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In this work, an enhanced optimal sliding mode control (EOSMC) strategy is proposed for an ultra-high-speed permanent magnet synchronous motor (UHPMSM) in energy-recovery centrifugal air compressor (ERCAC). The model of the control system is developed in the environment of MATLAB/Simulink. A speed controller according to EOSMC is designed to regulate the UHPMSM in ERCAC working in complex working conditions and reduce its speed tracking error. EOSMC constructs an enhanced optimal sliding mode surface by combining the control variables with the state vector and incorporating a comprehensive performance evaluation index. This sliding mode surface contains both the system architecture information and the system's expected performance information. The proposed control effect is compared with a traditional optimal sliding mode control in China heavy-duty commercial vehicle test cycle. The results show that the mean absolute error, mean relative error, and root mean square error of speed tracking decreased by 48.83%, 47.07%, and 2.68%, respectively.

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Extended State-Space Equation-Based Enhanced Optimal Sliding Mode Control for Ultra-High-Speed Permanent Magnet Synchronous Motor in Air Compressor Application

  • 会议论文

  • 发表日期：

    2026年

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  • Zemin Jin,
  • Kai Ou,
  • Xuezhi Zhang,
  • Yaxiong Wang

摘要

In this work, an enhanced optimal sliding mode control (EOSMC) strategy is proposed for an ultra-high-speed permanent magnet synchronous motor (UHPMSM) in energy-recovery centrifugal air compressor (ERCAC). The model of the control system is developed in the environment of MATLAB/Simulink. A speed controller according to EOSMC is designed to regulate the UHPMSM in ERCAC working in complex working conditions and reduce its speed tracking error. EOSMC constructs an enhanced optimal sliding mode surface by combining the control variables with the state vector and incorporating a comprehensive performance evaluation index. This sliding mode surface contains both the system architecture information and the system's expected performance information. The proposed control effect is compared with a traditional optimal sliding mode control in China heavy-duty commercial vehicle test cycle. The results show that the mean absolute error, mean relative error, and root mean square error of speed tracking decreased by 48.83%, 47.07%, and 2.68%, respectively.