This paper describes the application of statistical analysis to a $2.5kW$ proton exchange membrane fuel cell stack operation, by experimental design methodology, whereby robust design conditions were identified for the operation of fuel cell stacks. The function is defined as the relationship between the fuel cell power and the operating pressure and stoichiometry of the reactants. Four types of control factors, namely, the pressures of the fuel and oxidant and the flow rates of the fuel and oxidant, are considered to select the optimized conditions for fuel cell operation. All the four factors have two levels, leading a full factorial design requiring $24$ experiments leading to 16 experiments and fractional factorial experiments, $24−1$, leading to 8 experiments. The experimental data collected were analyzed by statistical sensitivity analysis by checking the effect of one variable parameter on the other. The mixed interaction between the factors was also considered along with main interaction to explain the model developed using the design of experiments. The robust design condition for maximum fuel cell performance was found to be air flow rate, and the interaction between the air pressure and flow rate compared to all other factors and their interactions. These fractional factorial experiments, presently applied to fuel cell systems, can be extended to other ranges and factors with various levels, with a goal to minimize the variation caused by various factors that influence the fuel cell performance but with less number of trials compared to full factorial experiments.

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