A two-echelon mobile charging system for electric vehicles with trucks and autonomous charging robots

Electric vehicle (EV) adoption is hindered by limited charging infrastructure and prolonged charging times. Mobile charging can alleviate these barriers by bringing charging services to parked vehicles. In practice, however, truck-based mobile chargers often struggle to access narrow residential streets and congested parking facilities, limiting their effectiveness in dense environments. To address this gap, this study proposes a novel two-echelon mobile charging system that combines trucks with autonomous charging robots (ACRs) to overcome accessibility limitations and improve operational efficiency. In this system, trucks transport ACRs between a central depot and satellite locations, while ACRs provide last-mile charging services within neighborhoods and parking facilities. We formulate this as a two-echelon mobile charger routing problem and develop a mixed-integer programming (MIP) model that captures routing decisions, time-window constraints, battery limitations, and ACR relocation requirements. Given the problem’s complexity, we develop a logic-based Benders decomposition approach combined with a branch-and-price algorithm, and introduce tailored problem-specific Benders cuts to accelerate convergence. Computational experiments demonstrate that our proposed algorithm efficiently solves the problem. Furthermore, our findings show that the coordinated truck-ACR operation significantly outperforms the standalone ACR-based approach.