Optimizing Switched Reluctance Motor Performance in Electric Vehicles: A Comparative Analysis of Hysteresis and Fuzzy Logic Control Methods

This paper focuses on implementing current control methods, including Hysteresis control, and fuzzy control, in Switched Reluctance Motors (SRM). This project aims to enhance current control to meet the evolving demands of the automotive industry, particularly in the context of EV applications. In this study, the control strategy for Switched Reluctance Motors (SRM) is investigated with a focus on optimizing power transitions. Through extensive analysis, optimum switch-on and switch-off angles are calculated to achieve a balance between maximum efficiency and minimum torque in SRM. The controller plays a crucial role in determining the turn-on and turn-off angles at every instant, ensuring that the converter switches are fired accordingly to meet the speed and torque demands. Moreover, it is observed that the average source current exhibits an inverse relationship with an increase in source voltage, while the average total torque demonstrates a direct proportionality to the rise in source voltage. Furthermore, there is a clear correlation between an increase in source voltage and both the motor speed and average total torque per ampere.