State Estimation and Remaining Useful Life Prediction of PMSTM Based on a Combination of SIR and HSMM

Guishuang Tian, Shaoping Wang, Jian Shi () and Yajing Qiao
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Guishuang Tian: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Shaoping Wang: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Jian Shi: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Yajing Qiao: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China

Sustainability, 2022, vol. 14, issue 24, 1-21

Abstract: The permanent magnet synchronous traction motor (PMSTM) is the core equipment of urban rail transit. If a PMSTM fails, it will cause serious economic losses and casualties. It is essential to estimate the current health state and predict remaining useful life (RUL) for PMSTMs. Directly obtaining the internal representation of a PMSTM is known to be difficult, and PMSTMs have long service lives. In order to address these drawbacks, a combination of SIR and HSMM based state estimation and RUL prediction method is introduced with the multi-parameter fusion health index (MFHI) as the performance indicator. The proposed method’s advantages over the conventional HSMM method were verified through simulation research and examples. The results show that the proposed state estimation method has small error distribution results, and the RUL prediction method can obtain accurate results. The findings of this study demonstrate that the proposed method may serve as a new and effective technique to estimate a PMSTM’s health state and RUL.

Keywords: permanent magnet synchronous traction motor (PMSTM); state estimation; remaining useful life (RUL) prediction; hidden semi-Markov model (HSMM); sample importance resampling (SIR); multi-parameter fusion health index (MFHI) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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