Variable numerous types of equipment/subsystems may exist in complex systems, which makes it difficult to analyze and identify electromagnetic emission sources. A theory named “basic emission waveform theory” is presented in this paper to solve this problem. This innovation theory characterizes emission with four basic waveforms, including square wave, sine wave, damped oscillation, and spike wave. Then, the effectiveness of the theory is discussed in both theoretical and engineering ways. In particular, the basic waveforms reflect the physical characteristics of the equipment. Furthermore, the basic waveforms generally do not vary with the locations or loading conditions. Therefore, the identification and analysis of an emission source can be realized by analyzing the basic waveforms from the emission of a complex system. Finally, the applications of damped oscillation and square wave in emission source identification field are used as validations of the proposed theory. Moreover, an example of emission source identification for an electric vehicle is also presented. The examples show that the proposed theory can be used to simply and accurately identify and analyze the emission sources of complex systems.

Accurate parasitic parameter extraction of high-frequency transformers is one of the key techniques to efficiently design a Switched-mode power supply(SMPS). An approach to accurately and efficiently extract the parasitic parameters of high-frequency transformers is proposed. The high-frequency transformer is first decomposed into first-order RL and second-order RLC circuits according to inherent step response characteristics. Through the measured discharging pulse and damped oscillation responses of the high-frequency transformer excited by a square wave, we can extract the equivalent circuit parameters through fitting the responses with Particle swarm optimization(PSO). The equivalent circuits of the high-frequency transformer with the desired parameters are obtained for the SMPS design. We validate the effectiveness and accuracy of the proposed method with simulations and measurements.