This paper presents a high-fidelity multi-physics dynamic model for electric vehicles, serving as a fundamental building block for intelligent vehicle-to-grid (V2G) integration systems. The model accurately captures complex vehicle dynamics of the powertrain, battery, and regenerative braking, enabling precise energy consumption evaluation, including in AI-driven V2G scenarios. Validated using real-world data from a Citroën Ami operating on urban routes in Naples, Italy, it achieved exceptional accuracy with a root mean square error (RMSE) of 1.28% for dynamic state of charge prediction. This robust framework provides an essential foundation for AI-driven digital twin technologies in V2G applications, significantly advancing sustainable transportation and smart grid integration through predictive simulation. Its versatility supports diverse fleet applications, from residential energy management and coordinated charging optimization to commercial car sharing operations, leveraging backup power during peak demand or grid outages, so to maximize distributed battery storage utilization.

The decarbonisation of short-sea passenger shipping is a central challenge within the broader transition toward intelligent and sustainable transportation systems. This paper presents a model-based design and techno-economic assessment of a Battery Energy Storage System (BESS) retrofitting a hybrid diesel-electric regional ferry operating the Naples-Ischia route (~19 nautical miles). An experimentally validated Equivalent Circuit Model (ECM) of a commercial LiFePO₄ cell, parameterised through Hybrid Pulse Power Characterisation (HPPC) tests at 10 °C, 25 °C, and 40 °C and validated via Extended Kalman Filter State-of-Charge (SOC) estimation, is embedded into a full-vessel dynamic model. This last encompasses propulsion, power generation, electrical distribution and battery subsystems. Two energy management strategies are evaluated against the conventional diesel-electric baseline: Strategy 1 (S1), combining in-port BESS discharge with shore-grid recharging; Strategy 2 (S2), adding controlled in-navigation recharging when SOC falls below 20%. S1 is found to achieve a 17% annual CO₂ reduction, while S2 yields superior 20-year economics, with annual net savings of ~€470,000, a simple payback period of 3.72 years, and ~6 battery replacements versus ~9 under S1. Also, adopting S2 allows maintaining a shallower average Depth of Discharge (DoD), namely ~40% vs. ~70% of S1. A multi-objective optimisation confirms that the proposed BESS layout occupies only 5% of the available garage area and satisfies Load Line Convention constraints without reducing commercial payload capacity. The presented integrated framework provides a replicable, multidisciplinary tool for BESS deployment across the Mediterranean short-sea ferry sector, directly contributing to the advancement of sustainable maritime transportation.