Keeping EVs powered on the go: optimizing battery-to-battery in-motion charging on intercity highway networks

The limited driving range and slow charging speed of electric vehicles (EVs) constrain long-distance intercity travel, making efficient charging solutions critical. While prior studies have shown that battery-to-battery in-motion charging (B2BIC) effectively reduces travel delays on single highways, its optimization across intercity highway networks remains unexplored. Addressing this gap, we develop a mixed-integer nonlinear programming (MINLP) model and reformulate it into a mixed-integer linear programming (MILP) model using a discretization method to enhance solvability. Case studies based on Chinese highway data validate the proposed approach. Key findings include: (1) Deployed energy-providing vehicles (EPVs) can operate continuously for over 18 hours without intermediate charging, with each delivering 100–200 kWh of energy per day using a 350 kWh battery; (2) Increasing the EPV fleet size and depot coverage significantly boosts energy delivery and reduces average EV travel time, though marginal benefits diminish beyond approximately 90 EPVs; (3) Larger EPV battery capacities further improve system performance (higher energy output and greater travel time reduction), while expanding from 3 to 7 depots has a limited impact under constant demand. These findings suggest that integrating B2BIC services into future EV charging infrastructures could substantially enhance system resilience and scalability, providing valuable guidance for planners and policymakers.