Fuel cell vehicles powered using Hydrogen/air fuel cells have received a lot of attention recently as possible alternatives to internal combustion engine. However, the combined problems of on-board Hydrogen storage and the lack of Hydrogen infrastructure represent major impediments to their wide scale adoption as replacements for IC engine vehicles. On board fuel processors that generate hydrogen from on-board liquid methanol (and other hydrocarbons) have been proposed as possible alternative sources of Hydrogen needed by the fuel cell.
This paper focuses on a methanol fuel processor using steam reformation of methanol to generate the Hydrogen required for the fuel cell stack. Since the steam reformation is an endothermic process the thermal energy required is supplied by a catalytic burner. Though a number of different designs for this type of fuel processor have been investigated, the general class of compact fuel processors characterized by close thermal integration of the burner and the reformer show the greatest promise for fuel cell vehicle applications.
Through the use of a model for the fuel processor, comprising of detailed models for the reformer, burner and CO cleanup units, we investigate the performance of the fuel processor from the viewpoints of efficiency and transient performance. In particular, the model can generate results in terms of a) steady state efficiencies b) response to transient step inputs c) Efficiency and dynamics in the context of its use in a fuel cell vehicle under standard driving cycles.
Our results illustrate the complex nature of the interaction between the fuel processor, the fuel cell stack and auxiliaries and the vehicle subsystem. In particular, they highlight a) the impact of fuel processor response times, b) the impact of control strategies, c) fuel processor-stack interactions, all, in the context of the ability of the vehicle to meet both the driving cycle and achieve high efficiencies. The results also suggest that steady state fuel processor efficiencies would not be very accurate predictors of fuel processor performance in an overall fuel cell vehicle.