Characterization of lithium-ion batteries after suffering micro short circuit induced by mechanical stress abuse

• Published in: Applied energy 2024-11, Vol.374, p.123931, Article 123931
• Main Authors: Gao, Renjing, Liang, Hong, Zhang, Yunfei, Zhao, Haihe, Chen, Zeyu
• Format: Article
• Language: English
• Subjects: Fault detection; Lithium-ion battery; Mechanical abuse; Micro short circuit; Safety management
• ISSN: 0306-2619
• DOI: 10.1016/j.apenergy.2024.123931

Micro short circuit (MSC) is a common type of the battery faults that can evolve into serious consequences. Early detection of MSC is crucial to improving battery safety, however, the characteristics of MSCs are covert and subtle, which makes fault detection very difficult. In this paper, we present a study on the characterization of the lithium-ion batteries (LIBs) that suffer from MSCs but have not yet failed. First, the battery extrusion tests are conducted to control the extrusion depth from 2 to 5 mm. Subsequently, 18 charge and discharge cycling tests and 36 capacity tests are carried out to investigate the characterizations of batteries with MSCs. The internal micro damages, including the separator fractures and electrode cracks, are observed under a scanning electron microscope. Based on the test data, this study quantifies the differences in capacity, voltage correlation coefficient, transient internal resistance, etc., between batteries with varying degrees of MSC and the normal fresh battery. In the incremental capacity analysis after extrusion, it is found that the left shift of main peak is a distinct property. The presented research and conclusions have the potential to be useful for further MSC fault diagnosis applications and to distinguish the MSCs from other types of faults and battery aging. •MSCs of the different extent are investigated based on controllable extrusion tests.•Internal cracks of membrane and cathode after extrusions are observed under SEM.•Characterizations of the batteries after suffering MSCs are depicted quantitively.•The peak left-shift of ICA curve is found to be an important diagnosis judgement.