Conventional photovoltaic (PV) systems integrate boost converters for maximum power point tracking (MPPT) but suffer from issues such as one-way power transfer, low voltage increase, and low efficiency during dynamic solar conditions. This paper presents a new control structure that combines a Dual Active Bridge (DAB) converter with a hybrid metaheuristic MPPT algorithm to overcome these issues. The DAB allows for two-way power transfer, provides galvanic isolation, and enables soft-switching which makes it a candidate for next-generation electric vehicle (EV) charging systems. To enhance power extraction, a hybrid MPPT method that combines the global radar-like search capabilities of the Whale Optimization Algorithm (WOA) with the fast local convergence characteristic of the Bat Algorithm (BA) is proposed. This strategy divides the DAB phase shift control in an adaptive manner with the aim of improving the MPPT response. Simulations conducted in MATLAB/Simulink and real-time testing through dSPACE DS1104 hardware-in-the-loop (HIL) confirmed improved tracking speed, lower output ripple, and higher conversion efficiency compared to BA, PSO, and Perturb-and-Observe (P&O) MPPT methods. The results of this study demonstrate the potential of these systems for smart and efficient EV charging infrastructure powered by renewable energy.