According to the analysis of amplitude variation curve, the amplitude of Group B signals also showed a trend of gradual decrease with the increase of cycle number, and the amplitude with a dominant frequency of 88 kHz decreased most significantly in the 400–500 cycles; the amplitude with a dominant frequency of 60 kHz decreased significantly in the 10–100 cycles, and the amplitude decreased slowly in the 100–600 cycles.
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Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries.
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It can be seen in Figure 9 that the amplitude of the two dominant frequencies showed a decreasing trend with the increase of cycle number, and the amplitude changed little at 0–300 cycles.
It is embedded in the battery management system to realize the online diagnosis function of battery SOH (State of Health), and thus has a high application prospect [ 12 , 13 , 14 , 15 , 16 , 17 , 18 ]; the data-driven method is based on the voltage, current, temperature, SOC (State of Charge), capacity, impedance and other data of lithium ion batteries during operation, realizes the determination of the health of lithium ion batteries in combination with algorithms, which is an important trend to realize battery state estimation and optimal management in the future [ 19 , 20 ]; the core idea of the fusion method is to combine, correlate and fuse multiple types of data, models or algorithms, and give full attention to their respective advantages to achieve a more precise and reliable collaborative estimation of lithium ion battery SOH.