Research On Control Technology Of Switched Reluctance Motor For Electric Vehicle

Traditional vehicles are gradually limited by the emission of vehicle exhaust due to the combustion of fossil energy.Electric vehicles have attracted more and more attention due to their advantages of low pollution,high torque and low cost.Among them,driving technology is one of the core technologies of electric vehicles.As a new generation of motor,switched reluctance motor(SRM)is more and more favored by electric vehicle developers because of its simple structure,high torque,low cost,high energy efficiency and other advantages.However,due to the large torque ripple problem of switched reluctance motor(SRM),it is necessary to establish an appropriate SRM model and use the appropriate control algorithm to make the whole system both fast and low torque ripple.The main work of this paper is as followsThrough the mechanical and electrical parameters of SRM,the finite element simulation model is established,and the flux angle current data of the model is compared with the measured data to verify the feasibility of the model.The flux angle current data of the model and the measured data are used as the training data set,and the least squares support vector machine is used to build the model.The genetic algorithm is used to optimize the model,and the objective function of the genetic algorithm is improved to obtain better parameters of the support vector machine.The model obtained by the support vector machine is compared with the model trained by the neural network,Finally,through the mathematical model of SRM and the support vector machine model,the overall SRM model is established in MATLAB.The current chopping control is used as the control method,and the current waveform is compared with the actual current chopping control SRM.After adding the first-order inertia link,the current waveform obtained by simulation is close to the actual current waveform,The model is used as the controlled object to study the control algorithm.The voltage switch table is derived from the mathematical model of SRM,and the control system with PI speed loop and DTC torque loop is established by using the switch table in MATLAB,and compared with the traditional current chopper control.The first-order active disturbance rejection controller(ADRC)is obtained by the mechanical equation of SRM.The system with speed loop as ADRC and torque loop as DTC is built on MATLAB.The parameters of the whole system are optimized by using chaos particle swarm optimization algorithm.The optimized system is compared with the traditional current chopper control system and the non optimized system The speed response and torque ripple of the system based on intelligent algorithm are compared.Finally,the software design is completed by using the experimental platform with DSP as the control core.Through the experiment,the ADRC system and the current chopper control system are compared,which shows that the control system in this paper has better dynamic response and static response.