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Cited by 361

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Fault Detection for Modular Multilevel Converters Based on Sliding Mode Observer

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Shao, Shuai, Wheeler, Patrick W., Clare, Jon C., Watson, Alan J.·2013·IEEE Transactions on Power Electronics

Abstract

This letter presents a fault detection method for modular multilevel converters which is capable of locating a faulty semiconductor switching device in the circuit. The proposed fault detection method is based on a sliding mode observer (SMO) and a switching model of a half-bridge, the approach taken is to conjecture the location of fault, modify the SMO accordingly and then compare the observed and measured states to verify, or otherwise, the assumption. This technique requires no additional measurement elements and can easily be implemented in a DSP or microcontroller. The operation and robustness of the fault detection technique are confirmed by simulation results for the fault condition of a semiconductor switching device appearing as an open circuit.

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Metadata

Authors
Shao, S., Wheeler, P. W., Clare, J. C., & Watson, A. J.
Venue
IEEE Transactions on Power Electronics
Published
2013-11
Volume
28
Issue
11
Pages
4867-4872
ISSN
  • 0885-8993 (ISSN-L)
  • 1941-0107
OpenAlex
W2061146253
Cited by
361
References
1
FWCI
19.57
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Fault Detection for Modular Multilevel Converters Based on Sliding Mode Observer. https://app.cochat.ai/papers/10.1109/tpel.2013.2242093
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Shao, S., Wheeler, P. W., Clare, J. C., & Watson, A. J. (2013). Fault Detection for Modular Multilevel Converters Based on Sliding Mode Observer. IEEE Transactions on Power Electronics. https://doi.org/10.1109/tpel.2013.2242093

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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.