Online SSA-Based Real-Time Degradation Assessment for Inter-Turn Short Circuits in Permanent Magnet Traction Motors

• Published in: Electronics (Basel) Vol. 14; no. 10; p. 2095
• Main Authors: Cheng, Zhenglin, Li, Xueming, Liu, Kan, Chen, Zhiwen, Jiang, Fengbing
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 21.05.2025
• Subjects: Accuracy; Algorithms; Analysis; Circuits; Degradation; Efficiency; Fault diagnosis; Fault location; Fourier transforms; Insulation; Magnetic fields; Magnets, Permanent; Methods; Neural networks; Parameter estimation; Parameter identification; Permanent magnets; Real time; Search algorithms; Short circuits; Synchronous motors; Traction; Working conditions
• ISSN: 2079-9292; 2079-9292
• DOI: 10.3390/electronics14102095

Inter-turn short circuits (ITSCs) in permanent magnet synchronous motors (PMSMs) pose significant risks due to their subtle early symptoms and rapid degradation. To address this, we propose an online real-time diagnostic method for assessing the degradation state. This method employs the Sparrow Search Algorithm (SSA) for the online real-time identification of fault characteristic parameters. Following an analysis of the fault mechanisms of inter-turn short circuits, a mathematical model has been developed to include the short-circuit turns ratio and insulation resistance. An evaluation index has also been developed to assess the degree of fault-related degradation. To address the strong nonlinearity of parameters in the fault model, the SSA is employed for the real-time joint identification of parameters that characterize the relationship between fault location and degradation degree. Simulation experiments demonstrate that the SSA achieves convergence within 40 iterations, with a relative error below 5% and absolute error less than 0.007, outperforming traditional algorithms like the PSO, a significant improvement in the early detection of degradation caused by inter-turn short circuits and a step forward in technical support ensuring greater reliability and safety for the traction systems used in rail transit.