Analysis of Switched Reluctance Motor Drives Using ANSYS Simplorer

Switching Reluctance motors are widely used in modern electric vehicle applications as well as many other industrial settings. In contrast to IMs and PMSMs, SRMs provide a number of crucial qualities for electric vehicle propulsion systems. Outstanding dependability, the capacity to withstand high working temperatures, a broad speed range, compatibility with gearless operation, and simplicity of manufacture are a few of these. SRMs are widely used in many different applications, which opens up possibilities for improving their driving system. Although managing the switching angles and current magnitude effectively is a challenging undertaking, it is possible to control an SRM. Switching reluctance motors are easier to make and repair than other motor types because of their simpler structure. Due to their low electrical and magnetic losses, SRMs are extremely efficient and can help increase the range of electric vehicles. The suggested study might look into how various converter topologies, like the usage of converters with many levels, soft-switching methods, or power factor correction, affect SRM performance. SRMs have a high torque density, which makes them perfect for applications which deal with space and weight are important considerations, like in robotics, aerospace, or electric cars. To improve the performance of the SRM, the suggested driver system may use cutting-edge control techniques such model predictive control, adaptive control, or neural networks. Electric cars needing fast acceleration and deceleration rates benefit from SRMs' ability to operate at high speeds. The simulation may also examine the effects of various operational parameters, including temperature, torque, speed, and efficiency, on SRM performance. The proposed effort intends to create an appropriate driver system for ANSYS Simplorer's comparative analysis of SRM. The simulation checked for four different converters.