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Access Right: info:eu-repo/semantics/closedAccessAuthor: Alpaydin, Guvenc Umur

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    Article
    Mathematical Modeling of a Direct Dimethyl Ether Fuel Cell
    (Wiley-hindawi, 2022) Alpaydin, Guvenc Umur; Durmus, Gizem Nur Bulanik; Colpan, C. Ozgur; Devrim, Yilser
    In this study, a mathematical model of a direct dimethyl ether fuel cell (DDMEFC) is developed to examine the effect of operating conditions on voltage losses and cell performance. In modeling, the electrochemical relations and mass balances are used to find the cell voltage for the given conditions. The values of some modeling parameters are determined using experimental data through curve fitting. For validation purposes, in-house experimental studies are conducted. For this purpose, Pt50Ru25Pd25/C, Pt40Ru40Pd20/C, and Pt50Pd50/C anode catalysts are synthesized by the microwave method. The effects of these synthesized catalysts and the operating conditions (cell temperature, the molar ratio of dimethyl ether, and water) on the DDMEFC performance are discussed by comparing the activation and ohmic polarization as well as the polarization curves using the model developed. This cell-level modeling approach could be considered as a preliminary step in the design process of a DDMEFC stack.
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    Conference Object
    Optimization of modeling parameters of of a direct dimethyl ether fuel cell (DDMEFC)
    (Ieee, 2019) Alpaydin, Guvenc Umur; Colpan, C. Ozgur; Devrim, Yilser
    Direct alcohol fuel cells are one of the suitable candidates for sustainable power generation in portable applications. Among the different alcohol types that can be used in these fuel cells, DME, which is almost non-toxic at room temperature and easy to liquefy, and has a molecular structure similar to methanol, is one of the suitable options. For this reason, many studies have been carried out to develop direct dimethyl ether fuel cell (DDMEFC). Mathematical modeling studies also play an important role in the development of DDMEFC since they enable the understanding of the performance of the fuel cells more thoroughly. In this study, a model has been developed by using the principles of conservation chemical species and electrochemistry. A modeling study was performed using MATLAB. The values of some modeling parameters were estimated using the genetic algorithm optimization technique.