{"title":"考虑内部短路故障的锂离子电池组电池芯不一致分类","authors":"Youngbin Song, Minhwan Seo, Shina Park, S. W. Kim","doi":"10.23919/ICCAS52745.2021.9650054","DOIUrl":null,"url":null,"abstract":"Initial parameter variances between cells in battery packs occur in a manufacturing process. Furthermore, this difference is intensified as the pack is being used, resulting in differences in capacity and the state of charge (SOC) between cells. Cell inconsistencies decrease the energy efficiency, and low-capacity cells in packs can occur an internal short circuit (ISC) fault which causes a thermal runaway in severe cases. However, the ISC may be misdiagnosed as cell inconsistencies and vice versa because the impacts of cell inconsistencies and the ISC are similar in particular charge/discharge. In this paper, a model-based cell inconsistency classification method is proposed. The equivalent circuit model of the fresh cell is used as a reference model, making it possible to save efforts in constructing parameter look-up tables for various degrees of aging. In addition, we use the SOC difference feature that can clearly distinguish the effects of inconsistencies and ISC using the reference SOC calculated by the nominal capacity. The proposed method was verified in simulation for various types and degrees of cell inconsistencies and ISC, and accurately identified inconsistent cells and ISC cells, thereby leading to efficient energy use and early detection of the ISC fault.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cell Inconsistency Classification for Lithium-Ion Battery Packs Considering Internal Short Circuit Fault\",\"authors\":\"Youngbin Song, Minhwan Seo, Shina Park, S. W. Kim\",\"doi\":\"10.23919/ICCAS52745.2021.9650054\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Initial parameter variances between cells in battery packs occur in a manufacturing process. Furthermore, this difference is intensified as the pack is being used, resulting in differences in capacity and the state of charge (SOC) between cells. Cell inconsistencies decrease the energy efficiency, and low-capacity cells in packs can occur an internal short circuit (ISC) fault which causes a thermal runaway in severe cases. However, the ISC may be misdiagnosed as cell inconsistencies and vice versa because the impacts of cell inconsistencies and the ISC are similar in particular charge/discharge. In this paper, a model-based cell inconsistency classification method is proposed. The equivalent circuit model of the fresh cell is used as a reference model, making it possible to save efforts in constructing parameter look-up tables for various degrees of aging. In addition, we use the SOC difference feature that can clearly distinguish the effects of inconsistencies and ISC using the reference SOC calculated by the nominal capacity. The proposed method was verified in simulation for various types and degrees of cell inconsistencies and ISC, and accurately identified inconsistent cells and ISC cells, thereby leading to efficient energy use and early detection of the ISC fault.\",\"PeriodicalId\":411064,\"journal\":{\"name\":\"2021 21st International Conference on Control, Automation and Systems (ICCAS)\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 21st International Conference on Control, Automation and Systems (ICCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ICCAS52745.2021.9650054\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ICCAS52745.2021.9650054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cell Inconsistency Classification for Lithium-Ion Battery Packs Considering Internal Short Circuit Fault
Initial parameter variances between cells in battery packs occur in a manufacturing process. Furthermore, this difference is intensified as the pack is being used, resulting in differences in capacity and the state of charge (SOC) between cells. Cell inconsistencies decrease the energy efficiency, and low-capacity cells in packs can occur an internal short circuit (ISC) fault which causes a thermal runaway in severe cases. However, the ISC may be misdiagnosed as cell inconsistencies and vice versa because the impacts of cell inconsistencies and the ISC are similar in particular charge/discharge. In this paper, a model-based cell inconsistency classification method is proposed. The equivalent circuit model of the fresh cell is used as a reference model, making it possible to save efforts in constructing parameter look-up tables for various degrees of aging. In addition, we use the SOC difference feature that can clearly distinguish the effects of inconsistencies and ISC using the reference SOC calculated by the nominal capacity. The proposed method was verified in simulation for various types and degrees of cell inconsistencies and ISC, and accurately identified inconsistent cells and ISC cells, thereby leading to efficient energy use and early detection of the ISC fault.