Research On Speed Control System Of Permanent Magnet Synchronous Motor For Electric Vehicle

With the development of the automobile industry,while facilitating people’s travel,it is also brought serious environmental pollution problems.Therefore,electric vehicles powered by electric power have received attention from the automotive industry for their cleanliness and environmental protection.Electric vehicles run on motor drives,which permanent magnet synchronous motor(PMSM)has been widely used in electric vehicles due to its advantages of high efficiency and high power density.As the core of the electric vehicle control system,the motor speed regulation system has become a research hot-spot at home and abroad.In order to improve the speed regulation performance of permanent magnet synchronous motor for electric vehicles,vector control is usually applied to the motor speed control system.In this thesis,permanent magnet synchronous motor speed regulation system based on vector control is studied,based on the simulation of the permanent magnet synchronous motor PID control speed control system,this thesis analyzes the problem that the traditional PID speed controller can not meet the performance index of small overshoot and strong anti-disturbance ability due to the fixed PID parameters when it is applied to motor speed regulation.In response to these questions,this article on the basis of consulting a large number of domestic and foreign literature,Firstly,introduce BP neural network to adjust PID parameters,and the specific analysis of the process of setting PID parameters by BP neural network,it can be known that BP neural network has the drawback of slow convergence rate and easy to fall into local optimum.Secondly,optimization of network weights using adaptive genetic algorithm with strong global search ability,the process of optimizing BP neural network by adaptive genetic algorithm is studied,and then the adaptive genetic algorithm is adopted to optimize the BP neural network PID control in the speed outer loop of the motor speed control system.Finally,MATLAB/Simulink software is used to simulate PMSM speed regulation system under PID control,BP neural network control and adaptive genetic algorithm to optimize BP neural network PID control method,simulation results show that the BP neural network PID control optimized by adaptive genetic algorithm is applied to the motor speed regulation system,System response speed is accelerated,improved anti-interference and tracking performance,it can meet the need of high performance motor of electric vehicle.Based on the above theoretical analysis and research,TMS320F28335 is selected as the main control chip,the hardware and software of permanent magnet synchronous motor speed regulation system are designed in this thesis.And set up an experimental platform for speed control experiments,The results show that the control scheme designed in this thesis has certain advantages.