Design of a Robust Adaptive Cascade Fractional‐Order Nonlinear‐Based Controller Enhanced Using Grey Wolf Optimization for High‐Power DC/DC Dual Active Bridge Converter in Electric Vehicles

ABSTRACT The dual active bridge (DAB) converter is a key technology in electric vehicles (EVs), offering efficient, bidirectional DC–DC power conversion with galvanic isolation. This paper presents a novel cascade control strategy incorporating a fractional‐order PID (FOPID) controller in the outer loop for precise voltage regulation and an adaptive backstepping controller (ABSC) in the inner loop for robust current control. The ABSC is designed using Lyapunov stability theory, ensuring systematic stabilization of nonlinear dynamics and robust performance under disturbances. The FOPID controller introduces superior filtering characteristics, effectively mitigating high‐frequency measurement noise and transient disturbances, making it highly suitable for high‐frequency power electronics applications. A capacitor–inductor–inductor–capacitor filter is integrated with the DAB converter to achieve soft switching, improve efficiency, and reduce switching losses, particularly in high‐power applications. The grey wolf optimization (GWO) algorithm is employed to fine‐tune the gains of both control loops, balancing exploration and exploitation to ensure optimal performance. The proposed controller is validated through hardware‐in‐loop (HIL) experiments, including testing with a HIL‐emulated battery. The battery's behaviour is analysed under various conditions, including state‐of‐charge variations, demonstrating the controller's effectiveness in managing charging and discharging cycles. Results confirm that the robust adaptive cascade controller significantly enhances the reliability and efficiency of DAB converters, making it ideal for real‐world EVs and renewable energy applications.