{"title":"Dynamic analysis of a Li-Iron Phosphate cell using the electro-chemical modelling approach","authors":"Hamed H. Afshari, R. Ahmed, M. Farag, S. Habibi","doi":"10.1109/ITEC.2016.7520188","DOIUrl":null,"url":null,"abstract":"Accurate modeling of batteries has an important and challenging role in battery management systems. In this paper, dynamics of a Li-Iron Phosphate (LiFePO4) cell are simulated using an electro-chemical model. This model was obtained by simplifying a full-order electro-chemical model into the single particle model. In the single particle model the diffusion of lithium inside each electrode is modeled assuming that each electrode is a single particle. This model is then parameterized using input-output data captured from a battery test setup and by applying the genetic algorithm for optimization. The genetic algorithm calculates numeric values of parameters by minimizing the error that is the difference between the measured terminal voltage and simulated one obtained by the electro-chemical model. Dynamics of the (LiFePO4) cell are then investigated in order to determine the state of charge (SOC) of the cell over time.","PeriodicalId":280676,"journal":{"name":"2016 IEEE Transportation Electrification Conference and Expo (ITEC)","volume":"334 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Transportation Electrification Conference and Expo (ITEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITEC.2016.7520188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Accurate modeling of batteries has an important and challenging role in battery management systems. In this paper, dynamics of a Li-Iron Phosphate (LiFePO4) cell are simulated using an electro-chemical model. This model was obtained by simplifying a full-order electro-chemical model into the single particle model. In the single particle model the diffusion of lithium inside each electrode is modeled assuming that each electrode is a single particle. This model is then parameterized using input-output data captured from a battery test setup and by applying the genetic algorithm for optimization. The genetic algorithm calculates numeric values of parameters by minimizing the error that is the difference between the measured terminal voltage and simulated one obtained by the electro-chemical model. Dynamics of the (LiFePO4) cell are then investigated in order to determine the state of charge (SOC) of the cell over time.