CJEE

Chinese Journal of Electrical Engineering ›› 2021, Vol. 7 ›› Issue (3): 111-123.doi: 10.23919/CJEE.2021.000030

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Fault-tolerant Deadbeat Model Predictive Current Control for a Five-phase PMSM with Improved SVPWM*

Suleman Saeed1, Wenxiang Zhao1,*, Huanan Wang1, Tao Tao1, Faisal Khan2   

  1. 1. School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China;
    2. Department of Electrical and Computer Engineering, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, Pakistan
  • Received:2021-04-21 Revised:2021-06-21 Accepted:2021-07-21 Online:2021-09-25 Published:2021-09-17
  • Contact: * E-mail: zwx@ujs.edu.cn
  • About author:Suleman Saeed received the B.Sc. degree in Electrical Engineering from COMSATS University Islamabad, Wah Cantt, Pakistan, in 2018. Currently, he is working toward the M.Sc. degree in Electrical Engineering from Jiangsu University, Zhenjiang, China. His research interests include control of multi-phase permanent-magnet machines and power electronics.
    Wenxiang Zhao (M’08-SM’14) received the B.Sc. and M.Sc. degrees in Electrical Engineering from Jiangsu University, Zhenjiang, China, in 1999 and 2003, respectively, and the Ph.D. degree in Electrical Engineering from Southeast University, Nanjing, China, in 2010.He has been with Jiangsu University since 2003, where he is currently a Professor with the School of Electrical Information Engineering. From 2008 to 2009, he was a Research Assistant with the Department of Electrical and Electronic Engineering, University of Hong Kong, Hong Kong, China. From 2013 to 2014, he was a Visiting Professor with the Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, UK. His current research interests include electric machine design, modeling, fault analysis, and intelligent control. He has authored and co-authored over 200 technical papers in these areas.
    Huanan Wang received the B.Sc. degree in Electrical Engineering in Changzhou Institute of Technology, Changzhou, China, in 2018. He is currently working toward the M.Sc. degree in Electrical Engineering at Jiangsu University, Zhenjiang, China. His interest includes the control of multi-phase permanent-magnet machines.
    Tao Tao received the B.Sc. degree in Electrical Engineering from Nanjing Agricultural University, Nanjing, China, in 2009, and the Ph.D. degrees from Jiangsu University, Zhenjiang, China, in 2020, all in Electrical Engineering.He has been with Jiangsu University since 2021, where he is currently a Lecturer in the School of Electrical Information Engineering. His research interests include control of multi-phase permanent-magnet machines.
    Faisal Khan was born in Utmanzai, Charsadda, Khyber Pakhtunkhwa, Pakistan, in 1986. He received the B.S. degree in Electronics Engineering and the M.S. degree in Electrical Engineering from the COMSATS Institute of Information Technology Islamabad, Abbottabad Campus, Pakistan, in 2009 and 2012, respectively, and the Ph.D. degree in Electrical Engineering from Universiti Tun Hussein Onn Malaysia, Malaysia, in 2017. From 2010 to 2012, he was a Lecturer with the University of Engineering and Technology, Peshawar, Abbottabad Campus. Since 2017, he has been an Assistant Professor with the Electrical and Computer Engineering Department, COMSATS University Islamabad, Abbottabad Campus, where he is currently the Head of Electric Machine Design Research Laboratory. He is the author of more than 100 publications. His research interests include design of flux-switching, synchronous, induction, linear, and dc machines. He received multiple research awards. He is a Member of IEEE and IEEE-IES Electrical Machines Technical Committee.
  • Supported by:
    * National Natural Science Foundation of China under Grant 52025073, in part by the Key Research and Development Program of Jiangsu Province under Grant BE2018107, and in part by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

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Abstract: The main drawbacks of traditional finite set model predictive control are high computational load, large torque ripple, and variable switching frequency. A less complex deadbeat (DB) model predictive current control (MPCC) with improved space vector pulse-width modulation (SVPWM) under a single-phase open-circuit fault is proposed. The proposed method predicts the reference voltage vector in the α-β subspace by employing the deadbeat control principle on the machine predictive model; thus, the exhaustive exploration procedure is avoided to relieve the computational load. To perform the constant switching frequency operation and achieve better steady-state performance, a modified SVPWM strategy is developed with the same conventional structure, which modulates the reference voltage vector. This new approach is based on a redesigned and adjusted post-fault virtual voltage vector space distribution that eliminates the y-axis harmonic components in the x-y subspace and ensures the generation of symmetrical PWM pulses. Meanwhile, the combined merits of the DB, MPCC, and SVPWM methods are realized. To verify the effectiveness of the proposed control scheme, comparative experiments are performed on a five-phase permanent magnet synchronous motor (PMSM) drive system.

Key words: Five-phase, fault-tolerant, permanent magnet, deadbeat model predictive control, space vector modulation