Bjorn A. C. van de Ven, R. W. H. Sneijders, F. Hoekstra, H. Bergveld, M. Donkers
{"title":"Combined Cell-Level Estimation of State-of-Charge and Temperature in Battery Packs","authors":"Bjorn A. C. van de Ven, R. W. H. Sneijders, F. Hoekstra, H. Bergveld, M. Donkers","doi":"10.23919/ACC53348.2022.9867694","DOIUrl":null,"url":null,"abstract":"Accurately estimating the State-of-Charge (SoC) and temperature of lithium-ion cells inside a battery pack is critical for safe and reliable operation. This paper extends battery state estimation from single-cell SoC estimation towards a combined SoC and temperature estimation for a multi-cell pack. Combining the electrical and thermal models on a pack level allows for the inclusion of thermal interaction between the cells in a compact manner. The resulting coupled model is used in an extended Kalman filter with correlated noise and a forgetting factor, that is extended with model-residual-based tuning to accommodate differences in magnitude between the electrical and thermal parts of the coupled model. Combined estimation of temperature and SoC decreases the SoC error by around 50%, while the included thermal model adds an accurate estimate of the individual cell temperatures. This provides insight into the temperature distribution, without requiring a large number of temperature sensors.","PeriodicalId":366299,"journal":{"name":"2022 American Control Conference (ACC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 American Control Conference (ACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ACC53348.2022.9867694","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Accurately estimating the State-of-Charge (SoC) and temperature of lithium-ion cells inside a battery pack is critical for safe and reliable operation. This paper extends battery state estimation from single-cell SoC estimation towards a combined SoC and temperature estimation for a multi-cell pack. Combining the electrical and thermal models on a pack level allows for the inclusion of thermal interaction between the cells in a compact manner. The resulting coupled model is used in an extended Kalman filter with correlated noise and a forgetting factor, that is extended with model-residual-based tuning to accommodate differences in magnitude between the electrical and thermal parts of the coupled model. Combined estimation of temperature and SoC decreases the SoC error by around 50%, while the included thermal model adds an accurate estimate of the individual cell temperatures. This provides insight into the temperature distribution, without requiring a large number of temperature sensors.