Simulation and optimization of diesel autothermal reformer for fuel cell applications
Proton-electrolyte membrane (PEM) fuel cell systems offer a potential power source for utility and mobile applications. One of the most promising alternatives for large power requirements is to obtain the hydrogen from a liquid hydrocarbon fuel. A diesel fuel is an attractive option as feeds to fuel...
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Format: | Thesis |
Language: | English |
Published: |
2007
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Online Access: | http://eprints.utm.my/id/eprint/3119/1/SitiNorhanumFadliMFChe2007.pdf |
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Summary: | Proton-electrolyte membrane (PEM) fuel cell systems offer a potential power source for utility and mobile applications. One of the most promising alternatives for large power requirements is to obtain the hydrogen from a liquid hydrocarbon fuel. A diesel fuel is an attractive option as feeds to fuel processor. Unfortunately, diesel fuel reforming is complicated and requires much higher temperatures. With the help of Aspen HYSYS 2004.1 the steady state model has been develop to optimize the performance, analyze the fuel processor and total system performance In this case study, the PEM fuel cell system consists of the fuel processing and clean-up section, PEM fuel cell section and auxiliary units. While the fuel processing and clean-up section consists of Autothermal Reformer, High-temperature Shift, Medium-temperature Shift, Low-temperature Shift, and Preferential Oxidation. The purpose of this study is to identify the influence of various operating parameters such as A/F and S/F ratio on the system performance that is also related to its dynamic behaviours. From the steady state model optimization using Aspen HYSYS 2004.1, an optimized reaction composition, in terms of hydrogen production and carbon monoxide concentration, corresponds to A/F ratio of 45 and S/F ratio of 25. Under this condition, n-hexadecane conversion of 100%, H2 yield of 19.8% on wet basis and carbon monoxide concentration of 25.428ppm can be achieved. The fuel processor efficiency is about 52.85% under these optimized conditions. |
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