Open-Circuit Fault Diagnosis for T-Type Three-Level Inverter via Improved Adaptive Threshold Sliding Mode Observer

T-type three-level inverters have been extensively utilized in renewable energy generation, motor drive systems, and other power conversion applications. However, failures in semiconductor devices critically reduce the operational reliability of power conversion systems. While significant progress has been made in the diagnosis of single-switch open-circuit (OC) faults, the precise location and detection of simultaneous double-switch OC faults remain challenging. Therefore, this paper proposes a fault diagnosis method, integrating an improved adaptive sliding mode observer (IASMO) and dynamic current threshold detection. First, the IASMO is constructed through the hybrid logic dynamic model, achieving accurate and rapid estimation of phase currents. Then, integrating estimated with actual currents accomplishes the design of detection variables and adaptive thresholds. Subsequently, fault location variables are formulated to achieve accurate localization of both single-switch and double-switch faults. Finally, Simulation and experimental results demonstrate that the proposed method effectively identifies 18 types of OC faults within 75% of the current cycle, with high efficiency and robustness.

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Publication Details

Journal
Applied Sciences
Published
2025-05-28
DOI
https://doi.org/10.3390/app15116063
Citations
1
Primary Topic
Multilevel Inverters and Converters
Type
article
Field-Weighted Citation Impact
0.73

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Open-Circuit Fault Diagnosis for T-Type Three-Level Inverter via Improved Adaptive Threshold Sliding Mode Observer

Xiaoyan Zhang, Suping Zhao, Kun Wang, Song Gao et al.
1 citations
Applied Sciences
Multilevel Inverters and Converters
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article

Open-Circuit Fault Diagnosis for T-Type Three-Level Inverter via Improved Adaptive Threshold Sliding Mode Observer

Xiaoyan Zhang, Suping Zhao, Kun Wang, Song Gao, Ziyan Shang, Chaobo Chen
article en
1 citations

Abstract

T-type three-level inverters have been extensively utilized in renewable energy generation, motor drive systems, and other power conversion applications. However, failures in semiconductor devices critically reduce the operational reliability of power conversion systems. While significant progress has been made in the diagnosis of single-switch open-circuit (OC) faults, the precise location and detection of simultaneous double-switch OC faults remain challenging. Therefore, this paper proposes a fault diagnosis method, integrating an improved adaptive sliding mode observer (IASMO) and dynamic current threshold detection. First, the IASMO is constructed through the hybrid logic dynamic model, achieving accurate and rapid estimation of phase currents. Then, integrating estimated with actual currents accomplishes the design of detection variables and adaptive thresholds. Subsequently, fault location variables are formulated to achieve accurate localization of both single-switch and double-switch faults. Finally, Simulation and experimental results demonstrate that the proposed method effectively identifies 18 types of OC faults within 75% of the current cycle, with high efficiency and robustness.

Applied SciencesVol. 15(11)
Xi'an Technological University (CN)
National Natural Science Foundation of China, Key Research and Development Projects of Shaanxi Province
Openalex Percentile: Top 28%
Multilevel Inverters and Converters
0.73
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