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A Simulation Model for SiC MOSFET Switching Transients Controlled by an Adaptive Gate Driver with the Capability of Reducing Switching Losses and EMI across the Full Operating Range

Title data

Li, Zheming ; Maier, Robert ; Bakran, Mark-M.:
A Simulation Model for SiC MOSFET Switching Transients Controlled by an Adaptive Gate Driver with the Capability of Reducing Switching Losses and EMI across the Full Operating Range.
2022
Event: EPE 2022 ECCE Europe , 05.-09.09.2022 , Hannover.
(Conference item: Conference , Paper )

Abstract in another language

In this paper, the performance of an intelligent-gate-driver-based self-regulating gate control approach,
which can reduce switching losses and EMI at SiC MOSFET turn-off and turn-on, is investigated by
simulation and verified by measurements. Firstly, a MOSFET behavior model is presented and confirmed
with double pulse measurement results of this approach. Based on this model, the performance
of this approach in continuous operation is evaluated and compared with measurement in continuous
operation. It is verified that there is a good match between measurement and simulation. The trade-off
between switching losses and EMI is improved significantly by the proposed gate control approach
compared to simple gate control with a single gate resistance.

Further data

Item Type: Conference item (Paper)
Refereed: Yes
Institutions of the University: Faculties > Faculty of Engineering Science > Chair Mechatronics > Chair Mechatronics - Univ.-Prof. Dr.-Ing. Mark-M. Bakran
Profile Fields > Advanced Fields > Advanced Materials
Profile Fields > Emerging Fields > Energy Research and Energy Technology
Research Institutions > Research Units > ZET - Zentrum für Energietechnik
Faculties
Faculties > Faculty of Engineering Science
Faculties > Faculty of Engineering Science > Chair Mechatronics
Profile Fields
Profile Fields > Advanced Fields
Profile Fields > Emerging Fields
Research Institutions
Research Institutions > Research Units
Result of work at the UBT: Yes
DDC Subjects: 600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 23 Sep 2022 12:19
Last Modified: 23 Sep 2022 12:19
URI: https://eref.uni-bayreuth.de/id/eprint/71956