Lightweight Electric Vehicles (EVs) require a system that is efficient, reliable, and low maintenance. Among the available options, the Brushless DC (BLDC) motor is desirable due to its compact design, high torque-to-weight ratio, and the absence of mechanical commutation. However, BLDC motors have control challenges because of nonlinear behaviors like back-EMF distortion and load sensitivity. Traditional Proportional-Integral (PI) controllers often have difficulty keeping performance under these dynamic conditions. In this study four closed-loop speed control strategies have been compared for BLDC motors: PI, Hysteresis-PI, Fuzzy Logic, and Hybrid Fuzzy-PI controllers. The aim is to optimize performance for energy-efficient lightweight EVs. Each controller is modified and simulated in MATLAB/Simulink under the same load and speed conditions applied on all four controllers. The performance of the controllers evaluated through settling time, steady-state error, overshoot, and rise time. Simulation results indicate that traditional PI controllers are simple to implement, but they do not adapt well to dynamic changes. The Hysteresis-PI controller showed the best overall performance. It provided the fastest response and improved system stability, making it a strong candidate for future EV propulsion systems.
Taha et al. (2026) studied this question.