Research On The Torque Ripple Minimization Of Switched Reluctance Motor

With the rapid development of modern power electronics,switched reluctance motor is widely used in various fields such as haulage,aerospace and general industry.Its outstanding advantages are high output efficiency,wide speed range,good dynamic response,and flexible control methods.However,due to the structural characteristics of the body and the step-by-step mode of operation,it has a larger instantaneous torque ripple compared with traditional AC and DC motors,especially torque ripple at a low speed is more obvious,hindering the switch reluctance motor Further promotion and application.Therefore,the research on torque ripple reduction of switched reluctance motor has important theoretical and practical value.By studying the basic principle and basic mathematical model of switched reluctance motor,the relative constraint equations of switched reluctance motor are derived.Because of the saturation of magnetic circuit,the nonlinear factors such as hysteresis effect are difficult to be mathematically resolved,which seriously affects the control performance of switched reluctance motor.In order to improve the control accuracy of quantitative analysis,a nonlinear model of switched reluctance motor is established by means of look-up table combined with finite element analysis.Taking into account the influence of turn-on angle and turn-off angle on torque pulsation,the optimal selection of turn-on and turn-off angle was analyzed according to magnetic co-energization,and the influence of turn-on and turn-off angle on the torque ripple is compared through the simulation.The fuzzy switching angle controller is established based on the fuzzy logic.Torque ripple is mainly caused by the pulsed excitation method.Aiming at the problem of torque fluctuation during commutation,a closed-loop torque ripple suppression simulation model of desired current was established by applying a cosine torque distribution function and fuzzy logic to optimize the switching angle in Matlab.In order to obtain a more accurate expected current,the Back Propagation neural network is combined with Levenberg Marquardt optimization algorithm to establish a torque reversal model of the switched reluctance motor.Comparing the simulation results with the simulation results of the current chopping control mode,The results show that the torque ripple rate of the method is reduced and the torque ripple can be suppressed better.At last,using TMS320F28335DSP as the control chip,the power topology of switched reluctance motor,the driving circuit,the position signal conditioning circuit,the current sampling circuit and other hardware parts are designed,and the double closed loop program of the speed and current is written.The precise rotor position angle is obtained by the method of software subdivision.The experimental results show that torque distribution function combined with double closed loop reduces the torque ripple range,which validates the effectiveness of the paper method and lays a foundation for further research.