Research On Field Weakening Control Of Permanent Magnet Synchronous Motor For Electric Vehicle

With the vigorous development of new energy electric vehicles in my country,in order to improve the anti-load disturbance and stable driving requirements of electric vehicles,the built-in permanent magnet synchronous motor(Interior Permanent Magnet Synchronous Motor,IPMSM)used in electric vehicles must have good field weakening speed regulation performance.In the field weakening control process,changes in the motor’s AC-DC axis inductance and permanent magnet flux linkage parameters will cause the motor speed and torque to fluctuate,which reduces the motor’s ability to resist load disturbances.The fuzzy-neural network algorithm is beneficial to improve the stability of the system and does not depend on the system parameters.This paper designs the PI algorithm of the fuzzy-neural network and applies it to the IPMSM variable alternating-axis voltage single-current field weakening algorithm to improve the system resistance in the IPMSM field weakening control Load disturbance capability and steady-state characteristics,the research work of this paper is as follows:(1)First,establish the mathematical model of IPMSM for vehicles,and study the IPMSM vector control strategy and field weakening control principle.Finally,choose the variable quadrature axis voltage single current algorithm to apply to IPMSM field weakening control,and simulate and analyze the influence of IPMSM quadrature axis and direct axis inductance and permanent magnet flux parameter changes on the motor speed output characteristics.(2)Through the simulation experiment of the variable quadrature axis voltage single current field weakening control algorithm using the traditional PI controller,the results show that the dynamic characteristics and stability of the system are poor.Introduce a fuzzy intelligent algorithm that does not depend on system parameters,and through simulation experiments,it is obtained that the dynamic response characteristics and anti-interference ability of the fuzzy PI controller under the first-order inertia link are better than the traditional PI controller.Therefore,the fuzzy PI controller is designed to replace the speed loop.The traditional fixed gain PI controller.The simulation experiment under the condition of sudden increase and decrease of load interference is carried out through MATLAB/simulink software.The experimental results show that the application of the fuzzy PI controller algorithm reduces the speed and torque output fluctuations of the field weakening control algorithm using the conventional fixed gain PI controller..(3)On the basis of the fuzzy PI algorithm,the BP neural network algorithm is introduced,and the fuzzy-neural network algorithm is constructed to apply to the IPMSM variable alternating-axis voltage single-current field weakening control system.The simulation contrasts and analyzes the dynamic response characteristics of the traditional PI controller,the fuzzy PI controller and the PI controller based on BP neural network under the first-order inertia link.The results show that the fuzzy-neural network algorithm has a smaller reduction in overshoot and system response.time.Then through the MATLAB/simulink simulation software,the fuzzy-neural network-based PI control algorithm and the fuzzy PI control algorithm are simulated under the condition of sudden increase and decrease of load interference.The experimental results show that the application of the fuzzy-neural network PI controller is better than the application The fuzzy PI controller field weakening control system improves the response accuracy of the speed output by 3%,the torque output response accuracy by 9%,and the direct-axis current output response accuracy by 12%.The fluctuation of speed and torque is more effectively restrained,and the control accuracy of the system is improved.