In high-power charging for battery-electric long-haul road transport and heavy-duty vehicles, predictability of charging sessions at public charging stations can be valuable both for the vehicle side and the charging infrastructure side. For drivers and fleet management, predictability enables reliable route planning and alignment of charging with statutory driving and resting periods. For charging stations, advance knowledge of charging demands supports efficient operation under possible limitations in grid connection, including control of local energy storage systems or gird services.

Booking-based charging has the potential to reduce uncertainty related to charger availability and queueing on the vehicle side, as well as increasing the predictability of energy demand from the perspective of charging infrastructure operators. While pilot implementations for booking of charging slots for heavy-duty vehicles at a specific station and time exist, at present, no booking system for high-power charging of heavy-duty vehicles has been established as a broadly deployed market solution.

Furthermore, the design space for booking-based charging remains open. With systems for booking separate charging slots as described above, the responsibility for route planning remains with drivers or fleet management, limiting the possibility to capture system-level effects. Nevertheless, different pricing mechanisms may attempt to reflect local availability of charging power or the opportunity cost of flexibility at the charging station, and translate these effects to the value of route changes. An alternative class of approaches extends this to booking an origin-destination defined route along with energy guarantees. Charging station operators may then route vehicles to charge at specific stations, within the given constraints on route points, times, or resting periods. Depending on system design, a secondary market may allow charging point operators to trade charging needs, allowing fulfilling route requirements while balancing system efficiency.

In this work we will therefore explore and evaluate the effects of different methods for enhancing predictability. We consider how alternative frameworks as described previously influence both vehicle and infrastructure side. Intelligent system for integrating the energy system with the transport sector will accelerate the transition to a fossil-free heavy-duty transport sector.