Because of their high torque, high power density, and appropriate speed range, brushless DC (BLDC) motors are the top choice for lightweight electric vehicles. The application's goal is to use a Hall position sensor to build a speed-closed loop BLDC driver. The Enhanced Exploration of Aquila optimized control for speed in brushless DC motor is presented in this study as a new conceptual upgrade of Aquila optimization. In this study we employ and optimization – driven methodology to fine tune both the PI speed and voltage controllers, where the objective function is centered on minimizing errors. We evaluate the performance of our approach in contrast to a system utilizing AO optimization. When compared to the existing optimization of the PI controller, MATLAB simulation results reveal that the suggested optimized controller is more effective in the time domain performance.
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Vighneshwari et al. (2024) studied this question.
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