基于多状态耦合的退役动力电池模组双阶段分选方法

doi:10.19799/j.cnki.2095-4239.2024.0843

摘要/Abstract

摘要：

为有效降低退役动力电池梯次利用寿命损耗，提高电池模组运行过程中功能状态的一致性，本文提出了考虑电池能量状态（State of Energy, SOE）、健康状态（State of Health, SOH）及功率状态(State of Power, SOP）的多状态耦合的电池模组分选方法。首先，提取退役动力电池基本电性能参数（如容量、电压、内阻等），建立了电池模组SOE、SOH及SOP多状态耦合表征模型；其次，估计电池模组SOE特性，预测梯次利用电池模组SOH一致性，采用改进K-means聚类算法对电池模组进行了第一阶段的动态分选。最后，建立了电池模组耦合多参量的SOP表征模型，估计了电池模组中电池之间SOP偏差，对电池模组进行了第二阶段的动态分选。通过仿真算例分析验证该方法有效提高了退役动力电池梯次利用过程中模组的一致性，降低了系统运行的寿命损耗，为梯次利用储能大规模应用提供理论基础。

关键词: 多状态耦合, 退役动力电池模组, 双阶段分选, 改进K-means聚类, 动态一致性

Abstract:

To effectively reduce the lifetime loss of retired power batteries and improve the consistency of functional states during the operation of battery modules, this paper proposes a multi-state coupled battery module screening method that considers the State of Energy (SOE), State of Health (SOH), and State of Power (SOP). Firstly, the basic electrical performance parameters of retired power batteries (such as capacity, voltage, internal resistance, etc.) are extracted, and a multi-state coupling characterization model for battery modules SOE, SOH, and SOP is established. Secondly, the SOE characteristics of battery modules are estimated, and the hierarchical utilization of battery module SOH consistency is predicted. An improved K-means clustering algorithm is used for the first stage of dynamic sorting of battery modules. Finally, a multi parameter SOP characterization model for battery module coupling is established, and the SOP deviation between batteries in the battery module is estimated. The battery module is dynamically sorted in the second stage. Through simulation case analysis, this method is verified to effectively improve the consistency of modules during the second utilization of retired power batteries, it also reduced system operational life loss. In addition, it provided a theoretical foundation for large-scale second utilization of energy storage systems.

Key words: Multi-state coupling, decommissioned power battery modules, two-stage sorting, improved K-means clustering, dynamic consistency

中图分类号:

TK01

李春生, 王生春, 宋驰, 刘立海, 颜宁. 基于多状态耦合的退役动力电池模组双阶段分选方法[J]. 储能科学与技术, doi: 10.19799/j.cnki.2095-4239.2024.0843.

Chunsheng Li, Shengchun Wang, Chi Song, Lihai Liu, Ning Yan. The two-stage sorting method for retired power battery modules based on multi-state coupling[J]. Energy Storage Science and Technology, doi: 10.19799/j.cnki.2095-4239.2024.0843.

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电池单体		电池模组
参数	值	参数	值
电池类型	方形钢壳电池	电压范围/V	2.0~3.8
电压范围/V	2.0~3.8	标称电压/V	3.2
标称电压/V	3.2	额定容量/Ah	80
额定容量/Ah	80	正极材料	磷酸铁锂
能量密度/(Wh/kg)	192	负极材料	石墨

筛选方法	集群离散度/%
筛选方法	集群1	集群2	集群3
K-means聚类	2.34	1.76	0.79
改进K-means聚类	2.06	1.19	0.66
离散提升度/%	11.97	32.39	16.46

误差区间	分组	电池模组编号
［0, 1.0%］	D1	C-2、C-3、C-4、C-5、C-7
［1.0%, 2.0%］	D2	C-1、C-6、C-9、C-10
超过2.0%	D3	C-8、C-11、C-12、C-13

考虑因素		循环次数
考虑因素		200	400
考虑SOP一致性/%	H1	77.29	66.67
	H2	77.75	66.53
	H3	78.37	66.21
不考虑SOP一致性/%		77.25	65.50

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