锂离子电池内短路检测算法及其在实际数据中的应用  

Research on the detection algorithm for internal short circuits in lithium-ion batteries and its application to real operating data

作　　者：潘岳 韩雪冰[1] 欧阳明高[1] 任华华[2] 刘巍 闫月君 PAN Yue;HAN Xuebing;OUYANG Minggao;REN Huahua;LIU Wei;YAN Yuejun(State Key Laboratory of Automotive Safety and Energy,Tsinghua University,Beijing 100084,China;Alibaba Group,Zhengzhou 450018,Henan,China)

机构地区：[1]清华大学汽车安全与节能国家重点实验室,北京100084 [2]阿里巴巴集团,河南郑州450018

出　　处：《储能科学与技术》2023年第1期198-208,共11页Energy Storage Science and Technology

基　　金：北京市自然科学基金项目(3212031);国家自然科学基金项目(52177217,52037006)。

摘　　要：锂离子电池被广泛应用于电动汽车领域和储能领域,锂离子电池内短路可能导致电池热失控,是潜在的安全威胁。为了检测电池是否发生内短路,本工作提出了一种基于长周期运行数据的锂离子电池内短路检测算法,本算法综合考虑内短路引起的一致性差异、自放电效应和异常温升效应,并对相关特征进行了指标提取,利用聚类算法对内短路电池进行精准定位,并借助归一化分数进行分级故障报警。本工作借助多个电池包的长周期运行数据对算法的有效性进行分析,分析结果证明本工作所提出的算法具有很高的检出率和较低的误报率。Lithium-ion batteries are commonly used in electric vehicles and energy storage.Internal short circuits in a lithium-ion battery could result in thermal runaway of the battery,which could be dangerous. To identify the incidence of internal short circuits, this work suggests a lithium-ion battery internal short circuit detection technique based on long-term operation data. This method takes into account the voltage and temperature inconsistency,the self-discharge effect, and the abnormal temperature rise effect induced by internal short circuits. Features are collected, and a clustering method is used to precisely locate the battery with internal short circuit. Graded fault alarms are provided with the use of normalized indicators. The algorithm’s effectiveness is evaluated using long-term operational data from a number of battery packs. The analytical findings demonstrate that the algorithm proposed in this study has a high detection rate and a low false alarm rate.

关 键 词：锂离子电池 聚类算法 归一化参数 内短路检测 

分 类 号：TM911.3[电气工程—电力电子与电力传动]