RESEARCH ON SORTING TECHNOLOGY OF CASCADE UTILIZATION OF RETIRED POWER BATTERIES

Li Jianlin; Wang Zhe; Li Yaxin; Liu Ruotong; Yan Hu; Huang Bibin

doi:10.19912/j.0254-0096.tynxb.2021-0859

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (1) : 418-425. DOI: 10.19912/j.0254-0096.tynxb.2021-0859

RESEARCH ON SORTING TECHNOLOGY OF CASCADE UTILIZATION OF RETIRED POWER BATTERIES

Li Jianlin¹, Wang Zhe¹, Li Yaxin¹, Liu Ruotong¹, Yan Hu², Huang Bibin²

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Abstract

In this paper, the entropy weight method is used to calculate the weight of each characteristic parameter of the retired battery firstly. According to the calculation result, the remaining capacity, open circuit voltage and discharge DC equivalent internal resistance of the battery are selected as the sorting factors of battery clustering. Secondly, the support vector machine algorithm is used to predict the remaining capacity of the retired battery. Finally, the K-means clustering algorithm is used to divide the battery into four levels, and the accuracy of the method is proved through experiments.

Key words

retired power battery / battery sorting / entropy weight method / capacity prediction / support vector machine / K-means clustering algorithm

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Li Jianlin, Wang Zhe, Li Yaxin, Liu Ruotong, Yan Hu, Huang Bibin. RESEARCH ON SORTING TECHNOLOGY OF CASCADE UTILIZATION OF RETIRED POWER BATTERIES[J]. Acta Energiae Solaris Sinica. 2023, 44(1): 418-425 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0859

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