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Cited by 16

The DOI matches its Crossref record.

Simulation and experimental investigation of parallel connected IGBTs

Alvarez, Rodrigo, Fink, Karsten, Bernet, Steffen·2010·2010 IEEE International Conference on Industrial Technology
DOI 10.1109/icit.2010.5472617
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Abstract

The increasing demand for large power ratings and the physically limited maximum current density of semiconductor devices in power electronics make the connection of semiconductor in parallel or series an interesting alternative for high power applications. The major problem of the IGBT parallel connection is the current unbalance of parallel devices, which requires the selection of the devices, a manual parameterization of gate units and a substantial device derating in state of the art high power IGBT Voltage Source Converters. This paper presents a new scheme for the non-destructive parameter extraction of IGBTs and a simulative study of the influence of different parameters on the current distribution of parallel connected IGBTs. The investigations show that the delay time of parallel switched IGBTs can be used to achieve a balanced current distribution despite potentially varying parameters like gate-emitter threshold voltages and internal gate resistances. The results are experimentally verified by measurements in a 500 V, 800A test set-up applying 1700V, 450 A IGBTs and inverse diodes.

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Research works printed but not linked: 19

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  11. yang, 2005, investigation of parallel connection of igbts, 2005 International Conference on Electrical Machines and Systems ICEMS-05, 1, 833, 10.1109/ICEMS.2005.202654 · DOI
  12. 10.1109/EPE.2005.219697 · DOI
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Cited by

Metadata

Authors
Alvarez, R., Fink, K., & Bernet, S.
Venue
2010 IEEE International Conference on Industrial Technology
Publisher
IEEE
Published
2010
Pages
824-831
DOI
10.1109/icit.2010.5472617
Cited by
16
References
0

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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.