Research On Dual Vector Model Predictive Current Control Of Permanent Magnet Synchronous Motor

Permanent Magnet Synchronous Motor（PMSM）has high power density and wide torque and rotational speed operating range,so it is widely used in electric vehicles,aerospace,robotics and other fields.Aiming at the problems of crosscoupling,output delay,and parameter mismatch in vector control,this dissertation adopts the Model Predictive Control（MPC）strategy,and uses its predicted state to weaken the influence of output delay on decoupling.Feedback correction and rolling optimization are used to eliminate the influence of parameter mismatch on the control performance,improve the current tracking ability,and then improve the system performance.First,this dissertation discusses the characteristics of PMSM with different structures,selects the built-in PMSM as the control object,deduces the mathematical model of the motor in the rotating coordinate system,and analyzes the principle of the PMSM vector control strategy.Then,on the basis of vector control,a predictive controller is used to replace the current inner loop PI regulator,and a Model Predictive Current Control（MPCC）system is built.The error between the predicted value of the stator current and the feedback value in the system is used as the Judging criteria,select the appropriate voltage vector to drive the operation of the motor,so as to achieve the purpose of speeding up the current response speed.In order to improve the performance of the control system,this dissertation mainly adopts the following measures.（1）In the traditional model predictive current control system,only one optimal voltage vector can be selected for each sampling period to act on the next sampling period.Due to the limited control set,its steadystate performance is poor.In this dissertation,dual The vector model predicts the current control,and selects the voltage vector twice in each sampling period.By assigning the action time,the synthesized new voltage vector can more accurately obey the given.（2）When the actual hardware is executed,the prediction control calculation time is too long,which will affect the steady-state performance of the control system.this dissertation studies this,and simplifies the selection range of the two voltage vectors to ensure the accuracy of the voltage vector.At the same time,the calculation amount of the control system is reduced and its robustness is improved.（3）In this dissertation,the built-in permanent magnet synchronous motor is selected as the control object,and the Maximum Torque Per Ampere（MTPA）control method is introduced into the model predictive current control to make full use of its reluctance torque to improve the operating efficiency of the motor.Finally,the three control strategies of traditional MPCC,duty cycle MPCC and the improved dual-vector MPCC designed in this dissertation are simulated and verified by experiments,and the experimental results of the three in dynamic and steady state are compared and analyzed.The experimental results show that the improved dual-vector MPCC has better dynamic,steady-state performance and robustness than the traditional MPCC and duty cycle MPCC.