Electromagnetic Analysis And Model Predictive Flux Control Algorithm Of Permanent Magnet Synchronous Linear Motor

The traditional core permanent magnet synchronous linear motor has disadvantages of cogging effect and large positioning force due to its structural characteristics.The mover of the permanent magnet synchronous linear motor without core is composed of winding and fixed by epoxy resin.There is no core structure,so there is no cogging effect and the mass of the mover is small,which is conducive to improving the dynamic performance of the permanent magnet synchronous linear motor and achieving high-precision control of the linear motor.In this paper,the air gap magnetic field and thrust characteristics of the ironless permanent magnet synchronous linear motor(ILPMSLM)are analyzed.The model predictive flux control algorithm of the linear motor is studied.The main research contents of this paper are as follows:1)Firstly,the research status of linear motor at home and abroad is analyzed.The working principle and basic structure of linear motor are introduced.2)The structure of the two-sided coreless permanent magnet synchronous linear motor is introduced.The distribution of the air gap magnetic field of the motor is calculated by the analytic method.The expression of the air gap magnetic field of the motor is derived.The variation law of the air gap magnetic field of the motor is analyzed.On this basis,the thrust expression of the permanent magnet synchronous linear motor is derived.In the finite element software,the two-dimensional analysis model of the motor is established.The air gap magnetic field and thrust of the motor are calculated.The results of the analytical method and the finite element method are compared and analyzed.The thrust experiment of the motor is carried out,which proves the accuracy of the results of the analytical method.3)The principle of coordinate change in motor control is introduced.The mathematical model of permanent magnet synchronous linear motor in three-phase static coordinate system,two-phase static coordinate system and two-phase rotating coordinate system is obtained.The direct thrust control strategy and implementation method for PMSM are introduced.4)The basic principle of model predictive control algorithm and its classification in motor control application are introduced.The model predictive thrust control algorithm is studied,and its control principle and implementation process are analyzed.The modelpredictive thrust control is applied to the control of permanent magnet synchronous linear motor.In order to reduce the thrust fluctuation of linear motor under model predictive thrust control,the model predictive thrust control based on duty ratio is applied to the control of linear motor.The calculation formula of duty ratio of optimal voltage vector is obtained by analyzing its control principle.Through simulation analysis,it is proved that the performance of model predictive thrust control based on duty ratio is better than that of traditional model predictive thrust control.5)In order to solve the problem that it is difficult to design the weight coefficient of the objective function in the model predictive thrust control,and to further reduce the thrust fluctuation,the model predictive flux control is applied to the control of the permanent magnet synchronous linear motor.On this basis,the model predictive flux control based on dual vector control is proposed and applied to the control of permanent magnet synchronous linear motor.The selection method of the second voltage vector in the voltage vector group is proposed.The correctness of the theoretical analysis results is proved by the simulation analysis of the control algorithm.The simulation results of model predictive flux control based on dual vector control and model predictive thrust control based on duty ratio control are compared and analyzed,which proves that the former has better control effect.Finally,two control algorithms are tested on the experimental platform of permanent magnet synchronous linear motor.The correctness of theoretical analysis and simulation results is proved by analyzing the experimental results.