Electric Vehicle Power Propulsion System Control Based on Time-Varying Fractional Calculus: Implementation and Experimental Results

Abstract

Nowadays, due to the fact that motor efficiency is strictly related to the diminution of emissions, researchers pay much attention to find a robust and efficient motor control technique for hybrid electric vehicles (HEVs). In this study, an optimal type-2 fuzzy fractional proportional plus integral derivative (IT2FOFP+ID) controller is applied to solve the throttle position and speed control problem of the HEVs. It is undeniable that the performance and effectiveness of the fuzzy-based proportional-integral-derivative (PID) controllers are dependent on its gains’ value. Hence, a novel improved heuristic technique, called IJAYA algorithm, is employed for the online tuning of the coefficients embedded in the specific controller structure. In contrast with the classical control methodologies that suffer from the lack of the self-regulating feature, the established controller has been adjusted online automatically. As another advantage of this control strategy, it is a model-free scheme and does not need the mathematical computation to identify the system model. To appraise the supremacy of the optimal IT2FOFP+ID controller than the other prevalent methodologies, a highly nonlinear EV model is utilized as a case study. In addition, the usefulness and robustness of the proposed method are tested by the experimental data, the EPA New York City Cycle. In the end, the new time-varying proposed technique is validated and implemented in hardware-in-the-loop real-time simulation based on OPAL-RT to study the feasibility of the designed IT2FP+ID controller with check outcomes on a physical platform.