Online Parameter Identification Based on MTPA Operation for IPMSM

This paper proposes a model-based forecasting method to estimate electrical parameters of an Interior Permanent Magnet Synchronous Motor(IPMSM) using Maximum Torque Per Ample(MTPA) control strategy. Parameter identification technology is practical in the field of motor control, and the model-based forecasting method proposed in this paper, is practical due to its simplicity and obtaining fast convergency simultaneously. In addition, parameters identified by the algorithm can be updated and used in control strategies automatically in real time, which also enhances the control performance. Finally, the model-based forecasting method put forward in this paper is verified on a prototype of an IPMSM by simulation.