Application of wavelet analysis theory in storage energy system of lithium battery

The group technology is the bottleneck of large-scale lithium battery storage energy system. The estimate of residual capacity of SOC (state of charge) is an important method to realize large-scale group technology and the resistance of battery is a major index evaluating SOC. Wavelet analysis theory is used for equivalent circuit model of lithium battery aiming at the characteristics of output signal with gaussian white noise when the lithium battery is discharged or charged. The output of current signal and voltage signals in lithium battery are decomposed into multi-scale functions by choosing the optimum wavelet base function to realize filter processing of noise signals, and then the filtered signals be reconstructed to obtain more accurate battery resistance. Compared with the traditional filtering method (LMS adaptive method), wavelet filtering method provided in this paper can effectively remove interference signals and realize accurately estimate of SOC for lithium battery in large-scale battery storage energy system with certain practical significance for group technology.