SoC Estimation in Lithium-Ion Batteries with Noisy Measurements and Absence of Excitation

IF 4.6 4区 化学 Q2 ELECTROCHEMISTRY Batteries Pub Date : 2023-11-28 DOI:10.3390/batteries9120578
Miquel Martí-Florences, Andreu Cecilia Piñol, A. Clemente, Ramon Costa-Castelló
{"title":"SoC Estimation in Lithium-Ion Batteries with Noisy Measurements and Absence of Excitation","authors":"Miquel Martí-Florences, Andreu Cecilia Piñol, A. Clemente, Ramon Costa-Castelló","doi":"10.3390/batteries9120578","DOIUrl":null,"url":null,"abstract":"Accurate State-of-Charge estimation is crucial for applications that utilise lithium-ion batteries. In real-time scenarios, battery models tend to present significant uncertainty, making it desirable to jointly estimate both the State of Charge and relevant unknown model parameters. However, parameter estimation typically necessitates that the battery input signals induce a persistence of excitation property, a need which is often not met in practical operations. This document introduces a joint state of charge/parameter estimator that relaxes this stringent requirement. This estimator is based on the Generalized Parameter Estimation-Based Observer framework. To the best of the authors’ knowledge, this is the first time it has been applied in the context of lithium-ion batteries. Its advantages are demonstrated through simulations.","PeriodicalId":8755,"journal":{"name":"Batteries","volume":"256 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Batteries","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.3390/batteries9120578","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ELECTROCHEMISTRY","Score":null,"Total":0}
引用次数: 0

Abstract

Accurate State-of-Charge estimation is crucial for applications that utilise lithium-ion batteries. In real-time scenarios, battery models tend to present significant uncertainty, making it desirable to jointly estimate both the State of Charge and relevant unknown model parameters. However, parameter estimation typically necessitates that the battery input signals induce a persistence of excitation property, a need which is often not met in practical operations. This document introduces a joint state of charge/parameter estimator that relaxes this stringent requirement. This estimator is based on the Generalized Parameter Estimation-Based Observer framework. To the best of the authors’ knowledge, this is the first time it has been applied in the context of lithium-ion batteries. Its advantages are demonstrated through simulations.
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
锂离子电池中的 SoC 估算(噪声测量和无激励
准确的充电状态估计对于使用锂离子电池的应用至关重要。在实时场景中,电池模型往往具有很大的不确定性,因此需要对充电状态和相关未知模型参数进行联合估算。然而,参数估计通常需要电池输入信号具有持续激励特性,而这一需求在实际操作中往往无法满足。本文件介绍了一种放宽这一严格要求的充电状态/参数联合估算器。该估计器基于广义参数估计观测器框架。据作者所知,这是首次将其应用于锂离子电池。通过模拟演示了它的优势。
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
Batteries
Batteries Energy-Energy Engineering and Power Technology
CiteScore
4.00
自引率
15.00%
发文量
217
审稿时长
7 weeks
期刊最新文献
A Health Assessment Method for Lithium-Ion Batteries Based on Evidence Reasoning Rules with Dynamic Reference Values Facile Fabrication of Porous MoSe2/Carbon Microspheres via the Aerosol Process as Anode Materials in Potassium-Ion Batteries Voltage and Overpotential Prediction of Vanadium Redox Flow Batteries with Artificial Neural Networks An Industrial Perspective and Intellectual Property Landscape on Solid-State Battery Technology with a Focus on Solid-State Electrolyte Chemistries Recent Advances in Electrospun Nanostructured Electrodes in Zinc-Ion Batteries
×
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