Modeling on High‐Frequency Parasitic Parameters of Artificial Mains Network Based on Improved Differential Evolution Algorithm

Abstract

ABSTRACTThe performance of the artificial mains network (AMN) has an important influence on the accuracy of the conducted electromagnetic interference (EMI) noise measurement. The high‐frequency features of the AMN like impedance and voltage division factor (VDF) should be calibrated to enhance the precision of the conducted EMI noise measurement. Because the parasitic parameters of passive devices at high‐frequency have a significant influence on the performance of the AMN, a high‐frequency model of the AMN with parasitic parameters is established in the current study, and the high‐frequency parasitic parameters are extracted based on an improved differential evolution (DE) algorithm and AMN topology. The live wire impedance and VDF of R&S AMN ENV216 are obtained according to the presented approach. The results of the proposed method are compared with those extracted using the scattering parameters and a vector network analyzer, and the effectiveness of the method is validated. This study will aid in the calibration of the AMN and contribute to the accurate measurement of conducted EMI noise in electronic devices.