Research On Predictive Current Control Of Permanent Magnet Synchronous Motor

Different from the traditional motor,permanent magnet synchronous motor has many advantages,it has small volume,small loss and high efficiency,so it is widely used.However,with its popularity,the performance requirements of its drive system in many occasions,such as aerospace and electric vehicles,are gradually improving.For the drive system,the current control as the core link,its importance is self-evident.In the field of current control,predictive current control has many advantages,such as high steady-state accuracy,fast response and so on.Although the predictive current control has a large amount of calculation,the microprocessor technology can solve this problem,so the problem of large amount of calculation is no longer a disadvantage.In this paper,firstly,the mathematical model of the motor is established in the three-phase static coordinate system,including its voltage equation and flux linkage equation.Then,the model in the static coordinate system is transformed according to the relevant principles of coordinate transformation,so as to obtain the model of the motor in the two-phase rotating coordinate system.Finally,the first-order Taylor formula is used to discretize the mathematical model.At this time,a series of formula substitution and transformation can get the final model.Secondly,due to the delay of sampling period,this paper chooses to introduce the delay link in the current control loop.Because predictive current control requires high accuracy of the model,if the motor parameters change,the output of the motor will have a deviation.After analyzing this problem,the results show that the error of stator inductance parameters will affect the stability of the system,while the error of permanent magnet flux parameters will cause static error of q-axis current.Finally,this conclusion is proved by a series of simulation experiments.In this paper,the method of parameter identification is used to identify the inductance and flux on-line and modify the model.The identification method used is based on ant colony algorithm,but the traditional ant colony algorithm has some defects,such as too long search time in the early stage and easy to fall into local optimum in the later stage.This paper puts forward improvement measures,The simulation results show that compared with the traditional ant colony algorithm,the performance of the improved ant colony algorithm is greatly improved.Finally,experiments are carried out on the platform of TMS320F28335 chip to further verify the relationship between predictive current control performance and motor parameters.The experimental results show that the proposed method can accurately identify the parameters when motor parameters change,so that the control system still has good performance,the correctness and feasibility of the proposed parameter identification strategy are proved.