{"title":"基于anfiss的锂离子电池充电优化控制新方法","authors":"Salam Hussein, Ahmed Jabbar Abid, A. Obed","doi":"10.1109/ICPEA56918.2023.10093226","DOIUrl":null,"url":null,"abstract":"Lithium-ion rechargeable batteries are considered one of the most energy storage batteries that are used in several portable electrical devices at present. Unwise charges of lithium-ion batteries can damage or reduce the battery life. Charging methods are several but may conflict with manufacturers- recommendations which leads to shortening battery life and reduced efficiency. This paper presents an Adaptive neuro-fuzzy inference system (ANFIS) system that controls fast charging based on manufacturer recommendations using the CC-CV (Constant Current and Constant Voltage) method on Lithium-Ion batteries. The ANFIS model has been trained based on the recommendations of the manufacturer. Based on the simulation results, the proposed system offers accuracy in the matter of current is 1.28 mA (0.044% of the total capacity).","PeriodicalId":297829,"journal":{"name":"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)","volume":"396 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ANFIS-Based New Approach for an Optimal Lithium-Ion Battery Charging Control\",\"authors\":\"Salam Hussein, Ahmed Jabbar Abid, A. Obed\",\"doi\":\"10.1109/ICPEA56918.2023.10093226\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Lithium-ion rechargeable batteries are considered one of the most energy storage batteries that are used in several portable electrical devices at present. Unwise charges of lithium-ion batteries can damage or reduce the battery life. Charging methods are several but may conflict with manufacturers- recommendations which leads to shortening battery life and reduced efficiency. This paper presents an Adaptive neuro-fuzzy inference system (ANFIS) system that controls fast charging based on manufacturer recommendations using the CC-CV (Constant Current and Constant Voltage) method on Lithium-Ion batteries. The ANFIS model has been trained based on the recommendations of the manufacturer. Based on the simulation results, the proposed system offers accuracy in the matter of current is 1.28 mA (0.044% of the total capacity).\",\"PeriodicalId\":297829,\"journal\":{\"name\":\"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)\",\"volume\":\"396 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPEA56918.2023.10093226\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPEA56918.2023.10093226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ANFIS-Based New Approach for an Optimal Lithium-Ion Battery Charging Control
Lithium-ion rechargeable batteries are considered one of the most energy storage batteries that are used in several portable electrical devices at present. Unwise charges of lithium-ion batteries can damage or reduce the battery life. Charging methods are several but may conflict with manufacturers- recommendations which leads to shortening battery life and reduced efficiency. This paper presents an Adaptive neuro-fuzzy inference system (ANFIS) system that controls fast charging based on manufacturer recommendations using the CC-CV (Constant Current and Constant Voltage) method on Lithium-Ion batteries. The ANFIS model has been trained based on the recommendations of the manufacturer. Based on the simulation results, the proposed system offers accuracy in the matter of current is 1.28 mA (0.044% of the total capacity).