volume | PIER Journals

Abstract

The open-circuit fault diagnosis of switches in quasi-Z-source inverters (qZSI) is challenging. Existing methods struggle to simultaneously achieve high robustness and low computational complexity without additional sensors. In this study, an open-circuit fault diagnosis method based on an improved super-twisting non-singular fast terminal sliding-mode observer (IST-NFTSMO) and hybrid features is proposed. The stator currents were estimated in real time by the IST-NFTSMO, and residuals were generated accordingly. By analyzing differences in the statistical distributions of residuals between healthy and faulty conditions, two features were extracted: average log-likelihood ratio (ALLR) and signed cumulative ratio (SCR). The ALLR is used for rapid fault detection, whereas the SCR is used for accurate localization of faulty switches. The proposed method was implemented entirely based on existing current sensors. No additional voltage sensors were required. Moreover, the diagnostic thresholds are adaptively adjusted according to variations in speed and load. The experimental results demonstrate that both single-switch and dual-switch open-circuit faults can be diagnosed rapidly and accurately. Compared with conventional methods, higher robustness and lower computational complexity were achieved.

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Dr. Yang Zhang

Dr. Moutao Li

Dr. Shaoziyi Wu

Dr. Jiahao Zhang

Dr. Qianghui Xiao