Cyclic aging monitoring of lithium-ion battery based on acoustic emission

A timely and accurate understanding of the state of health (SOH) of lithium-ion batteries is essential for early detection and prediction of their potential safety risks. Acoustic emission (AE) can perform dynamic non-destructive testing of lithium-ion batteries under normal charge-discharge cycles, and detect the deformation of internal electrodes of the battery behavior. In this paper, firstly, the whole aging process of lithium-ion batteries and recorded AE signals are monitored. Secondly, the waveform and signal time interval from AE signals during battery aging in the time domain is extracted. Thirdly, the spectrum of AE signals is analyzed. The experimental results show that the total number of AE signals will change with the decline of battery capacity and SOH. The turning point in the time interval waveform of the battery AE signal can be used to identify the constant current or voltage charging mode. The AE signals of batteries mainly exist in two frequency bands, where the content of frequency band 1 is about 10kHz-120kHz, and the range of frequency band 2 is about 130kHz-180kHz. The maximum amplitude of frequency bands 1 and 2 shows their characteristics during the charging and discharging process.