Methodology for Parasitic Elements Extraction of SiC Power Module Based on N-Port Measurement

This paper presents a measurement-based methodology focused on the parasitic extraction of RL elements involved in the commutation power loop of SiC-based power modules. It can be seen as a black/grey-box model that considers a set of Scattering-parameters (S-Parameters) measurements for a given number of ports (N) externally available in a power module under test. The proposed approach allows us to build, in some hours, a model intended to be a behavior representation as close as possible to the physics of the power module. Uncertainties and errors of measurement are managed by optimization regression algorithm based on least-square using the Gauss-Newton-Raphson (GNR) method. Experimental results using a SiC-based power module with different samples are presented for validation purposes.

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Publication Details

Journal
IEEE Transactions on Power Electronics
Published
2025-05-15
DOI
https://doi.org/10.1109/tpel.2025.3570619
Citations
2
Primary Topic
Silicon Carbide Semiconductor Technologies
Type
article
Field-Weighted Citation Impact
1.46
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article

Methodology for Parasitic Elements Extraction of SiC Power Module Based on N-Port Measurement

Sébastien Serpaud, Victor D. N. Santos, Bernardo Cougo, Gregory Arthur de Almeida Carlos et al.
2 citations
IEEE Transactions on Power Electronics
Silicon Carbide Semiconductor Technologies
1.46
article

Methodology for Parasitic Elements Extraction of SiC Power Module Based on N-Port Measurement

Sébastien Serpaud, Victor D. N. Santos, Bernardo Cougo, Gregory Arthur de Almeida Carlos, Fabio Coccetti
article en
2 citations

Abstract

This paper presents a measurement-based methodology focused on the parasitic extraction of RL elements involved in the commutation power loop of SiC-based power modules. It can be seen as a black/grey-box model that considers a set of Scattering-parameters (S-Parameters) measurements for a given number of ports (N) externally available in a power module under test. The proposed approach allows us to build, in some hours, a model intended to be a behavior representation as close as possible to the physics of the power module. Uncertainties and errors of measurement are managed by optimization regression algorithm based on least-square using the Gauss-Newton-Raphson (GNR) method. Experimental results using a SiC-based power module with different samples are presented for validation purposes.

IEEE Transactions on Power ElectronicsVol. 40(10)
IRT M2P (FR), Safran (France) (FR)
Openalex Percentile: Top 18%
Silicon Carbide Semiconductor Technologies
1.46
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