An Eco-Charging Strategy for Heavy-Duty Electric Vehicles via Graph Optimization

An optimization framework for trip and charging planning for electric heavy-duty vehicles is proposed in this paper. Building upon and extending previous work on light-duty vehicles, our approach models energy-aware routing by constructing a state-augmented graph that jointly captures geographic position and battery state-of-charge. We refine the route model to include detailed vehicle dynamics and speed constraints specific to heavy-duty vehicles, and introduce an alternative graph construction method that avoids the computational complexity of lexicographic products by generating only feasible nodes. The resulting framework enables efficient trip planning that accounts for driving behavior, road characteristics, and charging infrastructure. Simulation results demonstrate the effectiveness of the approach in reducing energy consumption and ensuring operational feasibility for long-haul freight transport.