A Concise Analytical Datasheet-Driven Turn-Off Overvoltage Prediction Method for SiC MOSFET Based on Accurate Overvoltage Timing Estimation

An analytical datasheet-driven turn-off overvoltage prediction method is proposed in this paper. Firstly, a linearly simplified turn-off transition model distinguishing overvoltage point from the end of the turn-off transient is presented. Additionally, a concise expression for turn-off overvoltage prediction is derived based on accurate overvoltage timing estimation. Moreover, the processes of parameters extraction and calibration are also illustrated. Notably, all parameters utilized in the proposed prediction method are entirely extracted and calibrated from the datasheets without any other measurements, which means it is fast and low-cost. Subsequently, five different SiC MOSFETs are packaged in N-cell phase-leg modules, and a double pulse test (DPT) platform is established to verify the proposed prediction method under a wide range of operating conditions. Experimental results indicate that the proposed turn-off overvoltage prediction method is accurate in most operating conditions. Finally, the errors are analyzed and the applicability range of the proposed prediction method is discussed.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Power Electronics
Published
2025-05-09
DOI
https://doi.org/10.1109/tpel.2025.3568327
Primary Topic
Silicon Carbide Semiconductor Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Concise Analytical Datasheet-Driven Turn-Off Overvoltage Prediction Method for SiC MOSFET Based on Accurate Overvoltage Timing Estimation

Wubin Kong, Yimin Zhou, Yunchan Wu, Cheng Qian et al.
IEEE Transactions on Power Electronics
Silicon Carbide Semiconductor Technologies
article

A Concise Analytical Datasheet-Driven Turn-Off Overvoltage Prediction Method for SiC MOSFET Based on Accurate Overvoltage Timing Estimation

Wubin Kong, Yimin Zhou, Yunchan Wu, Cheng Qian, Xiaojie Shi
article en

Abstract

An analytical datasheet-driven turn-off overvoltage prediction method is proposed in this paper. Firstly, a linearly simplified turn-off transition model distinguishing overvoltage point from the end of the turn-off transient is presented. Additionally, a concise expression for turn-off overvoltage prediction is derived based on accurate overvoltage timing estimation. Moreover, the processes of parameters extraction and calibration are also illustrated. Notably, all parameters utilized in the proposed prediction method are entirely extracted and calibrated from the datasheets without any other measurements, which means it is fast and low-cost. Subsequently, five different SiC MOSFETs are packaged in N-cell phase-leg modules, and a double pulse test (DPT) platform is established to verify the proposed prediction method under a wide range of operating conditions. Experimental results indicate that the proposed turn-off overvoltage prediction method is accurate in most operating conditions. Finally, the errors are analyzed and the applicability range of the proposed prediction method is discussed.

IEEE Transactions on Power ElectronicsVol. 41(2)
Huazhong University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 92%
Silicon Carbide Semiconductor Technologies
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.

A Concise Analytical Datasheet-Driven Turn-Off Overvoltage Prediction Method for SiC MOSFET Based on Accurate Overvoltage Timing Estimation — Wubin Kong, Yimin Zhou, et al. · IEEE Transactions on Power Electronics (2025) | TGRS Research Map | TGRS