Application of a modified wavelet threshold denoising algorithm in system identification of WPTS

System identification is an effective method to model a wireless power transfer system when it is used for wireless charging of electric vehicles. However, system identification using raw data directly is often unsatisfactory due to the inevitable noise interference from system operation and signal acquisition. This study proposes an improved wavelet threshold denoising (WTD) algorithm with optimized algorithm parameters and design methods. First, the number of decomposition layers is determined based on the signal spectrum diagram. Second, adaptive thresholds are designed for different decomposition layers. Third, the hierarchical threshold is combined with the hardness adjustable threshold function. Last, recursive least squares is employed to obtain a system model with the data denoised by the proposed method. Experiments demonstrate that the improved WTD method increases the accuracy of system identification to 85.42%, which verifies the effectiveness of the proposed method. An internal model controller is also designed based on the obtained model.