Fuzzy Control Research Of Brushless DC Motor For Electric Vehicle Based On Particle Swarm Algorithm

With the continuous development of traditional automotive industry,the dependence on energy and environmental pollution has become a prominent social problem.Because of its outstanding advantages of energy saving and environmental protection,electric vehicles have become a hot research topic in the field of automobile,which represents the future development trend of the automobile.The control system is the core part of the electric vehicle drive motor.Its performance directly determines the performance of the electric vehicle.In this paper,permanent magnet brushless DC motor is used as the driving motor of electric vehicle.The mathematical model of the brushless DC motor drive system and the dynamic model of the electric vehicle are established.We use double closed loop control method drive system method.The reason of torque ripple of brushless DC motor is analyzed,and the current hysteresis method is used to solve the problem.Two kinds of Brushless DC motor signal detection methods are presented,which are equipped with position sensors and position sensors respectively.According to the characteristics of electric vehicle,the position sensor signal detection method is selected.The permanent magnet brushless DC motor is a multivariable,strongly coupled nonlinear system.In this paper,a fuzzy PID controller is designed based on the combination of PID control,fuzzy control and particle swarm optimization.And the control parameters of the fuzzy PID controller are optimized by improved particle swarm optimization algorithm.The whole control simulation model of brushless motor is established based on MATLAB.Three different control schemes,which are conventional PID control,fuzzy PID control and fuzzy PID control based on particle swarm optimization,are simulated under different working conditions.The simulation results show that the fuzzy PID control based on particle swarm optimization presents better control effect.It can better adapt to the complex operation conditions such as vehicle acceleration and deceleration motion and be more suitable for practical application in electric vehicle brushless DC motor.