ARCHIVES

This paper presents a hydrogen-efficient eco-driving and eco-routing strategy for fuel-cell electric vehicles (FCEVs) that simultaneously optimizes the path selection and speed trajectory planning in presence of traffic and terrain uncertainty. In contrast to traditional path search, which focuses on either minimizing distance or time, the provided approach optimizes hydrogen consumption while considering travel time and stack compatibility through connection of route-level energy model with predictive vehicle dynamics. Candidate route is constructed based on an enriched road map with grades, speed limits, signalize intersections and stochastically varying traffic states. A constrained eco-driving planner computes, for every segment of the road network, a speed profile compliant with safety and comfort bounds (among them limits on acceleration/jerk), respecting the speed regulation constrains and emitting stop- and-go if necessary, based on traffic forecast. A multi-objective optimizer (NSGA-II/MOPSO) generates a Pareto set of optimal route–speed solutions providing trade-offs between minimizing hydrogen consumption, time trip and powertrain stress proxies associated to fuel-cell degradation (i.e., fuel-cell’s power slew and low-load idling duration). On line, when traffic conditions are found different from the predicted one, a lightweight receding-horizon update of the selected Pareto solution guarantees feasibility and robustness. Simulation results on mixed urban–highway networks under uncertain congestion and variable terrain demonstrate that the proposed eco-routing with eco-driving leads to 7–15% reduction in hydrogen consumption over time-optimization planning and 4–10% lower than that of speed-unconcerned eco-routing (the same percentage improvement is observed in terms of CO2 emissions), while achieving comparable arrival times (typically within 2–6%). The technique also reduces hostile fuel-cell transients and ancillary load, increasing a payload stress index by 10–25% relative to baseline cruise-control techniques. We conclude that integrating multi-objective route planning and time-dependent predictive eco-driving may provide efficient hydrogen savings and durability advantages to FCEVs formulations in uncertain realistic traffic conditions.