Fuzzy adaptive sliding mode control with exponential reaching law for enhanced 4WD electric vehicle speed control

Abstract

This paper discusses a novel fuzzy adaptive sliding mode control (FASMC) strategy for a four-wheel-drive (4WD) electric vehicle (EV), incorporating an exponential reaching law (ERL) and a fuzzy adaptive switching gain to enhance speed tracking. The classical SMC technique often suffers from the chattering problem, which can degrade the dynamic control performance of the electric vehicle. To address these challenges, the proposed hybrid controller employs an exponential reaching law to ensure fast convergence and reduced chattering, while a fuzzy logic-adaptation mechanism dynamically adjusts the switching gain to improve robustness against uncertainties and external disturbances. First, the mathematical model of the motor derived for achieving speed regulation using the classical SMC with an exponential reaching law based on indirect-field-oriented control (FOC). Then, the proposed control technique is designed to automatically adjust the ERL gain using a fuzzy logic controller to ensure precise vehicle speed control, optimizing the vehicle's dynamics under varying road conditions. This novel configuration enables the development of a 4WD EV control framework with an optimized controller, serving as the foundation for implementing our proposed study. The results validate the proposed method's superiority, delivering lower chattering, enhanced tracking precision, and greater robustness compared to traditional SMC while adhering to control standards. This control framework presents a viable advancement for 4WD EV motion management, supporting safer, more effective autonomous vehicle technologies.