Early stage internal short circuit fault diagnosis for lithium-ion batteries based on local-outlier detection
Early stage internal short circuit fault diagnosis for lithium-ion batteries based on local-outlier detection
复制标题
基于局部异常值检测的锂离子电池早期内部短路故障诊断
DOI：
10.1016/j.est.2022.106196
复制
发表时间：
2023-01
影响因子：
9.4
通讯作者：
Long Chang
中科院分区：
文献类型：
--
作者：
Haitao Yuan;Naxin Cui;Changlong Li;Zhongrui Cui;Long Chang
内部短路（ISC）被认为是导致电池热失控的主要原因之一，是锂离子电池应用于储能的关键障碍。针对ISC早期故障特征不明显、检测速度慢的问题，提出了一种基于局部引力异常检测的ISC快速诊断方法。在串联电池模块中，电池端电压被归一化以表征比电压幅值对故障更敏感的电压趋势，这提高了故障诊断的速度。然后通过局部重力异常检测算法对归一化电压进行评估以检测故障，通过该算法放大由故障引起的异常以实现早期诊断ISC故障的能力。在城市测功机行车计划测试中，对不同严重程度的ISC故障进行了多组实验，结果表明，该方法在故障特征不明显的情况下也能准确、快速地检测出ISC故障。
Internal short circuit (ISC) is considered to be one of the main causes of battery thermal runaway, which is a critical obstacle to the application of lithium-ion batteries for energy storage. Aiming at inconspicuous characteristics and slow detection speed of early stage ISC faults, this paper proposes a fast diagnostic method for ISC based on local-gravitation outlier detection. In the serial battery module, the cell terminal voltages are normalized to characterize voltage trends that are more sensitive to faults than voltage magnitudes, which improves the speed of fault diagnosis. The normalized voltages are then evaluated by a local gravity outlier detection algorithm to detect faults, by which the anomalies caused by the faults are amplified to achieve the ability to diagnose early ISC faults. The performance of the method is validated under the Urban Dynamometer Driving Schedule test, where several sets of experimental results for ISC faults of varying severity showed that the proposed method could detect them accurately and rapidly even when the fault characteristics are not obvious.
登录
查看更多内容
通过零度以下环境下的正交实验对锂离子电池放电电压进行建模
影响因子：
9.4
作者：
Huixing Meng;Yan-Fu Li;Chen Zhang
通讯作者：
Chen Zhang
影响因子：
7.7
作者：
Satadru Dey;Ying Shi;K. Smith;Andrew M. Colclasure;Xuemin Li
通讯作者：
Satadru Dey;Ying Shi;K. Smith;Andrew M. Colclasure;Xuemin Li
影响因子：
9.2
作者：
Long Chang;Chunyu Wang;Chenghui Zhang;Lin-jing Xiao;N. Cui;Hongyu Li;Jianfeng Qiu
通讯作者：
Long Chang;Chunyu Wang;Chenghui Zhang;Lin-jing Xiao;N. Cui;Hongyu Li;Jianfeng Qiu
影响因子：
9.2
作者：
Ouyang, Minggao;Zhang, Mingxuan;Zheng, Yuejiu
通讯作者：
Zheng, Yuejiu
影响因子：
7.7
作者：
Sidhu, Amardeep;Izadian, Afshin;Anwar, Sohel
通讯作者：
Anwar, Sohel