DWT-based SOH prediction using the output voltage deviation among the cells in the LiFePO4 battery pack for ESS applications

Electrochemical differences, namely voltage variance among the cells in the LiFePO₄ battery pack (rack) is generally related to degradation period, then the magnitude of the voltage variance of the degraded battery pack is increased when compared to the other case of non-degraded battery pack. Therefore, this approach gives insight to the design and implementation of the improved state-of-health (SOH) prediction based on the discrete wavelet transform (DWT) suitable for analysing and evaluating output voltage signal deviation (OVSD) among the cells in the LiFePO₄ battery pack for energy storage system (ESS) applications. The discharging/charging voltage signal (DCVS) is applied as source data in the DWT-based analysis due to its ability to extract information from the non-stationary and transient phenomena simultaneously in both the time and frequency domain. By using the wavelet decomposition including the multi-resolution analysis (MRA), the SOH information among the cells in the LiFePO₄ battery pack can be extracted from signals including approximation A_n and detail D_n components over a wide frequency range. In addition, through the statistical analysis of the DCVS and two components among the cells for comparison between degraded and non-degraded battery packs, appropriate SOH of an arbitrary pack can be predicted. Verification results indicate the robustness of the proposed approach for the reliable SOH.