{"title":"Numerical study of the DEKF parameter identification capabilities in fuel cell EIS tests","authors":"G. Petrone, G. Spagnuolo, W. Zamboni","doi":"10.1109/IESES.2018.8349849","DOIUrl":null,"url":null,"abstract":"In this paper, a numerical study of the identification capabilities of a time-domain parameter estimator for polymeric electrolyte membrane fuel cells (FCs) under electrochemical impedance spectroscopy (EIS) test is proposed. The estimator is a discrete-time Dual Extended Kalman Filter (DEKF). The FC is stimulated with sinusoidal input, typical of EIS tests, and the DEKF identifies the parameters of a linear first-order RC model representing the FC. The impact of the time-domain discretization and of the input signal frequency on the estimation performances are discussed. The results allow to design an effective sequential estimation approach.","PeriodicalId":146951,"journal":{"name":"2018 IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IESES.2018.8349849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper, a numerical study of the identification capabilities of a time-domain parameter estimator for polymeric electrolyte membrane fuel cells (FCs) under electrochemical impedance spectroscopy (EIS) test is proposed. The estimator is a discrete-time Dual Extended Kalman Filter (DEKF). The FC is stimulated with sinusoidal input, typical of EIS tests, and the DEKF identifies the parameters of a linear first-order RC model representing the FC. The impact of the time-domain discretization and of the input signal frequency on the estimation performances are discussed. The results allow to design an effective sequential estimation approach.
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