TABLE OF CONTENTS The modeling studies presented in the previous sections may be used to address several practical considerations such as fuel cell optimization and design under uncertainty. Despite their significances, however, little effort has been made to systematically address these issues for fuel cell systems. Two approaches were adopted by Pitchumani and coworkers to seek the optimal design and operating conditions for PEM fuel cells [32], [254]. In the first approach, a methodology is illustrated for model-based design and optimization of the operating and design parameters using a comprehensive parametric analysis on the various physical and electrochemical phenomena [32]. Specific optimization solutions were obtained by changing one of the operating or design parameters while fixing the values of the remaining ones. Alternatively, Mawardi et al. [254] provided an optimization framework to derive more general optimum solutions. Furthermore, to analyze the effects of uncertainty in the operating and design parameters on the fuel cell performance, a sampling based stochastic model was developed by Mawardi et al. [255] to predict the variability of power density of the fuel cell. The two optimization approaches and the stochastic modeling framework are discussed in Sections 4.5.1 4.5.3, respectively.
In the approach adopted by Mishra et al. [32], the optimization of a PEM fuel cell is based on systematic parametric studies and consideration of a few illustrative constraints on cell operation. A comprehensive numerical model was developed by combining a one-dimensional...
