A Novel Radial Force Ripple Suppression Method of Switched Reluctance Machines based on Force Sharing Function

Switched reluctance machines (SRMs) are widely valued because of their efficient cost and robust structure. However, the serve vibration and noise limit their application. The large radial force ripple is one of the main causes of vibration and noise for SRMs. This paper proposes a model predictive control (MPC) based on a novel force sharing function (FSF) to effectively reduce the radial force ripple of SRMs. The FSF is constructed based on the optimal flux-linkage curve, and online compensation is added to realize the real-time optimization of FSF. Based on the measured rotor position, phase current, and phase flux-linkage, the radial force of the SRM is predicted for all possible switching states, the cost function is constructed, and the operating state with the minimum cost function value is applied to control the power converter. To verify the feasibility and effectiveness of the strategy, simulation and experimental verification are performed with a three-phase 12/8-pole SRM, and the results prove that the proposed method can effectively suppress the force ripple.