A Optimization Of SRM Torque Sharing Algorithm Based On Iterative Learning Control

Because of simple maintenance,strong fault tolerance,large starting torque,low cost and wide speed range,Switched Reluctance Motor(SRM)been widely used in many demanding environmental conditions.However,due to the switched reluctance motor itself doubly salient structure as well as its use in the form of switching power supply causes the motor torque ripple and noise is relatively large,which restricts its development and application in more fields.Therefore,how to effectively reduce the torque ripple of SRM has become the focus of research scholars.Paper firstly introduces the development of SRM and its main features,for switched reluctance motor torque ripple and noise shortcomings,we analyzed the causes of torque ripple and noise.We analyzed the advantages and disadvantages of control strategy at home and abroad,which suppressing the torque ripple of SRM.Secondly,through the introduction of traditional SRM current control method and analysis of Iterative Learning Control(ILC)of the principles and characteristics.For current control of SRM,the current contorl strategy based on PWM iterative learning is proposed,which for a given current continuous learning in order to achieve the precision tracking desired currents.Then combine the entire torque control system,at the unit of torque-current control,through the study of the traditional torque sharing function(TSF),a torque control strategy based on nonlinear compensation of ILC is proposed.Through iterative learning in real-time optimization of the TSF,thereby adjusting the current value of each phase winding at different locations,optimization of the given current waveform of SRM.The optimal TSF through the unit of torque and current dual iterative learning control,which achieve to suppressing the torque ripple of SRM.Finally,the simulation model and system experiment platform is built,the average current controller based on improved ILC and the entire torque control system based on ILC were studied experimentally.Through the simulation and experimental analysis,the system can respond quickly to the mutation conditions,and through appropriate learning times to achieve reduced torque ripple,which verify the research has certain theoretical and practical value.