{"title":"基于等效电路+ UKF滤波算法的锂电池SOC校正技术","authors":"Huang Chencheng, L. Jian","doi":"10.1109/AICIT55386.2022.9930284","DOIUrl":null,"url":null,"abstract":"In matlablSimulink environment, the first-order Thevenin equivalent circuit model and the traceless Kalman filtering algorithm are established, and theparameters of different SOCs and temperatures on the battery model are identified by establishing hybrid power pulse characteristic experiments, and the distinguished parameters are substituted into the UKF algorithm for simulation experiments. Experimental results show that the estimation of the state of charge has high accuracy.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Lithium battery SOC correction technology based on equivalent circuit + UKF filtering algorithm\",\"authors\":\"Huang Chencheng, L. Jian\",\"doi\":\"10.1109/AICIT55386.2022.9930284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In matlablSimulink environment, the first-order Thevenin equivalent circuit model and the traceless Kalman filtering algorithm are established, and theparameters of different SOCs and temperatures on the battery model are identified by establishing hybrid power pulse characteristic experiments, and the distinguished parameters are substituted into the UKF algorithm for simulation experiments. Experimental results show that the estimation of the state of charge has high accuracy.\",\"PeriodicalId\":231070,\"journal\":{\"name\":\"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AICIT55386.2022.9930284\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICIT55386.2022.9930284","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lithium battery SOC correction technology based on equivalent circuit + UKF filtering algorithm
In matlablSimulink environment, the first-order Thevenin equivalent circuit model and the traceless Kalman filtering algorithm are established, and theparameters of different SOCs and temperatures on the battery model are identified by establishing hybrid power pulse characteristic experiments, and the distinguished parameters are substituted into the UKF algorithm for simulation experiments. Experimental results show that the estimation of the state of charge has high accuracy.