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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DEPLOYING FAST CHARGING INFRASTRUCTURE FOR ELECTRIC VEHICLES IN URBAN NETWORKS: AN ACTIVITY-BASED APPROACH

This paper explores an important problem under the domain of network modeling, the optimal configuration of charging infrastructure for electric vehicles (EVs) in urban networks considering EV users' daily activities and charging behavior. This study proposes a charging behavior simulation model considering different initial state of charge (SOC), travel distance, availability of home chargers, and the daily schedule of trips for each traveler. The proposed charging behavior simulation model examines the complete chain of trips for EV users as well as the interdependency of trips traveled by each driver. The problem of finding the optimum charging configuration is then formulated as a mixed-integer nonlinear programming problem that considers the dynamics of travel time and travel distance, the interdependency of trips made by each driver, limited range of EVs, remaining battery capacity for recharging, waiting time in queue, and detour to access a charging station. This problem is solved using a metaheuristic approach for a large-scale case network. A series of examples are presented to demonstrate the model efficacy and explore the impact of energy consumption on the final SOC and the optimum charging infrastructure.

Chain of Trips↗
DOE OSTI2025

Enhancing EV Motor Design Through Knowledge-Based AI and Hierarchical Fuzzy Logic Model

This work presents a novel approach to optimizing electric vehicle motor design through the integration of Knowledge-Based Artificial Intelligence (KB-AI) and Hierarchical Fuzzy Logic. Traditional motor design processes are time-intensive, relying heavily on iterative simulations and domain-specific expertise. These processes are further complicated by the nonlinear relationships between key design parameters. The proposed framework addresses these challenges by systematically encoding expert knowledge from scientific literature into a fuzzy logic system, allowing for the efficient handling of complex design variables. The hierarchical fuzzy logic model reduces computational complexity by decomposing the nonlinear relationships into manageable rule sets while maintaining design accuracy. The proposed methodology was applied to the design of a 100 kW motor, yielding optimal values for key parameters. This resulted in a compact motor design with a volume of 2.2 liters, showcasing the framework’s ability to deliver high-performance, application-specific motor configurations.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗
DOE OSTI2025

Macro-micro multiscale modeling to assist the design of HPDC Al castings microstructure and alloys for EV super-large body structures (Phase 1)

Implementation of High Pressure Die Casting (HPDC) Aluminum (Al) body structures for high volume electrified vehicles (EV) to improve electric efficiency remains a key strategy within many original equipment manufacturers (OEM)s. In addition to high strength for safety requirements, superior Self Piercing Riveting (SPR) performance is demanded for HPDC Al alloys to be compatible with high volume SPR joining. In this work, it is proposed to extend and validate an existing Contractor finite element multiscale macro-micro modeling approach to quantify the influence of the microstructure of HPDC alloys on the fracture strain/displacement under 3-point bend and clinch testing. The success of this work will allow to replace solution treatment stage with low energy consumption heat treatment (HT) processes, or to design new non heat treatable (NHT) HPDC Al alloys to eliminate HT requirements. Ultimately, this project will facilitate the application of HPDC Al alloys for super-large vehicle structures to significantly reduce vehicle weight and thus improving energy efficiency. The purpose of this project is to extend and validate an existing f

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2002

Transport of Photoelectrons in the Nightside Magnetosphere

Kinetic modeling results are analyzed to examine the transport of photoelectrons through the nightside inner magnetosphere. Two sources are considered, those on the dayside from direct solar illumination and those across the nightside from light scattered by the upper atmosphere and geocorona. A natural filter exists on the nightside for the dayside photoelectrons. Coulomb collisions erode the distribution at low energies and low L shells, and magnetospheric convection compresses the electrons as they drift toward dawn. It is shown that for low-activity levels a band of photoelectrons forms between L = 4 and 6 that extends throughout the nightside local times and into the morning sector. For the scattered light photoelectrons the trapped zone throughout the nightside is populated with electrons of E less than 30 eV. At high L shells near dawn, convective compression on the nightside yields an accelerated population with electrons at energies up to twice the ionospheric energy maximum (that is, roughly 1200 eV for dayside photoelectrons and 60 eV for scattered light electrons). Modeled energy and pitch angle distributions are presented to show the features of these populations.

Khazanov, G. V.↗
DOE OSTI2025

Macro-micro multiscale modeling to assist the design of HPDC Al castings microstructure and alloys for EV super-large body structures (Phase 1)

Implementation of High Pressure Die Casting (HPDC) Aluminum (Al) body structures for high volume electrified vehicles (EV) to improve electric efficiency remains a key strategy within many original equipment manufacturer (OEM)s. In addition to high strength for safety requirements, superior Self-Piercing Riveting (SPR) performance is demanded for HPDC Al alloys to be compatible with high volume SPR joining. In this work, it is proposed to extend and validate an existing Contractor finite element multiscale macro-micro modeling approach to quantify the influence of the microstructure of HPDC alloys on the fracture strain/displacement under 3-point bend and clinch testing. The success of this work will allow to replace solution treatment stage with low energy consumption heat treatment (HT) processes, or to design new non heat treatable (NHT) HPDC Al alloys to eliminate HT requirements. Ultimately, this project will facilitate the application of HPDC Al alloys for super-large vehicle structures to significantly reduce vehicle weight, and thus improving energy efficiency. The purpose of this project is to extend and validate an existing finite element code, which is based on the Contractor developed macro-micro multi-scale modeling approach, to numerically simulate the three-point bending and clinch test and study the influences of material microstructural characteristics and phase properties on the rivetability. The macro-micro modeling approach begins with a sample scale model and identify the location, which is mostly prone to failure, the deformation history of the boundaries of that location calculated will be used to drive a microstructure-based sub-models where the material microstructure and microscale properties are considered. Using this approach, the wrap-bending failure for two Al alloys are correctly predicted for the first time. This will start with phase I effort of building a framework of macro-micro three point bending test and clinch test of Al10SiMgMn HPDC alloy in the as-cast and T7 heat treated conditions. Those results will then be validated with experimental test results. The phase II effort will involve the utilization of the knowledge learned in phase I to establish the quantitative correlation between the microstructure characteristics and the riveting performance, which will be further used to guide the optimization of HPDC Al alloy microstructure using heat treatment process to achieve sufficient rivetability to join large thin-wall HPDC alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Software/Hardware Framework for Efficient and Safe Emergency Response in Post-Crash Scenarios of Battery Electric Vehicles

The adoption rate of battery electric vehicles (EVs) is rapidly increasing. Electric vehicles differ significantly from conventional internal combustion engine vehicles and vary widely across different manufacturers. Emergency responders (ERs) and recovery personnel may have less experience with EVs and lack timely access to critical information such as the extent of the stranded energy present, high-voltage safety hazards, and post-crash handling procedures in a user-friendly manner. This paper presents a software/hardware interactive tool named Electric Vehicle Information for Incident Response Solutions (EVIRS) to aid in the quick access to emergency response and recovery information. The current prototype of EVIRS identifies EVs using the VIN or Make, Model, and Year, and offers several useful features for ERs and recovery personnel. These features include integration and easy access to emergency response procedures tailored to an identified EV, vehicle structural schematics, the quick identification of battery pack specifications, and more. For EVs that are not severely damaged, EVIRS can perform calculations to estimate stranded energy in the EV’s battery and discharge time for various power loads using either EV dashboard information or operational data accessed through the CAN interface. Knowledge of this information may be helpful in the post-crash handling, management, and storage of an EV. The functionality and accuracy of EVIRS were demonstrated through laboratory tests using a 2021 Ford Mach-E and associated data acquisition system. The results indicated that when the remaining driving range was used as an input, EVIRS was able to estimate the pack voltage with an error of less than 3 V. Conversely, when pack voltage was used as an input, the estimated state of charge (SOC) error was less than 5% within the range of 30–90% SOC. Additionally, other features, such as retrieving emergency response guides for identified EVs and accessing lessons learned from archived incidents, have been successfully demonstrated through EVIRS for quick access. EVIRS can be a valuable tool for emergency responders and recovery personnel, both in action and during offline training, by providing crucial information related to assessing EV/battery safety risks, appropriate handling, de-energizing, transport, and storage in an integrated and user-friendly manner.

25 ENERGY STORAGE↗
DOE OSTI2023

Investigating the effect of aluminum oxide fixed charge on Schottky barrier height in molybdenum oxide-based selective contacts

A tunneling atomic layer deposited (ALD) AlO x layer was inserted in a Si|SiO x |AlO x |MoO x |metal tunnel diode structure to investigate the impact of fixed interface charge on Schottky barrier height. ALD AlO x provides a synthesis-tunable fixed charge and can provide excellent field effect passivation at the SiO x |AlO x interface. A large (>1 × 10 12 q.cm –2 ) negative fixed charge density was expected to decrease Schottky barrier height on p-type silicon and increase Schottky barrier height on n-type silicon by up to 0.4 eV based on an electrostatic model. Fixed charge density and interface trap state density were measured using a thick layer of AlO x in metal oxide semiconductor capacitor structures (MOSCAPs); Schottky barrier height and specific contact resistivity were measured using a tunneling-active layer of AlO x in contacted structures with MoO x . In some samples, HfO x interface layers were inserted between AlO x and silicon to quench the fixed negative charge. The Schottky barrier height was found to vary with processing conditions but did not have a strong correlation with expected fixed charge density. Here, while fixed charge may play a role in determining the Schottky barrier height, other parameters also have significant affect. Further work is needed to minimize contact resistivity and elucidate other factors impacting the Schottky barrier height.

14 SOLAR ENERGY↗
DOE OSTI2026

Efficient Low-Temperature Direct Lithium Extraction from Chloride Brines Enabled by High-Capacity Sorbent

The demand for lithium, a key component in rechargeable batteries for electric vehicles and renewable energy storage systems, has surged in recent years. Meeting this demand requires efficient extraction methods that are both environmentally friendly and economically viable. This study investigates the utilization of the high-capacity sorbent amorphous aluminum hydroxide for enabling efficient direct lithium extraction at low temperatures. Traditional extraction methods often involve acid-leaching and energy-intensive processes that are not only expensive but also environmentally taxing. In contrast, our approach leverages the exceptional sorption properties of amorphous aluminum hydroxide to facilitate lithium extraction directly from brine, achieving extraction efficiencies of 94.4% in case 1 and 96.2% in case 2 at low temperatures. Kinetic modeling using the Avrami–Erofe’ev framework reveals a nucleation-growth mechanism ( n = 0.71, k = 0.131 h –1 ), providing quantitative insights into the solid-state phase transformation process. This method significantly reduces energy consumption and minimizes the environmental footprint. Through systematic experimentation and optimization, we demonstrate the effectiveness and scalability of our approach, highlighting its potential to revolutionize lithium extraction processes. Our findings highlight the potential of high-capacity sorbents, particularly amorphous aluminum hydroxide toward sustainable lithium production, contributing to the advancement of clean-energy technologies.

anions↗
DOE OSTI2025

ADMX Axion Dark Matter Bounds around 3.3 μ eV with Dine-Fischler-Srednicki-Zhitnitsky Discovery Ability

We report the results of a QCD axion dark matter search with discovery ability for Dine-Fischler-Srednicki-Zhitnitsky (DFSZ) axions using an axion haloscope. Sub-Kelvin noise temperatures are reached with an ultralow noise Josephson parametric amplifier cooled by a dilution refrigerator. This work excludes (with a 90% confidence level) DFSZ axions with masses between 3.27 to 3.34 μ eV , assuming a standard halo model with a local energy density of 0.45 G e V / cm 3 made up 100% of axions. Published by the American Physical Society 2025

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Colorado Residential Resiliency and Managed Charging

Validate and model impacts of electric vehicle (EV) home charging on service transformers; analyze diverse grid locations and configurations to determine 'risk factors'; finalize/deliver new design tools and typical EV load curves; improve/issue new construction standards for transformers, secondaries, and services. To ensure residential charging equity, smart charge management strategies will be studied and analyzed with the goal of creating affordable demand charges for customers.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1981

The 805 second X-ray pulsar H2252-035

It is shown that the X-ray flux from the 3.6 hr binary system H2252-035 is modulated at a period of 805 sec, and that its spectrum is consistent with either (1) a 1.4 photon index power law, or (2) a greater-than-20-keV thermal model. A 560 + or - 350 eV equivalent-width iron line at about 6.7 keV is noted, and the possibility that the H2252-035 system contains a slowly rotating neutron star is discussed.

White, N. E.↗
NASA NTRS2004

Assessment of High-Voltage Photovoltaic Technologies for the Design of a Direct Drive Hall Effect Thruster Solar Array

A three-year program to develop a Direct Drive Hall-Effect Thruster system (D2HET) begun in 2001 as part of the NASA Advanced Cross-Enterprise Technology Development initiative. The system, which is expected to reduce significantly the power processing, complexity, weight, and cost over conventional low-voltage systems, will employ solar arrays that operate at voltages higher than (or equal to) 300 V. The lessons learned from the development of the technology also promise to become a stepping-stone for the production of the next generation of power systems employing high voltage solar arrays. This paper summarizes the results from experiments conducted mainly at the NASA Marshal Space Flight Center with two main solar array technologies. The experiments focused on electron collection and arcing studies, when the solar cells operated at high voltages. The tests utilized small coupons representative of each solar array technology. A hollow cathode was used to emulate parts of the induced environment on the solar arrays, mostly the low-energy charge-exchange plasma (1012-1013 m-3 and 0.5-1 eV). Results and conclusions from modeling of electron collection are also summarized. The observations from the total effort are used to propose a preliminary, new solar array design for 2 kW and 30-40 kW class, deep space missions that may employ a single or a cluster of Hall- Effect thrusters.

Mikellides, I. G.↗
DOE OSTI2021

Evaluating long-term emission impacts of large-scale electric vehicle deployment in the US using a human-Earth systems model

While large-scale adoption of electric vehicles (EVs) globally would reduce carbon dioxide (CO 2 ) and traditional air pollutant emissions from the transportation sector, emissions from the electric sector, refineries, and potentially other sources would change in response. Here, a multi-sector human-Earth systems model is used to evaluate the net long-term emission implications of large-scale EV adoption in the US over widely differing pathways of the evolution of the electric sector. Our results indicate that high EV adoption would decrease net CO 2 emissions through 2050, even for a scenario where all electric sector capacity additions through 2050 are fossil fuel technologies. Greater net CO 2 reductions would be realized for scenarios that emphasize renewables or decarbonization of electricity production. Net air pollutant emission changes in 2050 are relatively small compared to expected overall decreases from recent levels to 2050. States participating in the Regional Greenhouse Gas Initiative experience greater CO 2 and air pollutant reductions on a percentage basis. These results suggest that coordinated, multi-sector planning can greatly enhance the climate and environmental benefits of EVs. Additional factors are identified that influence the net emission impacts of EVs, including the retirement of coal capacity, refinery operations under reduced gasoline demands, and price-induced fuel switching in residential heating and in the industrial sector.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Short-Term Load Forecasting Considering EV Charging Loads with Prediction Interval Evaluation

Short-term load forecasting plays a critical role in power system planning and operation. Along with the electrification of various loads, electricity demands are becoming increasingly hard to predict. Notably, the recent rise in electric vehicles (EVs) has further contributed to this unpredictability. To address this issue, this paper proposes a probabilistic load forecasting strategy utilizing Gaussian process regression, structured in a day-ahead manner. While many works focus on deterministic prediction, probabilistic forecasting offers additional insights into variability and uncertainty, enabling more flexible and reliable operation for power systems. To enhance the accuracy of the load forecasting model, the inputs include features related to EV charging habits as well as commonly used weather information. The load forecasting results are evaluated using various metrics, including conventional ones that assess the accuracy of point forecasts, as well as additional metrics that test the reliability of prediction intervals. The proposed load forecasting method is finally tested on real residential power consumption data and EV charging data sampled from real-world sources. The results prove that the new features can greatly improve the performance of the load forecasting method.

electrical vehicle↗
DOE OSTI2024

Levelized cost of charging of extreme fast charging with stationary LMO/LTO batteries

Extreme DC fast charging for electric vehicles (EVs) could be competitive with the internal combustion engine refueling experience and enable longer-distance travel, which could help with EV adoption and decarbonization, but these systems have high capital costs and extremely variable high-power demands. Behind-the-meter systems (BTMS) could support extreme-fast-charging (XFC) stations to increase nationwide adoption of EVs. Here, this study examines the optimal break-even levelized cost of charging (LCOC) across 96 BTMS scenarios to enable low-wait XFC stations providing 200 miles of charge in 10 min. This research simulates LCOC via synthetic XFC-capable EV loads, machine-learned battery life models from testing data, and nonlinear optimal controls, co-minimizing complex utility costs and battery replacements. An aggregate optimal BTMS design treating each EV load as equal likely gives an optimal LCOC per utility rate, the average of which is $\$$0.59/kWh. In addition, the sensitivity of optimal and off-optimal design factors, the long-life LMO/LTO chemistry, and optimized controls are analyzed. The battery control model, based on battery stressors to compare chemistries, optimizes LMO/LTO resting state of charge and cycle depth without compromising cost reduction, which enables greater flexibility in operation. The LCOC savings due to replacement reduction are small, up to $\$$0.035/kWh (6%), with an average of $\$$0.02/kWh (3.5%). Compared with gasoline stations, the aggregate XFC station design achieves comparable speed, experience of service, and cost at $\$$3.81/gal gasoline, showing that EVs can replace gasoline vehicles even for longer-distance travel.

25 ENERGY STORAGE↗
DOE OSTI2023

Impact Analysis of Future Electric Vehicles Using Model of Real Distribution Feeders

Globally, the number of electric vehicles (EVs) continues to increase. This on-going trend poses challenges for power distribution systems. The inclusion of electric vehicle supply equipment (EVSE) should be compatible with a changing energy system, whose structure is becoming increasingly distributed. The impact of future EVs should be analyzed and considered in the system planning and upgrades. In this study, impact analysis of future EVs is conducted for a utility company of U.S. West Coast. Real data of distribution feeders is converted into the GridLAB-D model for running power flow analysis. An estimation of the additional loading of EVs in 2050 is provided by the utility company. Simple mitigation methods are tested to improve voltage profiles and complete this case study.

Xie, Jing↗
NASA NTRS1993

Photoresponse Model for Si_(1-x)Ge_x/Si Heterojunction Internal Photoemission Infrared Detector

A photoresponse model has been developed for the Si_(1-x)Ge_x/Si heterojunction internalphotoemission (HIP) infrared detector at wavelengths corresponding to photon energies less than theFermi energy. A Si_(0.7)Ge_(0.3)/Si HIP detector with a cutoff wavelength of 23 micrometers andan emission coefficient of 0.4 eV^(-1) has been demonstrated. The model agrees with the measureddetector response at lambda greater than 8 micrometers. The potential barrier determined by themodel is in close agreement (difference similar to 4 meV) with the potential barrier determined by theRichardson plot, compared to the discrepancies of 20-50 meV usually observed for PtSi Schottkydetectors.

Lin, T.↗