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RESEARCH PAPER

Optimization of the Operating Parameters of a Proton Exchange Membrane Fuel Cell for Maximum Power Density

[+] Author and Article Information
A. Mawardi, F. Yang

 Advanced Materials and Technologies Laboratory, Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269-3139

R. Pitchumani1

 Advanced Materials and Technologies Laboratory, Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269-3139r.pitchumani@uconn.edu

1

Corresponding author.

J. Fuel Cell Sci. Technol 2(2), 121-135 (Jan 07, 2005) (15 pages) doi:10.1115/1.1867978 History: Received November 01, 2004; Accepted January 07, 2005; Revised January 07, 2005

The performance of fuel cells can be significantly improved by using optimum operating conditions that maximize the power density subject to constraints. Despite its significance, relatively scant work is reported in the open literature on the model-assisted optimization of fuel cells. In this paper, a methodology for model-based optimization is presented by considering a one-dimensional nonisothermal description of a fuel cell operating on reformate feed. The numerical model is coupled with a continuous search simulated annealing optimization scheme to determine the optimum solutions for selected process constraints. Optimization results are presented over a range of fuel cell design parameters to assess the effects of membrane thickness, electrode thickness, constraint values, and CO concentration on the optimum operating conditions.

Copyright © 2005 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

Schematic illustration of a proton exchange membrane (PEM) fuel cell

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Figure 2

Schematic diagram of Nelder–Mead simplex search combined with simulated annealing optimization

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Figure 3

Validation of the numerical PEM fuel cell model with the data from Refs. 13,22

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Figure 4

(a) Optimum power density, and the corresponding constraints: (b) maximum temperature difference, (c) minimum hydration, and (d) cell potential, for the set of parameters represented by case 0

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Figure 5

Optimum decision variables: (a) temperature, (b) N2∕O2 mole fraction, (c) CO2∕H2 mole fraction, (d) anode and cathode pressures, (e) relative humidities in anode and cathode, and (f) anode and cathode stoichiometries, for the set of parameters represented by case 0

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Figure 6

(a) Optimum power density, and the corresponding constraints: (b) maximum temperature difference, (c) minimum hydration, and (d) cell potential, for the set of parameters represented by case 1; the results from case 0 (dashed lines) are included for comparison

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Figure 7

Optimum decision variables: (a) temperature and cathode relative humidity, (b) anode and cathode pressures, (c) N2∕O2 mole fraction and cathode stoichiometry, and (d) CO2∕H2 mole fraction and anode stoichiometry, for the set of parameters represented by case 1; the optimum decision variables from case 0 (dashed lines) are included for comparison. The optimum relative humidity at the anode, RHa∗=1.1

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Figure 8

(a) Optimum power density, and the corresponding constraints: (b) maximum temperature difference, (c) minimum hydration, and (d) cell potential, for the set of parameters represented by case 2; the results from case 0 (dashed lines) are included for comparison

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Figure 9

Optimum decision variables: (a) temperature and cathode relative humidity, (b) anode and cathode pressures, (c) N2∕O2 mole fraction and cathode stoichiometry, and (d) CO2∕H2 mole fraction and anode stoichiometry, for the set of parameters represented by case 2; the optimum decision variables from case 0 (dashed lines) are included for comparison. The optimum relative humidity at the anode, RHa∗=1.1

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Figure 10

(a) Optimum power density, and the corresponding constraints: (b) maximum temperature difference, (c) minimum hydration, and (d) cell potential, for the set of parameters represented by case 3; the results from case 0 (dashed lines) are included for comparison

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Figure 11

Optimum decision variables: (a) temperature and cathode relative humidity, (b) anode and cathode pressures, (c) N2∕O2 mole fraction and cathode stoichiometry, and (d) CO2∕H2 mole fraction and anode stoichiometry, for the set of parameters represented by case 3; the optimum decision variables from case 0 (dashed lines) are included for comparison. The optimum relative humidity at the anode. RHa∗=1.1

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Figure 12

(a) Optimum power density, and the corresponding constraints: (b) maximum temperature difference, (c) minimum hydration, and (d) cell potential, for the set of parameters represented by case 4; the results from case 0 (dashed lines) are included for comparison

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Figure 13

Optimum decision variables: (a) temperature and cathode relative humidity, (b) anode and cathode pressures, (c) N2∕O2 mole fraction and cathode stoichiometry, and (d) CO2∕H2 mole fraction and anode stoichiometry, for the set of parameters represented by case 4; the optimum decision variables from case 0 (dashed lines) are included for comparison. The optimum relative humidity at the anode, RHa∗=1.1

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Figure 14

(a) Optimum power density, and the corresponding constraints: (b) maximum temperature difference, (c) minimum hydration, and (d) cell potential, for the set of parameters represented by case 5; the results from case 0 (dashed lines) are included for comparison

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Figure 15

Optimum decision variables: (a) temperature and cathode relative humidity, (b) anode and cathode pressures, (c) N2∕O2 mole fraction and cathode stoichiometry, and (d) CO2∕H2 mole fraction and anode stoichiometry, for the set of parameters represented by case 5; the optimum decision variables from case 0 (dashed lines) are included for comparison. The optimum relative humidity at the anode, RHa∗=1.1

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