Electric vehicle charging harmonic wave identification method based on wavelet transform

Abstract

The invention discloses an electric vehicle charging harmonic wave identification method based on wavelet transform. Firstly wavelet characteristic analysis and signal layering are performed on a charging voltage / current signal. A threshold parameter is calculated according to a threshold characteristic function. Noise filtering is performed. Based on the steps, according to a time approximation parameter and a spatial local characteristic parameter of the voltage / current signal in charging operation of the electric vehicle, localization analysis is performed on the signal waveform in charging operation of the electric vehicle in time domain and frequency domain simultaneously, thereby establishing a high-resolution harmonic wave identification algorithm. The electric vehicle charging harmonic wave identification method has advantages of overcoming a defect of local harmonic wave signal filtering smoothing in the charging process of the electric vehicle, reflecting detail characteristic of the signal, settling a problem of insufficient capability of Fourier transform in charging harmonic wave identification of the electric vehicle, improving accuracy in charging electric energy quality and electric energy metering of the electric vehicle.

Description

technical field [0001] The invention relates to an electric vehicle charging electric energy metering and electric energy quality monitoring system, in particular to a wavelet transform-based electric vehicle charging harmonic identification method. Background technique [0002] During the charging process of electric vehicles, harmonic signals change in real time, and the complexity of harmonics continues to increase, such as transient mutations and white noise interference. The fast Fourier transform (FFT) algorithm is suitable for the field of periodic harmonic analysis. The periodic signal is decomposed into the superposition form of different frequency components according to the Fourier series, and then the separated signal is used to calculate the electric energy related parameters. It is suitable for the detection of steady-state harmonics. FFT has better frequency domain resolution and higher measurement accuracy. However, the FFT algorithm cannot approach the mea...

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Problems solved by technology

The main purpose of the present invention is to overcome the shortcoming that the FFT method will filter and smooth the local harmonic signal in the charging process of the electric vehicle, reflect the detailed characteristics of the signal, solve the problem that the Fourier transform is insufficient in the harmonic identification of electric vehicle charging, and improve Electric vehicle charging power quality and accuracy of power metering

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