Performance Optimization Of Model Predictive Control For Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor(PMSM)has the advantages of high reliability,simple structure,and high efficiency.Due to its advantages and high performance,the control methods related to PMSM have attracted the attention of domestic and foreign researchers.In addition,the rapid development of power electronics technology has promoted the popularization of PMSM,making it widely used in fields such as aerospace,lathes,and transportation.In order to meet the performance requirements of PMSM drive systems under different conditions,scholars have proposed many control methods with different performance advantages.Model predictive control(MPC)is one of the representative types.For the PMSM drive system controlled by the MPC method,although the system has good dynamic performance,its steady-state performance still needs improvement.There are three basic methods to improve its steady-state performance: one is to increase the control frequency of the control system;Secondly,increase the prediction step size;The third is to use multiple voltage vectors for target vector synthesis within each control cycle.The first two methods are limited in practical applications by chips and computing power,and cannot be widely used in various situations.In the third method,as the number of synthesized vectors increases,its dynamic performance is weakened and the switching frequency significantly increases.In response to the contradiction between steady-state performance,dynamic performance,and switching frequency in the third method,this article will optimize and study the problem from two aspects.The traditional three vector model predictive current control(MPCC)method uses a combination of two non zero vectors and one zero vector to apply to the motor in each control cycle,which improves the steady-state performance of the system.In order to further improve the steady-state performance of the control system,the third chapter of this article proposes two hybrid multi vector MPCC methods.The first method is the hybrid three vector MPCC method,which selects more optimal three voltage vectors to apply to the motor by minimizing current ripple,thereby improving the steady-state performance of the system without increasing the switching frequency.The second method is the four vector MPCC method,which selects three non zero vectors and one zero vector to be applied to the motor in each control cycle.By minimizing current ripple,the duration of the four voltage vectors is redistributed,which can improve the steady-state performance of the system without increasing the switching frequency.Finally,a comparison was made between the hybrid multi vector MPCC method and the traditional three vector MPCC method through experiments,which verified that the proposed method can improve the steady-state performance of PMSM systems during high-speed operation and ensure almost consistent switching frequencies.In addition,the four vector MPCC method has a more significant improvement in the control effect of PMSM systems.Secondly,in order to solve the problem of weakening the dynamic performance of the traditional three vector MPCC method due to the increase in the number of vectors,the fourth chapter of this article proposes a model predictive switching control method,which mainly includes steady-state control strategies and switching control methods.Its steady-state control strategy is a four segment MPCC method.Based on the selected three vector MPCC,two zero vectors are evenly distributed at both ends of adjacent control cycles,and the last zero vector of the previous control cycle is consistent with the previous zero vector of the current control cycle.This reduces the switching frequency while improving the steady-state performance of the system.In addition,by judging the motor working condition module,different control strategies are used to determine the motor working condition,and only one control strategy is selected in the same control cycle.Finally,the experiment verifies that this method has better steady-state and dynamic performance than the traditional three vector MPCC method,and reduces the system switching frequency.