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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

TSDC: Transportation Secure Data Center: Real-World Data for Planning, Modeling, and Analysis

The Transportation Secure Data Center is a centralized repository for high-resolution transportation data from hundreds of travel and transit surveys and studies. It makes vital transportation data broadly available to users while preserving the privacy of survey participants. It houses surveys and studies conducted by state departments of transportation, metropolitan planning organizations, transit agencies, cities, and other public agencies. Meanwhile, the Livewire Data Platform empowers research, industry, and academic partners to easily and securely preserve, maintain, share, discover, and gain access to transportation and mobility data. Livewire accommodates a range of datasets, including behavioral, experimental, model, analytical, and raw data at the vehicle, traveler, and system levels. Datasets support mobility research and planning spanning urban science, connected and automated vehicles, fueling and charging infrastructure, mobility decision science, multimodal transportation, vehicle efficiency, and more.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Foil Bearing Supported Compressor-Expander

R&D Dynamics Corporation (RDD) is developing a fuel cell system compressor-expander designed for heavy-duty vehicle applications. The system emphasizes high reliability, versatility, long service life, and cost-effective mass production. Its design integrates a high-speed centrifugal compressor/expander, oil-free foil air/gas bearings, a direct current permanent magnet (DCPM) motor, and an inverter utilizing silicon carbide (SiC) switches. Key advantages include high efficiency, compact size and reduced weight, enhanced reliability, and elimination of oil contamination risks. The technology targets multiple sectors such as long-haul semi-trucks, mining and construction equipment, power generation, data centers, marine systems, and other heavy machinery. Evaluation units are ready for shipment, and manufacturing capabilities are currently being developed. Contract Number: DE-EE0009617 (2021).

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Analysis Program (2023 Annual Progress Report)

This document summarizes the progress of VTO Analysis projects supported during the fiscal year 2023. The VTO Analysis Program supports mission-critical technological, economic, and interdisciplinary analyses to assist in prioritizing VTO technology investments and to inform research portfolio planning. These efforts provide essential vehicle and market data, modeling and simulation, and integrated and applied analyses, using the unique capabilities, analytical tools, and expertise resident in the DOE’s national laboratory system. VTO Analysis projects also demonstrate additional capabilities and expertise provided by research partnerships that may include academia, the private sector, and non-profit organizations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

High Voltage High Power Traction Inverter Thermal Management

This project develops thermal management solutions for various 530-kW inverter topologies being developed by Oak Ridge National Laboratory (ORNL). The thermal management solutions will provide high thermal performance and be designed to keep inverter components (e.g., power modules, capacitors) within allowable operating temperatures to help meet the project objectives. Steady-state and transient thermal models of the inverter and cooling system will be created and used to predict component temperatures under various drive cycle conditions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Resilient and Cost-Effective Hybrid Li-Ion Battery Energy Storage System for Sites with Solar Generation and Electric Vehicle (EV) Charging (CRADA Final Report, CRD-19-00799)

The batteries of an energy storage system designed for multiple use-cases are traditionally selected to withstand the highest rate at which a battery is discharged relative to its maximum capacity (C-rate) and cycling requirements of the most intense use-case. However, this is not cost-effective given that the price of the batteries is strongly correlated to C-rate and cyclability. We propose to establish design guidelines for a hybrid energy storage system and test an edge controller that uses high-power and high-energy batteries for high- cyclability use cases such as frequency regulation and electric vehicle (EV) charging and low-cost batteries for low-power and low-cyclability use cases such as summer peak loads. The three main objectives of this proposal are (i) establishing sizing guidelines for such a hybrid storage system, (ii) installing a hybrid storage system in the Energy Systems Integration Facility (ESIF) sized based on those guidelines, and (iii) testing an edge controller specific for the system through hardware tests.

14 SOLAR ENERGY↗
DOE OSTI2024

Misalignment Tolerant Three-phase Wireless Fast Charging System for Electric Vehicles

This project proposes improving the technology level of the three-phase wireless charging technology developed at Oak Ridge National Laboratory (ORNL). Successful commercialization of wireless charging systems require that they meet strict safety standards for electromagnetic field emissions and interoperability with other wireless charging technology. ORNL has previously demonstrated a 50kW three-phase wireless power transfer system with 95% efficiency. This prototype system weighed less than 50% of similar high-power wireless charging system while simultaneously exhibiting better safety characteristics. Due to better material utilization, the reduction in mass is expected to translate into similar cost reduction for the magnetic coupler. Additionally, the smaller footprint of the system can ease vehicle integration difficulties that would be encountered using other technology. Furthermore, the three-phase design can be made to operate with existing single-phase coupler design more easily and without intentional physical misalignment which would otherwise pose safety issues. This project developed ORNL’s WPT technology to satisfy the specifications and requirements for electric vehicle (EV) charging. The result of the project will be a prototype and reference design for a high-power wireless charging system—including magnetics, power electronics, and controls—serving as a baseline for product development.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

EV Forecasting-Based Model Predictive Control for Distribution System Congestion Mitigation

The uncoordinated charging of electric vehicles (EVs) in time and space brings congestion issues to the distribution network. This paper proposes an EV charging demand forecasting-based model predictive control (MPC) method for distribution system congestion management. To effectively forecast the time-series EV station charging demand, a hybrid forecasting model that integrates the long short-term memory network (LSTM) and Transformer is proposed. The Transformer-LSTM model is trained using a one-year real historical charging dataset of EV stations to forecast future charging demand in 15-minute intervals. This informs the MPC for distribution network congestion management and minimization of PV curtailment. Numerical results carried out on the modified IEEE 123-bus distribution system demonstrate that the proposed method can effectively resolve line congestion issues through EV smart charging and PV curtailment while outperforming other benchmarks.

ADVANCED PROPULSION SYSTEMS,SOLAR ENERGY↗
DOE OSTI2024

Safety Codes and Standards Review and Gap Analysis for Applicability to Hydrogen Rail Refueling, Defueling, Maintenance, and Storage

Hydrogen-powered locomotives may present an alternative to diesel for achieving transportation-related decarbonization, energy security, and resilience goals. As an emerging technology, hydrogen locomotives may not have adequate representation in current safety codes and standards. NFPA 2 and other appropriate codes and standards were reviewed to identify technical gaps in the code for hydrogen rail defueling, refueling, maintenance, and storage. Several technical gaps pertaining to setback distances, allowable quantities, ventilation rates, and grounding have been identified. Fueling requirements can be informed by road vehicle standards but may need to be revised for larger quantity hydrogen locomotive systems. Since there are no hydrogen-specific locomotive design and safety standards, some aspects of diesel-based locomotive standards may apply. CGA G- 5.5 currently provides the most guidance on height, placement, orientation, and design of vent systems, while other standards emphasize the importance of shielding vent stacks and provide requirements for orientation of their discharge.

08 HYDROGEN↗
DOE OSTI2025

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗
DOE OSTI2026

A High Power Density and High Efficiency Traction Drive Based on a Segmented Inverter and an Axial and Radial Flux Hybrid Machine

Eaton Corporation and Oak Ridge National Laboratory (ORNL) collaborated to develop a high performance traction drive system aimed at increasing power density and overall efficiency. The system integrates Eaton’s hybrid flux motor—combining radial and axial flux paths to convert end-winding and structural elements into torque-producing components—with ORNL’s high-power-density segmented inverter. This motor design achieves higher torque density within the same footprint as traditional radial flux machines by effectively utilizing end turns. ORNL’s segmented inverter reduces the DC bus capacitor requirement by over 50% compared to standard voltage source inverters (VSIs), achieving power densities exceeding 100 kVA/L. The dual-module architecture also enables six-phase operation, aligning with Eaton’s motor design. Together, the motor and inverter offer a compact, efficient traction drive system with the potential for significant reductions in system weight and improvements in powertrain efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System: Preprint

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Integrating the Mobility Energy Productivity Metric Into the Delaware Department of Transportation Statewide Model

The Mobility Energy Productivity (MEP) metric quantifies the quality of mobility at a given location and evaluates how changes in the transportation system impact mobility over time, such as through infrastructure investments. This study demonstrates the integration of the MEP metric into the Delaware Department of Transportation's (DelDOT's) transportation planning process by utilizing data from its statewide travel demand model. Specifically, the study assesses MEP for the 2020 baseline conditions and three alternative scenarios - 2030, Churchman, and Old Orchard - across multiple travel modes, including driving, walking, biking, and transit. The findings highlight that mobility and accessibility in Delaware are primarily supported by the driving mode, while transit services remain relatively limited, often ranking below biking and walking in many areas. In the 2030 scenario, where network operations and opportunities expand as projected, overall statewide accessibility declines, although Kent and Sussex counties experience improvements. The results from the Churchman and Old Orchard scenarios indicate that local network enhancements can positively influence accessibility, though primarily at a localized level, demonstrating MEP's capability to capture regional accessibility changes. Further, the National Renewable Energy Laboratory team successfully transferred MEP operational knowledge to the DelDOT team through dockerization, enabling DelDOT to independently run MEP for various scenarios of interest. Integrating MEP into DelDOT's planning framework supports future project evaluations and decision-making by incorporating access to opportunities as a key dimension of transportation system assessment.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Measuring Flexibility through Reduction Potential

As electrical loads, electric vehicles (EVs) are distinguished in many cases by their substantial flexibility. Harnessing this flexibility, however, requires a precise characterization of its timing and degree. Current approaches to flexibility characterization tend to be limited either by the complexity of their representation or their inability to capture aggregate flexibility across multiple vehicles. In this paper, we present the reduction potential matrix, a novel metric capturing fleet-level EV load flexibility while being both straightforward to calculate and intuitive to interpret. We use the metric to quantify flexibility for two operationally distinct commercial groups: freight vehicles and transit buses. While we find that both vehicle groups have substantial flexibility, its timing, magnitude, and duration varies across the groups. We describe how this variability translates into variation in the each group's role as a grid resource, and conclude with a discussion of how system planners, fleet operators, and other stakeholders can use the novel metric to cultivate symbiosis between vehicles and the grid.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Human Supervision of Autonomous Vehicle Fleet Operations and Associated Passenger Communications: Preprint

Advances in automated vehicle (AV) technology and expanded operations are rapidly emerging with Automated Mobility District (AMD) deployments in global cities. NLR's AMD research addresses critical elements of human supervision of AV fleet operations and associated passenger communications for vehicles in which no driver or safety attendant is present. Although sufficiently advanced AVs no longer have direct oversight by a driver, fleet management remains staffed with operations personnel at the operations command and control (OCC) facility. This paper examines the functionality of the OCC, drawing comparisons of how automated train control and automated people mover OCCs operate. Within an AMD, the OCC manages various vehicle types, sizes, and operational modes, including on-demand and fixed route service, to facilitate a 'network of networks' for transport within a metropolitan area. The OCC serves as oversight for multiple AV fleets assisting AVs via remote operation of vehicles, communication, and dispatching personnel to resolve problems. The OCC also coordinates system operation, geographically staging vehicles, and managing weather, police, and emergency events. Informed by traffic management center (TMC) strategies using highly integrated software and communications, OCCs facilitate seamless information flows. OCC personnel remotely assist passengers and oversee multi-party operation to ensure safety and security. Although social norms mitigate large-capacity unattended vehicle operations, social interaction in multi-party automated small vehicles has little precedent. This poses a new frontier for society and requires research to effectively understand and manage. Future research will monitor OCC implementations, passenger interfaces, and deployment scaling of initial AMD systems.

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 OSTI2025

High Efficiency and Transient Air Systems for Affordable Load-Following Heavy Duty Truck Fuel Cells

Hydrogen fuel cell powered vehicles are one of the potential paths to reducing vehicle emissions. An important subsystem of the hydrogen fuel cell system is an air handling system that provides the needed oxygen (in air) to react with hydrogen in the fuel cell stack for electric power generation. Today’s systems use an electric motor to power an air compressor that supplies oxygen to the fuel cell stack. This process requires significant electrical power and is the largest parasitic power loss in hydrogen fuel cell vehicles. In addition to parasitic power loss, hydrogen fuel cell systems often have reliability issues associated with the air handling system. Reliability is of significant concern for heavy duty applications (especially long-haul applications). This project aims to improve both the electrical power consumption and reliability of hydrogen fuel cell air handling systems to meet the needs of heavy duty on-highway vehicle applications.

08 HYDROGEN↗