A Novel MTPA-Flux Weakening Feedforward Control Strategy of PMSM Based on On-line Model Parameter Update

The traditional MTPA-flux weakening control method depends on the off-line calibration and PI feedback(leading angle control method). This will cause insufficient responsiveness if the motor parameters change. This paper proposes a novel MTPA-flux weakening feedforward control strategy based on model parameter updates. To reduce the real-time calculation load, the Ferrari collocation method is used to solve the quartic equation to obtain the MTPA explicit format model, and the discrete bisection method is used to quickly solve the working point in the flux weakening stage. By judging the relationship among the target torque working line, the voltage limiting circle and the current limiting circle, the intersection point with the minimum current loss is selected as the working point. The advantages of the designed MTPA-flux weakening feedforward control strategy are verified by implementing the simulation based on a permanent magnet synchronous motor model. The simulation results show that the MTPA-flux weakening feedforward control strategy has better smoothness in mode switching than the look-up table-based MTPA method and the leading angle flux weakening control method, the responsiveness is improved by 60% under transient conditions. When the inductance parameters of PMSM change, the current working point is recalculated based on the updated parameter in real-time, which effectively suppresses the working fluctuation.