储能科学与技术 ›› 2022, Vol. 11 ›› Issue (1): 221-227.doi: 10.19799/j.cnki.2095-4239.2021.0333

• 储能测试与评价 • 上一篇    下一篇

老化锂电池模组关键电池性能参数的量化分析

袁梓菡1(), 严晓2,3(), 杨涛1   

  1. 1.复旦大学信息科学与工程学院，上海 200433
    2.香港大学香港量子人工智能实验室，香港 999077
    3.上海玫克生储能科技有限公司，上海 201600
  • 收稿日期:2021-07-12 修回日期:2021-07-26 出版日期:2022-01-05 发布日期:2022-01-10
  • 通讯作者: 严晓 E-mail:1113648654@qq.com;sean.x.yan@ms-battery.cn
  • 作者简介:袁梓菡（1996—），女，硕士研究生，研究方向为储能电池的量化分析、梯次利用，E-mail：1113648654@qq.com|严晓，教授，研究方向为锂电池储能的数字化运维，E-mail：sean.x.yan@ms-battery.cn。

Quantitative analysis of key battery performance parameters of aging lithium battery module

Zihan YUAN1(), Xiao YAN2,3(), Tao YANG1   

  1. 1.School of information science and engineering, Fudan University, Shanghai 200433, China, Shanghai 201600, China
    2.Hong Kong quantum Artificial Intelligence Laboratory, University of Hong Kong, Hong Kong 999077, China, Shanghai 201600, China
    3.Shanghai MeiKeSheng Energy Storage Technology Co. Ltd. , Shanghai 201600, China
  • Received:2021-07-12 Revised:2021-07-26 Online:2022-01-05 Published:2022-01-10
  • Contact: Xiao YAN E-mail:1113648654@qq.com;sean.x.yan@ms-battery.cn

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摘要：

退役的动力电池随着新能源电动汽车产业的加速发展而逐渐增多，为了对退役的锂电池进行评估、维护、梯次利用，本工作提出一种老化锂电池模组关键电池性能参数的量化分析研究方法，采用免拆解的“零时间成本”的快速检测方法，仅需要一次充电数据即可在单体层面上对内阻、相对充电时间差值和充电截止电压等关键电池参数(key battery parameter，KBP)进行表征，通过这些KBP的箱型图检测异常单体。基于容量增量(capacity increment，IC)曲线估算各单体的可充电容量以及放电截止时刻可继续放出容量，将其与异常单体对比，提出具体的维保建议，包括均衡、替换两种方式，并给出预期效果，即可以在维护前评估该维护措施的有效性，避免无效维护。本工作共进行了三次实验，均对单体层面关键电池参数进行了量化分析，实验一由于KBP异常存在于同一单体中，因此只能进行替换维护，通过容量计算，预计维护后可提升电池包放电容量12.57%；实验二由于KBP异常存在于不同单体中，因此可以进行均衡维护，通过容量计算，预计维护后可提升整体模组放电容量的35.9%；实验三由于各单体间差异性较小，部分KBP不存在异常值，因此无需采取维护措施。

关键词: 老化电池模组, 量化, 性能参数

Abstract:

The number of retired energy storage batteries is gradually increasing with the rapid development of the new energy electric vehicle industry. To evaluate, maintain, and utilize retired lithium batteries, this study proposes a quantitative analysis method for the key battery performance parameters of an aging lithium battery module that adopts the “zero time cost” rapid detection method without disassembly. The key battery parameters (kbps), including the internal resistance, relative charging time difference, and charging cut-off voltage, can be characterized at the single-cell level by only one charging datum. The abnormal cells can then be detected by a box diagram of these kbps. The rechargeable capacity of each monomer and the continuous discharge capacity at the discharge cut-off time are estimated and compared with the abnormal monomer based on the capacity increment curve. Accordingly, specific maintenance suggestions are put forward, including equalization or replacement, and the expected effect is given, that is, the effectiveness of maintenance measures can be evaluated before maintenance to avoid an invalid maintenance. Three experiments were performed herein, and the kbps at the cell level were quantitatively analyzed. In Experiment 1, only a replacement maintenance can be conducted because an abnormal kbp exists in the same cell. A capacity calculation estimated that the discharge capacity of the battery pack can be increased by 12.57% after maintenance. In Experiment 2, a balanced maintenance can be performed because an abnormal kbp exists in different cells. The capacity calculation also estimated that the discharge capacity of the whole module can be increased by 35.9% after maintenance. Lastly, in Experiment 3, no abnormal value was found in some kbps due to the small difference among the monomers; hence, no maintenance measures were needed.

Key words: aging battery module, quantification, performance parameters

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