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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.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Convergence of Vehicle Electrification and Automation - Enabling Sustainable Automated Mobility Districts

The transportation industry is entering a new frontier with three major simultaneous transformations: electrification, automation, and on-demand services. All three directly affect the same spaces of vehicle technology, infrastructure, and system operational performance. Further, each area of change adds its own driving forces of complexity to the others' design challenges. This paper explores these transformations, framing the implications for vehicle technology and infrastructure and their impact on operating concepts and strategies, which in turn impact the sustainability of the transportation infrastructure in the built environment. Specifically, this paper examines battery-electric vehicles operating in a fully automated fleet within an "automated mobility district" (AMD) setting with multiple on-demand services. From this examination, the paper assesses the implications for transportation electrification, comparing and contrasting traditional fixed-route services with those of on-demand transit and automated transit networks, including the trade-offs between vehicle range (battery capacity), charging parameters, power availability, and operations predictability with respect to policy and infrastructure configurations. The paper also addresses the configuration and management of boarding and alighting zones (also called pickup and drop-off zones), and the need for complementary infrastructure intelligence at intersections and curbs. Finally, conclusions are drawn with respect to the system integration and analysis needs for AMDs regarding resilience and sustainability of mobility infrastructure.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Modeling of RMS Current in CSI Filter Capacitor and Minimum Conduction Loss Operation of CSI-Fed PMSM Drives for Traction Applications

This paper presents a new minimum conduction loss (MCL) torque control algorithm for current source inverter- (CSI-) fed permanent-magnet synchronous machine drives that improves the overall machine drive efficiency by minimizing the combined conduction losses in the inverter and machine at each operating point. First, analytical models of conduction losses in CSI-fed motor drives are presented, and a closed-form expression for optimal d-axis stator current to achieve MCL operation is derived. An expression for the rms current in both wye- and delta-connected CSI output capacitors is derived. A detailed simulation model that emulates the operation of a 100 kW SiC CSI-fed integrated machine drive (IMD) has been developed based on experimental results and finite element analysis. This simulation model is used to evaluate the proposed MCL control algorithm applied to a CSI-fed IMD system for a battery-electric vehicle traction drive, and the predicted total drive system loss with MCL control is compared to predicted losses with maximum-torque-per-ampere (MTPA) and minimum dc-link current (MDCC) control. Results show that MCL control can achieve loss reductions compared to the other two control algorithms over a wide range of operating conditions, with significant loss reductions >20% in the medium-speed regime.

42 ENGINEERING↗
DOE OSTI2024

Maritime Battery Electrification Simulator (MariBES) v1

MariBES is a Python-based software designed for calculating emissions and energy consumption in maritime transportation. This software is capable of performing calculations for multiple vessels, facilitating emission analysis at regional, national, and international scales. It also allows for the examination of energy consumption under various resource such as heavy fuel oil, diesel, and battery-electric, enabling the assessment of different decarbonization strategies in the maritime sector. MariBES utilizes public data on ship activities combined with detailed vessel specifications, significantly enhancing the accuracy of its simulations. This approach marks a considerable advancement over previous models that were constrained by limited spatial and temporal resolution. It features a temporal resolution based on 5-minute intervals and a spatial resolution using precise coordinates.

Moon, HeeSeung↗
DOE OSTI2026

Individual Motorist Data - Ohio EV Ownership Trends

The individual motorist dataset contains data and analysis of consumer electric vehicle (EV) ownership trends in rural Appalachian Ohio in comparison with statewide trends. The data span four years, from Q1 2020 to Q2 2023 (partial). They are sourced from the Ohio Bureau of Motor Vehicles registration records and contain detail on drivetrain type (battery-electric vehicle [BEV] or plug-in hybrid electric vehicle [PHEV]); specific vehicle make and model; and registration location at county, city, and ZIP code levels of spatial resolution. Registration data are analyzed at the county level against such indicators as median income, poverty status, urban-rural status, and density of public charging infrastructure. In addition to tabular data, a GIS shapefile with many analysis fields joined is included.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Detailed Simulation Datasets Quantifying U.S. DOE VTO/HFTO R&D Benefits Across Light- to Heavy-Duty Vehicles

For more than 20 years, Argonne National Laboratory’s Vehicle & Mobility Systems Department has assessed how R&D investments by the U.S. Department of Energy’s Transportation Technologies Office and Alternative Fuels and Feedstocks Office affect vehicle energy use and cost. The analyses are performed using Autonomie, Argonne’s full-vehicle simulation tool for energy consumption, performance, and cost. The study covers five time frames ranging from present day through 2050, with more than 30 vehicle classes and applications (10 light duty and >20 medium and heavy duty), as well as six powertrain configurations (conventional, start-stop, hybrid electric vehicle, plug-in hybrid electric vehicle, battery-electric vehicle, and fuel cell electric vehicle) and five fuels (gasoline, diesel, natural gas, hydrogen, and electricity). Low and high technology uncertainty scenarios have been considered to capture a realistic range of outcomes. The resulting datasets include the assumptions used (i.e., efficiency, $/kWh), vehicle-level data (power, energy, weight, and cost), and outputs such as energy consumption, manufacturer’s suggested retail price, and total cost of ownership. These data are critical to stakeholders working in transportation, technology assessment, and long-term R&D planning.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
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 OSTI2021

Why Regional and Long-Haul Trucks are Primed for Electrification Now

Zero emission freight trucks are needed to both improve public health and reduce global greenhouse gas emissions but at the same time are generally believed to be uneconomical. However, recent dramatic declines in battery prices and improvement in their energy density have created opportunities for battery-electric trucking today that were seldom anticipated just a few years ago. At the current global average battery pack price of $135 per kilowatt-hour (kWh) (realizable when procured at scale), a Class 8 electric truck with 375-mile range and operated 300 miles per day when compared to a diesel truck offers about 13% lower total cost of ownership (TCO) per mile, about 3-year payback and net present savings of about US $200,000 over a 15-year lifetime. This is achieved with only a 3% reduction in payload capacity. Even this small penalty can be reversed cost-effectively through light-weighting, in any case, only matters for a small fraction of trucks which regularly utilize their maximum payload. Electric trucks appear poised to also meet the performance demands for a large share of regional and long-haul trucking today. The estimated average distance traveled between 30- minute driver breaks is 150 miles and 190 miles for regional-haul and long-haul trucks respectively in the US. Thirty minutes of charging using 500 kW or mega-Watt scale fastchargers would add sufficient range without impairing operations and economics of freight movement. However, as with almost any clean technology, higher upfront capital costs of both vehicles and charging infrastructure are major barriers when electric trucking is in its infancy. Without strong policy support, coordinated investments in both vehicle manufacturing and fuel infrastructure will not be forthcoming on the scale needed to harness the true potential of battery electric trucks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
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

High Efficiency Powertrain for Heavy Duty Trucks Using Silicon Carbide (SiC) Inverter

The objective of the High Efficiency Propulsion (HEP) project is to research, develop, and demonstrate life cycle cost-effective Class 8 battery electric vehicles utilizing an 800 V high efficiency and compact 250 kW continuous power SiC inverter designed to support the commercial operations of the high continuous loads and challenging shock/vibration environment of heavy-duty trucks with an electrified axle specifically designed for high performance and efficiency in battery-electric Class 8 trucks used in medium range (~250 miles) distribution, and compared to the baseline Peterbilt 579 electric truck fleet performance using an IGBT inverter. The project was split into 3 budget periods, with the first two being design and development focused, and the final one is an on-vehicle demonstration phase of the high efficiency SiC traction drive inverter with daily mileage accumulation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Analyzing Potential Greenhouse Gas Emissions Reductions from Plug-In Electric Vehicles: Report for CRC Project, "Carbon Return on Investment for Electrified Vehicles"

Investment in battery and electrification technologies has the potential to greatly reduce vehicular greenhouse gas (GHG) emissions, as a battery-electric vehicle (BEV) will have zero tailpipe emissions. However, there will be GHG emissions associated with production of the vehicle including its battery, and with any carbon-emitting electricity sources used to charge the vehicle. This study explores the GHG reduction benefits of different plug-in electric vehicle (PEV) designs in the context of factors such as electricity production mix, per-vehicle battery requirements, and varying battery market growth scenarios. The analyses focus on the U.S. light-duty vehicle (LDV) market, which accounts for nearly 60% of U.S. transportation sector GHG emissions - over twice as much as the next largest contributing transportation sub-sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

LOCOMOTIVES - Comprehensive Impact and Cost Assessment Framework of Carbon Lowering Approaches for the US Rail Freight System

The goal of this project is to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first quarter, the project focused on collecting data, establishing a simulation workflow, and engaging industry through the creation of the Industry Advisory Board (IAB). In the second quarter, the project focused on selecting fuel pathways and powertrain technologies, setting performance targets, conducting a techno-economic analyses, and developing the simulation framework that would serve as the backbone of the future toolhead. The third quarter involved developing an industry-oriented interactive dashboard powered by a five-step sequential framework, as well as holding industry advisory board meetings as per the initial technology-to-market plan. In the remaining project quarters, the NUFRIEND dashboard were fine-tuned with the help of IAB member feedback and in-depth scenario analyses were conducted to support the techno-economic analysis of energy sources. Additionally, dashboard documentation, project insights, and open-source code on GitHub were prepared and released. Throughout the project, the team completed testing and analysis of all model components, integrated all initial test scenarios, and conducted stakeholder engagement. Lower-carbon drop-in fuels can be deployed as admixtures and are considered uniform across the network at a desired penetration rate, while hydrogen and battery-electric technology deployment poses a more complex problem as they require significant investments to be made in the siting of refueling/charging facilities and the replacement of locomotive fleets. Thus, strategies for locating and sizing refueling/charging facilities on a railroad’s network to meet their energy demands were developed to inform deployment decisions. To address this challenge, the Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework presents a five-step sequential framework to select O-D paths, locate facilities, reroute flows, size facilities, and evaluate the deployment for alternative energy sources that require locomotive powertrains to be converted and new refueling infrastructure to be deployed. The NUFRIEND Framework is an industry-oriented tool for simulating the deployment of new energy technologies across the US freight rail network. The framework provides a comprehensive network-level optimization and scenario simulation tool for decarbonizing the freight rail sector, addressing the uncertainties surrounding technological developments by supporting sensitivity analyses for different operational and technological parameters through a transparent and flexible input module. It offers practical alternatives to diesel locomotives and can be applied for any railroad considering the specific network structure and freight demand, outputting evaluation metrics for the associated emissions and costs relative to diesel operations. A number of relevant simulation scenarios were run and analyzed for key insights on the value of different alternative technologies for freight rail decarbonization. The project developments and findings have been presented at numerous conferences and events.

08 HYDROGEN↗
DOE OSTI2023

Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States

While the market for medium- and heavy-duty battery-electric vehicles (MHD EVs) is still nascent, a growing number of these vehicles are being deployed across the U.S. This study used over 2.3 million miles of operational data from multiple types of MHD EVs across various regions and operating conditions to address knowledge gaps in total cost of ownership and operational range. First, real-world energy cost savings were determined: MHD fleets should experience energy cost savings each year from 2021 to 2035, regardless of vehicle platform, with the greatest savings seen in transit buses (up to USD 4459 annually) and HD trucks (up to USD 3284 annually). Second, to help fleets across various geographies throughout the U.S. assess the suitability of EVs for their year-round operating needs, operational range was modeled using the XGBoost algorithm (R2: 70%) given 22 input features relevant to vehicle efficiency. Finally, this paper recommends (1) that MHD fleets apply energy-saving practices to minimize the impacts of cold temperatures and high congestion levels on vehicle efficiency and range, and (2) that local hauling fleets select trucks with a nominal range nearly double the expected maximum daily range to account for range losses under local, urban driving conditions.

Qiu, Yin (ORCID:0009000900948794)↗
DOE OSTI2025

Hydrogen and Electric Charging Infrastructure for Heavy-Duty Trucks: A Nationally Scalable Megaregion Assessment

Decarbonizing regional and long-haul freight is challenging due to the limitations of battery-electric commercial vehicles and infrastructure constraints. Hydrogen fuel cell medium- and heavy-duty vehicles (MHDVs) offer a viable alternative, aligning with the decarbonization goals of the Department of Energy and commercial entities. Historically, alternative fuels like compressed natural gas and liquefied propane gas have faced slow adoption due to barriers like infrastructure availability. To avoid similar issues, effective planning and deploying zero-emission hydrogen fueling infrastructure is crucial. This research develops deployment plans for affordable, accessible, and sustainable hydrogen refueling stations, supporting stakeholders in the decarbonized commercial vehicle freight system. It aims to benefit underserved and rural energy-stressed communities by improving air quality, reducing noise pollution, and enhancing energy resiliency. This research also provides a blueprint for replacing diesel in over-the-road Class 8 freight truck applications with hydrogen fueling solutions. The study focuses on the Texas Triangle Megaregion (I-45, I-35, and I-10), the I-10 corridor between San Antonio, TX, and Los Angeles, CA, and the I-5/CA-99 corridors between Los Angeles, CA, and San Francisco, CA. This area represents a significant portion of U.S. heavy-duty freight movement, carrying ~8.5% of the national freight volume. Using the OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport) modeling framework, the study conducts an advanced assessment of commercial vehicles, road and freight networks, and energy systems. The framework integrates data on freight mobility, traffic, weather, and energy pathways to deliver a region-specific, optimized vehicles powertrain architectures, infrastructure deployment solutions, operational logistics, and energy pathways. By considering all vehicle origin-destination pairs utilizing these corridors and all feasible fueling station location options, the framework's genetic algorithm identifies the minimum number and optimal locations of hydrogen refueling stations, ensuring no vehicle is stranded. It also determines fuel schedules and quantities at each station. A roadmap for station deployment based on multiple adoption trajectories ensures a strategic rollout of hydrogen refueling infrastructure.

Sujan, Vivek [ORNL] (ORCID:0000000269882342)↗
DOE OSTI2022

Decarbonizing Medium & Heavy-Duty On-Road Vehicles

We analyze the decarbonization potential of medium and heavy-duty vehicles (MHDVs) across multiple vehicle classes and market segments. We evaluate the timeframe in which zero-emission vehicles (ZEVs) could achieve cost parity with conventional diesel vehicles and the implications for energy and emissions. Our results show that ZEVs can achieve cost parity with conventional vehicles by 2035 across the majority of vehicle classes and market segments. Emissions reductions range from 27% to 77% by 2050 relative to 2019 across multiple fuel cost and technology progress sensitivities. Multiple technology pathways are viable for decarbonization, including battery-electric vehicles and hydrogen fuel cell electric vehicles. This presentation is based on previous work published by NREL: Ledna, C., Muratori, M., Yip, A., Jadun, P., and Hoehne, C. 2022. Decarbonizing Medium & Heavy-Duty On-Road Vehicles: Zero-Emission Vehicles Cost Analysis. National Renewable Energy Laboratory, https://www.nrel.gov/docs/fy22osti/82081.pdf.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Freight Electrification, Moving Goods While Managing Grid Impacts

Analyzing freight data from the Salt Lake City inland port demonstrates significant potential forintegrating battery-electric freight vehicles (BEVs) into key transportation corridors. Our partnership with freight operators like RSD and MWCS, and other companies moving freight around the port, provided valuable fleet telemetry and operationalinsights, highlighting critical corridors on and around I-15 and I-80.

Source record↗
DOE OSTI2026

Fleet Hydrogen Basics

Hydrogen is one transportation fuel option public and private heavy-duty vehicle fleets can consider. Heavy-duty hydrogen fuel cell electric vehicles provide the performance benefits of electric drivetrains (e.g., high instantaneous torque for heavy loads and performance improvements at high altitudes and on steep grades) and can contribute to air quality improvements in high-traffic areas. For some regions and duty cycles, hydrogen could be a better fit for heavy-duty fleets than current battery-electric options because of the increased range and faster fueling times.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Electrification pathways for U.S. passenger vehicles

As electric vehicle (EV) adoption continues to accelerate, we explore the implications of different adoption trajectories that achieve a full transition to EVs by 2050 for U.S. light-duty passenger vehicles (LDVs). Using a vetted transportation system model, we find that achieving 100% EV sales by 2040 would decrease tailpipe greenhouse gases (GHGs) by 90% between 2022 and 2050, leaving about 45 million gasoline vehicles on the road. Achieving 100% sales by 2035, tailpipe emissions decrease 93%, with about 28 million gasoline vehicles on the road in 2050 (9% of stock). Slower EV adoption, reaching 100% sales by 2045, would result in 69 million gasoline vehicles on the road in 2050. Fully electrifying passenger vehicles by 2050 would require a full transition to EVs sales in the 2030s coupled with either changes to mobility, or an accelerated stock turnover in the 2040s with additional 19–30% annual LDV sales.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Final Report for ARPA-E LOCOMOTIVES Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) Project

The Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) is a unique, fully integrated, open-source software tool used to evaluate strategies for cost-effectively deploying advanced locomotive technologies and associated infrastructure. ALTRIOS simulates freight-demand-driven train scheduling, mainline meet-pass planning, locomotive dynamics, train dynamics, energy conversion efficiencies, and energy storage dynamics of line-haul train operations. Because new locomotives represent a significant long-term capital investment and new technologies must be thoroughly demonstrated before deployment, this tool provides guidance on the risk/reward trade-offs and operation integration of different technology rollout strategies. An open, integrated simulation tool is valuable for identifying future research needs and making decisions on technology development, routes, and train selection. This final report details the ALTRIOS software architecture, major modules and components, and data validation process. It demonstrates the software's utility through a 30-year rollout case study targeting high penetration of advanced powertrain technologies by 2050 for two BNSF Railway routes: loaded taconite ore trains from Hibbing, Minnesota, to Superior, Wisconsin, and mixed-freight trains from Superior to Minneapolis, Minnesota.

33 ADVANCED PROPULSION SYSTEMS↗