An electric circuit based EV battery model for runtime prediction and state of charge tracking

K. Sarrafan, D. Sutanto, K. Muttaqi
{"title":"An electric circuit based EV battery model for runtime prediction and state of charge tracking","authors":"K. Sarrafan, D. Sutanto, K. Muttaqi","doi":"10.1109/ITEC-INDIA.2017.8333899","DOIUrl":null,"url":null,"abstract":"Battery modeling plays a crucial role in improving the performance of battery powered systems especially in electric vehicle (EV) applications. To date, many state-of-the-art battery models have been proposed by researchers to improve the performance of electric vehicles. In this paper, an electric circuit based approach for electric vehicle battery model capable of capturing dynamic capacity rate effects for runtime prediction, state of charge tracking and I-V performance is proposed. To compare the results, two well-known electrical circuit based battery models are accurately modeled in MATLAB Simulink and the accuracy and the simplicity of each model are then compared with the proposed model in this paper with the emphasis on rate capacity effects for state of charge tracking and runtime prediction. To extract the battery parameters and to verify the results of each battery model, experimental tests have also been conducted on four Li-ion LGHG2 3 Ah battery cells connected in series.","PeriodicalId":312418,"journal":{"name":"2017 IEEE Transportation Electrification Conference (ITEC-India)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Transportation Electrification Conference (ITEC-India)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITEC-INDIA.2017.8333899","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Battery modeling plays a crucial role in improving the performance of battery powered systems especially in electric vehicle (EV) applications. To date, many state-of-the-art battery models have been proposed by researchers to improve the performance of electric vehicles. In this paper, an electric circuit based approach for electric vehicle battery model capable of capturing dynamic capacity rate effects for runtime prediction, state of charge tracking and I-V performance is proposed. To compare the results, two well-known electrical circuit based battery models are accurately modeled in MATLAB Simulink and the accuracy and the simplicity of each model are then compared with the proposed model in this paper with the emphasis on rate capacity effects for state of charge tracking and runtime prediction. To extract the battery parameters and to verify the results of each battery model, experimental tests have also been conducted on four Li-ion LGHG2 3 Ah battery cells connected in series.
基于电路的电动汽车电池运行预测与充电状态跟踪模型
电池建模对于提高电池供电系统的性能起着至关重要的作用,特别是在电动汽车(EV)应用中。到目前为止,研究人员已经提出了许多最先进的电池模型来提高电动汽车的性能。本文提出了一种基于电路的电动汽车电池模型方法,该方法能够捕获动态容量率效应,用于运行时预测、充电状态跟踪和I-V性能。为了比较结果,在MATLAB Simulink中对两种知名的基于电路的电池模型进行了精确建模,并与本文提出的模型进行了准确性和简便性的比较,重点研究了倍率容量对充电状态跟踪和运行时预测的影响。为了提取电池参数并验证每种电池模型的结果,还对4个串联的LGHG2 3 Ah锂离子电池进行了实验测试。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信