第12讲:电池模型在故障诊断中的应用【AESA孙万洲】 | |||
发表时间:2020-09-17 阅读次数: | |||
相关文献 [1] Xiong R, Sun WZ, Yu QQ, Sun FC. Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles[J]. Applied Energy, 2020, 279, 115855. (点击下载) [2] Xiong R, Ma SX, Li HL, Sun FC, Li J. Toward a Safer Battery Management System: A Critical Review on Diagnosis and Prognosis of Battery Short Circuit[J]. iScience 2020, 23. (点击下载) [3] Yang R, Xiong R, Ma S, Lin X. Characterization of external short circuit faults in electric vehicle li-ion battery packs and prediction using artificial neural networks. Appl Energy 2020; 260: 114253. (点击下载) [4] Wu C, Zhu C, Ge Y, Zhao Y. A diagnosis approach for typical faults of lithium-ion battery based on extended Kalman filter. Int J Electrochem Sci 2016:5289–301. (点击下载) [5] Xia B, Mi C. A fault-tolerant voltage measurement method for series connected battery packs. J Power Sources, 2016; 308: 83–96. (点击下载) [6] Xiong R. Battery Management Algorithm for Electric Vehicles[M]. Springer, 2020. [7] Xiong R, Shen W. Advanced battery management technologies for electric vehicles[M]. John Wiley & Sons, 2019. [8] 熊瑞. 动力电池管理系统核心算法[M]. 北京:机械工业出版社,2018. |
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