Multi-Objective Optimization of Current Waveform of Bearingless Switched Reluctance Motor for Torque Ripple and Radial Force Ripple Reduction

In this paper, the multi-objective optimization of current waveform of the bearingless switched reluctance motor (BSRM) with the independent control strategy is investigated to reduce torque ripple and radial suspension force ripple. At first, the analytical model of BSRM is introduced. The current waveform for the independent control strategy based on the analytical model is calculated, then the transient electromagnetic torque and suspension force is obtained. In order to reduce the torque ripple and suspension force ripple, the analytical model is combined with the multi-objective genetic particle swarm optimizer. The Pareto front is searched after the iterations. Then, the final optimal solution is selected from the searched Pareto front and the electromagnetic performance is analyzed. Compared with the electromagnetic performance of the current waveform before optimization, the torque ripple and suspension force ripple are both reduced after the multi-objective optimization, which indicates the proposed multi-objective optimization of current waveform of BSRM with the independent control strategy is effective and feasible.