Online battery model parameters identification approach based on bias-compensated forgetting factor recursive least squaresOA
Online battery model parameters identification approach based on bias-compensated forgetting factor recursive least squares
Dong Zhen;Jiahao Liu;Shuqin Ma;Jingyu Zhu;Jinzhen Kong;Yizhao Gao;Guojin Feng;Fengshou Gu
School of Mechanical Engineering,Hebei University of Technology,Tianjin,300401,ChinaAdvanced Equipment Research Institute Co.,Ltd.of HEBUT,Tianjin,300401,ChinaSchool of Mechanical Engineering,Hebei University of Technology,Tianjin,300401,ChinaSchool of Mechanical Engineering,Hebei University of Technology,Tianjin,300401,ChinaCollege of Information Science and Engineering,Hohai University,Nanjing,210098,ChinaSchool of Mechanical Engineering,Hebei University of Technology,Tianjin,300401,ChinaAdvanced Equipment Research Institute Co.,Ltd.of HEBUT,Tianjin,300401,ChinaSchool of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai,200240,China
Lithium-ion batteryBattery modelRecursive least squaresParameter identification
Lithium-ion batteryBattery modelRecursive least squaresParameter identification
《新能源与智能载运（英文）》 2025 (3)
51-61,11
This work was supported by the Scientific Research Project of Tianjin Education Commission(Grant No:2023KJ303),Hebei Provincial Department of Education(Grant No:C20220315),Tianjin Natural Sci-ence Foundation(Grant No:21JCZDJC00720),Hebei Natural Science Foundation(Grant No:E2022202047).
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