断层(地质)
陷入故障
电池(电)
皮尔逊积矩相关系数
故障指示器
故障检测与隔离
相关系数
遗忘
计算机科学
可靠性工程
拓扑(电路)
算法
工程类
数据挖掘
电子工程
电气工程
人工智能
数学
统计
机器学习
功率(物理)
物理
量子力学
地震学
地质学
语言学
哲学
执行机构
作者
Zongxiang Li,Yan Yang,Liwei Li,Dongqing Wang
标识
DOI:10.1016/j.est.2022.106584
摘要
Fault diagnosis for battery circuit is particularly important for the safe management of electric vehicles. Previous correlation based fault diagnosis method only detect some faults, ignores the coupled faults, load connection faults and the problem of current data submerged. In this paper, a multi-fault online diagnosis approach combining a non-redundant measurement topology and weighted Pearson correlation coefficient (WPCC) is adopted to detect various circuit faults by weighted measured data with different forgetting factors. The main advantages are: 1) With adding the connected resistances between the battery pack and the load, the non-redundant measurement topology contains a current sensor and the same number of voltage sensors as those of the battery cells without adding complexity to the system. 2) By adding different weights with bigger forgetting factor to more recent data, a period signal aided WPCC approach is adopted to forget historical data and stress the recent data, so as to online detect the circuit faults. 3) Different from the previous same kind of fault judgement idea, the comprehensive judgement rule are used to online judge the battery abuse faults, connection faults, sensor faults, adjacent homogeneous faults and adjacent hybrid faults. The experiment results show that the investigated method can distinguish and locate the above faults accurately.
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