Modeling and Validation of Common-Mode Emissions in Wide Bandgap-Based Converter Structures

• Published in: IEEE transactions on power electronics Vol. 35; no. 8; pp. 8034 - 8049
• Main Authors: Lemmon, Andrew N., Brovont, Aaron D., New, Christopher D., Nelson, Blake W., DeBoi, Brian T.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analytical models; Capacitors; Electromagnetic interference; Electromagnetic interference (EMI); Empirical analysis; Energy gap; equivalent circuits; Frequency ranges; Integrated circuit modeling; Mathematical model; packaging; Parasitics (electronics); Power converters; Power electronics; power semiconductor devices; Switches
• ISSN: 0885-8993; 1941-0107
• DOI: 10.1109/TPEL.2019.2963883

Modern power converters designed with wide band-gap (WBG) semiconductors are known to generate substantial conducted electromagnetic interference (EMI) as a side effect of high-edge-rate and high-frequency switching. This article provides a consolidated treatment of an approach to the derivation of common-mode equivalent models that are useful for analyzing this increased EMI signature. Also included is a step-by-step demonstration of this approach applied to a prototype converter that exemplifies many practical power electronic applications. For empirical validation of the developed model, this converter is operated within a custom-designed EMI characterization testbed that is similar to the setup specified by MIL-STD-461 CE-102. Good agreement is achieved between analytical predictions and empirical results in both the time domain and the frequency domain. Spectral comparisons are shown to be especially accurate in the frequency range between 10 kHz and 30 MHz, which is the principal range of interest for controlling conducted emissions in WBG-based systems. In order to achieve the demonstrated model agreement, a set of parasitic parameter values were obtained through impedance characterization of the system under study. Identification of the critical parasitic elements that must be quantified to achieve good predictive capability for the presented model represents one of the specific contributions of this article.