Prediction of overshoot and crosstalk of low-voltage GaN HEMT using analytical model

Ultra-fast switching speed and low switching loss of the gallium nitride high electron mobility transistors enable the realisation of high power density converter with excellent conversion efficiency. However, the rapid switching transition leads to significant overshoot and crosstalk issues that ca...

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Main Authors: Wu, Yingzhe, Yin, Shan, Dong, Minghai, Jin, Shoudong, Li, Hui, Cheng, Yuhua, See, Kye Yak
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/163027
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1630272022-11-16T03:28:32Z Prediction of overshoot and crosstalk of low-voltage GaN HEMT using analytical model Wu, Yingzhe Yin, Shan Dong, Minghai Jin, Shoudong Li, Hui Cheng, Yuhua See, Kye Yak School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Fast Switching High Electron-Mobility Transistors Ultra-fast switching speed and low switching loss of the gallium nitride high electron mobility transistors enable the realisation of high power density converter with excellent conversion efficiency. However, the rapid switching transition leads to significant overshoot and crosstalk issues that can degrade the performance of the devices. To facilitate the evaluation of these effects on low-voltage gallium nitride devices, this paper develops an analytical model to predict overshoot and crosstalk during switching transitions accurately and efficiently. The model is constructed based on the detailed circuit deduction of various stages of the device's switching process. It also considers the voltage-dependent junction capacitances as well as the forward and the reverse transconductances. The simulated results obtained from the model are validated experimentally. With the model, the impacts of parasitic elements, especially the power loop inductance, on voltage/current overshoots and spurious voltage due to crosstalk can be easily evaluated, which provides valuable design guidelines for power conversion applications using low-voltage gallium nitride high electron mobility transistor. Published version This work was supported in part by the Project for Transformation of Scientific and Technological Achievements in Sichuan Province under Grant M112021ZHCG0011, and in part by the Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province. 2022-11-16T03:28:32Z 2022-11-16T03:28:32Z 2022 Journal Article Wu, Y., Yin, S., Dong, M., Jin, S., Li, H., Cheng, Y. & See, K. Y. (2022). Prediction of overshoot and crosstalk of low-voltage GaN HEMT using analytical model. IET Power Electronics, 15(13), 1295-1321. https://dx.doi.org/10.1049/pel2.12305 1755-4535 https://hdl.handle.net/10356/163027 10.1049/pel2.12305 2-s2.0-85129869087 13 15 1295 1321 en IET Power Electronics © 2022 The Authors. IET Power Electronics published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Fast Switching
High Electron-Mobility Transistors
spellingShingle Engineering::Electrical and electronic engineering
Fast Switching
High Electron-Mobility Transistors
Wu, Yingzhe
Yin, Shan
Dong, Minghai
Jin, Shoudong
Li, Hui
Cheng, Yuhua
See, Kye Yak
Prediction of overshoot and crosstalk of low-voltage GaN HEMT using analytical model
description Ultra-fast switching speed and low switching loss of the gallium nitride high electron mobility transistors enable the realisation of high power density converter with excellent conversion efficiency. However, the rapid switching transition leads to significant overshoot and crosstalk issues that can degrade the performance of the devices. To facilitate the evaluation of these effects on low-voltage gallium nitride devices, this paper develops an analytical model to predict overshoot and crosstalk during switching transitions accurately and efficiently. The model is constructed based on the detailed circuit deduction of various stages of the device's switching process. It also considers the voltage-dependent junction capacitances as well as the forward and the reverse transconductances. The simulated results obtained from the model are validated experimentally. With the model, the impacts of parasitic elements, especially the power loop inductance, on voltage/current overshoots and spurious voltage due to crosstalk can be easily evaluated, which provides valuable design guidelines for power conversion applications using low-voltage gallium nitride high electron mobility transistor.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Wu, Yingzhe
Yin, Shan
Dong, Minghai
Jin, Shoudong
Li, Hui
Cheng, Yuhua
See, Kye Yak
format Article
author Wu, Yingzhe
Yin, Shan
Dong, Minghai
Jin, Shoudong
Li, Hui
Cheng, Yuhua
See, Kye Yak
author_sort Wu, Yingzhe
title Prediction of overshoot and crosstalk of low-voltage GaN HEMT using analytical model
title_short Prediction of overshoot and crosstalk of low-voltage GaN HEMT using analytical model
title_full Prediction of overshoot and crosstalk of low-voltage GaN HEMT using analytical model
title_fullStr Prediction of overshoot and crosstalk of low-voltage GaN HEMT using analytical model
title_full_unstemmed Prediction of overshoot and crosstalk of low-voltage GaN HEMT using analytical model
title_sort prediction of overshoot and crosstalk of low-voltage gan hemt using analytical model
publishDate 2022
url https://hdl.handle.net/10356/163027
_version_ 1751548564353318912