Identification of Flux Linkage Map of Permanent Magnet Synchronous Machines Under Uncertain Circuit Resistance and Inverter Nonlinearity

This paper proposes a novel scheme for the identification of the whole flux linkage map of permanent magnet synchronous machines, by which the map of dq-axis flux linkages at different load or saturation conditions can be identified by the minimization of a proposed estimation model. The proposed method works on a conventional three-phase inverter based vector control system and the immune clonal based quantum genetic algorithm is employed for the global searching of minimal point. Besides, it is also noteworthy that the influence of uncertain inverter nonlinearity and circuit resistance are cancelled during the modeling process. The proposed method is subsequently tested on two PMSMs and shows quite good performance compared with the finite element prediction results.