Junjie Tao, Shunli Wang, Wen Cao, Paul Takyi-Aninakwa, Carlos Fernandez, Josep M. Guerrero
{"title":"锂离子电池储能系统的充电状态和健康状态估算综述","authors":"Junjie Tao, Shunli Wang, Wen Cao, Paul Takyi-Aninakwa, Carlos Fernandez, Josep M. Guerrero","doi":"10.1007/s11581-024-05686-z","DOIUrl":null,"url":null,"abstract":"<div><p>With the gradual transformation of energy industries around the world, the trend of industrial reform led by clean energy has become increasingly apparent. As a critical link in the new energy industry chain, lithium-ion (Li-ion) battery energy storage system plays an irreplaceable role. Accurate estimation of Li-ion battery states, especially state of charge (SOC) and state of health (SOH), is the core to realize the safe and efficient utilization of energy storage systems. This paper presents a systematic and comprehensive evaluation and summary of the most advanced Li-ion battery state estimation methods proposed in the past 3 years, focusing on analyzing data-driven state estimation algorithms. At the same time, the latest Li-ion battery data sets and data selection methods are analyzed, and future research trends and possible challenges are proposed. This review will provide a valuable reference for future academic research in Li-ion battery state estimation.</p></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A comprehensive review of state-of-charge and state-of-health estimation for lithium-ion battery energy storage systems\",\"authors\":\"Junjie Tao, Shunli Wang, Wen Cao, Paul Takyi-Aninakwa, Carlos Fernandez, Josep M. Guerrero\",\"doi\":\"10.1007/s11581-024-05686-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>With the gradual transformation of energy industries around the world, the trend of industrial reform led by clean energy has become increasingly apparent. As a critical link in the new energy industry chain, lithium-ion (Li-ion) battery energy storage system plays an irreplaceable role. Accurate estimation of Li-ion battery states, especially state of charge (SOC) and state of health (SOH), is the core to realize the safe and efficient utilization of energy storage systems. This paper presents a systematic and comprehensive evaluation and summary of the most advanced Li-ion battery state estimation methods proposed in the past 3 years, focusing on analyzing data-driven state estimation algorithms. At the same time, the latest Li-ion battery data sets and data selection methods are analyzed, and future research trends and possible challenges are proposed. This review will provide a valuable reference for future academic research in Li-ion battery state estimation.</p></div>\",\"PeriodicalId\":599,\"journal\":{\"name\":\"Ionics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ionics\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11581-024-05686-z\",\"RegionNum\":4,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ionics","FirstCategoryId":"92","ListUrlMain":"https://link.springer.com/article/10.1007/s11581-024-05686-z","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
A comprehensive review of state-of-charge and state-of-health estimation for lithium-ion battery energy storage systems
With the gradual transformation of energy industries around the world, the trend of industrial reform led by clean energy has become increasingly apparent. As a critical link in the new energy industry chain, lithium-ion (Li-ion) battery energy storage system plays an irreplaceable role. Accurate estimation of Li-ion battery states, especially state of charge (SOC) and state of health (SOH), is the core to realize the safe and efficient utilization of energy storage systems. This paper presents a systematic and comprehensive evaluation and summary of the most advanced Li-ion battery state estimation methods proposed in the past 3 years, focusing on analyzing data-driven state estimation algorithms. At the same time, the latest Li-ion battery data sets and data selection methods are analyzed, and future research trends and possible challenges are proposed. This review will provide a valuable reference for future academic research in Li-ion battery state estimation.
期刊介绍:
Ionics is publishing original results in the fields of science and technology of ionic motion. This includes theoretical, experimental and practical work on electrolytes, electrode, ionic/electronic interfaces, ionic transport aspects of corrosion, galvanic cells, e.g. for thermodynamic and kinetic studies, batteries, fuel cells, sensors and electrochromics. Fast solid ionic conductors are presently providing new opportunities in view of several advantages, in addition to conventional liquid electrolytes.