Reliability evaluation method of PMFSM system based on hidden Markov

To solve the complex calculation in the reliability evaluation of the motor system with the Markov model, this study developed a reliability evaluation method based on the hidden Markov model (HMM). Next, the developed method was employed in a type of permanent magnet hybrid segmented flux-switching machine (PMFSM). By analyzing and simplifying the components of the PMFSM system, the reliability measurement standard and the failure modes of the respective component were examined, and the relationships between the failure modes of each component and the system parameters were built. The optimal parameter observation sequence was determined by calculating the Minkowski distance, and the HMM was iteratively calculated by using the Baum-Welch algorithm. Moreover, the state transition probability matrix of the system was built, and the system reliability was evaluated. As revealed from the calculation results, the reliability of the PMFSM system is significantly higher than that of the conventional structure at the same time, and the mean time to failure (MTTF) of the PMFSM system is 14.8% higher than that of the conventional structure. Compared with the conventional evaluation method based on the Markov model, the two methods have similar reliability results for conventional and novel PMFSM systems, and the variation trend is the same. It shows that the proposed reliability evaluation method is feasible and effective, and the calculation is simple. The work in this study provides a basis for the design of the novel PMFSM system, and a practical engineering method to efficiently evaluate the reliability of other motor systems.