B. Bairwa, Santoshkumar Hampannavar, Kaushik S Vishal, K. Bhargavi
{"title":"Modeling and Simulation for Capacity Fade Prediction of Lithium-Ion Battery","authors":"B. Bairwa, Santoshkumar Hampannavar, Kaushik S Vishal, K. Bhargavi","doi":"10.1109/EUROCON52738.2021.9535594","DOIUrl":null,"url":null,"abstract":"This work shows the modeling and simulation-based health analysis for the lithium-ion battery. In the lithiumion batteries health is the burning issue. In this work health is predicted for the lithium-ion single cell. The lithium-ion generic model is trained by the various number of charging and discharging cycles 100 cycle to 1000 cycles for the analysis. Lithium-ion battery voltage is predicted with aging at constant discharging rate 1C. The capacity of the battery compared with the SoC of the with time and voltage. Nominal 3.8 volt and 2Ah rated Lithium Ion NMC cell have been investigated for this work .This study exhibits the lithium ion battery health condition with higher use of the battery in the everyday day life. The simulation results show the overall capacity fading behaviour in the proposed work.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EUROCON52738.2021.9535594","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
This work shows the modeling and simulation-based health analysis for the lithium-ion battery. In the lithiumion batteries health is the burning issue. In this work health is predicted for the lithium-ion single cell. The lithium-ion generic model is trained by the various number of charging and discharging cycles 100 cycle to 1000 cycles for the analysis. Lithium-ion battery voltage is predicted with aging at constant discharging rate 1C. The capacity of the battery compared with the SoC of the with time and voltage. Nominal 3.8 volt and 2Ah rated Lithium Ion NMC cell have been investigated for this work .This study exhibits the lithium ion battery health condition with higher use of the battery in the everyday day life. The simulation results show the overall capacity fading behaviour in the proposed work.