Comprehensive Black Box EMI Model of Power Electronics Converters in Supraharmonics Frequency Range

Predicting electromagnetic interference (EMI) in the 2–150 kHz range using accurate power converter models is receiving significant attention from the electromagnetic compatibility community. However, developing these models is challenging due to the difficulty in accessing detailed information about the converter internal architecture, including parasitic elements. This complexity complicates the precise prediction of EMI at both the device and system levels. This study proposes a simplified black-box model for both single-phase and three-phase converters, tailored for complex EMI analyses. The model accounts for both differential mode (DM) and common mode (CM) equivalents, enabling effective noise mitigation during EMI design. Additionally, the modeling process incorporates an online impedance measurement technique, allowing converters to be modeled while in operation. A simple experimental approach for validating the proposed black-box model is also presented. The experimental results demonstrate that DM impedance is heavily influenced by the converter’s <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on/off</small> status. The proposed black-box models have been validated with a high level of accuracy, revealing that CM impedance asymmetry in the single-phase converter is a key factor during the validation process.

Institutions

Publication Details

Journal
IEEE Transactions on Electromagnetic Compatibility
Published
2025-10-07
DOI
https://doi.org/10.1109/temc.2025.3607560
Primary Topic
Mental Health Treatment and Access
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comprehensive Black Box EMI Model of Power Electronics Converters in Supraharmonics Frequency Range

IEEE Transactions on Electromagnetic Compatibility
Mental Health Treatment and Access
article

Comprehensive Black Box EMI Model of Power Electronics Converters in Supraharmonics Frequency Range

article en

Abstract

Predicting electromagnetic interference (EMI) in the 2–150 kHz range using accurate power converter models is receiving significant attention from the electromagnetic compatibility community. However, developing these models is challenging due to the difficulty in accessing detailed information about the converter internal architecture, including parasitic elements. This complexity complicates the precise prediction of EMI at both the device and system levels. This study proposes a simplified black-box model for both single-phase and three-phase converters, tailored for complex EMI analyses. The model accounts for both differential mode (DM) and common mode (CM) equivalents, enabling effective noise mitigation during EMI design. Additionally, the modeling process incorporates an online impedance measurement technique, allowing converters to be modeled while in operation. A simple experimental approach for validating the proposed black-box model is also presented. The experimental results demonstrate that DM impedance is heavily influenced by the converter’s <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on/off</small> status. The proposed black-box models have been validated with a high level of accuracy, revealing that CM impedance asymmetry in the single-phase converter is a key factor during the validation process.

IEEE Transactions on Electromagnetic CompatibilityVol. 67(6)
Aalborg University (DK)
Openalex Percentile: Top 41%
Mental Health Treatment and Access
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.