Prediction and Analysis of EMI Spectrum Based on the Operating Principle of EMC Spectrum Analyzers

Abstract

EMC spectrum analyzers are popularly used for electromagnetic interference (EMI) measurement in power electronics systems. Depending on the specifications of EMI standards, the EMI measurement could be very time consuming. Conventionally, the fast Fourier transform is used to derive the EMI spectrum from the measured time-domain waveforms. However, these results may not agree with the measurement results from spectrum analyzers, and sometimes the difference could be significant. In this paper, a technique to quickly and accurately predict and analyze the EMI spectrum from time-domain waveforms is proposed. The technique is developed based on the spectrum analyzer's operating principle and the requirements of EMI standards. The EMI spectra of three modulation schemes are also analyzed. Theoretical analysis, simulations, and experiments were all conducted. The predicted peak, quasi-peak, and average EMI matches the measured EMI in whole conductive frequency range. The developed technique can accurately predict EMI using much shorter time than conventional EMC spectrum analyzers and it saves cost of expensive spectrum analyzers.