Speed Control Analysis of an Electric Vehicle by Using Fuzzy-PID Type 1 and Type 2

Abstract

This paper investigates the speed control of an electric vehicle using three different control strategies: a classical PID controller, a type-1 fuzzy self-tuning PID controller, and a type-2 fuzzy self-tuning PID controller. A longitudinal dynamic model of the electric vehicle is developed in MATLAB/Simulink to evaluate and compare the performance of the proposed controllers under identical operating conditions. The fuzzy-based controllers adapt the PID gains online according to the speed error and its derivative, improving system robustness against nonlinearities and parameter uncertainties. Simulation results demonstrate that both fuzzy-PID controllers outperform the conventional PID in terms of overshoot reduction, settling time, and steady-state accuracy. Furthermore, the type-2 fuzzy-PID controller shows superior performance compared to the type-1 approach, particularly in handling higher levels of uncertainty. These results confirm the effectiveness of fuzzy logic-based adaptive control for electric vehicle speed regulation.