Modeling and survey analysis evaluates robot-based electric vehicle charging, indicating that deployment success hinges on user behavior, fleet sizing, and dynamic pricing strategies.
The rapid increase in electric vehicle (EV) usage requires scalable and flexible charging solutions that minimize user effort and infrastructure constraints. One such solution is robot-based EV charging, which automates the charging process to increase convenience and ease of use. This work investigates the feasibility of deploying mobile charging robots in selected parking scenarios, with a focus on user acceptance and the economic viability from the perspective of infrastructure operators. The research is guided by three objectives: identifying user requirements; modelling realistic charging behaviour; and evaluating operational strategies for mobile charging fleets, including fleet sizing, impact of nearby charging infrastructure, and pricing approaches. A dedicated user survey and a predictive behavioural model informed the simulation studies used to assess optimal deployment strategies. The results suggest that, while mobile charging robots can enhance the user experience and increase infrastructure flexibility, their effectiveness depends on user behaviour, temporal demand patterns, and well-designed interaction and pricing mechanisms. These findings provide a basis for evaluating the integration of mobile charging robots as a complement to stationary charging infrastructure.
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Wessel et al. (2026) studied this question.
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