Contadini, José F., Claudia V. Diniz, Daniel Sperling, Robert M. Moore (2000) Design and Energy Requirements for Future Marketing Activities of Gaseous Hydrogen Fuel for Fuel Cell Vehicles. Institute of Transportation Studies, University of California, Davis, Research Report UCD-ITS-RR-00-17
Rapid improvements in fuel cell technology are bringing fuel cell vehicles closer to commercialization. Air quality and climate change have been principal motivations for developing fuel cell vehicles, but air quality and greenhouse gas impacts can vary greatly depending upon the performance and design characteristics of the fuel supply system. The energy requirement of each possible fuel supply configuration is one of the basic parameters required to calculate the future emissions of the criteria pollutants and the greenhouse gases.
In this paper, we analyze the energy attributes of a hydrogen fuel supply system for fuel cell vehicles. We examine several pathways, focusing on the upstream part of the system. We use a component model of the Fuel Upstream Energy and Emissions Model (FUEEM) being developed at UC Davis using MatLab/Simulink software. To handle uncertainty in future technology attributes and system designs, as well as unreliability of some data, FUEEM uses probabilistic functions and relies on an international expert advisory panel to establish the major inputs. The statistical attributes of the Monte Carlo technique such as Latin hypercube sampling and rank order correlations among variables are handled in the component model using @Risk software.
We present results for alternative gaseous hydrogen fuel supply systems. We analyze high-pressure bulk storage vessels, transmission pipelines, local distribution pipelines and fuel stations, and present energy requirements for hydrogen compression by electric motors, natural gas reciprocating engines, and different pipelines lengths and pressures. Hydrogen losses (fugitive, venting, etc.) are considered in terms of energy loss. Local emissions associated with the use of natural gas engines are calculated too. The results are obtained in terms of probabilistic curves, which are very rich information for decision-making, showing maxinium, minimum, mode, and mean values, along with the probability of each single value within the range.