Feature Extraction Method for DC Charging Signal of Electric Vehicle

The high-power DC charging of electric vehicle charging stations leads to a large amount of ripple and unsteady waves in the power grid, which seriously affects power quality. The existing algorithms cannot accurately identify the signal characteristics of the fundamental wave, ripple, and the unsteady wave, and it is urgent to develop a comprehensive signal feature extraction method. Aiming at the time-varying characteristics of fundamental and non-steady-state waves in DC charging signals, the layered parameters of wavelet transform are modified, a multi-resolution method is established, and the fundamental and unsteady wave signals are identified and separated. Based on the amplitude-frequency and phase-frequency characteristics of DC charging signal, Fourier transform (FFT) is used to identify the amplitude and frequency of each sub-ripple, and a signal feature recognition method based on Fourier/wavelet transform is proposed to extract the signal characteristics of the DC charging process. The experimental results show that the signal feature recognition method based on Fourier/wavelet transform can identify the DC charging signal characteristics of electric vehicle with high accuracy, and can separate the unsteady state signal from the steady state signal.