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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Garnet solid electrolyte blended LiNi 0.6 Mn 0.2 Co 0.2 O 2 as high-voltage stable cathodes for advanced lithium-ion batteries

Ni-rich LiNi 1-x Co x/2 Mn x/2 O 2 layered materials have been widely adopted as cathodes for current electric vehicles (EVs) due to their high gravimetric and volumetric energy densities. However, their high-voltage instability (e.g., > 4.3 V vsLi ) limited their usable capacities corresponding to about 60 – 70 % of theoretical capacities. The major problems of high-voltage operation stem from instability of Ni 3+/4+ at cathode-electrolyte interphase (CEI) in contact with electrolytes. Here we propose garnet-type Li 6.7 La 3 Zr 1.7 Ta 0.3 O 12 (LLZT) solid-electrolyte-blended LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC) as high-voltage stable cathodes. The LLZT not only passivates the CEI but scavenges protons and moisture in electrolytes. From well-balanced ionic and electronic transport properties, 5 wt% LLZT blended NMC cathodes delivered enhanced electrochemical performances in full-cells. Unlike other complicated coating processes, our proposed solid-electrolyte blending approach can be readily implementable in commercial Li-ion batteries due to its manufacturing friendliness, energy saving, and cost effectiveness.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Operational Simulation of Multi-Functional Charging Station for Sustainable Transportation

As transportation systems move toward electrification and decarbonization, multifunctional charging stations (MFCS) are emerging as key infrastructure for electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs). This paper presents a simulation model of an MFCS that integrates solar photovoltaic (PV), wind power, battery storage, hydrogen (\mathrm{H}_{2}) production, dual-pressure \mathrm{H}_{2} storage, fuel cells, and dynamic grid interactions. The model simulates daily operations using 5 -minute resolution data to capture realtime variability in renewable energy (RE), demand, and electricity prices. A flexible dispatch algorithm dynamically allocates energy for EV charging, \mathrm{H}_{2} production, storage, and grid transactions while respecting system constraints. Results show that the MFCS effectively prioritizes RE usage, minimizes waste, meets diverse energy demands, and achieves net operational profit. The model serves as a valuable decision-support tool for designing and optimizing integrated clean energy hubs for zero-emission transportation.

Gbadegoye, Jeremiah [University of Tennessee, Knox↗
DOE OSTI2020

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids: Preprint

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. Different types of DERs such as Photovoltaics (PV), energy storage, electric vehicles (EVs), etc. have varying effects on the grid based on how and where they are deployed. Again, the DER deployment and its impact are network-dependent, while the traditional electric grids were not designed to host DERs. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper investigates the impacts of integrating a mix of DERs in the utility distribution network in Colorado, U.S. Firstly, BTM DERs at the residential scale including distributed PV; battery energy storage systems (BESS); heating, ventilation, and air-conditioning (HVAC) load; electric water heater (EWH) load; and EVs are modeled. The impacts of integrating these resources on the distribution network are evaluated by conducting time-series simulations for different scenarios considering different days to capture the worst-case conditions. Monte Carlo simulations are conducted to generate the realistic EV charging profile. The voltage issues, substation transformer loadings, and critical nodes in the network are identified with the incorporation of uncoordinated EV charging loads and other DER in the network. This analysis helps visualize the DER impact on the grid, identify the challenges, and provides an insight into the new distribution management and control needs to enable reliable and resilient distribution grid operations. Additionally, further analysis is performed to estimate the daily residential electricity cost with the inclusion of DERs under time-of-use tariffs. The result shows the daily residential electricity cost reduced by 20:7% on average with DERs compared to the case without DERs.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2021

Molten Salt Assisted Low-Temperature Electro-Catalytic Graphitization of Coal Chars

A great effort has been centered around developing clean energy technologies (energy storage devices) to curtail burning fossil fuels' deleterious environmental effects. Rechargeable batteries [lithium-ion batteries (LIBs)] are among the most invested and investigated storage devices showing potential to transform fossil fuel-powered mobility to next-generation safe electromobility. However, LIBs powered electric vehicles (EV) are expensive due to the high-cost graphite anode associated with LIBs. Herein, the synthesis of low-cost, highly crystalline nano-graphite with a tunable microstructural architecture has been demonstrated via molten salt assisted low-temperature electro-catalytic graphitization of coal chars, traditionally non-graphitizable carbon. Thus, graphite derived from coal chars exhibited nanoflake architecture and delivered high reversible capacity, stable long cycle life, and excellent electrochemical performance under fast charging/discharging conditions (5C, ~12 min charge/discharge time). This finding paves the way to manufacture cost-effective high-energy-density batteries using as-synthesized graphite from readily available coal sources that could propel the EVs to the next level.

25 ENERGY STORAGE↗
DOE OSTI2024

Battery Energy Storage Systems: A Review of Energy Management Systems and Health Metrics

With increasing concerns about climate change, there is a transition from high-carbon-emitting fuels to green energy resources in various applications including household, commercial, transportation, and electric grid applications. Even though renewable energy resources are receiving traction for being carbon-neutral, their availability is intermittent. To address this issue to achieve extensive application, the integration of energy storage systems in conjunction with these resources is becoming a recommended practice. Additionally, in the transportation sector, the increased demand for EVs requires the development of energy storage systems that can deliver energy for rigorous driving cycles, with lithium-ion-based batteries emerging as the superior choice for energy storage due to their high power and energy densities, length of their life cycle, low self-discharge rates, and reasonable cost. As a result, battery energy storage systems (BESSs) are becoming a primary energy storage system. The high-performance demand on these BESS can have severe negative effects on their internal operations such as heating and catching on fire when operating in overcharge or undercharge states. Reduced efficiency and poor charge storage result in the battery operating at higher temperatures. To mitigate early battery degradation, battery management systems (BMSs) have been devised to enhance battery life and ensure normal operation under safe operating conditions. Some BMSs are capable of determining precise state estimations to ensure safe battery operation and reduce hazards. Precise estimation of battery health is computed by evaluating several metrics and is a central factor in effective battery management systems. In this scenario, the accurate estimation of the health indicators (HIs) of the battery becomes even more important within the framework of a BMS. This paper provides a comprehensive review and discussion of battery management systems and different health indicators for BESSs, with suitable classification based on key characteristics.

Nazaralizadeh, Solmaz (ORCID:0009000737004039)↗
DOE OSTI2023

A Solid Zn-Ion Conductor from an All-Zinc Metal–Organic Framework Replete with Mobile Zn 2+ Cations

Here, we describe the synthesis and properties of Zn 3 [(Zn 4 Cl) 3 (BTT) 8 ] 2 (ZnZnBTT, BTT 3– = 1,3,5-benzenetristetrazolate), a heretofore unknown member of a well-known, extensive family of metal–organic frameworks (MOFs) with the general formula M II 3 [(M II 4 Cl) 3 (BTT) 8 ] 2 , which adopts an anionic, sodalite-like structure. As with previous members in this family, ZnZnBTT presents two crystallographically distinct metal cations: a skeletal Zn 2+ site, fixed within Zn 4 Cl(tetrazole) 8 secondary building units (SBUs), and a charge-balancing Zn 2+ site. Self-assembly of ZnZnBTT from its building blocks has remained elusive; instead, we show that ZnZnBTT is readily accessed by quantitative postsynthetic exchange of all Mn 2+ ions in MnMnBTT with zinc. We further demonstrate that ZnZnBTT is a promising Zn-ion conductor owing to the mobile charge-balancing extra-framework Zn 2+ cations. The new material displays a Zn-ion conductivity of σ = 1.15 × 10 –4 S/cm at room temperature and a relatively low activation energy of E a = 0.317 eV, enabling potential applications in the emerging field of quasi-solid-state zinc-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Dendrite Growth Morphology Modeling in Liquid and Solid Electrolytes

The main goal of this project is to develop a multi-scale modeling approach that connects micron-scale phase-field models and atomic-scale density functional theory (DFT)-based simulations via parameter- and relationship-passing in order to predict Li-metal dendrite morphology evolution, in both liquid and solid electrolytes. The key hypothesis of the DFT-informed phase-field multiscale modeling approach is that it can capture the electrochemical-mechanical driving forces and incorporate the roles of nano-meter-thin solid electrolyte interphase (SEI) in liquid electrolytes as well as of the microstructures of micro-meter-thick solid electrolytes (SEs) for all-solid-state batteries. In this project, we have formulated and implemented phase-field models to incorporate the electrochemical driving forces in liquid electrolytes and then incorporate mechanical driving forces to simulate dendrite growth in solid electrolytes with resolved microstructures. We have implemented two treatments for the SEI: an explicit model to include the microstructure of the SE or SEI in the phase field model and an implicit model to simulate the impact of nano-meter thick SEI in liquid electrolytes by varying the electrode/electrolyte interfacial properties. The key interfacial properties, including the electronic and ionic transport properties, the charge transfer reaction kinetics, and mechanical properties, were computed by DFT-based calculations. At the DFT-based model, one key advancement is to directly predict the charge transfer reaction kinetics at a complex Li/SEI/electrolyte interface by linking DFT with density functional tight binding (DFTB) calculations. As the main accomplishments, we have demonstrated two successful predictions in both solid electrolyte and liquid electrolyte based on this multiscale approach. The predicted intergranular Li dendrite growth in LLZO revealed the importance of trapped electrons at internal interfaces in the microstructure of LLZO. The predicted electroplating morphology of mossy Li and faceted Mg agreed well with experiments. The insights provided by the multiscale model and the model enabled electrolyte and SEI design will accelerate the development of Li-metal electrode for high energy density batteries, that meet DOE’s target on cell density (>350 Wh/kg) and cost below $100/kWhuse for EV applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Optimized Renewable Energy Integration for EV High-Power Dynamic Wireless Charging Systems

Dynamic wireless charging for electric vehicles is an emerging technology to reduce on-board battery size and extend driving range. Due to its unique characteristic of vehicle-speed-related pulse-like load profile, the high-power dynamic wireless charging system (DWCS) introduces high stress to the utility grid. In this paper, an optimization model for renewable energy integration in the DWCS is proposed to mitigate the grid impact and minimize the operation costs of the whole system. As the load profile of DWCS is related to the traffic volume and various approaching vehicle speeds, the annual average daily traffic data and a stochastic model are used to develop 24-hour load profile of DWCS. To find a tradeoff between grid impact mitigation and operation costs minimization, relationships among power demand from power grid, photovoltaic (PV) capacity, wind energy (WE) capacity and energy storage (ES) capacity are analyzed, and the optimization objective and constraints are developed. Numerical simulation results demonstrate that energy storage integration can greatly mitigate the grid impact of DWCS, and optimal ratio of PV and WE can significantly reduce the operation cost of DWCS.

Zeng, Rong↗
DOE OSTI2025

Integrated On-Board Charger for Dual Motor Based Electric Vehicle Power Train

This paper presents an integrated on-board charger for dual motor based electric vehicle (EV) power train with silicon carbide semiconductor switch-based traction inverters. The proposed charger architecture reconfigures the traction inverters to be used in the battery charging mode, thereby eliminating several high frequency switches and their accessories. The motor windings are reused as line inductors for the power factor correction (PFC) rectifier stage in the charging mode thereby reducing the requirements of magnetic components. The architectures reduce the cost, weight, and volume of the EV power train. Simulation results are presented to demonstrate the working principle of the proposed architecture.

Mukherjee, Subho [ORNL] (ORCID:0009000672297925)↗
DOE OSTI2022

Battery anode design: From 1D nanostructure to 3D nanoarchitecture – Enabling next-generation energy storage technology

Recently, many studies have reported the efficacy of 1D silicon nanostructures as anode materials (mostly nanowires) due to their large surface to volume ratio which could be an advantage in terms of charging kinetics. Anode design is a crucial factor for the further development of lithium-ion battery (LIB) technology, especially in terms of achieving the high charging rate performance, as typically needed in electric vehicles (EV). 3D nanostructures have been identified as the key to dramatically enhanced charging rate of LIB, in addition to the change of materials (from carbon-based anode to silicon-based). However, existing fabrication methodologies for 3D nanostructures are inherently expensive – using advanced lithography techniques or other nanopatterning methodologies, as well as using additive manufacturing approaches. Electrospinning (as an integrated additive manufacturing methodology) may be used to produce low-cost 3D-printed fiber structures. Here, in the present study, we demonstrate the groundwork in this field of research in the past 3–4 years, which would allow the extension of this special additive manufacturing approach to reach nanoscale 3D-printed fiber structures more economically and with scalability for manufacturing. This would pave the way to achieve the order of magnitude increase in battery charging rate as needed to realize the vision of the electrification of mobility/transportation.

25 ENERGY STORAGE↗
DOE OSTI2023

Optimal Power Sharing Speed Compensation in On-road Wireless EV Charging Systems

Dynamic wireless charging of electric vehicles (EV) is an emerging technology with the potential to address range anxiety and reduce the size of batteries or provide charge-sustaining operation. Charging demand for dynamic wireless charging systems (DWCS) varies greatly in response to location-specific traffic behaviors including the number and speed of vehicles. This paper highlights the potential reduction of load variation with speed compensation and simulates opportunities to maximize the number of cars charged concurrently through “power sharing” or altering power output to slower cars while maintaining a maximum delivered energy. An improved sub-minute model for synthetic traffic is proposed to effectively model DWCS load on high speed roadways and a power electronics model is created based on an existing prototype developed by ORNL to investigate the potential for power sharing. Reductions in the average speed of traffic can greatly increase instantaneous DWCS load by as much as 26%, complicating capacity sizing. Parametric studies with a LCC-S power electronics model shows feasible power reduction of more than 20%, while maintaining a maximum achievable efficiency greater than 90%. Speed compensation on a roadway with large speed variation can reduce average power expected by 21% and increase the maximum number of cars charged simultaneously by 30%. The application of power sharing may significantly reduce load variability due to speed, allow for increased car hosting capability, and guarantee a maximum energy delivered.

Lewis, Donovin D.↗
DOE OSTI2022

K 3 SbS 4 as a Potassium Superionic Conductor with Low Activation Energy for K–S Batteries

Abstract Solid‐state K‐ion conducting electrolytes are key elements to address the current problems in K secondary batteries. Here, we report a sulfide‐based K‐ion conductor K 3 SbS 4 with a low‐activation energy of 0.27 eV. W‐doped K 3− x Sb 1− x W x S 4 ( x =0.04, 0.06, 0.08, 0.10 and 0.12) compounds were also explored for increasing vacancy concentrations and improving ionic conductivity. Among them, K 2.92 Sb 0.92 W 0.08 S 4 exhibits the highest conductivity of 1.4×10 −4 S cm −1 at 40 °C, which is among the best reported potassium‐ion conductors at ambient temperature. In addition, K 2.92 Sb 0.92 W 0.08 S 4 is electrochemically stable with long‐chained potassium polysulfide of K 2 S x . A room‐temperature solid potassium–sulfur (K−S) battery system has therefore been successfully demonstrated, which is the first K−S battery prototype using non‐commercial inorganic‐based electrolyte to block the polysulfide shuttle.

Shao, Jieren↗
DOE OSTI2022

K 3 SbS 4 as a Potassium Superionic Conductor with Low Activation Energy for K–S Batteries

Abstract Solid‐state K‐ion conducting electrolytes are key elements to address the current problems in K secondary batteries. Here, we report a sulfide‐based K‐ion conductor K 3 SbS 4 with a low‐activation energy of 0.27 eV. W‐doped K 3− x Sb 1− x W x S 4 ( x =0.04, 0.06, 0.08, 0.10 and 0.12) compounds were also explored for increasing vacancy concentrations and improving ionic conductivity. Among them, K 2.92 Sb 0.92 W 0.08 S 4 exhibits the highest conductivity of 1.4×10 −4 S cm −1 at 40 °C, which is among the best reported potassium‐ion conductors at ambient temperature. In addition, K 2.92 Sb 0.92 W 0.08 S 4 is electrochemically stable with long‐chained potassium polysulfide of K 2 S x . A room‐temperature solid potassium–sulfur (K−S) battery system has therefore been successfully demonstrated, which is the first K−S battery prototype using non‐commercial inorganic‐based electrolyte to block the polysulfide shuttle.

25 ENERGY STORAGE↗
DOE OSTI2024

EVs@Scale NextGen Profiles: High Level Analysis and Procedures Report

As part of the U.S. DOE EVs@Scale consortium, the NextGen Profiles (NGP) project presents analysis and results from the study of High Power Charging Electric Vehicles and Battery Charging Infrastructure. High Power Charging equipment is capable of recharging electric vehicle traction batteries at power levels of 200KW and above. The NextGen Profiles project has three pillars of investigation: Electric Vehicle Charging Profile Capture, Electric Vehicle Service Equipment Performance Characterization and Fleet Utilization analysis. All NextGen Profiles project testing was conducted under test conditions that comprise a diverse range of realistic real-world operating conditions including nominal conditions that should transfer the maximum allowable energy in the minimum time possible and off-nominal conditions that typify charging performance under suboptimal charging conditions. Results from 13 unique EVs, eight EVSEs and four electrified fleets are included in the NextGen Profiles project analysis.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Demonstration of an AI-driven workflow for dynamic x-ray spectroscopy

X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but requires collecting data at many energy points which can be time-consuming. While adaptive sampling methods exist for efficiently collecting spectroscopic data, they often lack domain-specific knowledge about the structure of XANES spectra. Here we demonstrate a knowledge-injected Bayesian optimization approach for adaptive XANES data collection that incorporates understanding of spectral features like absorption edges and pre-edge peaks. We show this method accurately reconstructs the absorption edge of XANES spectra using only 15–20% of the measurement points typically needed for conventional sampling, while maintaining the ability to determine the x-ray energy of the sharp peak after the absorption edge with errors less than 0.03 eV, the absorption edge with errors less than 0.1 eV; and overall root-mean-square errors less than 0.005 compared to traditionally sampled spectra. Our experiments on battery materials and catalysts demonstrate the method’s effectiveness for both static and dynamic XANES measurements, improving data collection efficiency and enabling better time resolution for tracking chemical changes. This approach advances the degree of automation in XANES experiments, reducing the common errors of under- or over-sampling points near the absorption edge and enabling dynamic experiments that require high temporal resolution or limited measurement time.

Bayesian optimization↗
DOE OSTI2025

EVs@Scale Next-Gen Profiles - EV Profile Capture 2024

As part of the U.S. DOE EVs@Scale consortium Next-Gen Profiles (NGP) project, the profile capture and analysis of production electric vehicles undergoing high power charging (HPC) is conducted over a wide range of conditions to explore variance and performance. Charge session parameters are collected from both the electric vehicle (EV) and electric vehicle supply equipment (EVSE) at a rate of 10Hz and entered into a time-series database for analysis. These charge profiles are captured under nominal and off-nominal conditions, exploring the impact of battery state of charge (SOC), battery temperature, vehicle condition, smart charge management (SCM), and EVSE limitations. Nominal conditions are defined to be ideal conditions that should transfer the maximum allowable energy in the minimum possible amount of time. Nominal condition profiles are compared across EVs to characterize state-of-the-art EV charging performance against one another. Off-nominal condition profiles are compared against its nominal condition profile counterpart to highlight the variance across less desirable starting conditions within a single EV. This EV Profile Capture 2024 report stands as an update from the EV Profile Capture 2023 report to include the additional EV & EVSE assets tested and analyzed in 2024. The major updates within this report include the addition of three next-generation electric vehicles, added test cases, and further analysis. This expansion of analysis includes power profiles, power distribution, quantifying SOC, energy and range performance, EVSE limitation impacts, boost converter performance, etc. Additionally, NGP time-series data has been used as input towards three national laboratory-led grid modelling efforts: ANL’s IEEE-37 HIL model, INL’s Caldera model, and NREL’s EVI-X model. A summary of these platforms and how NGP has worked to improve their effectiveness has also been added to this years’ report.

Thurston, Sam↗
DOE OSTI2024

Control and Optimization of Energy Storage System in Power Distribution System

The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate fast-charging infrastructure for long-distance trips. Extreme fast charging (XFC) technology can recharge EVs in less than 10 minutes for 200 miles range. Firstly, a novel robust optimization-based mixed integer linear programming model is proposed to size a battery energy storage system (BESS) and PV system in an XFCS. In this part, it is assumed that the sizing and location of the XFCS are known. Secondly, the aforesaid assumption is relaxed, and a strategic multi-period coordinated planning model is proposed to optimally site and size BESS-assisted charging stations in a highway transportation network and PV systems in a power distribution network by considering the coupling between both networks. Optimal operation and control of BESS-assisted EV charging stations are vital to alleviate the adverse impact of extreme fast charging of EVs on the host power network. A joint solution is proposed to mitigate the steady state and transient impact of extremefast charging of EVs and ensure grid-friendly integration of XFCSs with the host grid. Lastly, to make the operation of the XFCS cost-effective, a multi-layered energy management framework is proposed for the XFCS by considering forecast uncertainties, monthly demand charges reduction, and BESS degradation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

A Unified Wireless Charger, On-Board Charger, and Auxiliary Power Module for Electric Vehicle Charging Systems

This paper proposes a unified electric vehicle (EV) charging architecture that integrates wireless power transfer (WPT), an on-board charger (OBC), and an auxiliary power module (APM) within a single architecture. By sharing a multi-functional magnetic structure and active switch bridges, the proposed topology eliminates additional transformers and converter stages, reducing hardware complexity and improving power density. A multipurpose magnetic design achieves magnetic decoupling among the WPT, OBC, and APM functions while maintaining the required coupling for each mode. Through electrical reconfiguration, the WPT operates as an LCC-S converter, whereas the OBC and APM operate as dual-active-bridge (DAB) converters. The system supports multiple operating modes, including simultaneous high-voltage and lowvoltage battery charging. Finite-element and circuit simulations verify the magnetic characteristics and system operation, demonstrating the feasibility of the proposed unified architecture for EV charging applications.

Jo, Cheolhui [ORNL] (ORCID:0000000322692434)↗