Energy Management based on Optimal Hybridization and Minimum Hydrogen Consumption: A Case Study of FC-Battery-SC Modular Train

This paper deals with an energy management strategy for a catenary-free modular train using a combination of fuel cell (FC), battery (BAT) and supercapacitor (SC). The objective is to identify the best sizing with compromising functional constraints to each source appropriately. The strategy first uses an equivalent consumption minimization (ECMS) algorithm to minimize the fuel consumption (hydrogen) while keeping the state of charge of different components in a safe range. Then, particle swarm optimization (PSO) algorithm is applied to optimize the sizing of the embedded sources. The compared results, simulated in Matlab/ Simulink environment, prove that PSO contributes to effectively reduce the embedded weight by 10% compared to the ECMS sizing results while achieving an appropriate power distribution.