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A Survey on Fault Diagnosis and Fault Tolerant Methodologies for Permanent Magnet Synchronous Machines

Abstract

This paper presents a comprehensive survey of fault diagnosis and fault tolerant approaches for permanent magnet synchronous machines (PMSM). PMSMs are prominent in the pervading usage of electric motors, for their high efficiency, great robustness, reliability and low torque inertia. In spite of their extensive appliance, they can be quite non-resilient and inadequate in operation when faults appear in motor drive apparatus such as inverters, stator windings, sensors, etc. These may lead to insulation failure, torque fluctuations, overcurrent or even system collapse. On that account, fault diagnosis and fault tolerant methods are equipped to enhance the stability and robustness in PMSMs. Progressive methodologies of PMSM fault diagnosis and tolerance are classified, discussed, reviewed and compared in this paper, beginning with mathematical modeling of PMSM and then scrutinizing various fault conditions in PMSMs. Finally, the scope of research on the topic is highlighted. The contribution of this review is to emphasize optimistic schemes and to assist researchers with the latest trends in this field for future directions.

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Correspondence to Erphan A. Bhuiyan.

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Erphan A. Bhuiyan is currently pursuing the B.Sc. degree in mechatronics engineering from Rajshahi University of Engineering & Technology (RUET), Bangladesh. He is currently working on a formula student electric vehicle project.

His research interests include control theory and applications, fault diagnosis, fault tolerant control, electrical machines, mechatronics systems and electric vehicle technologies.

Md. Maeenul Azard Akhand is currently pursuing the B.Sc. degree in mechatronics engineering from Rajshahi University of Engineering and Technology, Bangladesh. He is currently working on a formula student electric vehicle project.

His research interests include fault diagnosis and tolerant control of electric vehicles, automotive engineering, robust control of mechatronics system and virtual power plant.

Sajal Kumar Das received the Ph.D. degree in electrical engineering from University of New South Wales, Australia on 2014. In May 2014, he was appointed as a research engineer in National University of Singapore (NUS), Singapore. In January 2015, he joined in Department of Electrical and Electronic Engineering of American International University-Bangladesh (AIUB) as an assistant professor. He continued his work at AIUB until he joined in Department of Mechatronics Engineering of Rajshahi University of Engineering and Technology, Bangladesh as a lecturer on September, 2015. He is currently working as an assistant professor in RUET.

His research interests include control theory and applications, mechatronics system control, robotics, and power system control.

Md. F. Ali is currently working as an assistant professor from Department of Mechatronics Engineering, Rajshahi University of Engineering and Technology, Bangladesh.

His research interests include power electronics, control theory and applications, mechatronics, and artificial intelligence.

Z. Tasneem is currently working as an assistant professor at Department of Mechatronics Engineering, Rajshahi University of Engineering and Technology, Bangladesh from February, 2018.

Her research interests include power electronics, control system, mechatronics, and aerodynamics.

Md. R. Islam is currently working as a lecturer in Department of Mechatronics Engineering, Rajshahi University of Engineering and Technology, Bangladesh. Previously, he was appointed as the head of Department of Mechanical Engineering, Bangladesh Army University of Science and Technology (BAUST), Bagladesh from February 2015 to August 2018.

His research interests include mechatronic systems design, robotics, control system and renewable energy.

D. K. Saha received the B.Sc. degree in mechanical engineering from Rajshahi University of Engineering and Technology, Bangladesh in 2012. He is pursuing the M.Sc. degree in mechanical engineering in RUET. Currently, he is working as a lecturer in Department of Mechatronics Engineering, RUET. Before, he was in Walton Hi-Tech Industries Ltd. as research & development engineer in Refrigerator Cooling Design Section.

His research interests include vibration-based condition monitoring, machine learning, and mechatronics.

Faisal R. Badal received the B.Sc. degree in mechatrans engineering from Rajshahi University of Engineering and Technology, Bangladesh in 2017. He is currently working as a lecturer in Department of Mechatronics Engineering, Rajshahi University of Engineering and Technology, Bangladesh.

His research interests include smartgrid, artificial intelligence, machine learning, natural language processing, and robotics.

Md. H. Ahamed received the B.Sc. degree in mechatronics engineering from Rajshahi University of Engineering and Technology, Bangladesh in 2017. He is currently pursuing the M. Sc. degree in engineering in the Department of Computer Science and Engineering, Rajshahi University of Engineering and Technology, Bangladesh. He is working as a lecturer in Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology.

His research interests include machine vision, artificial intelligence, machine learning, robotics, and image processing.

S. I. Moyeen received the B.Sc. degree in computer science and engineering from Rajshahi University of Engineering and Technology, Bangladesh in 2017. In November 2019, she joined Department of Mechatronics Engineering of Rajshahi, University of Engineering and Technology, Bangladesh as a lecturer.

Her research interests include data mining and big data, web development, IoT, cloud computing, image processing, and artificial intelligence.

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Bhuiyan, E.A., Akhand, M.M.A., Das, S.K. et al. A Survey on Fault Diagnosis and Fault Tolerant Methodologies for Permanent Magnet Synchronous Machines. Int. J. Autom. Comput. 17, 763–787 (2020). https://doi.org/10.1007/s11633-020-1250-3

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Keywords

  • Permanent magnet synchronous machine (PMSM)
  • fault diagnosis
  • fault tolerant control system (FTCS)
  • fault detection
  • stability