Asal Zabetian-Hosseini, Amin Ghazanfari, Benoit Boulet
{"title":"A finite-state machine-based control design for thermal and state-of-charge balancing of lithium iron phosphate battery using flyback converters","authors":"Asal Zabetian-Hosseini, Amin Ghazanfari, Benoit Boulet","doi":"10.1002/bte2.20230055","DOIUrl":null,"url":null,"abstract":"<p>Battery cell balancing plays a vital role in maximizing the performance of the battery system by enhancing battery system capacity and prolonging the battery system life expectancy. Active cell balancing using power converters is a promising approach to maintaining uniform state of charges (SoCs) and temperatures across battery cells. The SoC balancing function in the battery management system (BMS) increases the battery pack capacity, and the temperature balancing function mitigates variations in the aging of battery cells due to unbalanced temperatures. In this work, a finite-state machine-based control design is proposed for lithium iron phosphate (LFP) battery cells in series to balance SoCs and temperatures using flyback converters. The primary objective of this design is to ensure balanced SoCs by the end of the charging session while mitigating the temperature imbalance during the charging process. To achieve the SoC and temperature balancing functions using the same balancing circuits, a finite-state machine control design decides on the operating mode, and a balancing strategy balances either temperature or SoC depending on the operating mode. The proposed control design has the advantages of low computational burden, simple implementation compared to the optimization-based controller found in the literature, and the proposed balancing strategy offers faster balancing speed compared to conventional methods. The effectiveness of the proposed strategy is validated on battery cell RC models in series with unbalanced SoCs and temperatures.</p>","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"3 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bte2.20230055","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Battery Energy","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/bte2.20230055","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
Battery cell balancing plays a vital role in maximizing the performance of the battery system by enhancing battery system capacity and prolonging the battery system life expectancy. Active cell balancing using power converters is a promising approach to maintaining uniform state of charges (SoCs) and temperatures across battery cells. The SoC balancing function in the battery management system (BMS) increases the battery pack capacity, and the temperature balancing function mitigates variations in the aging of battery cells due to unbalanced temperatures. In this work, a finite-state machine-based control design is proposed for lithium iron phosphate (LFP) battery cells in series to balance SoCs and temperatures using flyback converters. The primary objective of this design is to ensure balanced SoCs by the end of the charging session while mitigating the temperature imbalance during the charging process. To achieve the SoC and temperature balancing functions using the same balancing circuits, a finite-state machine control design decides on the operating mode, and a balancing strategy balances either temperature or SoC depending on the operating mode. The proposed control design has the advantages of low computational burden, simple implementation compared to the optimization-based controller found in the literature, and the proposed balancing strategy offers faster balancing speed compared to conventional methods. The effectiveness of the proposed strategy is validated on battery cell RC models in series with unbalanced SoCs and temperatures.