Enhancement of the Switched Reluctance Motor Performance for Electric Vehicles Applications Using Predictive Current Control

In this paper, the Switched Reluctance Motor (SRM) performance for electric vehicles applications has been enhanced by using Model Predictive Control (MPC). With the help of predictive control techniques, the SRM current and torque ripples can be reduced compared to tradition current control techniques. MPC provides a good characteristic for motor drives converters among other controllers, these characteristics may include fast response, accuracy, and suitability. MPC applied for SRM converter to remains the motor current tracked the reference current signal with the smallest values of current ripples by selecting the optimal switches state, consequently the motor torque ripples will be reduced. In this work, the nonlinear 6/4 SRM model is used in a simulation with symmetrical converter and the converter controller algorithm is achieved using C-code. The controller which proposed in this work is tested at different loading conditions and the obtained results confirm that the MPG can drive the SRM efficiently compared to other methods such as Hysteresis Current Control (HCC).