Research On Torque Control Strategy Of PMSM Based On Model Prediction

Global energy consumption and environmental pollution are increasing at present.Chinese government proposed a strategy to comprehensively promote the development of new energy industry at the two sessions in 2018 in order to solve these problems.Electric vehicles,as a clean vehicle using new energy,have the advantages of energy saving and environmental protection.Subsequently,the government also continued to introduce preferential policies for electric vehicles,which makes electric vehicles more promising.Permanent magnet synchronous motors have outstanding features such as high resolution,precise positioning and stable low-speed operation,which makes them widely used in electric vehicle drive systems.The acceleration performance that directly affects the driving experience is very demanding,so a high-performance torque control strategy is necessary in the motor-driven control of electric vehicles.This paper takes the permanent magnet synchronous motor drive system as the research object,and mainly studies the torque control strategy based on model prediction.First,the structure of the permanent magnet synchronous motor,the mathematical model of the motor in three different coordinate systems,and the characteristics and basic principles of traditional direct torque control are introduced in this paper.And simulation modeling is performed in MATLAB/Simulink environment based on the mathematical models of permanent magnet synchronous motors and inverters.Secondly,a new direct torque control strategy based on model prediction is proposed for the problem of ripples of flux and torque in the direct torque control of permanent magnet synchronous motors.This is a kind of scalable output finite-set model predictive torque control strategy.The quasi-output voltage vector is selected through the driving table,and then the quasi-output voltage vector is optimized and adjusted according to the calculation result predicted by the model.It expands the vector range that can be output and improves the control performance of the flux and torque,compared with the traditional limited control set model predictive torque control.In addition,ripples and calculations are reduced.Thirdly,an online parameter identification is introduced based on the proposed new torque control strategy for the problem that the parameters involved in the model do not match the actual parameters of the target.The design of the adaptive law by establishing a parameter identification model is completed,which can identify the stator resistance and stator inductance parameters online during system operating.The stator resistance and stator inductance parameters of the control strategy are updated in the actual running process.The interference caused by the reduced model mismatch is reduced to some extent.Finally,a comprehensive experimental platform of d SPACE and Tyhpoon 402 HIL is built based on the "V" process development method.The traditional direct torque control,the traditional finite-control-set model predictive torque control and the proposed torque control in this paper are compared through offline simulation and online experiments.The simulation and experimental results show that the two traditional control methods have large flux and torque ripples,and the proposed scalable output finite-control-set model predictive torque control strategy can effectively reduce ripples of flux and torque,and it can correctly identify the motor parameters.