退役动力电池梯级利用分选技术研究

李建林, 王哲, 李雅欣, 刘若桐, 闫湖, 黄碧斌

太阳能学报 ›› 2023, Vol. 44 ›› Issue (1) : 418-425.

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太阳能学报 ›› 2023, Vol. 44 ›› Issue (1) : 418-425. DOI: 10.19912/j.0254-0096.tynxb.2021-0859

退役动力电池梯级利用分选技术研究

  • 李建林1, 王哲1, 李雅欣1, 刘若桐1, 闫湖2, 黄碧斌2
作者信息 +

RESEARCH ON SORTING TECHNOLOGY OF CASCADE UTILIZATION OF RETIRED POWER BATTERIES

  • Li Jianlin1, Wang Zhe1, Li Yaxin1, Liu Ruotong1, Yan Hu2, Huang Bibin2
Author information +
文章历史 +

摘要

首先利用熵权法对退役电池各特征参数进行权重计算,依据计算结果选取电池剩余容量、开路电压和放电直流等效内阻作为电池聚类的分选因子。其次利用支持向量机算法预测退役电池剩余容量,最后利用K-均值聚类算法将电池分成4种等级,并通过实验证明了该方法的准确性。

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.

关键词

退役动力电池 / 电池分选 / 熵权法 / 容量预测 / 支持向量机 / K-均值聚类算法

Key words

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

引用本文

导出引用
李建林, 王哲, 李雅欣, 刘若桐, 闫湖, 黄碧斌. 退役动力电池梯级利用分选技术研究[J]. 太阳能学报. 2023, 44(1): 418-425 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0859
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
中图分类号: TK513.5   

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基金

北京市自然科学基金(KZ202110009014); 国家电网有限公司总部科技项目资助:《面向电网企业的退役动力电池梯次利用辅助决策关键技术研究及软件开发》(项目编号:5419-201957216A-0-0-00)

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