中国电气工程学报（英文） ›› 2018, Vol. 4 ›› Issue (2): 65-81.

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  • 出版日期:2018-06-25 发布日期:2019-10-31

Performance Evaluation of Two-Vector-Based Model Predictive Current Control of PMSM Drives

Yongchang Zhang1,*, Lanlan Huang1, Donglin Xu1, Jiali Liu1, Jialin Jin1   

  1. 1. Inverter Technologies Engineering Research Center of Beijing, North China University of Technology, Beijing 100144, China
  • Online:2018-06-25 Published:2019-10-31
  • Contact: *,E-mail:zyc@ncut.edu.cn.
  • About author:Yongchang Zhang (M’10, SM’18) received the B.S. degree from Chongqing University, China, in 2004 and the Ph.D. degree from Tsinghua University, China, in 2009, both in electrical engineering. From August 2009 to August 2011, he was a Postdoctoral Fellow at the University of Technology Sydney, Australia. He joined North China University of Technology in August 2011 as an associate professor. Currently he is a full professor and the director of Inverter Technologies Engineering Research Center of Beijing. He has published more than 100 technical papers in the area of motor drives, pulse width modulation and AC/DC converters. His current research interest is model predictive control for power converters and motor drives. Lanlan Huang was born in 1994. She received the B.S. degree in renewable energy science and engineering from North China University of Technology, Beijing, China, in 2016, where she is currently working toward the master’s degree in electrical engineering. Her research interests include model predictive control of PMSM drives. Donglin Xu was born in 1992. He received the B.S. degree in electrical engineering from North China University of Technology, Beijing, China, in 2015, where he is currently working toward the master’s degree in electrical engineering. His research interests include model-predictive control of doubly fed induction generators. Jiali Liu was born in 1989. He received the B.S. degree in electrical engineering from North China Institute of Science and Technology, Beijing, China, in 2013. He is currently working toward the master’s degree in electrical engineering at the North China University of Technology, Beijing. His research interests include model-predictive control of permanent magnet synchronous machine drives. Jialin Jin was born in 1993. He received the B.S. degree from North China University of Technology in 2017. He is currently working toward the Master degree in electrical engineering at North China University of Technology, Beijing, China. His research interest is model predictive control of permanent magnet synchronous motor drives.

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Abstract: Conventional model predictive current control (MPCC) applies only one vector during one control period, which produces large torque and flux ripples and high current harmonics in permanent magnet synchronous motor (PMSM) drives. Recently MPCC with duty cycle control has been proposed to improve the steady state performance by applying one non-zero vector and one null vector during one control period. However, the prior method requires lots of calculations and predictions to find the optimal voltage vectors and calculate their respective duration. Different from prior enumeration-based MPCC, this paper proposes an efficient two-vector MPCC by applying two arbitrary voltage vectors during one control period. The reference voltage vector is firstly calculated based on the principle of deadbeat current control. Two optimal vectors and their duration are then obtained in a very efficient way, which does not require the calculation of current slopes in prior MPCC methods. The proposed method is compared to the state-of-the-art predictive control methods, including conventional MPCC, MPCC with duty cycle control, deadbeat control with space vector modulation (SVM) and modulated model predictive control (M2PC). Both simulation and experimental results prove that the proposed method achieves better steady state performance than conventional MPCC with or without duty cycle and the dynamic response is not degraded. Under the condition of insufficient dc bus voltage, the proposed method outperforms deadbeat control and M2PC by presenting even higher speed range and less torque ripples.

Key words: Predictive control, current control, PMSM drives