Lithium-ion batteries have widely used as the power sources of electric vehicles (EVs). Accurate and rapid state of health (SOH) estimation in the battery management system (BMS) plays an essential part in improving the reliability and safety of electric systems. This paper develops an active acoustic emission (AE) sensing technology for nonintrusive and rapid battery SOH estimation. The proposed method takes consideration into the changing internal battery material properties under different levels of degradation. In this method, the power ultrasound is used to propagate into the layered battery and excite different AE events of the battery under different cycles. The AE transducer from the opposite side of the battery can actively sense the elastic waves that reflect the life status. This allows more state information to be captured in a wide frequency band for effective SOH estimation. The results indicate that the RMS of the AE signal can be indicative of battery SOH, and the frequency band 270-300 kHz can provide a more linear SOH estimation under various discharging stages. It is validated that the developed technique can achieve rapid and reliable SOH estimation of lithium-ion batteries.
|Title of host publication
|2022 27th International Conference on Automation and Computing
|Subtitle of host publication
|Smart Systems and Manufacturing, ICAC 2022
|Chenguang Yang, Yuchun Xu
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 10 Oct 2022
|27th International Conference on Automation and Computing - Bristol, United Kingdom
Duration: 1 Sep 2022 → 3 Sep 2022
Conference number: 27
|27th International Conference on Automation and Computing
|1/09/22 → 3/09/22