African vulture optimizer algorithm for fuzzy logic speed controller of fuel cell electric vehicle

Abstract

This research article introduces a novel optimization strategy for fuel cell electric vehicles (FCEVs) in order to reduce the integral square error to enhance dynamic performance. African vulture optimizer algorithm (AVOA) improves a speed fuzzy logic controller's (FLC) internal controller settings. The AVOA is renowned for its simplicity in implementation, and low demand on computational resources. The speed drive of FCEV is investigated using MATLAB/Simulink 2023a. The results of FLC-AVOA provide lower settling time, lower overshoot, lower undershoot, and high dynamic response when compared to FLC and proportional-integral (PI) controllers designed using genetic algorithm (GA). The FLC-AVOA reduced the rising time for speed dynamic response by 2.31% and the maximum peak overshoot by 55.23% as compared to FLC-GA.