A Novel Two-Step Flux Linkage Identification for PMSMs Considering Magnetic Saturation and Spatial Harmonics

Accurate identification of flux linkages through experimental tests is important for both motor design validations and the development of advanced control techniques for permanent magnet synchronous machines (PMSMs). This paper proposes a novel two-step flux linkage identification method for PMSMs considering both magnetic saturation and spatial harmonics. In step one, an offline estimation of the flux linkages considering magnetic saturation based on genetic algorithm is proposed, while the spatial harmonics effect has been mitigated compared with the existing method. In the second step, the Kalman filter is employed to estimate the spatial harmonics online based on the proposed state-space observer with the estimated offline data in step one. Therefore, the proposed method achieves to consider both magnetic saturation and spatial harmonics for PMSM flux linkage identification. The proposed model and approach are tested on both interior PMSM and surface-mounted PMSM using the finite element analysis (FEA) supported co-simulation and show good performance compared with the FEA results.