Sensorless Finite-Control Set Model Predictive Torque Control With Minimized Switching States for SRM Drives

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Abstract
In this paper, a sensorless finite-control set model predictive torque control (FCS-MPTC) strategy is proposed for switched reluctance motor (SRM) drives. To minimize the switching vector candidates and relieve the computing pressure in traditional MPTC methods, the flux linkage closed loop is adopted to assist candidate vector screening. In the controller, the flux linkage of each phase is calculated via the flux integral with the terminal voltage and phase currents. Through alpha belta transformation, the rotating flux angle and rotational speed can be estimated via phase locked loop (PLL). As the rotor position angle is synchronizing with the rotating flux angle, thus can be estimated directly by compensating the angle bias between them. The estimated position angle can be used for modeling the flux linkage and deriving the predicted torque, which is utilized in constructing the cost function in the MPTC method. Based on the aforementioned control process, the position sensorless control can be fully achieved. The experiments are performed under a 12/8 SRM test-bed, which verify the validity of the proposed method
Funding Information
  • National Natural Science Foundation of China (52477055)
  • Excellent Research and Innovation Teams in Universities in Anhui Province (2023AH010021)

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