<p>A high-performance and energy-efficient control strategy is critical for ensuring reliable bidirectional power transfer between the grid and lithium-ion batteries in vehicle-to-grid (V2G) applications. This paper presents an adaptive continuous control set model predictive control (CCS-MPC) strategy designed for a three-phase bidirectional active front-end (AFE) converter integrated with an interleaved buck-boost DC/DC converter. The high degree of integration allows fast transitions from grid-to-vehicle (G2V) to V2G modes of operation which are essential requirements for the integration with the unstable grid. The framework of CCS-MPC with fixed switching frequency ensures the minimization of total harmonic distortion (THD) levels with enhanced operational quality to meet strict grid standards and compliances. To enhance resilience to modeling errors and external disturbances, the control algorithm guarantees that in fluctuating grid conditions, accurate state estimation and stability are maintained throughout the predictive controlling system. It surpasses conventional control approaches on parameters such as power quality, adaptability, and design robustness, which makes it very promising for the improvement of V2G systems. The proposed CCS-MPC-based control scheme is versatile and energy efficient, making it suitable for the next generation of EV charging stations. Experimental validation on a 12.5 kW hardware prototype achieved THD levels below 2%, stable DC-link voltage (DLV) and unity power factor (UPF), showcasing the system’s capability to deliver high power quality and reliability. This study emphasizes the ability of the proposed methodology to overcome existing barriers to successfully applying V2G technological solutions for sustainable energy development and grid integration.</p>