一种基于电化学阻抗谱的大规模退役锂离子电池的软聚类方法  

A Soft Clustering Method for the Large-Scale Retired Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy

作　　者：来鑫[1] 陈权威 邓聪 韩雪冰[2] 郑岳久[1] Lai Xin;Chen Quanwei;Deng Cong;Han Xuebing;Zheng Yuejiu(School of mechanical engineering,University of Shanghai for Science and Technology,Shanghai,200093,China;School of vehicle and transportation,Tsinghua University,Beijing,100084,China)

机构地区：[1]上海理工大学机械工程学院,上海200093 [2]清华大学车辆与运载学院,北京100084

出　　处：《电工技术学报》2022年第23期6054-6064,共11页Transactions of China Electrotechnical Society

基　　金：国家自然科学基金项目(51977131,51877138);上海市自然科学基金项目(19ZR1435800);汽车安全与节能国家重点实验室项目(KF2020)资助。

摘　　要：退役锂离子电池的分选目前存在效率与精度不可兼得的问题,严重制约大规模退役锂电池梯次利用的经济性与安全性。该文针对以上问题,提出一种基于电化学阻抗谱(EIS)的退役锂离子电池软聚类方法。首先,对退役锂离子电池进行EIS测试和弛豫时间(DRT)分析,利用BP神经网络建立电池容量与DRT关联模型,并用于大规模电池容量的快速估计。然后,构建电池容量、欧姆内阻与DRT特征等六维度判据,在此基础上提出一种基于高斯混合模型的电池软聚类方法。该方法在考虑电池内部重要电化学特征的基础上实现了退役锂离子电池的软聚类,大大提高了聚类结果的准确性与灵活性。最后,通过计算轮廓系数和进行混合脉冲功率特性(HPPC)实验对聚类结果进行验证。实验结果表明,获取电池容量的时间由标准容量测试的3h缩短到10min,容量预测误差控制在4%以内;所提出的软聚类分类方法能提高电池重组的灵活性,并能保证重组电池具有很好的一致性。The sorting efficiency and accuracy of retired lithium-ion batteries(RLIBs)cannot be obtained at the same time,which seriously restricts the economy and safety of echelon utilization of large-scale RLIBs.To address these issues,a soft clustering method for the large-scale RLIBs based on Electrochemical Impedance Spectroscopy(EIS)is proposed in this study.First,the EIS test and distribution of relaxation times(DRT)analysis are conducted on RLIBs,and then a correlation model between battery capacity and DRT is established using the BP neural network,which is used for the rapid estimation of large-scale battery capacity.Second,six dimensional criteria such as battery capacity,ohmic internal resistance,and DRT characteristics are constructed.On this basis,a soft clustering method based on Gaussian mixture model is proposed.In this method,the important electrochemical characteristics in the battery is considered,and the soft clustering of RLIBs is implemented,which greatly improves the accuracy and flexibility of clustering results.Finally,the clustering results are verified by calculating the contour coefficients and performing HPPC experiments.Experimental results show that the time to obtain battery capacity is shortened from 3 hours in standard capacity test to 10 minutes,and the capacity prediction error is controlled within 4%.The proposed soft clustering method can improve the flexibility of battery regrouped and ensure the satisfactory consistency of regrouped batteries.

关 键 词：容量估计 退役锂离子电池 软聚类 电化学阻抗谱 弛豫时间 

分 类 号：TM912[电气工程—电力电子与电力传动]