{"title":"Development and Application of Battery Management System for Storage System of the Auxiliary Power Unit of EMUs","authors":"Hanxiao Liu, Yang Li, Bin Duan, Liwei Li","doi":"10.1109/SPIES55999.2022.10082066","DOIUrl":null,"url":null,"abstract":"The bullet trains use electric traction. As a key component, the electrical system provides power for the operation of the whole vehicle. The auxiliary power unit (APU) provides power for the electric multiple unit (EMU) electrical system. Nickel-cadmium batteries are used as backup power supply. With the train running, the storage battery inevitably appears a certain degree of aging. In order to improve the service life and safety of EMU batteries, realize the omnidirectional monitoring and management of batteries, and establish the life prediction model and optimal replacement strategy of batteries, this paper designs a battery management system (BMS). The BMS adopts a master-slave structure. The master module is based on S32K144 automotive microcontroller, and the slave module is based on MC33771 in AFE chips. The BMS can collect and analyze the operation parameters of the battery in real time. The ampere-hour integration method and Extended Kalman Filter (EKF) were used to estimate the SOC (state of charge) of the battery in real time. Simulation in Simulink software and experimental verification show that the estimation error can be within 2%.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"4 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPIES55999.2022.10082066","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
The bullet trains use electric traction. As a key component, the electrical system provides power for the operation of the whole vehicle. The auxiliary power unit (APU) provides power for the electric multiple unit (EMU) electrical system. Nickel-cadmium batteries are used as backup power supply. With the train running, the storage battery inevitably appears a certain degree of aging. In order to improve the service life and safety of EMU batteries, realize the omnidirectional monitoring and management of batteries, and establish the life prediction model and optimal replacement strategy of batteries, this paper designs a battery management system (BMS). The BMS adopts a master-slave structure. The master module is based on S32K144 automotive microcontroller, and the slave module is based on MC33771 in AFE chips. The BMS can collect and analyze the operation parameters of the battery in real time. The ampere-hour integration method and Extended Kalman Filter (EKF) were used to estimate the SOC (state of charge) of the battery in real time. Simulation in Simulink software and experimental verification show that the estimation error can be within 2%.