Virtual Back EMF Injection-Based Online Full-Parameter Estimation of DTP-SPMSMs Under Sensorless Control

Under sensorless control, the position estimation error in permanent magnet (PM) synchronous machines (PMSMs) will lead to parameter estimation errors. In this article, by injecting a novel square wave virtual back EMF (VBEMF) into either of two position observers for both three phase sets in dual-three phase surface-mounted PMSMs (DTP-SPMSMs), it is found that the fluctuation of sum of q-axis voltages in both sets will decrease as the parameter estimation accuracies of stator resistance and inductance in both position observers increase. Therefore, the fluctuation of sum of q-axis voltages can be minimized to estimate stator inductance and resistance, which is immune to position error. The PM flux linkage is correspondingly estimated from identified back EMF utilizing Kalman filter (KF) algorithm. Moreover, utilizing the DTP winding characteristic of DTP-SPMSMs, the proposed VBEMF is only injected into one set, which can reduce the torque ripple by about 50%. The experiments are given to validate the proposed method.