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Cited by 6

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Static Current Unbalance of Paralleled SiC MOSFET Modules in the Final Layout

Jauregi, Ander, Garrido, David, Baraia-Etxaburu, Igor, Garcia-Bediaga, Asier, Rujas, Alejandro·2020·2020 IEEE Vehicle Power and Propulsion Conference (VPPC)

Abstract

Silicon Carbide (SiC) MOSFETs enable enhanced performance of power converters in several applications. Parallel connection of SiC MOSFETs become mandatory for medium power applications due to the current rate of existing modules. A balanced current sharing between paralleled MOSFETs is desired to maximize the power capability of each device, maximizing the power capability of the whole system. This work studies the static current unbalance of two paralleled 1200V-400A SiC MOSFET modules with individual gate driver. Experimental measurements are done focused on parasitic inductance caused by electromechanical layout.

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Citations

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Research works printed but not linked: 16

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  14. sakaguchi, 2017, Characterization of 3.3 kv and 6.5 kv sic mosfets, PCIM Europe 2017 International Exhibition and Conference for Power Electronics Intelligent Motion Renewable Energy and Energy Management, 1
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  16. mao, 2017, Passive Balancing of Switching Transients between Paralleled SiC MOSFETs

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Metadata

Authors
Jauregi, A., Garrido, D., Baraia-Etxaburu, I., Garcia-Bediaga, A., & Rujas, A.
Venue
2020 IEEE Vehicle Power and Propulsion Conference (VPPC)
Publisher
IEEE
Published
2020-11
Pages
1-5
Cited by
6
References
0

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CoChat. (2026). Citation check: Static Current Unbalance of Paralleled SiC MOSFET Modules in the Final Layout. https://app.cochat.ai/papers/10.1109/vppc49601.2020.9330969
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Jauregi, A., Garrido, D., Baraia-Etxaburu, I., Garcia-Bediaga, A., & Rujas, A. (2020). Static Current Unbalance of Paralleled SiC MOSFET Modules in the Final Layout. 2020 IEEE Vehicle Power and Propulsion Conference (VPPC). https://doi.org/10.1109/vppc49601.2020.9330969

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.