Publication Detail
System Dynamics and Efficiency of the Fuel Processor for an Indirect Methanol Fuel Cell Vehicle
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UCD-ITS-RP-01-24 Presentation Series |
Suggested Citation:
Ramaswamy, Sitaram, Meena Sundaresan, Robert M. Moore, Anthony R. Eggert (2000) System Dynamics and Efficiency of the Fuel Processor for an Indirect Methanol Fuel Cell Vehicle. American Institute of Aeronautics and Astronautics (2000-3048)
35th Intersociety Energy Conversion Engineering Conference and Exhibit (IECEC), Las Vegas, NV, July 24 - 28, 2000
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 onboard 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 onboard liquid methanol (and other Hydrocarbons) have been proposed as possible alternative sources of Hydrogen needed by the Fuel Cell.
This paper investigates the dynamic response and efficiency of the on-board Fuel Processor in an Indirect-Methanol Fuel Cell Vehicle. This is carried out using a Fuel Processor model developed in the Matlab/Simulink environment. The Fuel Processor model includes detailed subsystem models for the Steam-Reformer, Methanol/Hydrogen burner, pre-heaters and CO cleanup stages.
The discussion of Fuel Processor dynamic response is in the context of the demands placed on the Fuel Processor when operating the Fuel Cell Vehicle under different drive cycles. Operation of the Fuel Cell Vehicle under these drive cycles translates into stringent performance requirements for the Fuel Processor. These requirements further help determine the best possible Fuel Processor design, control scheme, and overall operating strategy. The subsequent transient response of the now-optimized Fuel Processor sub-system is investigated to ensure that it meets the dynamic power demands of the Fuel Cell Vehicle.
The impact of operating steady state load conditions on the Fuel Processor efficiency is also investigated. This is then compared with efficiencies obtained under dynamic load conditions. This comparison illustrates the impact of dynamic operation on the average Fuel Processor efficiency over a drive cycle that one might expect to see during the operation of an Indirect-Methanol Fuel Cell Vehicle and also hints at the possible effect on overall miles/gallon equivalent performance.
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 onboard 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 onboard liquid methanol (and other Hydrocarbons) have been proposed as possible alternative sources of Hydrogen needed by the Fuel Cell.
This paper investigates the dynamic response and efficiency of the on-board Fuel Processor in an Indirect-Methanol Fuel Cell Vehicle. This is carried out using a Fuel Processor model developed in the Matlab/Simulink environment. The Fuel Processor model includes detailed subsystem models for the Steam-Reformer, Methanol/Hydrogen burner, pre-heaters and CO cleanup stages.
The discussion of Fuel Processor dynamic response is in the context of the demands placed on the Fuel Processor when operating the Fuel Cell Vehicle under different drive cycles. Operation of the Fuel Cell Vehicle under these drive cycles translates into stringent performance requirements for the Fuel Processor. These requirements further help determine the best possible Fuel Processor design, control scheme, and overall operating strategy. The subsequent transient response of the now-optimized Fuel Processor sub-system is investigated to ensure that it meets the dynamic power demands of the Fuel Cell Vehicle.
The impact of operating steady state load conditions on the Fuel Processor efficiency is also investigated. This is then compared with efficiencies obtained under dynamic load conditions. This comparison illustrates the impact of dynamic operation on the average Fuel Processor efficiency over a drive cycle that one might expect to see during the operation of an Indirect-Methanol Fuel Cell Vehicle and also hints at the possible effect on overall miles/gallon equivalent performance.