Smart Charging and V2G Integration for Milan’s Shared Electric Mobility

Abstract

This study investigates the potential of AI-enabled smart charging and Vehicle-to-Grid integration to support sustainable shared electric mobility because of their importance in reducing transport-related emissions, improving fleet availability, increasing charging efficiency, and strengthening data-driven urban energy management. The main objective is to evaluate how smart charging and V2G can enhance the environmental, functional, and technical performance of shared electric mobility through the case of Milan, Italy. To achieve this objective, the study combines a Litmap-based literature context with an analytical case-study model based on three indicators: transport-related emission reduction, improvement in urban-use efficiency, and intelligent data-processing capability. The results showed that Milan’s annual mean NO₂ concentration decreased from 34 µg/m³ in 2024 to approximately 32 µg/m³ in 2025, representing a 5.88% reduction. The average traffic congestion index also declined slightly from 27.68 to 27.58, corresponding to a 0.36% improvement in urban-use efficiency. The city demonstrated an advanced level of intelligent data-processing capability through integrated urban platforms, shared-mobility monitoring, MaaS services, electric-fleet analysis, and V2G decision-support applications. However, full citywide autonomous AI-controlled charging and bidirectional energy exchange were not verified during the study period. The analytical model recorded a final score of 40.00 out of 100, indicating an unsatisfactory overall impact. The findings indicate that Milan has strong digital, institutional, and infrastructural foundations for AI-enabled smart charging and V2G, but more integrated real-time control, direct carbon-emission monitoring, renewable-energy coordination, and operational bidirectional charging are required to achieve measurable environmental and mobility benefits at the citywide operational level.