Joint Estimation of SOC and SOH for Lithium-Ion Batteries via Adaptive Variable Structure Observers

IF 7.2 1区 工程技术 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Industrial Electronics Pub Date : 2025-03-17 DOI:10.1109/TIE.2025.3546355
Hu Tang;Jian Chen;Yu Long;Zaisheng Wang
{"title":"Joint Estimation of SOC and SOH for Lithium-Ion Batteries via Adaptive Variable Structure Observers","authors":"Hu Tang;Jian Chen;Yu Long;Zaisheng Wang","doi":"10.1109/TIE.2025.3546355","DOIUrl":null,"url":null,"abstract":"A new method for obtaining the state of charge (SOC) and state of health (SOH) in real time for lithium-ion batteries is proposed on a two-order battery mode of rewritten mode equations. The mode equations are being rewritten to solve the difficulties of obtaining the error of state variable required for the observer feedback. Four adaptive variable structure observers (AVSOs) collaborate to estimate the four state variables to get SOC. Two AVSOs calculate SOH by estimating the battery’s internal resistance and capacity. In addition, to lessen the presence of the switching term of sliding mode observer (SMO) that causes chattering, a “trans” function is used in AVSOs. To ensure that the gain is appropriate, an adaptive gain is concurrently constructed in AVSOs. Finally, the experiments show that its average values of mean absolute error and root mean square error in three temperatures are lower 3.2% and 4.7% for SOC and 0.7% and 0.9% for SOH compared to the terminal SMO.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 10","pages":"10605-10615"},"PeriodicalIF":7.2000,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Electronics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10929756/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

A new method for obtaining the state of charge (SOC) and state of health (SOH) in real time for lithium-ion batteries is proposed on a two-order battery mode of rewritten mode equations. The mode equations are being rewritten to solve the difficulties of obtaining the error of state variable required for the observer feedback. Four adaptive variable structure observers (AVSOs) collaborate to estimate the four state variables to get SOC. Two AVSOs calculate SOH by estimating the battery’s internal resistance and capacity. In addition, to lessen the presence of the switching term of sliding mode observer (SMO) that causes chattering, a “trans” function is used in AVSOs. To ensure that the gain is appropriate, an adaptive gain is concurrently constructed in AVSOs. Finally, the experiments show that its average values of mean absolute error and root mean square error in three temperatures are lower 3.2% and 4.7% for SOC and 0.7% and 0.9% for SOH compared to the terminal SMO.
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
基于自适应变结构观测器的锂离子电池SOC和SOH联合估计
提出了一种基于重写模态方程的二级电池模型实时获取锂离子电池充电状态(SOC)和健康状态(SOH)的新方法。对模态方程进行了改写,解决了获取观测器反馈所需状态变量误差的困难。四个自适应变结构观测器(avso)协同估计四个状态变量以获得SOC。两个avso通过估算电池的内阻和容量来计算SOH。此外,为了减少引起颤振的滑模观测器(SMO)的开关项的存在,在avso中使用了“trans”函数。为了保证增益的适当性,在avso中同时构造一个自适应增益。最后,实验表明,与终端SMO相比,其在三种温度下的平均绝对误差和均方根误差的平均值SOC分别低3.2%和4.7%,SOH分别低0.7%和0.9%。
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
IEEE Transactions on Industrial Electronics
IEEE Transactions on Industrial Electronics 工程技术-工程:电子与电气
CiteScore
16.80
自引率
9.10%
发文量
1396
审稿时长
6.3 months
期刊介绍: Journal Name: IEEE Transactions on Industrial Electronics Publication Frequency: Monthly Scope: The scope of IEEE Transactions on Industrial Electronics encompasses the following areas: Applications of electronics, controls, and communications in industrial and manufacturing systems and processes. Power electronics and drive control techniques. System control and signal processing. Fault detection and diagnosis. Power systems. Instrumentation, measurement, and testing. Modeling and simulation. Motion control. Robotics. Sensors and actuators. Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems. Factory automation. Communication and computer networks.
期刊最新文献
Virtual–Physical System-Based Deterministic Auto-Tuning for Adaptive Controller Gain Initialization in Grid-Tied Inverters Real-Time Reconstruction-Based Associated Discrete Circuit Model for Power Electronic Converters With Minimized Virtual Power Losses A New Active Capacitor-Embedded Pulsed Load Power Supply for Pulsed Power Suppression Cooperative Localization of USV in Heterogeneous Sensor Networks: A Consensus-Based Estimation Approach A Closed-Loop Adaptive Gate Delay Control for Fast Dynamic Voltage Balancing of Series-Connected SiC MOSFETs
×
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:604180095
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