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Cited by 144

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Active Gate Driver for Improving Current Sharing Performance of Paralleled High-Power SiC MOSFET Modules

Wen, Yang, Yang, Yuan, Gao, Yong·2021·IEEE Transactions on Power Electronics
DOI 10.1109/tpel.2020.3006071
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Abstract

Featuring higher switching speed and lower losses, the silicon carbide MOSFETs (SiC MOSFETs) are widely used in higher power density and higher efficiency power electronic applications as a new solution. Due to the limited current capability of a single module, more modules parallel-connected are necessary for higher power application. However, current sharing is the key obstacle. In this article, an active gate driver (AGD) for high-power SiC MOSFETs is presented to balance the currents of parallel-connected SiC MOSFET modules. The principle of the AGD is based on dynamic gate drive voltage adjustment to synchronize current edges and current slopes among parallel-connected SiC MOSFET modules automatically. Each AGD measures and controls the current of its SiC MOSFET module individually. No extra supervising control circuit is needed. In addition, the hardware and software configurations are independent of the system design and no restrictions on the number of SiC MOSFET modules connected in parallel exist. Finally, the switching performance of the AGD was experimentally verified on two parallel-connected SiC MOSFET modules in a multipulse test under constant and variable load currents. In addition, the effectiveness of AGD under different control topologies has been studied with simulation and verified using three parallel-connected SiC MOSFET modules.

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Citations

Cites

Research works printed but not linked: 33

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Cited by

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Metadata

Authors
Wen, Y., Yang, Y., & Gao, Y.
Venue
IEEE Transactions on Power Electronics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2021-02
Volume
36
Issue
2
Pages
1491-1505
ISSN
  • 0885-8993
  • 1941-0107
DOI
10.1109/tpel.2020.3006071
Cited by
144
References
1
Licence
Funders
  • National Natural Science Foundation of China (51477138)
  • Key Research and Development Program of Shaanxi in Shaanxi, China (2017ZDXM-GY-130)

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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.