Hybrid PEM fuel-cell/battery trains are a promising option to decarbonize non-electrified rail lines, yet their economic viability depends on powertrain sizing under mission- and route-specific constraints. This study presents a MATLAB-based simulation–optimization framework to size the fuel-cell stack, lithium-ion battery pack, and onboard hydrogen storage by minimizing the total cost of ownership (TCO, €/km). A longitudinal train dynamics model is coupled with a rule-based energy management strategy and semi-empirical degradation models for both battery capacity fade and fuel-cell voltage decay, enabling replacement-aware lifetime costing. To reduce computational burden, a surrogate-assisted global optimization is adopted within a nested sizing and feasibility loop, including a strict powertrain mass constraint. The framework is applied to representative regional passenger operations on three real-world Italian routes spanning short-, mid-, and long-range missions with distinct gradients and stop patterns. The results obtained demonstrate how the morphology of the route and the mass constraint act as drivers of the optimal degree of hybridisation. Specifically, the findings demonstrate that for high-gradient short-range routes, a higher battery-to-fuel cell ratio is required to maximise regenerative braking, while for long-range missions, the TCO is dominated by hydrogen consumption and fuel cell replacement costs. The proposed framework has been demonstrated to be a robust instrument for the cost-effective transition to hydrogen-powered rail transport.
Agati et al. (Fri,) studied this question.