T. Vincent, Peter J. Weddle, Aleksei La Rue, R. Kee
{"title":"锂离子电池电化学阻抗谱的原位识别","authors":"T. Vincent, Peter J. Weddle, Aleksei La Rue, R. Kee","doi":"10.1049/pbce123e_ch5","DOIUrl":null,"url":null,"abstract":"The monitoring and control of battery systems can be enhanced by data collection and analysis that provide insight into the internal behavior of the battery. A well-known example is electrochemical impedance spectroscopy (EIS), which is equivalent to estimating the frequency response of the battery impedance at a particular operating condition. System identification provides a method for implementing EIS using hardware commonly found in advanced battery-management systems. In this chapter, a possible implementation of online system identification is discussed and illustrated using both simulation and experimental data.","PeriodicalId":173898,"journal":{"name":"Data-Driven Modeling, Filtering and Control: Methods and applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"In situ identification of electrochemical impedance spectra for Li-ion batteries\",\"authors\":\"T. Vincent, Peter J. Weddle, Aleksei La Rue, R. Kee\",\"doi\":\"10.1049/pbce123e_ch5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The monitoring and control of battery systems can be enhanced by data collection and analysis that provide insight into the internal behavior of the battery. A well-known example is electrochemical impedance spectroscopy (EIS), which is equivalent to estimating the frequency response of the battery impedance at a particular operating condition. System identification provides a method for implementing EIS using hardware commonly found in advanced battery-management systems. In this chapter, a possible implementation of online system identification is discussed and illustrated using both simulation and experimental data.\",\"PeriodicalId\":173898,\"journal\":{\"name\":\"Data-Driven Modeling, Filtering and Control: Methods and applications\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data-Driven Modeling, Filtering and Control: Methods and applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/pbce123e_ch5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data-Driven Modeling, Filtering and Control: Methods and applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/pbce123e_ch5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In situ identification of electrochemical impedance spectra for Li-ion batteries
The monitoring and control of battery systems can be enhanced by data collection and analysis that provide insight into the internal behavior of the battery. A well-known example is electrochemical impedance spectroscopy (EIS), which is equivalent to estimating the frequency response of the battery impedance at a particular operating condition. System identification provides a method for implementing EIS using hardware commonly found in advanced battery-management systems. In this chapter, a possible implementation of online system identification is discussed and illustrated using both simulation and experimental data.