Research On Simulation And Control Strategy Of Pmsm For Electric Vehicle

Motor and its driving system are important parts of electric vehicles. Permanent magnet synchronous motor(PMSM) has advantages of small volume, light weight, high power density and high efficiency; therefore, it is suit for electric vehicle. But, as the working status of the electric vehicle is complex and PMSM is a typical nonlinear control object, the actual parameters of the motor will change according to the operation status. The control method of PMSM depends on the accurate parameters of the motor; the inaccurate parameters will lead to poor control performance, even the motor may be out of control. As a result, researching the simulation of PMSM and its control method will improve the performance of control method and give a way to evaluate the actual performance of control system.This paper researches the modeling and control strategy of PMSM and completes the following jobs.With the modeling and control strategy of PMSM as the researching object, this paper firstly discusses the development of analysis method and control strategy of PMSM and expounds the application of the intelligent control methods.The non-linear model of PMSM in Simulink is built based on establishing the linear model and the d-axis and q-axis inductance parameters calculated with finite element calculation.After analyzing the maximum torque per ampere(MTPA) control method with linear model, this paper elaborates the impact of parameter variations and puts forward MTPA control method based on the non-linear PMSM model and established the Simulink simulation control system.This paper also introduces the fuzzy PI control to the control system of non-linear PMSM model and researches the performance of the fuzzy PI controller by simulation.Through simulation experiments, the improved MTPA control method is compared with conventional MTPA control method and the fuzzy PI control method is compared with the conventional PI control method, which verify the affection of the improved control method and intelligent control method in nonlinear control of PMSM.