{"title":"基于卡尔曼滤波的锂离子电池充电状态估计","authors":"Atsushi Baba, S. Adachi","doi":"10.1109/CCA.2012.6402456","DOIUrl":null,"url":null,"abstract":"In this paper we propose an accurate state of charge (SOC) estimation method for a lithium-ion battery for hybrid electric vehicle (HEV) and electric vehicles (EV) use. Although it is important to accurately determine the SOC of a battery to achieve maximum efficiency and safety, none of the existing methods has achieved this perfectly. To address this issue, a model-based approach using a cascaded combination of two Kalman filters, “Series Kalman Filters,” is proposed and implemented. Its validity is verified by performing a series of simulations under a basic HEV operating environment.","PeriodicalId":284064,"journal":{"name":"2012 IEEE International Conference on Control Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"State of charge estimation of lithium-ion battery using Kalman filters\",\"authors\":\"Atsushi Baba, S. Adachi\",\"doi\":\"10.1109/CCA.2012.6402456\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we propose an accurate state of charge (SOC) estimation method for a lithium-ion battery for hybrid electric vehicle (HEV) and electric vehicles (EV) use. Although it is important to accurately determine the SOC of a battery to achieve maximum efficiency and safety, none of the existing methods has achieved this perfectly. To address this issue, a model-based approach using a cascaded combination of two Kalman filters, “Series Kalman Filters,” is proposed and implemented. Its validity is verified by performing a series of simulations under a basic HEV operating environment.\",\"PeriodicalId\":284064,\"journal\":{\"name\":\"2012 IEEE International Conference on Control Applications\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Control Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCA.2012.6402456\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Control Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCA.2012.6402456","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
State of charge estimation of lithium-ion battery using Kalman filters
In this paper we propose an accurate state of charge (SOC) estimation method for a lithium-ion battery for hybrid electric vehicle (HEV) and electric vehicles (EV) use. Although it is important to accurately determine the SOC of a battery to achieve maximum efficiency and safety, none of the existing methods has achieved this perfectly. To address this issue, a model-based approach using a cascaded combination of two Kalman filters, “Series Kalman Filters,” is proposed and implemented. Its validity is verified by performing a series of simulations under a basic HEV operating environment.