Multiple saliency-ratio model predictive control for variable reluctance flux controllable permanent magnet motors

For variable reluctance flux controllable permanent magnet (VRFCPM) motors, the alteration in saliency ratio caused by the variable magnetic circuit reluctance inevitably leads to the mismatch of the motor control parameters. To solve this problem, based on the model predictive control (MPC) principle, a multiple saliency-ratio model predictive control (MSR-MPC) method is proposed in this article. It focuses on the development of a saliency ratio predictive model and an improved cost function to enhance the performance of the VRFCPM motor in terms of current harmonic, tracking error, dynamic overshoot, and efficiency. In the proposed MSR-MPC method, the mathematic model with the variable saliency ratio is derived for VRFCPM motor where the voltage vector synthesis is also reconstructed. In addition, a model predictive controller is designed by considering multiple operating conditions, and the saliency ratio term is adopted for the cost function. Finally, comparative experiments are conducted to validate the effectiveness of the proposed control strategy.