Electric vehicles (EVs) are becoming increasingly popular, however, achieving smooth and efficient speed control remains a significant challenge. This paper introduces an innovative approach by proposing an AFUPID (adaptive fuzzy-PID) technique for regulating the speed of EVs utilizing a DC motor. The paper begins by presenting the hardware architecture and modeling of the DC motor within an EV. Subsequently, it critically analyzes the limitations of conventional PID and fuzzy logic control methods. The proposed methodology is an AFUPID controller, which intelligently adjusts PID coefficients based on fuzzy inference mechanisms. Simulation results verify the effectiveness of the AFUPID controller, showcasing a smoother response and reduced errors when compared to standard PID and fuzzy controllers. Furthermore, experimental results validate the exceptional performance of the proposed method in real-world implementation. In essence, this study provides a potential solution for robust adaptive speed control in EVs through the integration of fuzzy inference and PID control, addressing the challenges of achieving optimal speed regulation in EVs.