Net Hydrogen Consumption Minimization of Fuel Cell Hybrid Trains Using a Time-Based Co-Optimization Model

Abstract

With increasing concerns on transportation decarbonization, fuel cell hybrid trains (FCHTs) attract many attentions due to their zero carbon emissions during operation. Since fuel cells alone cannot recover the regenerative braking energy (RBE), energy storage devices (ESDs) are commonly deployed for the recovery of RBE and provide extra traction power to improve the energy efficiency. This paper aims to minimize the net hydrogen consumption (NHC) by co-optimizing both train speed trajectory and onboard energy management using a time-based mixed integer linear programming (MILP) model. In the case with the constraints of speed limits and gradients, the NHC of co-optimization reduces by 6.4% compared to the result obtained by the sequential optimization, which optimizes train control strategies first and then the energy management. Additionally, the relationship between NHC and employed ESD capacity is studied and it is found that with the increase of ESD capacity, the NHC can be reduced by up to 30% in a typical route in urban railway transit. The study shows that ESDs play an important role for FCHTs in reducing NHC, and the proposed time-based co-optimization model can maximize the energy-saving benefits for such emerging traction systems with hybrid energy sources, including both fuel cells and ESD.

Impact of On-Board Hybrid Energy Storage Devices on Energy-Saving Operation for Electric Trains in DC Railway Systems

“…Zhang et al [19] introduced the Mixed Integer Linear Programming (MILP) model to optimize the speed profile and the capacity configuration for on-board HESDs, which focused on minimum economic costs considering the long-term train operation. In [20], the authors showed that the capacity of SCs and speed trajectory for Fuel-cell hybrid trains could be co-optimized to achieve minimum net hydrogen consumption. The distance-based model was proposed to obtain the speed trajectory and capacity solution with energy flow constraints [21].…”

Modelling and Simulation of a Hydrogen-Based Hybrid Energy Storage System with a Switching Algorithm

“…All the highlighted advantages make hydrogen potentially a better choice than batteries in energy-demanding applications. For example, they could be implemented in heavy-duty vehicles to satisfy the energy demand in the transportation sector which accounts for almost a quarter of the total energy demand of the globe [26]. Studies have shown that fuel cell-powered heavy-duty vehicles offer better range, vehicle longevity, and significantly lower transportation and maintenance costs [27].…”