Capacity Fade Estimation of a Lithium-Ion Battery Through an Integrated Electrochemical Battery Model and Empirical Cycle Aging Model

S. Anwar
{"title":"Capacity Fade Estimation of a Lithium-Ion Battery Through an Integrated Electrochemical Battery Model and Empirical Cycle Aging Model","authors":"S. Anwar","doi":"10.1115/IMECE2020-24146","DOIUrl":null,"url":null,"abstract":"\n An electrochemical model based capacity fade estimation method for a Li-Ion battery is investigated in this paper. An empirical capacity fade model for estimating the state of health of a LiFePO4 electric vehicle battery was integrated with electrochemical battery model in Matlab/Simulink platform. This combined model was then validated against experimental data reported in the literature for constant current charge / discharge cycling. An HPPC current profile was then applied to the validated electrochemical-empirical battery prognosis model which reflected a real-time operating condition for charge and discharge current fluctuations in an electric vehicle battery. The combined model was simulated under the two different HPPC current inputs for three different cycle times. Additionally temperature was taken in account in estimating the cycle aging under the applied current profile to assess the present capacity remaining in the battery. The simulation results provided the state of health (SOH) of the battery for these cycling times which were comparable to the published experimental SOH values for constant current charge/discharge profiles. Thus this model can potentially be used to predict the capacity fade status of an electric vehicle battery.","PeriodicalId":23585,"journal":{"name":"Volume 7A: Dynamics, Vibration, and Control","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 7A: Dynamics, Vibration, and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/IMECE2020-24146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

An electrochemical model based capacity fade estimation method for a Li-Ion battery is investigated in this paper. An empirical capacity fade model for estimating the state of health of a LiFePO4 electric vehicle battery was integrated with electrochemical battery model in Matlab/Simulink platform. This combined model was then validated against experimental data reported in the literature for constant current charge / discharge cycling. An HPPC current profile was then applied to the validated electrochemical-empirical battery prognosis model which reflected a real-time operating condition for charge and discharge current fluctuations in an electric vehicle battery. The combined model was simulated under the two different HPPC current inputs for three different cycle times. Additionally temperature was taken in account in estimating the cycle aging under the applied current profile to assess the present capacity remaining in the battery. The simulation results provided the state of health (SOH) of the battery for these cycling times which were comparable to the published experimental SOH values for constant current charge/discharge profiles. Thus this model can potentially be used to predict the capacity fade status of an electric vehicle battery.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于电化学电池模型和经验循环老化模型的锂离子电池容量衰减估计
研究了一种基于电化学模型的锂离子电池容量衰减估计方法。在Matlab/Simulink平台上将LiFePO4电动汽车电池健康状态的经验容量衰减模型与电化学电池模型相结合。然后根据文献中报道的恒流充放电循环实验数据验证了该组合模型。然后,将HPPC电流分布应用于经过验证的电化学-经验电池预测模型,该模型反映了电动汽车电池充放电电流波动的实时运行状况。对两种不同HPPC电流输入、三种不同循环时间下的组合模型进行了仿真。此外,在估算应用电流剖面下的循环老化时考虑了温度,以评估电池的当前剩余容量。模拟结果提供了这些循环时间内电池的健康状态(SOH),与已发表的恒流充放电曲线的实验SOH值相当。因此,该模型可用于预测电动汽车电池的容量衰减状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Hardware-in-the-Loop Simulation for Large-Scale Applications Multi-Degree-of-Freedom Modeling for Electric Powertrains: Inertia Effect of Engine Mounting System On Structural Damping Characteristics in the Electro-Mechanical Impedance Method A Framework for Spatial 3D Collision Models: Theory and Validation Deep Neural Network Real-Time Control of a Motorized Functional Electrical Stimulation Cycle With an Uncertain Time-Varying Electromechanical Delay
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1