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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Battery Electrolyte Design for Electric Vertical Takeoff and Landing (eVTOL) Platforms

Here, the development of robust and high-performance battery systems is crucial for the advancement of Electric Vertical Takeoff and Landing (eVTOL) vehicles for urban air mobility. This study evaluates the performance of different lithium-ion battery chemistries under Electric Vertical Takeoff and Landing (eVTOL) load profiles. The actual flight data coupled with physical models is used to create discharge profiles for testing on developed lithium-ion cells for eVTOLs. The performance of a standard liquid electrolyte (1.2 M LiPF 6 in EC:EMC), labeled Gen-2, is benchmarked and compared with a fast-charging electrolyte (1.2 M LiFSI in EC:EMC), labeled XFC. Cell analysis involves the use of various techniques, such as impedance spectroscopy, polarization curves, and capacity retention measurements. Capacity retention is stable for both systems over 500 cycles, but unique discharge capacity trends are observed for different mission segments. During the initial takeoff hover stages, Gen-2 electrolytes experience substantial voltage fade, while XFC electrolytes maintain consistent behavior. In general, the Gen-2 electrolyte demonstrated lower discharge overpotentials and higher decay during cycling compared to the XFC electrolyte. This work highlights the complexity of eVTOL battery behavior and provides insights into battery system design, contributing to the advancement of battery energy storage solutions for urban air mobility.

25 ENERGY STORAGE↗
DOE OSTI2023

Electric Vehicle Lithium-Ion Battery Life Cycle Management

There is no question that electric vehicles (EVs), which are key for addressing climate change impacts from the transportation sector, are quickly gaining popularity and availability. With limits and other challenges related to the supply of critical battery minerals, maximizing the use of EV batteries and ensuring recovery of battery minerals is imperative. Therefore, proper end-of-life-cycle management (reuse and recycling) of these batteries must be part of the EV ecosystem from the perspective of both the supply chain and environmental footprint. Second use of batteries for energy storage systems extends the initial life of these resources and provides a buffer until economical material recovery facilities are in place. Although there are multiple pathways to recycling and recovery of materials, new recovery technologies are moving toward commercially available hydrometallurgy and promising direct recycling, which analysis has shown has the lowest overall carbon footprint. Strategically locating these plants close to battery collection further reduces transportation and thus recycling and recovering costs. Proper life cycle management could alleviate future lithium-ion battery materials supply chains for EVs. Governments and other stakeholders around the world have started initiatives and proposed regulations to address the challenges associated with life cycle management of EV lithium batteries. Finally, as manufacturers are increasingly faced with the likelihood of such extensive regulatory requirements, attention should be given to new designs, sales, and service models that can reduce life cycle management costs.

25 ENERGY STORAGE↗
DOE OSTI2023

Developing rapid electrochemical relithiation protocols for scalable relithiation of lithium-ion battery cathode materials

The recent and ongoing boom in electric vehicle sales has caused the circularity of the supply chain for electric vehicle battery materials to come under a great deal of scrutiny. Innovative recycling processes, or direct recycling, that offer the possibility of reducing the cost of recycling are one possible solution to regaining resources from end-of-life (EoL) electric vehicle batteries. Electrochemically shuttling lithium back into the cathode, or electrochemical relithiation, is a possible technique for restoring lithium content to NMC materials (EoL) in a direct recycling process. This study provides essential understanding towards developing an electrochemical relithiation protocol that will restore lithium loss in intercalation cathode materials that reach EoL by loss of lithium inventory (LLI) as opposed to other degradation mechanisms like loss of active material (LAM), cation mixing or phase transition. Electrochemically aged NMC cathode materials have been prepared and characterized to establish the extent of EoL material structural degradation and lithium loss. A model-informed experimental process is used to identify the optimal electrochemical relithiation protocol to minimize the time taken to relithiate EoL materials and maximize the amount of lithium restored. Protocols were evaluated based on their ability to enable rapid lithium intercalation, maintain structural uniformity in the EoL material and fully restore lithium content. An optimal protocol was identified at elevated temperatures utilizing a novel scanning voltage step.

25 ENERGY STORAGE↗
DOE OSTI2025

Coordinated Thermal Safety Attack and Defense on EV Battery Management Systems

Battery temperature sensor and battery current sensor data which are key sensing inputs to the Battery Management Controllers in electric vehicles, are vulnerable to possible cyber/ physical manipulation due to known vulnerabilities inherited from CAN bus technology that is used for in-vehicle communications between electronic control units that transfer sensing and control data. In this paper, we first create a simulation that enables us to evaluate impact of cyber physical attacks on electric vehicle battery management system in a controlled environment that violates thermal safety. Specifically, we emulate a Level 3 - DC fast charging system with SAE J1772/CCS, integrated with standard charging controls and thermal safety controls on EVs, and various sensing data flows. Second, we propose a coordinated current and battery temperature attack that has crippling economic, and safety impacts. Third, we quantify the usability, economic and safety impacts of such attacks as a function of the extent of data manipulation. Finally, we propose a physics model driven detection technique to detect presence of such attacks.

25 ENERGY STORAGE↗
DOE OSTI2020

Thermal Storage Performance of a Dual-Purpose Underground Thermal Battery for Shaping the Electric Demand of Buildings

A dual-purpose underground thermal battery (DPUTB) integrates a ground heat exchanger with underground thermal energy storage. It can be installed in shallow boreholes (less than 6 m deep) and thus is less expensive than the conventional ground heat exchangers. The thermal energy storage can be used to shave or shift the electric load for meeting the thermal demands of a building. The charging and discharging performance of a lab-scale DPUTB were tested. The test results show that the DPUTB can be fully charged within 4 h and can provide 34 W cooling continuously for 2.5 h with a supply water temperature below 14°C. A small amount of phase-change material significantly increased the thermal storage capacity.

Wang, Lingshi↗
DOE OSTI2025

Learning from Arctic Microgrids: Cost and Resiliency Projections for Renewable Energy Expansion with Hydrogen and Battery Storage

Electricity in rural Alaska is provided by more than 200 standalone microgrid systems powered predominantly by diesel generators. Incorporating renewable energy generation and storage to these systems can reduce their reliance on costly imported fuel and improve sustainability; however, uncertainty remains about optimal grid architectures to minimize cost, including how and when to incorporate long-duration energy storage. This study implements a novel, multi-pronged approach to assess the techno-economic feasibility of future energy pathways in the community of Kotzebue, which has already successfully deployed solar photovoltaics, wind turbines, and battery storage systems. Using real community load, resource, and generation data, we develop a series of comparison models using the HOMER Pro software tool to evaluate microgrid architectures to meet over 90% of the annual community electricity demand with renewable generation, considering both battery and hydrogen energy storage. We find that near-term planned capacity expansions in the community could enable over 50% renewable generation and reduce the total cost of energy. Additional build-outs to reach 75% renewable generation are shown to be competitive with current costs, but further capacity expansion is not currently economical. We additionally include a cost sensitivity analysis and a storage capacity sizing assessment that suggest hydrogen storage may be economically viable if battery costs increase, but large-scale seasonal storage via hydrogen is currently unlikely to be cost-effective nor practical for the region considered. While these findings are based on data and community priorities in Kotzebue, we expect this approach to be relevant to many communities in the Arctic and Sub-Arctic regions working to improve energy reliability, sustainability, and security.

25 ENERGY STORAGE↗
NASA NTRS1990

Making More Efficient Use Of Battery-Plate Mass

Improved active material for positive plate of lead/acid electric storage battery made with additional porosity to give electrolyte access to larger plate-surface area. 65 to 68 percent of active mass of plate used to generate electric current. Batteries with new plate material offer extremely long cycle life.

Rowlette, John J.↗
DOE OSTI2024

Auto Recycler Report: Results from a Questionnaire about Processing Electric Vehicles and Handling High-Voltage Batteries

With the transition to clean energy the demand for electric vehicles in the United States is rapidly growing. As demand continues to rise in the next couple of decades, sourcing materials (e.g., lithium, nickel, cobalt, graphite, etc.) to put into new batteries for electric vehicles will be critical. The U.S. does not have significant reserves of most of these materials and relies heavily on foreign countries. The lithium-ion batteries in electric vehicles are large and contain substantial amounts of critical materials, therefore, they are a promising source of materials for new batteries. Recycling electric vehicle batteries when they reach their end-of-life will enable the United States to generate a domestic supply of materials needed for future batteries. [1-3] The auto recycling industry is the largest collective owner of end-of-life vehicles in the U.S. and will be the primary handlers of battery-powered vehicles (i.e., hybrid or electric) when they reach the end of their useful life. In an effort to better understand how the auto recycling industry currently handles battery-powered vehicles and their high-voltage batteries, DOE’s ReCell Center for Advanced Battery Recycling (ReCell) developed a questionnaire and distributed it to various trade organizations in the automotive recycling industry.

25 ENERGY STORAGE↗
DOE OSTI2026

Comparative Assessment of Battery Carbon Footprint Calculation Frameworks to Support U.S. Battery Manufacturing

A “battery passport” is a digital record that provides comprehensive information about an individual battery across its life cycle. This concept has been introduced by Battery Regulation (EU) 2023/1542 [1], which applies to batteries for electric vehicles (EVs), industrial batteries with a capacities greater than 2 kWh, and batteries for light means of transport (LMT) greater than 2kWh sold in the European Union (EU) market – impacting manufacturers and exporters across multiple jurisdictions globally. Among its reporting mandates, a key feature of battery passports is the requirement for a carbon footprint (CF) calculation methodology supported by enhanced data granularity to enable traceable and verifiable CF results. While no other jurisdictions have yet adopted formal battery passport requirements like the EU’s, some are developing CF calculation methods to comply with the EU Battery Regulation or are creating CF-related regulations that could evolve in a similar direction, reflecting the growing importance of battery CF guidelines for manufacturers seeking to remain competitive in global markets.

Zhang, Jingyi [Argonne National Laboratory (ANL), ↗
DOE OSTI2020

Stochastic Virtual Battery Modeling of Uncertain Electrical Loads using Variational Autoencoder

Effective utilization of flexible loads for grid services, while satisfying end-user preferences and constraints, requires an accurate estimation of the aggregated predictive flexibility offered by the electrical loads. Recently, there have been efforts to quantify the predictive flexibility of thermostatic loads (e.g. residential air-conditioners, electric water-heaters) using the notion of virtual battery (VB), whose state evolution is governed by a first order dynamics including self-dissipation rate, and power and energy capacities. Identifying the VB model parameters for a collection of thermostatic loads, however, is challenging primarily due to uncertainties and lack of information regarding the end-user behavior, underlying device models and parameters. In this paper, we propose a \textit{variational autoencoder}-based deep learning algorithm to identify the parameters of the VB model. Using available sensors and meters data, the proposed algorithm generates not only point estimates of the VB parameters, but also confidence intervals around those values. Effectiveness of the proposed frameworks is demonstrated on a collection of electric water-heater loads, whose operation is driven by uncertain water usage profiles.

virtual battery, deep learning algorithms↗
DOE OSTI2022

Predicting peak day and peak hour of electricity demand with ensemble machine learning

Battery energy storage systems can be used for peak demand reduction in power systems, leading to significant economic benefits. Two practical challenges are 1) accurately determining the peak load days and hours and 2) quantifying and reducing uncertainties associated with the forecast in probabilistic risk measures for dispatch decision-making. In this study, we develop a supervised machine learning approach to generate 1) the probability of the next operation day containing the peak hour of the month and 2) the probability of an hour to be the peak hour of the day. Guidance is provided on preparation and augmentation of data as well as selection of machine learning models and decision-making thresholds. The proposed approach is applied to the Duke Energy Progress system and successfully captures 69 peak days out of 72 testing months with a 3% exceedance probability threshold. On 90% of the peak days, the actual peak hour is among the 2 h with the highest probabilities.

25 ENERGY STORAGE↗
NASA NTRS1985

Mathematical Storage-Battery Models

Empirical formula represents performance of electrical storage batteries. Formula covers many battery types and includes numerous coefficients adjusted to fit peculiarities of each type. Battery and load parameters taken into account include power density in battery, discharge time, and electrolyte temperature. Applications include electric-vehicle "fuel" gages and powerline load leveling.

Chapman, C. P.↗
DOE OSTI2025

Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities

Non-von Neumann computing using neuromorphic systems based on analogue synaptic and neuronal elements has emerged as a potential solution to tackle the growing need for more efficient data processing, but progress toward practical systems has been stymied due to a lack of materials and devices with the appropriate attributes. Recently, solid state electrochemical ion-insertion, also known as electrochemical random access memory (ECRAM) has emerged as a promising approach to realize the needed device characteristics. ECRAM is a three terminal device that operates by tuning electronic conductance in functional materials through solid-state electrochemical redox reactions. This mechanism can be considered as a gate-controlled bulk modulation of dopants and/or phases in the channel. Early work demonstrating that ECRAM can achieve nearly ideal analogue synaptic characteristics has sparked tremendous interest in this approach. More recently, the realization that electrochemical ion insertion can be used to tune the electronic properties of many types of materials including transition metal oxides, layered two-dimensional materials, organic and coordination polymers, and that the changes in conductance can span orders of magnitude has further attracted interest in ECRAM as the basis for analogue synaptic elements for inference accelerators as well as for dynamical devices that can emulate a wide range of neuronal characteristics for implementation in analogue spiking neural networks. At its core, ECRAM shares many fundamental aspects with rechargeable batteries, where ion insertion materials are used extensively for their ability to reversibly store charge and energy. Computing applications, however, present drastically different requirements: systems will require many millions of devices, scaled down to tens of nanometers, all while achieving reliable electronic-state tuning at scaled-up rates and endurances, and with minimal energy dissipation and noise. Further, in this review, we discuss the history, basic concepts, recent progress, as well as the challenges and opportunities for different types of ECRAM, broadly grouped by their primary mobile ionic charge carrier, including Li, protons, and oxygen vacancies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Frequency response measurements in battery electrodes

Electrical impedance spectroscopy was used to investigate the behavior of porous zinc, silver, cadmium, and nickel electrodes. State of charge could be correlated with impedance data for all but the nickel electrodes. State of health was correlated with impedance data for two AgZn cells, one apparently good and the other bad. The impedance data was fit to equivalent circuit models.

Thomas, Daniel L.↗
DOE OSTI2022

Vehicle-to-Grid Electric School Bus Commercialization Project

The Vehicle-to-Grid Electric School Bus Commercialization Project was chartered to advance the idea that the batteries in electric vehicles can play a valuable role in supporting the electric grid. As deployment of wind and solar generating resources accelerates to provide an ever-greater share of the nation’s electricity, concurrent investment in solutions that can offset their inherent intermittency will be necessary. Many types of energy storage systems have been proposed, and more than one type will find an economic fit in the grid of the future. Electric vehicle batteries have the potential to provide grid support services in an advantaged manner. The project’s method of exploring this proposition called for development and demonstration of a fleet of vehicle-to-grid (V2G) electric school buses. School buses were chosen because their energy storage capacity is large relative light-duty vehicles; they are typically domiciled in fleet settings; and the number of hours per year they are available for grid support services is high on an absolute basis (generally 80-85% of the hours in a year) and relative to other categories of medium- and heavy-duty vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Evaluating an Eco-Cooperative Automated Control System

The paper evaluates an Eco-Cooperative Automated Control (Eco-CAC) system on a large-scale network considering a combination of internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), and battery-only electric vehicles (BEVs) in a microscopic traffic simulation environment. We used a novel integrated control system that: (1) routes ICEVs, HEVs, and BEVs in a fuel/energy-efficient manner; (2) selects vehicle speeds based on anticipated traffic network evolution; (3) minimizes vehicle fuel/energy consumption near signalized intersections; and (4) intelligently modulates the longitudinal motion of vehicles along freeways within a cooperative platoon to minimize fuel/energy consumption. The study tested the system using the INTEGRATION software on the Los Angeles (LA), U.S., downtown network for three different demand levels: no congestion, mild congestion, and heavy congestion. The results demonstrated that the Eco-CAC system effectively reduces vehicle fuel and energy consumption, travel time, total delay, and stopped delay in heavily congested conditions. However, different vehicle compositions produced different results. In particular, the maximum energy consumption savings for BEVs (36.9%) for a current vehicle composition occurred at a 10% market penetration rate (MPR) of connected automated vehicles (CAVs) in mild congestion, while the maximum savings for a future vehicle composition (35.5%) occurred at a 50% CAV MPR in no congestion. The system reduced fuel consumption for ICEVs and HEVs by up to 5.4% and 6.3% at a 25% CAV MPR in heavy congestion for current and future vehicle compositions, respectively. However, the system increased total fuel consumption by up to 4.6% at a 50% CAV MPR in no congestion for a current vehicle composition. The study demonstrates that the effectiveness of the Eco-CAC system depends on traffic conditions, including congestion level, network configuration, CAV MPR, and vehicle composition.

Engineering↗