中国电气工程学报（英文） ›› 2021, Vol. 7 ›› Issue (3): 100-110.doi: 10.23919/CJEE.2021.000029

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  • 收稿日期:2021-05-11 修回日期:2021-06-25 接受日期:2021-08-09 出版日期:2021-09-25 发布日期:2021-09-17

Accurate Online MTPA Control of IPMSM Considering Derivative Terms*

Riyang Yang1,2, Tianfu Sun1,*, Wei Feng1, Shaojia He2, Songling Zhu1, Xiao Chen3   

  1. 1. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518000, China;
    2. Electromechanical Engineering College, Guilin University of Electronic Technology, Guilin 541000, China;
    3. Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield S1 3JD, UK
  • Received:2021-05-11 Revised:2021-06-25 Accepted:2021-08-09 Online:2021-09-25 Published:2021-09-17
  • Contact: * E-mail: tianfu.sun@foxmail.com
  • About author:Riyang Yang was born in China. He received the B.E. degree in Electrical Engineering and Automation from Guilin University of Electronic Technology, Guilin, China, in 2018. He is currently working toward the M.E. degree in Mechanical Engineering, Guilin University of Electronic Technology, Guilin, China.He was a guest student in Electric Drive at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences. Currently he is an Engineer at Shenzhen Zhaowei Machinery & Electronics Co., Ltd. His research interests include motor drives and parameter identification of IPMSM.
    Tianfu Sun was born in China. He received B.E. degree in Mechanical Engineering, M.Sc. degree in Civil Engineering (mechanics) from Dalian University of Technology, Dalian, China, in 2009 and 2012, respectively, and the Ph.D. degree in Electrical and Electronic Engineering from the University of Sheffield, Sheffield, UK, in 2016. From 2016 to 2017, he was with the Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, UK, where he was a Postdoctoral Research Fellow. He is currently working as an Associate Professor and a Senior Engineer in Electric Drives at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. He is also the Director of the Shenzhen Key Laboratory of Electric Vehicle Powertrain Platform and Safety Technology. His current research interests include power electronics and motor drives.
    Wei Feng received his B.Sc. degree in 2001 from Huazhong University of Science and Technology, received his Ph.D. degree in 2006 from Huazhong University of Science and Technology. Currently he is Professor in Shenzhen Institute of Advanced technology, Chinese Academy of Science. His main research interests include digital intelligent manufacturing and industrial electronics.
    Shaojia He was born in China. He receives the B.E. degree in Automatic Control Engineering from the University of Electronic Science and Technology of China, receives the M.E. degree in Detection Technology and Automatic Equipment from the University of Shanghai Science and Technology, and receives the Ph.D. degree in Control Theory and Control Engineering from the East China University of Science and Technology. Now, he is a Professor at the Guilin University of Electronic Technology. His main research interests include mechanical and electrical control equipment and power supply technology.
    Songling Zhu was born in China. He received the B.S degree in Biotechnology in 2014 from the Hunan Normal University, Changsha, China. He is currently a student in Electric Drive with the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. His research interests include power electronics and control of interior permanent magnet synchronous machines.
    Xiao Chen received the B.E. degree from the Harbin Institute of Technology, Weihai, China, in 2009, the M.E. degree from the Harbin Institute of Technology, Harbin, China, in 2011, and the Ph.D. degree from The University of Sheffield, Sheffield, UK, in 2015, all in Electrical Engineering. He is currently a Research Associate with the Department of Electronic and Electrical Engineering, The University of Sheffield. His current research interests include the modeling, design, and analysis of permanent-magnet synchronous machines for traction applications.
  • Supported by:
    * Key-Area R&D Program of Guangdong Province (2019B090917001, 2020B090925002), Guangdong-Hong Kong-Macao Greater Bay Area innovation project (2020A0505090002), Shenzhen Fundamental Research Program (JCYJ20180507182619669, JCYJ20170818164527303), Youth Innovation Promotion Association CAS (2021360) and the National Natural Science Foundation of China (51707191, U1813222).

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Abstract: The conventional maximum torque per ampere (MTPA) operation usually neglects the derivative terms of interior permanent magnet synchronous motor (IPMSM) parameters, which significantly influences MTPA control accuracy. In this study, an MTPA control scheme that considers the derivative terms is developed, and a parameter identification strategy that considers the inverter to be non-ideal is developed for the calculation of the IPMSM parameters and derivative terms. In addition, the estimation accuracy of the motor parameters is further improved through the calibration of the nonlinear factors of the inverter. Finally, the effectiveness and accuracy of the proposed method is verified by simulation. This paper proposes practical methods for both inverter parameter estimation and accurate online MTPA control.

Key words: MTPA, parameter identification, IPMSM, derivative terms, inverter nonlinearity