and therefore is often limited in density and geography. This paper explores the suitability of lower frequency, high availability, connected vehicle data for detailed powertrain simulation. A large data set of 1 Hz trajectories is used to quantify the accuracy loss when simulating energy consumption for conventional, hybrid, and battery electric powertrains using less than 1 Hz data. Techniques to upsample lower frequency drive cycle data in order to increase accuracy are also explored. Median energy consumption errors when simulating energy consumption for a 1/10 Hz trajectory are found to be 3-6% when compared to 1 Hz trajectories. Applying upsampling and interpolation techniques are shown to reduce the simulation errors by roughly 50%. The findings in this work can guide connected vehicle data collection specifications and processing techniques applied when using collected data for powertrain simulation.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Route Energy Prediction (RouteE) Powertrain Validation Report

The National Renewable Energy Laboratory's flagship package in the RouteE suite, RouteE-Powertrain, is a mesoscopic energy model that predicts vehicle energy consumption given discrete attributes that describe each segment or link in a vehicle's path on a road network. High-frequency, physics-based, powertrain simulators, such as NREL's FASTSim, are well-suited to model vehicle energy consumption when real driving data and a detailed understanding of the vehicle powertrain specifications are available. However, there are a variety of situations in the past, present (real-time), and future where high-frequency driving data and/or vehicle information may not be available, but reliable energy consumption is still desired, such as energy-aware vehicle routing. These are the ideal applications for RouteE-Powertrain. The suite of RouteE tools also includes RouteE-Compass, which is an eco-routing software that incorporates energy consumption into network routing algorithms, and RouteE-Mobile, which is a prototype smartphone navigation app to demonstrate the integrated capabilities of the RouteE suite for real-world eco-routing. The focus of this validation report is to share key metrics about the data sets and models behind RouteE-Powertrain. The set of RouteE-Powertrain models discussed in this report are made available through the RouteE web API through the NREL Developer Network.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Improving Efficiency of Off-Road Vehicles by Novel Integration of Electric Machines and Advanced Combustion Engines

Modern off-road equipment will increasingly rely on electrified implements that will deliver precision control with a smaller footprint than hydraulics. The primary energy converter, however, will be an onboard reciprocating internal combustion engine because of the power density of hydrocarbon fuels in comparison to electrical energy storage and the remote locations where much of this equipment is deployed. Adding energy storage and electric machines creates opportunities to improve efficiency while reducing emissions. This program investigated approaches to take advantage of the extra flexibility that an enhanced electrical system to enable high-efficiency, low-emissions combustion technologies. The current program evaluated hybridization of both the torque application and air-handling systems to maximize efficiency while minimizing cost. This program designed, analyzed and tested a hybrid off-road vehicle consisting of a series electric powertrain with energy storage, an electrified air system, and a 33% downsized diesel engine. Detailed comparisons were made between the base powertrain and the developed powertrain using powertrain simulations, engine testing, and vehicle testing. The key results of the study are: • The resulting vehicle reduces fuel consumption by 5% to 15% at equal productivity. The primary improvements were due to recovery of regenerative braking losses for cycles where large transients are encountered. • The electrified air system was an enabler to allow engine downsizing. This was most important for duty-cycles where the engine primarily operated at moderate loads and had few low speed high torque conditions. • Engine level improvements showed re-optimization of the powertrain is possible when electrified air handing is available. Increased exhaust gas recirculation and advanced injection timing allowed up to a 15% reduction in brake specific fuel consumption at equal NOx and transient response. Compared to the larger engine, the downsized engine achieves up to an 18% reduction in brake specific fuel consumption over the non-road transient cycle. • The life cycle analysis and total cost of ownership study showed that the hybrid powertrain has the potential to reduce 5-year CO2 and total cost of ownership by ~6% over the baseline vehicle. The results also indicated that a pure battery electric vehicle is not feasible in this application and is likely to increase the CO2 emissions due to the CO2 from battery production. A hybrid powertrain with low carbon fuels shows the potential to substantially reduce CO2 and total cost of ownership.

02 PETROLEUM↗
DOE OSTI2021

Development of in-use engine speed/torque heat maps across multiple heavy-duty commercial vehicle vocations

The U.S. Department of Energy (DOE) established the SuperTruck program with the goal of achieving brake thermal efficiency (BTE) greater than or equal to 55% as demonstrated in an operational heavy-duty (HD) diesel engine at a 65-miles-per-hour (mph) cruise point. Beyond the line-haul application, HD engines operate in a wide range of speed and torque conditions that are unlikely to yield the same efficiency under real-world operation. Thereby, the in-use engine heat maps described in this paper are a valuable tool to illustrate whether the engine-efficiency “sweet spot” matches the most frequent operating conditions. In this study, NREL developed engine heat maps to quantify the important operating points for various vocations using our Fleet DNA database of commercial fleet vehicle operations data. These heat maps clearly show that high-frequency operating points vary significantly according to vehicle vocation, while only a few of them match the sweet spot. Beyond the illustration, engine in-use heat maps can also be leveraged to build up reduced-order engine-efficiency models, needed by many rapid powertrain simulations. As case studies, nine reduced-order models – including line-haul truck, transfer truck, transit bus, transit bus with compressed natural gas (CNG) engine, drayage, refuse pickup, local delivery, utility truck, and school bus with CNG engine – using a trust-region reflective algorithm to fit the on-road data extracted based on the engine in-use heat maps.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Demonstration of Ego Vehicle and System Level Benefits of Eco-Driving on Chassis Dynamometer

Eco-Driving with connected and automated vehicles has shown potential to reduce energy consumption of an individual (i.e., ego) vehicle by up to 15%. In a project funded by ARPA-E, a team led by Southwest Research Institute demonstrated an 8-12% reduction in energy consumption on a 2017 Prius Prime. This was demonstrated in simulation as well as chassis dynamometer testing. The authors presented a simulation study that demonstrated corridor-level energy consumption improvements by about 15%. This study was performed by modeling a six-kilometer-long urban corridor in Columbus, Ohio for traffic simulations. Five powertrain models consisting of two battery electric vehicles (BEVs), a hybrid electric vehicle (HEV), and two internal combustion engine (ICE) powered vehicles were developed. The design of experiment consisted of sweeps for various levels of traffic, penetration of smart vehicles, penetration of technology, and powertrain electrification. The large-scale simulation study consisted of doing approximately 96,000 powertrain simulations. A sophisticated clustering scheme was built and utilized to down select representative traces for each scenario from the simulation study for vehicle testing on a chassis dynamometer. Furthermore, this paper provides a summary of individual ego vehicle testing as well as a comprehensive overview of the method utilized for down selecting representative traces from large scale simulation studies that can be used to quantify corridor level benefits. Vehicle test results along with corresponding analyses are presented.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Development of an Optimized Gasoline Surrogate Formulation for PACE Experiments and Simulations

New powertrain solutions are needed to address societal challenges stemming in part from a transportation sector which relies heavily on combustion of conventional hydrocarbon fuels like gasoline. One way to advance new solutions is through predictive simulations. Predictive simulations can potentially limit the extent of experimental validations, reduce time spent in engineering design cycles, unlock new strategies for high efficiency combustion with power density, and minimize tailpipe emissions. However, the simulation tools currently available are either too computationally expensive, inadequate in their accuracy, or a combination of the two. A DOE-funded consortium of national laboratories called the Partnership to Advance Combustion Engines (PACE) seeks to address this gap by rapidly delivering new knowledge and tools which enable market-competitive powertrain solutions for light-duty vehicles. Approaches to modeling combustion in powertrain systems typically incorporate computational fluid dynamics (CFD) simulations with chemical kinetic models. These CFD simulations generally use surrogate fuels featuring a limited number of existing components in a reduced kinetic model to limit computational costs. Such surrogate fuels often sacrifice matching several or more combustion and physical properties of the target gasoline fuel. Validation of surrogate fuels is also often only pursued for a small subset of standard metrics such as research or motor octane number (RON, MON). The purpose of this project is to develop an optimal E10 gasoline surrogate fuel suitable for tasks across PACE to facilitate rapid common analysis and progression toward consortium goals. This project received contributions from tasks led by eight PACE principal investigators. The project funding here reflects all tasks under Pitz, whose tasks also contributed to additional PACE projects. Based on the optimal gasoline surrogate fuel composition, a reduced chemical kinetic model will be shared with PACE researchers, industry, and the broader combustion community.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Impact of multimode range and location on urban fuel economy on a light-duty spark-ignition based powertrain using vehicle system simulations

Multimode engine operation uses two or more combustion modes to maximize engine efficiency across the operational range of a vehicle to achieve higher overall vehicle fuel economy than is possible with a single combustion mode. More specifically for this study, multimode solutions are explored that make use of boosted SI under high load operation and other advanced combustion modes such as advanced compression ignition (ACI) under part-load conditions to enable additional engine efficiency improvements across a broader range of the engine operating map. ACI combustion has well-documented potential to improve efficiency and emissions under part-load operation but poses challenges that limit full engine speed-load range. This study investigates the potential impact of ACI operational range on simulated fuel economy to help focus research on areas with the most opportunity for improving fuel economy. These simulations make use of a vehicle model, discretized engine data, and employ a systematic exploration of ACI operational range to estimate multimode fuel economy for a mid-size passenger vehicle over U.S. Environmental Protection Agency’s Urban Dynamometer Driving Schedule. The results of this study highlight operational ranges with the highest potential fuel economy and correspondingly areas of focus for multimode research and ACI engine operation1.

Curran, Scott↗
DOE OSTI2022

Projecting California Light-Duty Vehicle Attributes (2019-2035)

In this report, we estimated a set of future vehicle attribute scenarios for new light-duty vehicles for the California market using the Automotive Deployment Options Projection Tool (ADOPT). ADOPT starts simulations with all existing vehicle makes and models and endogenously creates new vehicle models over time based on assumed technology improvements and market conditions. For this study, we simulated four scenarios with varied technology, policy, and electric vehicle infrastructure assumptions. We aggregated simulation results into up to 30 vehicle classes (covering size and price classifications) for each powertrain, for six powertrains. We simulated model years 2019 to 2035. We present results for four vehicle attributes: vehicle acceleration, fuel economy (including electric and gasoline for plug-in hybrid electric vehicles [PHEVs]), vehicle range, and vehicle purchase price. We also present results showing the estimated number of vehicle models available in each vehicle class over time. In the Mid scenario, which contains conditions between our most conservative and most optimistic assumptions for emerging electric and hydrogen technologies, we observe improvements in acceleration, range (for battery-electric vehicles [BEVs]), and vehicle purchase price for electric and hydrogen powertrains. In some cases, we project that consumer preferences lead to trade-offs between vehicle attributes, such as reduced fuel economy in exchange for improved acceleration. Conventional vehicles show modest improvements in fuel economy in these scenarios due to the high numbers of BEV and PHEV sales, which reduce the improvements required in conventional vehicles to meet fleet fuel economy standards. In scenarios with advanced technology assumptions (including reduced battery price and improved energy density), we observe further improvements in BEV range and price relative to the improvements in the Mid scenario.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Simulation-Based Assessment of Energy Consumption of Alternative Powertrains in Agricultural Tractors

The objectives of this research were to develop simulation models for agricultural tractors with different powertrain technologies and evaluate the energy consumption in typical agricultural operations. Simulation models were developed for conventional, parallel hybrid electric, series hybrid electric, fuel cell hybrid, and battery electric powertrains. Autonomie vehicle simulation software (version 2022) was used for the simulations and the tractor models were simulated in two tilling cycles and in a road transport cycle with a trailer. The alternative powertrains were configured to have at least the same tractive performance as the conventional, diesel engine-powered tractor model. The simulation results showed that the potential of the parallel and series hybrid powertrains to improve energy efficiency depends heavily on the tractor size and the operating cycle conditions. The fuel cell hybrid and battery electric powertrains have a higher potential to reduce energy consumption and emissions but still have inherent technical challenges for practical operation. The battery-powered electric tractor would require improvements in the storage energy density to have a comparable operational performance in comparison to other powertrains. The fuel cell hybrid tractor already provided an adequate operating performance but the availability of hydrogen and refueling infrastructure could be challenging to resolve in the farming context.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Evaluating Class 6 Delivery Truck Fuel Economy and Emissions Using Vehicle System Simulations for Conventional and Hybrid Powertrains and Co-Optima Fuel Blends

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance. Comparisons were made between ultralow-sulfur diesel and a blend of 25% hexyl hexanoate with diesel. Model validation data were informed by 2019 model year Cummins ISB 6.7 L diesel engine maps and transient validation data in a pre-production hybrid configuration and a direct dyno coupled configuration with diesel fuel and a blend of 25% hexyl hexanoate with diesel.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Ambient and Initial Temperature Effects on Energy Consumption Rate Modeled in FASTSim

Ambient and initial temperatures significantly impact the energy consumption rate (ECR) of battery electric vehicles (BEVs) due to auxiliary loads and the temperature dependence of battery efficiency. This study introduces a streamlined, physics-based thermal modeling approach within the FASTSim tool that bridges the gap between oversimplified constant-load models and computationally expensive high-fidelity simulations. By employing a lumped thermal mass framework, the model captures fundamental energy balances and critical non-linear energy penalties while maintaining the computational efficiency required for expansive sensitivity studies. The simulations evaluated a compact BEV hatchback with a resistive heater over city (UDDS) and highway (HWFET) test cycles. Compared to a 22 degrees Celsius initial and ambient temperature baseline, a -7 degrees Celsius initial/ambient temperature resulted in a 221% increase in the ECR for the city cycle and a 100% increase for the highway cycle. Conversely, a 45 degrees Celsius initial / 40 degrees Celsius ambient temperature resulted in a 40% increase for UDDS and an 18% increase for HWFET. These results demonstrate that while cold conditions impose the most severe energy penalties due to resistive heating, the impact is consistently more pronounced in city driving where auxiliary loads represent a larger proportion of total energy. This lightweight yet robust framework enables researchers to rapidly quantify BEV thermal sensitivity across diverse climates without the need for high-overhead simulation environments.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Charting the Path to Electrification: Analyzing the Economic and Technological Potential of Advanced Vehicle Powertrains

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) is driving advancements in highway transportation by targeting energy efficiency, environmental sustainability, and cost reductions. This study investigates the fuel economy potential and cost implications of advanced powertrain technologies using comprehensive system simulations. Leveraging tools such as Autonomie and TechScape, developed by Argonne National Laboratory, this study evaluates multiple timeframes (2023–2050) and powertrain types, including conventional internal combustion engines, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs). Simulations conducted across standard regulatory driving cycles provide detailed insights into fuel economy improvements, cost trajectories, and total cost of ownership. The findings highlight key innovations in battery energy density, lightweighting, and powertrain optimization, demonstrating the growing viability of BEVs and their projected economic competitiveness with conventional vehicles by 2050. This work delivers actionable insights for policymakers and industry stakeholders, underscoring the transformative potential of vehicle electrification in achieving sustainable transportation goals.

Islam, Ehsan Sabri (ORCID:0000000200220180)↗
DOE OSTI2026

NLR Core Modeling & Decision Support Capabilities: FASTSim, RouteE, T3CO & OpenPATH

This project is part of the program area to develop and improve core capabilities for the Energy-Efficient Mobility Systems (EEMS) program that enable research, development and deployment of advanced mobility solutions and enhance the EEMS Program's ability to address system-level transportation challenges. Advancements to the Future Automotive Systems Technology Simulator (FASTSim), Route Energy Prediction Model (RouteE), Transportation Technology Total Cost of Ownership (T3CO) and Open Platform for Agile Trip Heuristics (OpenPATH) core capabilities under this project supports the overall EEMS Program goals to effectively evaluate energy and mobility impacts of future transportation technologies and services, and to identify the most promising pathways to reduce transportation costs and environmental harms, and to improve mobility access. This presentation was prepared for the 2026 Annual Merit Review of this project.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Future Automotive Systems Technology Simulator (FASTSim) Validation Report - 2021

The National Renewable Energy Laboratory's Future Automotive Systems Technology Simulator (FASTSim) captures the most important factors influencing vehicle power demands and performs large-scale fuel efficiency calculations very quickly. These features make FASTSim well suited to evaluate a representative distribution of real-world fuel efficiency over a large quantity of in-use driving profiles, which have become increasingly available in recent years owing to incorporation of Global Positioning System data collection into various travel surveys and studies. In addition, by being open source, computationally lightweight, freely available, and free from expensive third-party software requirements, analyses conducted using FASTSim may be easily replicated and critiqued in an open forum. This is highly desirable for situations in which technical experts seek to reach consensus over questions about what vehicle development plans or public interest strategies could maximize fuel savings and minimize adverse environmental impacts with an evolving vehicle fleet. While FASTSim continues to be refined and improved on an ongoing basis, this report compiles available runs using versions of the tool from the past few years to provide illustrative comparisons of the model results against measured data.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Port of New York and New Jersey Drayage Electrification Analysis

The National Renewable Energy Laboratory (NREL) evaluated the potential for drayage electrification in the Port of New York and New Jersey (PoNYNJ), with a focus on operators: Harbor Freight Transport (HF), Safeway Trucking (SWT), and International Motor Freight Inc (IMF). This report summarizes the data collection and electrification evaluation of all three drayage operators, includes detailed operational data, and identifies the performance requirements for battery electric tractors (BETs) and corresponding infrastructure operated within the context of PoNYNJ drayage operation. This report also details a methodology to evaluate opportunities, strategies, and challenges associated with future expansions of BETs in meeting PANYNJ emissions goals. The Port Authority has established a goal of achieving Net Zero carbon emissions by 2050 across all facilities, including from tenant and stakeholder sources such as drayage trucks. NREL used real-world performance data collected on the three PoNYNJ drayage operations, along with modeling and analysis tools to compare BET to diesel trucks. From March to July 2021, NREL collected 1Hz vehicle and engine data from 46 drayage trucks at the three operators totaling nearly 121,000 miles of operation, providing enough information to assess vehicle operations for electrification potential. A Future Automotive Systems Technology Simulator (FASTSim) electric truck powertrain model was validated using PoNYNJ data and scenarios were run to evaluate drayage truck electrification requirements over the real-world cycles. The first scenario examined BET viability with minimal changes to existing operations. This assumes the trucks charge when stopped for two hours or longer, have a functional battery size of 375 kWh, and can charge at 270 kilowatts (kW) average which are the specification of the commercially available Freightliner eCascadia. The second scenario looked at what operational, charging infrastructure, and BET technology changes would be needed to fully electrify. Finally, detailed analysis was run on charging rate structure to understand operational costs to the fleets. The studied drayage trucks averaged 5.1 MPG, spent roughly 9% of their energy at idle, and drove an average of 140 miles per day with a maximum daily distance of 573 miles. The FASTSim model results indicate a comparable BET would use 417 kWh of energy per day on average accounting for cargo weight, which is close to the full usable capacity of the eCascadia currently available on the market. Based on the daily average operating data, partial fleet electrification is possible with current technology. However, some specific days of operation would require over 1,600 kWh of energy due to longer distances traveled by the trucks and more intense operation. Trucks used for long distance and intense operation cannot be readily electrified with current technology without operational changes. Full adoption of BETs could reduce CO 2 emissions from these fleets by roughly 75% today, eliminating 76 metric tons of CO 2 (MTCO 2 ) per vehicle each year, which equates to 24,100 MTCO 2 per year for all three operators. Commercially available direct current fast chargers (DCFC) have charge rates up to 350 kW. Based on the average daily modeled energy use for each operator, current industrial rate structures, and the assumption of 350 kW peak charging, full drayage electrification would increase electricity consumption. In addition, peak demand usage would increase with unmanaged charging along with cost of electricity having a direct impact on cost per mile for electric vehicles. The resulting cost per mile for BETs along with comparable cost per mile for conventional diesel trucks are also examined at $\$$4.00 per gallon of diesel. It will be important for PANYNJ and the drayage operators within the PoNYNJ to consider these load impacts to their existing electrical infrastructure and devise operational strategies that avoid coincident charging of vehicles to mitigate demand charges. Despite these electricity cost increases, savings from reductions in diesel consumption will help offset the costs of this increased electricity consumption. However, prices of both electricity and diesel are subject to change based on various factors meaning the realized savings will vary over time. This shows BETs could be cost-competitive on an energy cost per mile basis for all scenarios while diesel is above $\$$3.00/gal. Further, if diesel prices dropped to the 15-year low of $2.33/gal, it would still be cost competitive to operate the EVs with electricity costs of 16.3 ¢/kWh or less.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Implementing Ordinary Differential Equation Solvers in Rust Programming Language for Modeling Vehicle Powertrain Systems: Preprint

Efficient and accurate ordinary differential equation (ODE) solvers are necessary for powertrain and vehicle dynamics modeling. However, current commercial ODE solvers can be financially prohibitive, leading to a need for accessible, effective, open-source ODE solvers designed for powertrain modeling. Rust is a compiled programming language that has the potential to be used for fast and easy-to-use powertrain models, given its exceptional computational performance, robust package ecosystem, and short time required for modelers to become proficient. However, of the three commonly used (>3,000 downloads) packages in Rust with ODE solver capabilities, only one has more than four numerical methods implemented, and none are designed specifically for modeling physical systems. Therefore, the goal of the Differential Equation System Solver (DESS) was to implement accurate ODE solvers in Rust designed for the component-based problems often seen in powertrain modeling. DESS is a text-based software package that provides a flexible framework for building and solving systems of ODEs. This allows DESS to be included as a dependency for automotive powertrain models that require a variety of solvers and solver configurations. Seven explicit ODE solver methods have been implemented in DESS: Euler’s, Heun’s, midpoint, Ralston’s, classic Runge-Kutta, Bogacki-Shampine, and Cash-Karp. These represent five fixed-step methods and two adaptive-step methods. This paper shows that the solver implementations increase accuracy and computational efficiency compared to Euler's method when modeling a system of three thermal masses in Rust. DESS also includes features designed for modeling component-based physical systems. Users can define relationships between nodes in their system, which the package then translates into a system of equations, leading to simpler and more intuitive code. In the case of a three-thermal-mass system, the user can specify node thermal properties (e.g., thermal capacitance), how nodes are interconnected, and thermal conductance between nodes rather than providing a system of equations. The core contribution from this work is an open-source, text-based Rust package with ODE solvers for automotive powertrain modeling to support cost-free, fast, and accurate simulation.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Autonomie Simulation Datasets in Support of U.S. DOT-NHTSA Advanced Vehicle Technology Research

Understanding how new vehicle technologies affect fuel economy and energy use is critical to the regulatory work performed by the U.S. Department of Transportation’s National Highway Traffic Safety Administration (NHTSA), which sets Corporate Average Fuel Economy (CAFE) standards under the Energy Policy and Conservation Act of 1975. In order to support this work, Argonne National Laboratory uses Autonomie, a full-vehicle simulation tool, to evaluate advanced powertrain architectures and their effects on vehicle energy consumption and performance. A wide range of vehicle classes has been assessed (i.e., internal combustion engine vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, battery-electric vehicles, and fuel cell electric vehicles), as well as the effects of various technology improvements such as lightweighting, aerodynamic refinements, and low-rolling-resistance tires. Simulations have been run across multiple drive cycles to capture fuel and electricity use under realistic operating conditions. The resulting datasets include detailed vehicle-level results, model assumptions, and validation reports, all of which have been made publicly available through NHTSA in support of the 2023 notice of proposed rulemaking covering light-duty vehicles for model years 2027 to 2035. These data are critical to stakeholders working in fuel economy regulation, vehicle technology assessment, and energy policy analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

HOLISTIC ENERGY EFFICIENCY ANALYSIS OF ELECTRIFIED OFF-HIGHWAY MATERIAL HANDLER: FROM DRIVE CYCLE CHARACTERIZATION TO POWERTRAIN, HYDRAULIC, AND THERMAL SYSTEM PERFORMANCE

Three complexities surrounding the operation and testing of hybrid electric, heavy-duty nonroad machines have been addressed experimentally and using 1D simulation. Their resolutions have been intertwined with the development of a prototype machine that was proven to reduce fuel consumption in excess of 20%. A real-world drive cycle that leveraged hydraulic cylinder position was developed and utilized to ensure accurate reproduction of hydraulic work between the baseline and hybrid machines, while simultaneously maintaining less than 5% RMS error in position for main load handling functions. The newly developed, machine-specific drive cycle also contributed towards making equivalent comparisons in energy consumption between machine types through composite performance metrics that were extrapolated over a typical shift duration. Lastly, this work addressed thermal management energy consumption, a topic of increasing popularity when discussing electrified vehicles, by proposing a 1.4% energy savings through special mechanization and control of cooling system components.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗