{"title":"Overview of Machine Learning-Enabled Battery State Estimation Methods","authors":"Yingjian Zhuge, Hengzhao Yang, Hao Wang","doi":"10.1109/APEC43580.2023.10131605","DOIUrl":null,"url":null,"abstract":"To ensure safe usage and robust performance of energy storage batteries, accurate state-of-charge (SOC) and state-of-health (SOH) estimations are required. Due to recent breakthroughs in machine learning and artificial intelligence methods, data-driven methods have attracted increased attention. This paper reports state-of-the-art research progress in machine learning-enabled methods for SOC and SOH estimations. Comprehensive comparisons are made in terms of the dataset, estimation accuracy, and battery type to provide a clear picture for SOC and SOH estimation. Moreover, the challenges and research opportunities on future SOC and SOH estimation are disclosed.","PeriodicalId":151216,"journal":{"name":"2023 IEEE Applied Power Electronics Conference and Exposition (APEC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Applied Power Electronics Conference and Exposition (APEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APEC43580.2023.10131605","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
To ensure safe usage and robust performance of energy storage batteries, accurate state-of-charge (SOC) and state-of-health (SOH) estimations are required. Due to recent breakthroughs in machine learning and artificial intelligence methods, data-driven methods have attracted increased attention. This paper reports state-of-the-art research progress in machine learning-enabled methods for SOC and SOH estimations. Comprehensive comparisons are made in terms of the dataset, estimation accuracy, and battery type to provide a clear picture for SOC and SOH estimation. Moreover, the challenges and research opportunities on future SOC and SOH estimation are disclosed.