155 / 2025-05-24 19:52:57
Model Predictive Current Control for Dynamic Enhancement in PMSM PHIL Simulation
model predictive current control, permanent magnet synchronous motor, power-level hardware-in-the-loop simulation
全文录用
Xingjian Zhao / Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences
Li Jiang / Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences
Ge Gao / Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences
Hong Lei / Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences
This paper addresses the issue of insufficient dynamic performance in traditional PI control for power-level hardware-in-the-loop (PHIL) simulations of permanent magnet synchronous motor (PMSM) controllers. An optimized algorithm based on model predictive current control (MPCC) is proposed. By constructing a PHIL platform integrated with a digital twin model and combining multi-step prediction with feedback correction mechanisms, control delays are effectively compensated, and model mismatch is suppressed. Experimental results demonstrate that compared to PI control, the MPCC algorithm reduces the root mean square error of current tracking by 42%, decreases the maximum overshoot of current and speed by 62% and 79%, respectively, and significantly enhances dynamic response. The study validates the engineering value of model predictive control in PHIL systems, providing an efficient solution for high-precision motor controller testing.
重要日期
  • 会议日期

    06月05日

    2025

    07月08日

    2025

  • 05月30日 2025

    初稿截稿日期

  • 06月08日 2025

    注册截止日期

主办单位
IEEE PELS
IEEE
承办单位
Southeast University
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