In view of the large current peak and torque ripple in the actual current chopping control of switched reluctance motor, a segmented PWM duty cycle analysis method of switched reluctance motor based on current chopping control is proposed in this paper. The method realizes the control of the winding current by adjusting the average voltage of the two ends of the winding in one cycle through the PWM duty cycle. At the same time, according to the inductance linear model, the conduction phase is divided into a small inductance region and an inductance rising region, and the analytical formulas of PWM duty cycle in the two regions are deduced respectively. Finally, through matlab/simulink simulation and motor platform experiment, the current chopping control is compared with the segmented PWM duty cycle analysis method in this paper. Simulation and experimental results show that the segmented PWM duty cycle analysis method can effectively reduce the current peak and torque ripple, and has high practical application value.

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Aiming at the problem of excessive torque ripple of switched reluctance motor (SRM), a three-interval PWM duty cycle adaptive control strategy is proposed in this paper. The method changes the PWM duty cycle to adjust the voltage across the windings according to the torque error, divides the interval according to the inductance linear model, and adapts to different PWM duty cycles in different intervals, different speeds, and different torque errors. And the optimal PWM duty cycle group under different rotation speeds is obtained by trial and error, and this duty cycle group is used as the control method to adapt the PWM duty cycle group. Finally, through Matlab/Simulink simulation and motor platform experiments, the three-interval fixed PWM duty cycle control strategy and the three-interval PWM duty cycle adaptive control strategy in this paper are compared. The results show that the three-interval PWM duty cycle adaptive control strategy proposed in this paper has a good torque ripple suppression effect in a wide speed and wide load range.

Switched reluctance motor (SRM) has many advantages, but when the motor is running, the fixed turn-on angle will cause the torque ripple of the motor at different speeds and loads. Therefore, an torque ripple control strategy of switched reluctance motor based on BP neural network is proposed. Firstly, the nonlinear relationship among speed, load torque and opening angle is established by using the fitting generalization ability of BP neural network. In this step, the optimal angle data under the minimum pulsation needs to be obtained by simulation. After collecting data, select and classify the data, and then train and improve the neural network, That nonlinear relationship is introduced into the motor control strategy, so that the motor can automatically adjust its opening angle according to different rotational speeds and load torques and achieve the purpose of reducing torque ripple under different working conditions. Finally, the motor simulation model is built in Matlab/Simulink, and the results are analyzed. This control strategy can control and reduce torque ripple.

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