GHz Range Surrogate Modeling of Transistor Switching Spectra

Abstract

Wide bandgap semiconductor devices enable improvements in power electronics efficiency and power density. However, their fast switching characteristics exacerbate high frequency electromagnetic interference challenges. Radiated emission prediction methods typically employ measured or calculated common-mode signals as AC noise sources based on transistor switching waveforms. These approaches are limited in bandwidth and are dependent on operation points. This work presents a novel measurement based modeling methodology with a measurement setup using a Gaussian Process Regression ($\mathcal {GPR}$) model to overcome the limitations by predicting the transistors drain voltage and source current in the frequency domain up to 1 GHz. We develop a setup to acquire the switching signals of a transistor in frequency domain across various operating conditions within a six dimensional input parameter space. Demonstrating in this article the simulation-based proof of concept of this approach, that a $\mathcal {GPR}$ model can predict the source current and the drain voltage of a transistor in frequency domain. The $\mathcal {GPR}$ model, which is trained in this work using simulation data, predicts the transistors source current in the frequency domain for unseen operating points with a maximum NRMSE of $2.1 \,\%$. These results are establishing a novel approach for noise source modeling in radiated emission models of power converter systems.