Switched reluctance motor(SRM)usually adopts Direct Instantaneous Torque Control(DITC)to suppress torque ripple.However,due to the fixed turn-on angle and the control mode of the two-phase exchange region,the conventi...Switched reluctance motor(SRM)usually adopts Direct Instantaneous Torque Control(DITC)to suppress torque ripple.However,due to the fixed turn-on angle and the control mode of the two-phase exchange region,the conventional DITC control method has low adaptability in different working conditions,which will lead to large torque ripple.For this problem,an improved DITC control method based on turn-on angle optimization is proposed in this paper.Firstly,the improved BP neural network is used to construct a nonlinear torque model,so that the torque can be accurately fed back in real time.Secondly,the turn-on angle optimization algorithm based on improved GRNN neural network is established,so that the turn-on angle can be adjusted adaptively online.Then,according to the magnitude of inductance change rate,the two-phase exchange region is divided into two regions,and the phase with larger inductance change rate and current is selected to provide torque in the sub-regions.Finally,taking a 3-phase 6/20 SRM as example,simulation and experimental verification are carried out to verify the effectiveness of this method.展开更多
基金supported by National Natural Science Foundation of China under Grant 52167005Science and Technology Research Project of Jiangxi Provincial Department of Education under Grant GJJ200826。
文摘Switched reluctance motor(SRM)usually adopts Direct Instantaneous Torque Control(DITC)to suppress torque ripple.However,due to the fixed turn-on angle and the control mode of the two-phase exchange region,the conventional DITC control method has low adaptability in different working conditions,which will lead to large torque ripple.For this problem,an improved DITC control method based on turn-on angle optimization is proposed in this paper.Firstly,the improved BP neural network is used to construct a nonlinear torque model,so that the torque can be accurately fed back in real time.Secondly,the turn-on angle optimization algorithm based on improved GRNN neural network is established,so that the turn-on angle can be adjusted adaptively online.Then,according to the magnitude of inductance change rate,the two-phase exchange region is divided into two regions,and the phase with larger inductance change rate and current is selected to provide torque in the sub-regions.Finally,taking a 3-phase 6/20 SRM as example,simulation and experimental verification are carried out to verify the effectiveness of this method.
