Exploring electric vehicle robot charging stations: A simulation-based approach for charging capacity improvement

Expanding electromobility has typically relied on deploying fixed charging stations (FCSs) infrastructure, but this is not the single solution. One innovative solution is using mobile charging robots (MCRs), which move around to charge parked vehicles and feature an internal battery storage system; MCRs are currently in early research and development (R&D) stages, but have not been fully deployed in practice. Beyond their technical development and control challenges, one concern still underexplored is how MCRs compare to conventional FCSs across different use cases. This research explores this gap with a discrete-event simulation approach, quantifying the capacity improvements brought by an ongoing MCR R&D project. The simulations assess four use case scenarios with different demand and FCS characteristics, and two MCR recharging strategies against the baseline FCS-only variation. Results indicate that the throughput improvement brought by MCRs depends on the implementation scenario, reaching a 302 % increase when complementing existing slow FCSs with known daily demand variability. The average cycle time in which vehicles are charged was also reduced across all scenarios. As such, the results better elucidate the potential benefits of MCRs, and can serve as the starting point for detailing their application in practice.