{"title":"用径向基函数估计铅酸蓄电池的充电状态","authors":"S. Malkhandi, S. Sinha, K. Muthukumar","doi":"10.1109/IECON.2001.976467","DOIUrl":null,"url":null,"abstract":"A radial basis function based learning system method has been proposed for estimation of state of charge (SOC) of lead acid battery. Coulomb metric method is used for SOC estimation with correction factor computed by radial basis function method. Radial basis function based technique is used for learning battery performance variation with time and other parameters. Experimental results are included.","PeriodicalId":345608,"journal":{"name":"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Estimation of state of charge of lead acid battery using radial basis function\",\"authors\":\"S. Malkhandi, S. Sinha, K. Muthukumar\",\"doi\":\"10.1109/IECON.2001.976467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A radial basis function based learning system method has been proposed for estimation of state of charge (SOC) of lead acid battery. Coulomb metric method is used for SOC estimation with correction factor computed by radial basis function method. Radial basis function based technique is used for learning battery performance variation with time and other parameters. Experimental results are included.\",\"PeriodicalId\":345608,\"journal\":{\"name\":\"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IECON.2001.976467\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.2001.976467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimation of state of charge of lead acid battery using radial basis function
A radial basis function based learning system method has been proposed for estimation of state of charge (SOC) of lead acid battery. Coulomb metric method is used for SOC estimation with correction factor computed by radial basis function method. Radial basis function based technique is used for learning battery performance variation with time and other parameters. Experimental results are included.