A Statistical Submodule Open-circuit Failure Diagnosis Method for MMCs Enabling Failure Detection, Localization and Classification

With the increasing application of the modular multilevel converter (MMC), diagnosis of submodule (SM) open-circuit failures is becoming a popular topic. SM open-circuit failure diagnosis normally requires failure detection and failure localization. Almost all existing SM open-circuit failure diagnosis methods execute failure detection and failure localization separately. This not only complicates the diagnosis process, but also results in longer diagnosis time. In this paper, an SM open-circuit failure diagnosis method enabling combined failure detection and localization is proposed. The proposed method is established based on the characteristics that capacitor voltages of faulty SMs variate differently from those of normal SMs. A quantification index of capacitor voltage variation is first proposed. By evaluating the corresponding index values of all SMs with the quartile analysis, failure detection and localization can be implemented simultaneously. What's more, the quartile analysis results can also identify faulty switching devices in the SM, which provides more flexibility for failure tolerant control. The proposed method performs relatively easy and requires no extra hardware resources. Meanwhile, both single and multiple failures can be properly handled whether faulty SMs are in the same or different arms. Besides, the proposed method is immune to parameter uncertainties owing to its statistical property. Experimental results under various failure scenarios are presented to verify the effectiveness of the proposed method.