Acoustic emission analysis of 18, 650 lithium-ion battery under bending based on factor analysis and the fuzzy clustering method. (November 2020) - Tang, Can; Yuan, Zengrui; Liu, Gang; Jiang, Shiping; Hao, Wenfeng
Highlights: AE was used to monitor the three-points bending failure process of the 18, 650 LIB. AE signals were analyzed using factor analysis and fuzzy clustering method. The characteristics of the AE signals of damaged 18, 650 LIB were obtained. The different failure modes of the LIBs were recognized by the AE characteristics. Abstract: Mechanical damage to lithium-ion batteries (LIBs) has always been a key problem in the practical application of LIBs. It is a hazard if LIB deformation and damage processes cannot be detected in time. In this paper, the acoustic emission (AE) technique was applied to monitor the 18, 650 LIB three-points bending failure process, which solved the ineffective voltage monitoring problem in the 18, 650 LIB three-points bending failure process. The acquired AE signals were analyzed in the time domain and also via factor analysis (FA) and the fuzzy clustering method (FCM). The characteristics of the AE signals of various damage types throughout the entire bending process of the 18, 650 LIB, as well as the expansion of the various damage types throughout the entire bending failure process, were obtained. Results showed that the AE technique effectively monitored the entire mechanical failure process of LIBs and that the FA and FCM were effective at studying the mechanical damage types of LIBs as well as the expansion processes of various damage types.