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Predictive modeling and testing of a diesel derived solid oxide fuel cell tail gas spark-ignition engine

dc.contributor.authorCountie, Matthew, author
dc.contributor.authorOlsen, Daniel, advisor
dc.contributor.authorWindom, Brett, committee member
dc.contributor.authorBaker, Daniel, committee member
dc.date.accessioned2020-09-07T10:08:48Z
dc.date.available2020-09-07T10:08:48Z
dc.date.issued2020
dc.description.abstractSolid oxide fuel cell systems are being developed with total system efficiency targets over 70%. One approach is to provide excess fuel to the solid oxide fuel cell and develop an engine to provide power for mechanical and electrical equipment using exhaust gas from the fuel cell anode (tailgas). This tailgas contains hydrogen, carbon monoxide, methane, water, and carbon dioxide. Compared to natural gas the tailgas fuel has suppressed flame speeds, an extremely small lower heating value, and a low air-fuel ratio due to the presence of large amounts of oxidation products. A predictive model created in GT-Power was used to design an engine that can produce 14kW on tailgas fuel with a brake efficiency η>30%. The model base is an existing Kohler diesel engine. The diesel engine was modeled in GT-Power and validated to within 1% at the anticipated operating point. Using custom combustion models developed from testing several different tailgas blends in a CFR engine, several different engine conversions were modeled to explore different pathways to 30% brake efficiency. Design variations include Miller cycles, turbocharging, compression ratio, and fuel pre-treatment to increase reactivity. Once design parameters were established, an operation envelope was created to identify knock limits and maximum brake efficiency timing. These models helped guide the development of a physical prototype engine that was built and installed at the CSU Powerhouse Energy Campus. The prototype engine ran with simulated anode tailgas up to a maximum power level of 7.42 kW and a maximum brake efficiency of 27.34%, achieving 53% of the load target, and 91% of the efficiency target. The timings identified by GT-Power to be the point of maximum brake efficiency and knock initiation were tested at four different speeds on the prototype engine. After data collection, using the experimental power, engine speed, and ignition timing as initial conditions, the model is rerun. The accuracy of the models' prediction capability is tested by using these initial conditions to generate additional model output to compare with measured data. At low speeds and advanced ignition timings, the model matched well, within 10% on almost all metrics, but at retarded timings and high engine speeds, the model began to deviate in most parameters, especially overpredicting exhaust temperature and pressure. The discrepancies between model results and experimental data are discussed in detail. Model and experimental data matched well at advanced timings and low speeds, but deviated significantly at retarded timings and high speeds.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifierCountie_colostate_0053N_16222.pdf
dc.identifier.urihttps://hdl.handle.net/10217/212058
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2020-
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectengines
dc.subjectinternal combustion engine
dc.subjectdilute fuels
dc.subjectsolid oxide fuel cell
dc.subjectGT-power
dc.titlePredictive modeling and testing of a diesel derived solid oxide fuel cell tail gas spark-ignition engine
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineMechanical Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

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