Sensorless model prediction flux linkage control method for permanent magnet synchronous motor

Abstract

The invention belongs to the field of electromechanical control, and discloses a sensorless model prediction flux linkage control method for a permanent magnet synchronous motor. The method comprisesthe following steps: firstly, observing a motor rotating speed omega and a rotor position angle theta e through a sliding mode observer and a phase-locked loop based on SOGI; then, making the given rotating speed omega* and the rotating speed omega pass through a rotating speed loop SMC controller to obtain a given torque Te*; then, observing a load disturbance value according to the rotating speed omega and d/q axis current id/iq, and compensating the load disturbance value to the given torque Te* in a feedforward manner; and finally, substituting the observed rotating speed omega, the rotorposition angle theta e, the given torque Te*, the load disturbance value, the sampled three-phase voltage ua/ub/uc, the three-phase current ia/ib/ic and the like into a model prediction flux linkage control module for operation. According to the method, by adopting the mode of the sliding mode observer and the improved phase-locked loop, the rotor position estimation precision is improved; based on model prediction flux linkage control, setting of current loop parameters and weight coefficients is not needed; and sliding mode control and the load disturbance observer are combined, so that thesystem robustness and the anti-interference capacity are improved.

Description

technical field [0001] The invention relates to the field of electromechanical control, in particular to a sensorless model predictive flux linkage control method for a permanent magnet synchronous motor. Background technique [0002] The position sensorless control technology of the permanent magnet synchronous motor uses the relevant electrical signals in the winding to estimate the rotor position and speed, thus eliminating the mechanical sensor, reducing the size and cost of the motor, and increasing the reliability of the system. Current position estimation algorithms can be divided into two types based on signal injection and observers. The former uses the saliency of the motor to estimate the rotor position, but continuous injection of excitation signals requires complex signal processing, resulting in low inverter voltage utilization and slow dynamic response. The latter relies on the back electromotive force in the dynamic model to estimate the speed, which is easy...

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Problems solved by technology

The sliding mode observer algorithm is one of the latter. This algorithm has a simple structure, strong robustness, and fast dynamic response, but it also has filtering difficulties, large error in rotor position angle estimation, estimated value lags behind the actual value, and poor low-speed performance. question

[0003] In addition, for the position sensorless

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