Genetic algorithm based current optimization for torque ripple reduction of interior PMSMs

This paper investigates the torque ripple modeling and minimization for interior permanent magnet synchronous machine (PMSM). At first, a novel torque ripple model is proposed. In this model, both spatial harmonics of magnet flux linkage and current time harmonics induced by machine drive are considered, which includes the torque ripples resulted from magnet torque, reluctance torque and cogging torque. Based on the proposed model, a novel genetic algorithm (GA) based dq-axis harmonic currents optimization approach is proposed for torque ripple minimization. In this approach, the GA is applied to optimize both the magnitude and phase of the harmonic currents to achieve the objectives of: 1) minimizing the peak-to-peak torque ripple; 2) minimizing the sum of squares of the harmonic currents; and 3) maximizing the average torque component produced by the injected harmonic currents. The results demonstrate that the magnitude of the harmonic current can be significantly reduced by considering the phase angles of these harmonic currents as the optimization parameters. This leads to further suppression of the torque ripple when compared to that of a case where phase angles are not considered in the optimization. Also, an increase of the average torque is achieved when the optimum harmonic currents are injected. The proposed model and approach are evaluated with both numerical and experimental investigations on a laboratory interior PMSM.