Hongqing Cao , Jingxian Yu , Lishan Kang , Hanxi Yang , Xinping Ai
{"title":"基于混合进化算法的电池系统放电寿命建模与预测","authors":"Hongqing Cao , Jingxian Yu , Lishan Kang , Hanxi Yang , Xinping Ai","doi":"10.1016/S0097-8485(00)00099-1","DOIUrl":null,"url":null,"abstract":"<div><p>A hybrid evolutionary modeling algorithm (HEMA) is proposed to build the discharge lifetime models with multiple impact factors for battery systems as well as make predictions. The main idea of the HEMA is to embed a genetic algorithm (GA) into genetic programming (GP), where GP is employed to optimize the structure of a model, while a GA is employed to optimize its parameters. The experimental results on lithium–ion batteries show that the HEMA works effectively, automatically and quickly in modeling the discharge lifetime of battery systems. The algorithm has some advantages compared with most existing modeling methods and can be applied widely to solving the automatic modeling problems in many fields.</p></div>","PeriodicalId":79331,"journal":{"name":"Computers & chemistry","volume":"25 3","pages":"Pages 251-259"},"PeriodicalIF":0.0000,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0097-8485(00)00099-1","citationCount":"12","resultStr":"{\"title\":\"Modeling and prediction for discharge lifetime of battery systems using hybrid evolutionary algorithms\",\"authors\":\"Hongqing Cao , Jingxian Yu , Lishan Kang , Hanxi Yang , Xinping Ai\",\"doi\":\"10.1016/S0097-8485(00)00099-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A hybrid evolutionary modeling algorithm (HEMA) is proposed to build the discharge lifetime models with multiple impact factors for battery systems as well as make predictions. The main idea of the HEMA is to embed a genetic algorithm (GA) into genetic programming (GP), where GP is employed to optimize the structure of a model, while a GA is employed to optimize its parameters. The experimental results on lithium–ion batteries show that the HEMA works effectively, automatically and quickly in modeling the discharge lifetime of battery systems. The algorithm has some advantages compared with most existing modeling methods and can be applied widely to solving the automatic modeling problems in many fields.</p></div>\",\"PeriodicalId\":79331,\"journal\":{\"name\":\"Computers & chemistry\",\"volume\":\"25 3\",\"pages\":\"Pages 251-259\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S0097-8485(00)00099-1\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0097848500000991\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & chemistry","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0097848500000991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling and prediction for discharge lifetime of battery systems using hybrid evolutionary algorithms
A hybrid evolutionary modeling algorithm (HEMA) is proposed to build the discharge lifetime models with multiple impact factors for battery systems as well as make predictions. The main idea of the HEMA is to embed a genetic algorithm (GA) into genetic programming (GP), where GP is employed to optimize the structure of a model, while a GA is employed to optimize its parameters. The experimental results on lithium–ion batteries show that the HEMA works effectively, automatically and quickly in modeling the discharge lifetime of battery systems. The algorithm has some advantages compared with most existing modeling methods and can be applied widely to solving the automatic modeling problems in many fields.