Model Prediction Direct Speed Flux-weakening Control Strategy For Permanent Magnet Synchronous Motor Parameter Identification

After the proposal of the "dual carbon" strategic goal,the development of new energy vehicles has become an important path for our country to achieve this goal.In the field of new energy vehicles,permanent magnet synchronous motors are widely used due to their high power density,good dynamic performance,and high output torque.Therefore,improving the control performance of permanent magnet synchronous motors is of great significance for the development of new energy vehicles.By comparing the advantages and disadvantages of various motor control strategies,this article ultimately chooses the model prediction direct speed control strategy,The model prediction direct speed control strategy abandons the cascade structure of the system and has the advantages of simple control structure,fast dynamic response,and fewer adjustable parameters.However,under the premise of limited supply side voltage,this control strategy can only achieve stable operation at or below the base speed And this control strategy is based on the mathematical model of the motor to predict the future behavior of the system,with strong dependence on motor parameters.In response to the limited speed range of model prediction direct speed control strategy for permanent magnet synchronous motor,the model formula calculation method is used to expand the speed range.Model prediction direct speed flux-weakening control strategy is studied,which enables the motor to achieve stable operation above base speed even with limited supply side voltage.Due to the fact that the model prediction direct speed control strategy and the model formula calculation flux-weakening method rely on motor parameters,and motor parameters may change due to the influence of actual operating conditions,this paper studies model prediction direct speed flux-weakening control strategy for permanent magnet synchronous motor parameter identification.The recursive least squares method with forgetting factor is used to identify the stator inductance and permanent magnet flux of permanent magnet synchronous motor.The online ied stator inductance and permanent magnet flux values are input into the controller to modify the mathematical model of the motor,thereby improving the robustness of the model prediction direct speed flux-weakening control strategy.This article has conducted simulation and experimental verification on the research method.The results show that model prediction direct speed flux-weakening control strategy for permanent magnet synchronous motor enables the motor to operate smoothly in stages below base speed,transition stage,and flux-weakening stage.This verifies the feasibility of model prediction direct speed flux-weakening control strategy for permanent magnet synchronous motor.The model prediction direct speed flux-weakening control strategy for permanent magnet synchronous motor parameter identification can achieve accurate identification of stator inductance and permanent magnet flux,verifying the correctness of recursive least squares method with forgetting factor for identifying parameters of permanent magnet synchronous motor.Compared with the model prediction direct speed flux-weakening control strategy for permanent magnet synchronous motor,model prediction direct speed flux-weakening control strategy for permanent magnet synchronous motor parameter identification has smaller direct axis current mutation value,speed mutation value,and speed recovery time when the parameters are matched and the rated load is continuously suddenly increased or decreased.The steady-state error of direct axis current and quadrature axis current is smaller when the stator inductance parameters are mismatched.At the same time,the steady-state performance of the direct axis current,quadrature axis current,and speed is better,which improves the robustness of model prediction direct speed flux-weakening control strategy for permanent magnet synchronous motor.It is verified that the recursive least squares method with forgetting factor can improve the system’s anti-interference performance after identifying the parameters of the permanent magnet synchronous motor.