Optimization and Experimental Approaches to the Direct Methanol Fuel Cell Stack Using a Response Surface Methodology

  • سال انتشار: 1398
  • محل انتشار: مجله انرژی تجدیدپذیر و محیط زیست، دوره: 6، شماره: 2
  • کد COI اختصاصی: JR_JREE-6-2_004
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 620
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نویسندگان

Shima Sharifi

Department of Chemical Engineering, Faculty of Engineering and Center for Renewable Energy Research, University of Sistan and Baluchestan, Zahedan, Iran

Rahbar Rahimi

Department of Chemical Engineering, Faculty of Engineering and Center for Renewable Energy Research, University of Sistan and Baluchestan, Zahedan, Iran

Davod Mohebbi-Kalhori

Department of Chemical Engineering, Faculty of Engineering and Center for Renewable Energy Research, University of Sistan and Baluchestan, Zahedan, Iran

Can Ozgur Colpan

Department of Mechanical Engineering, Dokuz Eylul University, Buca, Izmir, Turkey

چکیده

The power density of a direct methanol fuel cell (DMFC) stack as a function of temperature, methanol concentration, oxygen flow rate, and methanol flow rate was studied using a response surface methodology (RSM) to maximize the power density. The operating variables investigated experimentally include temperature (50-75 °C), methanol concentration (0.5-2 M), methanol flow rate (15-30 ml min-1), and oxygen flow rate (900-1800 ml min-1). A new design of the central composite design (CCD) for a wide range of operating variables that optimize the power density was obtained using a quadratic model. The optimum conditions that yield the highest maximum power density of 86.45 mW cm-2 were provided using 3-cell stack at a fuel cell temperature of 75 °C with a methanol flow rate of 30 ml min-1, a methanol concentration of 0.5 M, and an oxygen flow rate of 1800 ml min-1. Results showed that the power density of DMFC increased with an increase in the temperature and methanol flow rate. The experimental data were in good agreement with the model predictions, demonstrating that the regression model was useful in optimizing maximum power density from the independent operating variables of the fuel cell stack.

کلیدواژه ها

Direct methanol fuel cell stack, maximum power density, Regression Model, Response Surface Methodology

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