{"title":"充电行为对锂电池SOH的影响","authors":"Zhiyu Xu, Xiao Yan, Bixiong Huang, Ying Wang, Dong Dong, Zhongcai Liu","doi":"10.1109/AEMCSE50948.2020.00144","DOIUrl":null,"url":null,"abstract":"Lithium battery SOH (State of Health) is one of the performance indicators of power battery, and the factors affecting SOH have been difficult issues. There are two main research methods, one is based on the experimental conditions of SOH estimation, the other is based on vehicle data for online SOH estimation and evaluation. Based on the actual vehicle data of electric vehicles, this study describes charging behavior and battery SOH with parameters. Use current, charge depth, charge frequency to indicate charge behavior, charge capacity to characterize the battery SOH. To study the effect of charge behavior on battery SOH, the biggest influencing factors of battery SOH are determined. Finally, the K-Means clustering algorithm explores different charging behaviors, and the results show that the differences between different categories are obvious.","PeriodicalId":246841,"journal":{"name":"2020 3rd International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The Effect of Charge Behavior on Lithium Battery SOH\",\"authors\":\"Zhiyu Xu, Xiao Yan, Bixiong Huang, Ying Wang, Dong Dong, Zhongcai Liu\",\"doi\":\"10.1109/AEMCSE50948.2020.00144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Lithium battery SOH (State of Health) is one of the performance indicators of power battery, and the factors affecting SOH have been difficult issues. There are two main research methods, one is based on the experimental conditions of SOH estimation, the other is based on vehicle data for online SOH estimation and evaluation. Based on the actual vehicle data of electric vehicles, this study describes charging behavior and battery SOH with parameters. Use current, charge depth, charge frequency to indicate charge behavior, charge capacity to characterize the battery SOH. To study the effect of charge behavior on battery SOH, the biggest influencing factors of battery SOH are determined. Finally, the K-Means clustering algorithm explores different charging behaviors, and the results show that the differences between different categories are obvious.\",\"PeriodicalId\":246841,\"journal\":{\"name\":\"2020 3rd International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 3rd International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AEMCSE50948.2020.00144\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 3rd International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AEMCSE50948.2020.00144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Effect of Charge Behavior on Lithium Battery SOH
Lithium battery SOH (State of Health) is one of the performance indicators of power battery, and the factors affecting SOH have been difficult issues. There are two main research methods, one is based on the experimental conditions of SOH estimation, the other is based on vehicle data for online SOH estimation and evaluation. Based on the actual vehicle data of electric vehicles, this study describes charging behavior and battery SOH with parameters. Use current, charge depth, charge frequency to indicate charge behavior, charge capacity to characterize the battery SOH. To study the effect of charge behavior on battery SOH, the biggest influencing factors of battery SOH are determined. Finally, the K-Means clustering algorithm explores different charging behaviors, and the results show that the differences between different categories are obvious.