{"title":"A new method for estimating lithium-ion battery capacity using genetic programming combined model","authors":"Hang Yao, X. Jia, Bo Wang, B. Guo","doi":"10.1109/phm-qingdao46334.2019.8942970","DOIUrl":null,"url":null,"abstract":"Lithium-ion battery is the main energy source widely used in many fields. Therefore, it is particularly essential for estimating the health of lithium-ion battery accurately, especially in important fields such as aerospace, rail transit and satellite. For lithium-ion battery, the battery capacity is a health index (HI) that best reflects its performance degradation. By estimating the battery capacity, the health status of the lithium-ion battery can be clearly identified. However, there are technical barriers to the direct measurement of battery capacity in engineering, and many characteristics and capacities of lithium-ion batteries have abrupt changes, so that it is difficult to calculate the battery capacity accurately by formula calculation. In this paper, a new method of genetic programming combined model is proposed, which can calculate the capacity of lithium-ion battery by formulating multiple monitored features with a certain precision. Therefore, the functional relationship between multiple features and HI is well measured, which lays a good foundation for the subsequent life prediction of battery.","PeriodicalId":259179,"journal":{"name":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/phm-qingdao46334.2019.8942970","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Lithium-ion battery is the main energy source widely used in many fields. Therefore, it is particularly essential for estimating the health of lithium-ion battery accurately, especially in important fields such as aerospace, rail transit and satellite. For lithium-ion battery, the battery capacity is a health index (HI) that best reflects its performance degradation. By estimating the battery capacity, the health status of the lithium-ion battery can be clearly identified. However, there are technical barriers to the direct measurement of battery capacity in engineering, and many characteristics and capacities of lithium-ion batteries have abrupt changes, so that it is difficult to calculate the battery capacity accurately by formula calculation. In this paper, a new method of genetic programming combined model is proposed, which can calculate the capacity of lithium-ion battery by formulating multiple monitored features with a certain precision. Therefore, the functional relationship between multiple features and HI is well measured, which lays a good foundation for the subsequent life prediction of battery.