Fault diagnosis in large format LiFePO4 ESS application through DWT-based MRA

An unexpected and instantaneous voltage sag in the energy storage system (ESS) application may cause irrespective breakdown and permanent internal damage of ESS. Therefore, this paper gives insight to the design and implementation of a novel methodology based on the application of discrete wavelet transform (DWT) to the fault diagnosis of the LiFePO₄ ESS application using discharging/charging voltage signal (DCVS). This DCVS is applied as source data in the DWT-based analysis due to its ability to extract variable information from the non-stationary and transient phenomena in both time and frequency domain simultaneously. Specifically, DWT-based multi-resolution analysis (MRA) technique in processing voltage-sag having DCVS dealing with a high frequency component D_n enables us to diagnose fault effectively in the ESS. The experimental results show that DWT-based approach is clearly appropriate for the high-efficient fault diagnosis in large format LiFePO₄ ESS application.