LAPSE:2023.14310v1
Published Article
LAPSE:2023.14310v1
An Accurate Switching Transient Analytical Model for GaN HEMT under the Influence of Nonlinear Parameters
Dong Yan, Lijun Hang, Yuanbin He, Zhen He, Pingliang Zeng
March 1, 2023
Abstract
The Gallium Nitride high electron mobility transistor (GaN HEMT) has been considered as a potential power semiconductor device for high switching speed and high power density application since its commercialization. Compared with the traditional Si transistors, GaN HEMT has faster switching speed and lower on-off loss. As a result, it is more sensitive to the nonlinear parameters due to the fast switching speed. The subsequent voltage and current overshooting will affect the efficiency and safety of the GaN HEMT and power electronic systems. In this paper, an accurate switching transient analytical model for GaN HEMT is proposed, which considers the effects of parasitic inductances, nonlinear junction capacitances and nonlinear transconductance. The model characteristic of turn-ON process and turn-OFF process is illustrated in detail, and the equivalent circuits are derived for each switching transition. The accuracy of the proposed model can be verified by comparing the predicted switching waveform and switching loss with that of the experimental results based on the double pulse test (DPT) circuit. Compared with the conventional model, the proposed model is more accurate and matches better with the experimental results than the conventional model. Finally, this model can be used for analyzing the influences of gate resistance, nonlinear junction capacitances, and parasitic inductances on switching transient waveform and refining calculation switching loss.
Keywords
double pulse test, GaN HEMT, nonlinear junction capacitance, nonlinear transconductance, parasitic inductance, switching transient analytical model
Subject
Suggested Citation
Yan D, Hang L, He Y, He Z, Zeng P. An Accurate Switching Transient Analytical Model for GaN HEMT under the Influence of Nonlinear Parameters. (2023). LAPSE:2023.14310v1
Author Affiliations
Yan D: College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China [ORCID]
Hang L: College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
He Y: College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China [ORCID]
He Z: College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
Zeng P: College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
Journal Name
Energies
Volume
15
Issue
8
First Page
2966
Year
2022
Publication Date
2022-04-18
ISSN
1996-1073
Version Comments
Original Submission
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PII: en15082966, Publication Type: Journal Article
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LAPSE:2023.14310v1
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https://doi.org/10.3390/en15082966
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