Alessandro Sassone, Donghwa Shin, Alberto Bocca, A. Macii, E. Macii, M. Poncino
{"title":"Modeling of the charging behavior of li-ion batteries based on manufacturer's data","authors":"Alessandro Sassone, Donghwa Shin, Alberto Bocca, A. Macii, E. Macii, M. Poncino","doi":"10.1145/2591513.2591592","DOIUrl":null,"url":null,"abstract":"The market of portable devices, wireless sensors, electric vehicles and storage systems has grown enormously in recent years. As a consequence, batteries and related technologies have become one of the major topics for researchers. Due to the large variety of applications in which batteries are involved, battery modeling is becoming an extremely important research topic. This relevance is witnessed by the number of papers addressing battery modeling.\n This paper proposes a methodology to build a battery model for the charge phase of secondary Lithium-Ion batteries resorting on data available in battery datasheets.\n The distinguishing feature of the proposed modeling methodology is that, even if the amount of information regarding the battery charge provided by manufacturers is, in most of the cases, very limited, it is able to extract anyway a model of the charging phase with a good amount of accuracy. Simulation results show, in fact, that the proposed model is able to accurately track the charge behavior with an average error of 1.35.","PeriodicalId":272619,"journal":{"name":"ACM Great Lakes Symposium on VLSI","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Great Lakes Symposium on VLSI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2591513.2591592","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
The market of portable devices, wireless sensors, electric vehicles and storage systems has grown enormously in recent years. As a consequence, batteries and related technologies have become one of the major topics for researchers. Due to the large variety of applications in which batteries are involved, battery modeling is becoming an extremely important research topic. This relevance is witnessed by the number of papers addressing battery modeling.
This paper proposes a methodology to build a battery model for the charge phase of secondary Lithium-Ion batteries resorting on data available in battery datasheets.
The distinguishing feature of the proposed modeling methodology is that, even if the amount of information regarding the battery charge provided by manufacturers is, in most of the cases, very limited, it is able to extract anyway a model of the charging phase with a good amount of accuracy. Simulation results show, in fact, that the proposed model is able to accurately track the charge behavior with an average error of 1.35.