A Novel Enhanced Fire Hawks Optimization Approach for Improving the Efficiency of Converter-Based Controllers in Switched Reluctance Motors

Abstract

Switched reluctance motors (SRMs) have gained popularity in various industrial applications due to their advantages, including structural simplicity, high reliability, low cost, and operational stability over a wide speed range without relying on rare-earth permanent magnet materials. However, these motors exhibit drawbacks such as weak torque density, low efficiency, and significant torque ripple, particularly in high-speed operation. An efficient converter-based control approach is proposed to manage speed and torque variations in SRM motors, addressing these issues. A multilevel converter (MC) is introduced as a fundamental component. The novel multilevel converter (NMC) accommodates SRMs with varying numbers of phases and exhibits quick demagnetization and excitation behaviors, enabling independent operation of each phase even during conduction overlaps. Subsequently, an effective controller is developed for the SRM motor, combining proportional integral derivative (PID) control with enhanced fire hawks optimization (EFHO). The EFHO optimizes the PID gain values to enhance controller performance. The converter operation minimizes torque ripple and facilitates speed management. The EFHO technique is a fusion of fire hawks optimization (FHO) and the sine cosine algorithm (SCA). This amalgamation improves the updating process of FHO by incorporating SCA. The proposed methodology is implemented in MATLAB and evaluated through various metrics, including SRM motor current, voltage, speed, and torque, under electric vehicle (EV) load conditions. Performance comparisons are conducted with traditional optimization algorithms such as the whale optimization algorithm (WOA) and ant colony optimization (ACO). The results validate the effectiveness of the proposed methodology in achieving improved SRM motor control and performance.