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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Parametric Study of State-of-Charge for an Electric Aircraft in Urban Air Mobility

The envisioned concept of urban air mobility is anticipated to support passenger transportation, cargo delivery, and emergency services in major metropolitan areas with increasing autonomy levels in the future. Distributed electric propulsion powered electric vertical takeoff and landing aircraft are expected to enable urban air mobility. However, the low specific energy of onboard lithium-ion polymer batteries and wind conditions impose constraints on flight endurance. Therefore, to enable autonomous urban air mobility operations using electric aircraft, one of the critical steps from a safety and efficiency perspective is to understand how various operational and environmental conditions impact the state-of-charge of the onboard lithium-ion polymer batteries. This research performs a parametric study of the state-of-charge for a NASA-proposed conceptual multirotor aircraft flight in the urban environment. The parameters considered for the parametric analysis are cruise airspeed, cruise altitude, climb and descent profiles, wind conditions (wind magnitude, wind direction relative to the route, and wind magnitude uncertainty), and required time of arrival.

Urban Air Mobility↗
NASA NTRS2021

Parametric Study of State of Charge for an Electric Aircraft in Urban Air Mobility

The envisioned concept of urban air mobility is anticipated to support passenger transportation, cargo delivery, and emergency services in major metropolitan areas with increasing autonomy levels in the future. Distributed electric propulsion powered electric vertical takeoff and landing aircraft are expected to enable urban air mobility. However, the low specific energy of onboard lithium-ion polymer batteries and wind conditions impose constraints on flight endurance. Therefore, to enable autonomous urban air mobility operations using electric aircraft, one of the critical steps from a safety and efficiency perspective is to understand how various operational and environmental conditions impact the state-of-charge of the onboard lithium-ion polymer batteries. This research performs a parametric study of the state-of-charge for a NASA-proposed conceptual multirotor aircraft flight in the urban environment. The parameters considered for the parametric analysis are cruise airspeed, cruise altitude, climb and descent profiles, wind conditions (wind magnitude, wind direction relative to the route, and wind magnitude uncertainty), and required time of arrival.

Urban Air Mobility↗
NASA NTRSDate not supplied

Simulation Studies for an Urban Air Mobility Aircraft using Hardware-In-Loop Experiments

Urban Air Mobility seeks to transport passengers, deliver cargo, and provide emergency transportation in major metropolitan areas. This will be accomplished with distributed electric-powered vertical takeoff and landing aircraft. The low specific energy of the current generation lithium-ion battery packs limit the operational range of electric aircraft. Limited range impacts safety by reducing the time available for analyzing and responding to errors and failures, and limiting the ability to fly to an alternative landing area or return to base. It is therefore critical to understand flight operational and environmental conditions that impact the onboard lithium-ion polymer battery pack’s health. With this as the motivation, experimental procedure in a laboratory setting, and results of the experiments performed on battery packs subject to power draw corresponding to power required during the different phases of flight of a NASA conceptual quadrotor aircraft in simulation are described. The fully charged battery is allowed to discharge at specific C-rates based on the power draw profile and the current and voltages are recorded. Observed results under different operating conditions and mission profiles are discussed.

UAM↗
DOE OSTI2023

MATBOX, an Open-Source Microstructure Analysis Toolbox for Meshing, Generation, Segmentation, and Characterization of 3D Heterogenous Volumes

Battery performance is strongly correlated with electrode microstructural properties. To account for its impact, lithium-ion battery (LIB) models either abstract the microstructural heterogeneity of composite electrodes using effective macroscopic properties (macro- or meso- scale models) or directly solve the system of equations on the microstructure geometry or mesh (microstructure-scale models). Therefore, to be adequate, both families of models require information from the microstructure geometry, which can be provided by the numerical tool presented in this work. MATBOX is a MATLAB open-source application [1] developed by NREL for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization and correlation, visualization, and microstructure meshing. MATBOX was originally developed for the analysis of LIB electrode microstructures; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphical-User Interface, requires no coding by the user, and is well documented. This presentation will illustrate various MATBOX features for the characterization of a LIB electrode, including a fully automated Representative Volume Element (RVE) analysis, the numerical generation of complex 'virtual' microstructure, including dual-layer electrodes and carbon-binder additive phase, and the meshing of a complex NMC/graphite full cell microstructure suitable for 3D finite-element modeling. Other modules (segmentation, visualization, and correlation) will be briefly presented. Thanks to its modular, open-source approach, MATBOX can easily incorporate third-party algorithms to eventually build a standard in the field that will benefit the whole scientific community. Effective diffusion coefficient [2], additive phase numerical generation [3], and meshing [4] third-party algorithms have been already integrated in the toolbox with more to come.

DIRECT ENERGY CONVERSION,MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Delivery-Risk-Aware Flexibility Scheduling and Dispatch for Aggregated Flexible Loads

Flexible loads like smart thermostats and water heaters can shift energy consumption and provide flexibility to the grid. However, this flexibility is dependent on occupant behavior and can lead to delivery risk, which causes utilities and grid operations to consider them as unreliable for purposes of grid operation. To date, they have not been well integrated into wholesale electricity markets or ancillary service offerings. With proper consideration of uncertainty and risk, these resources can be one of the most cost-effective sources of flexibility. This work uses stochastic optimization to quantify and bid flexibility from a fleet of flexible resources while considering their delivery risk.

DER↗
DOE OSTI2018

Investigation of Lithium Plating-Stripping Process in Li-Ion Batteries at Low Temperature Using an Electrochemical Model

Lithium plating leads to severe capacity fading and possible safety problems in lithium-ion batteries. Thus, non-destructive detection methods for lithium plating are critical for safe and reliable operation of lithium-ion batteries. In this paper, an electrochemical model incorporated with lithium plating and stripping reactions is established to investigate the lithium plating-stripping process at low temperature. The model is validated at different current rates and temperatures and can successfully predict the characteristic voltage plateau during the rest period after low temperature charging. Modeling analysis helps to develop detection method for lithium plating via differential analysis on the voltage plateau. Distinct local minima can be found in the differential voltage curves of the batteries with plated lithium. The time when the local minima occurs in the differential voltage curves exhibits a linear relationship with the amount of reversible lithium, and thus can be applied as a quantitative indicator for detection of lithium plating. The detection of lithium plating based on differential voltage analysis is further extended to the discharge voltage profiles of the batteries after low temperature charging, considering the effects of rest time.

25 ENERGY STORAGE↗
DOE OSTI2026

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

EverBatt: A Closed-loop Battery Recycling Cost and Environmental Impacts Model

The cumulative global electric vehicle (EV) sales surpassed 3.1 million units in 2017, with 1.9 million units of battery electric vehicles (BEVs), and 1.2 million units of plug-in hybrid electric vehicles (PHEVs). Of the cumulative global EV sales, The U.S. accounted for 0.40 million BEV sales, and 0.36 million PHEV sales (IEA 2018). Assuming a lifespan of 10 years for EVs, an average battery pack weight of 300 kg for BEVs, and an average battery pack weight of 200 kg for PHEVs, by 2027, 0.2 million metric tons of EV batteries would reach their end-oflife (EOL) in the U.S. Globally, the volume of spent automotive batteries would amount to 0.8 million metric tons by 2027. As the annual global EV sales are expected to grow from 1.4 million in 2017 to 21.5 million in 2030 (IEA 2018), the volume of spent automotive batteries would increase markedly beyond 2027.

25 ENERGY STORAGE↗
DOE OSTI2022

Industrial battery operation and utilization in the presence of electrical load uncertainty using Bayesian decision theory

Behind the meter battery storage is becoming increasing popular in all sectors, though enthusiasm has recently lagged in the industrial sector. Even though there may be many factors contributing to this including lack of innovation, prohibitive costs, and undesirable rate structures, a difficulty arises in accounting for uncertainty of electrical load in industrial facilities while still attempting to utilize battery storage as much as possible all while trying to achieve fiscal profitability. Here this study utilizes Gaussian process regression and Bayesian decision theory to organize load data and quantify electrical load uncertainty to properly and effectively discharge industrial battery storage. The study employs a simulation model to set battery load setpoints for the span of the utility billing period according to the degree of risk aversion. This combination of economic analysis according to utility billing period and utilization of degree of risk aversion to make decisions on the uncertainty of the data has not before been applied to battery storage. The method resulted in an annual average reduction of peak demand by 3.8 % at the lowest amount of savings and lowest risk aversion. The highest risk aversion resulted in an annual average reduction of peak demand of 7.5 %. The maximum reduction of peak load in any month was 13.8 % in the month of December with a relatively high risk aversion. With a the highest amount risk aversion tested, the model reduced demand ten of the twelve months of the year.

25 ENERGY STORAGE↗
NASA NTRS2019

A Multi-Physics Study on High-Specific Power Li-O2 Batteries for Electric Aircraft

Commercialization of lithium-air batteries faces many challenges, such as electrolyte decomposition, short cycle life, low energy and power density, etc. However, commercialization of Li-O2 batteries for aeronautics is much more challenging due to additional safety constraints on cyclability and performance (high specific power and specific energy). For this presentation, we will discuss inter-related aspects of physics-based modeling of a pack: cell and battery model calibration. In addition, we will evaluate and present optimal battery designs for high discharge current density, high discharge time, and low battery mass using simulation-based optimization.The Finite Element Model (FEM) used to simulate a Li-O2 cell is based on the work of Bevara [1]. The different aspects of the model are based on: porous electrode theory and concentrated electrolyte theory; quantum tunneling model for the resistance of conformal layer of discharge product (Li2O2) [1]; Butler-Volmer kinetics for electrochemical reaction; Fick's diffusion for oxygen transport; and an oxygen dissolution model is applied at the air/electrolyte interface [2]. The electrolyte properties such as ion conductivity, ion diffusion, oxygen diffusion, and mass density of the electrolyte were taken from Molecular Dynamics (MD) simulations [3]; while the other model parameters, which includes mass of cell components, were calibrated to match experiments at high discharge current densities. The cell mass includes the anode, cathode, separator, electrolyte, and other components (such as current collector). This calibrated model is used to perform parametric studies on cathode thickness, porosity, tortuosity, carbon particle size, electrolyte transport and material properties, partial pressure of oxygen, discharge time, and discharge current density to study optimal designs for high specific power and energy. References:1. Bevara, V. & Andrei, P. (2014), J. Electrochem. Soc. 161 (14), A2068-A2079.2.Mehta, M. & Andrei, P. (2015), J. Power Sources. 286, 299-308.3.Liyana-Arachchi, T.; Haskins, J.; Burke, C.; Diederichsen, K.; McCloskey, B.; & Lawson, J. (2018), J. Phys. Chem. B. 122 (36), 8548 - 8559.4.Choi, W.; Kikumoto, H.; Choudhary, R. & Ooka, R. (2018), Applied Energy, 209, 306-321.

Mehta, Mohit↗
DOE OSTI2019

Efficient Simulation and Abuse Modeling of Mechanical-Electrochemical-Thermal Phenomena in Li-Ion Batteries

This poster covered simultaneous coupling of electrochemical-thermal models with mechanical deformation in lithium ion batteries. Efficiency and stability of mechanical models was significantly enhanced by implementing electrochemical models into LS-DYNA using User-Defined Elements. Six case studies were built and licensed out to participants from Industry for initial testing and their feedback is being incorporated into these tools. Dynamic response of the cells was incorporated by measuring mechanical response of components at strain rates as high as 250 /s. Temperature range for property measurements was expanded (as high as 200 degrees C) to account for property changes at high temperatures experienced by cell components under battery abuse. Multi-cell validation has been expanded to include four different sets of experimental data, with support from various partners. Complex failure modes and fracture response are currently being investigated. These are still very challenging, given the limited amount of prior work available in the literature.

25 ENERGY STORAGE↗