Ride comfort, stability, and safety are the key criteria for evaluating the quality of vehicles, especially for the electric vehicle (EV) as the global automotive industry shifts toward sustainable and green transportation. Achieving these criteria heavily depends on the suspension system. To address this, the study establishes a comprehensive model that includes an eight-degrees-of-freedom (8-DOF) model and a steering model under the effects of random road excitations and driving conditions. The mathematical equations governing the vehicle's motion are formulated based on Newton's laws, while the nonlinear Pacejka's Magic Tire Formula is applied to represent tire behavior accurately. A Fuzzy Fractional-Order Proportional-Integral-Derivative (FFOPID) controller is then proposed for the EV's active suspension system (ASS) to enhance ride comfort, stability, and safety. In addition, the classical Proportional-Integral-Derivative (PID) controller and the fuzzy logic controller (FLC) are also implemented to serve as a baseline for evaluating the performance of the proposed FFOPID controller. A fishhook maneuver is incorporated into the study to evaluate vehicle performance in critical handling scenarios. To enhance the effectiveness of the control strategy, the Particle Swarm Optimization (PSO) algorithm is employed to optimize the controller parameters. Finally, the mathematical equations and proposed control strategies for the ASS are implemented in the Simulink environment of MATLAB. The root mean square (RMS) values of the acceleration of the human-seat system (azhs), vertical vehicle body (azb), pitch vehicle body (aϕb), roll vehicle body (aθb), suspension working space (SWS), and dynamic tire load (DTL) are selected as performance evaluation indices for the proposed control strategy. The results show that the proposed FFOPID not only outperforms the passive suspension system (PSS) but also proves to be more effective than the PID and FLC controllers in enhancing ride comfort, stability, and safety under severe operating conditions, which underscores the effectiveness of the proposed FFOPID controller in enhancing the overall quality of EVs.
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