{"title":"锂离子电池的健康状况评估:从电池到电池组的全面文献综述","authors":"Lingzhi Su, Yan Xu, Zhaoyang Dong","doi":"10.1049/enc2.12125","DOIUrl":null,"url":null,"abstract":"<p>Lithium-ion battery state-of-health (SOH) monitoring is essential for maintaining the safety and reliability of electric vehicles and efficiency of energy storage systems. When the SOH of lithium-ion batteries reaches the end-of-life threshold, replacement and maintenance are required to avoid fire and explosion hazards. This paper provides a comprehensive literature review of lithium-ion battery SOH estimation methods at the cell, module, and pack levels. Analysis and summary of the SOH definition based on the resistance, capacity, and energy indices are presented at each battery hierarchy level. A Comparison of SOH indices in terms of modelling complexity, required measurement time, and accuracy is provided. To the best of knowledge, a comprehensive classification of SOH estimation methods at different battery hierarchy levels is presented for the first time in this review. In addition, SOH estimation methods are further classified based on the applied methodologies, including direct measurement, model-based methods, data-driven methods, and hybrid model-data methods. Advantages and disadvantages of SOH estimation methods are summarized and compared across different battery hierarchy levels. A detailed summary of typical SOH estimation methods is presented along with the battery topology, operating conditions, and performance. The challenges and research prospects of lithium-ion battery SOH estimation are discussed from the cell to pack levels.</p>","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"5 4","pages":"224-242"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.12125","citationCount":"0","resultStr":"{\"title\":\"State-of-health estimation of lithium-ion batteries: A comprehensive literature review from cell to pack levels\",\"authors\":\"Lingzhi Su, Yan Xu, Zhaoyang Dong\",\"doi\":\"10.1049/enc2.12125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Lithium-ion battery state-of-health (SOH) monitoring is essential for maintaining the safety and reliability of electric vehicles and efficiency of energy storage systems. When the SOH of lithium-ion batteries reaches the end-of-life threshold, replacement and maintenance are required to avoid fire and explosion hazards. This paper provides a comprehensive literature review of lithium-ion battery SOH estimation methods at the cell, module, and pack levels. Analysis and summary of the SOH definition based on the resistance, capacity, and energy indices are presented at each battery hierarchy level. A Comparison of SOH indices in terms of modelling complexity, required measurement time, and accuracy is provided. To the best of knowledge, a comprehensive classification of SOH estimation methods at different battery hierarchy levels is presented for the first time in this review. In addition, SOH estimation methods are further classified based on the applied methodologies, including direct measurement, model-based methods, data-driven methods, and hybrid model-data methods. Advantages and disadvantages of SOH estimation methods are summarized and compared across different battery hierarchy levels. A detailed summary of typical SOH estimation methods is presented along with the battery topology, operating conditions, and performance. The challenges and research prospects of lithium-ion battery SOH estimation are discussed from the cell to pack levels.</p>\",\"PeriodicalId\":100467,\"journal\":{\"name\":\"Energy Conversion and Economics\",\"volume\":\"5 4\",\"pages\":\"224-242\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.12125\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Conversion and Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/enc2.12125\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Conversion and Economics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/enc2.12125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
State-of-health estimation of lithium-ion batteries: A comprehensive literature review from cell to pack levels
Lithium-ion battery state-of-health (SOH) monitoring is essential for maintaining the safety and reliability of electric vehicles and efficiency of energy storage systems. When the SOH of lithium-ion batteries reaches the end-of-life threshold, replacement and maintenance are required to avoid fire and explosion hazards. This paper provides a comprehensive literature review of lithium-ion battery SOH estimation methods at the cell, module, and pack levels. Analysis and summary of the SOH definition based on the resistance, capacity, and energy indices are presented at each battery hierarchy level. A Comparison of SOH indices in terms of modelling complexity, required measurement time, and accuracy is provided. To the best of knowledge, a comprehensive classification of SOH estimation methods at different battery hierarchy levels is presented for the first time in this review. In addition, SOH estimation methods are further classified based on the applied methodologies, including direct measurement, model-based methods, data-driven methods, and hybrid model-data methods. Advantages and disadvantages of SOH estimation methods are summarized and compared across different battery hierarchy levels. A detailed summary of typical SOH estimation methods is presented along with the battery topology, operating conditions, and performance. The challenges and research prospects of lithium-ion battery SOH estimation are discussed from the cell to pack levels.