基于信号的锂离子电池热失控故障早期检测

Early detection of thermal runaway fault in lithium-ion batteries based on signal decomposition

锂离子电池具有高能量密度、宽温度范围和寿命长等优点,在储能领域已被广泛应用。然而在实际应用中,电、热滥用或运行环境恶劣等原因可能引起电池组单体内部结构发生改变进而导致热失控事故,因此需要尽早实现电池潜在故障的准确检测。首先分析了锂离子电池热失控过程,之后介绍了基于信号分解的电池故障检测方法原理,包括经验模态分解和相关系数法,最后结合实际案例,通过K-means算法自动辨识电池组中故障单体,实现锂离子电池故障早期检测。

With the advantages of high energy density,wide temperature range and long service life,lithium-ion batteries are widely used in the field of energy storage.However,in practical applications,electrical and thermal abuse or harsh operating environments may cause changes in the internal structure of cells in the battery pack,resulting in thermal runaway accidents.Therefore,it is critical to early and accurately detect the potential battery faults.The thermal runaway process of lithium-ion battery was analyzed,then the principle of battery fault detection method based on signal decomposition was introduced,including empirical modal decomposition and correlation coefficient method,and finally combined with the practical applications to automatically identify the faulty cell by Kmeans algorithm to realize the early fault detection of lithium-ion batteries.