Spatial Imaging of Local Degradations in Li-Ion Batteries Using Sparsely Distributed Active Sensors

This study investigates the integrity of lithium-ion batteries (LIBs) with the aid of guided ultrasonic waves (GUWs) generated by an active sensing network. Despite the expanding demands for secondary batteries in industrial fields, safety concerns remain with respect to LIBs in conventional battery management systems (BMSs). In order to avoid such safety concerns, including unpredictable explosions of LIBs, we developed a novel noninvasive imaging method to inspect the health status of LIBs with a relatively large spatial area using GUWs. We attached nine piezoelectric transducers on the surface of a LiFePO4 (LFP) battery by sectoring it into four spatial regions. The localized mechanical degradation of the LIB was simulated by attaching a weight that caused acoustic mismatch and wave interference. Numerical simulation results showed that acoustic signal changes caused by mechanical degradation in LIBs varied with the frequency and time domains. We investigated a status index based on the continuous wavelet transform (CWT) for application to the probabilistic reconstruction algorithm (PRA). The method was then validated using an actual LFP battery with dimensions of approximately $210\times 300\times 12$ mm3. The proposed method exhibited superior performance as compared with other existing indices, effectively capturing suspicious spatial regions with a high contrast-to-noise ratio (CNR) of over 19%. The proposed Li-ion battery health status imaging method holds promise for inspecting and monitoring the integrity of specific spatial areas in LIBs.