Development of a novel computational tool for optimizing the operation of fuel cells systems: Application for phosphoric acid fuel cells

Zervas, Panagiotis; Tatsis, A. G.; Sarimveis, Haralambos; Markatos, N.C.

doi:10.1016/j.jpowsour.2008.06.081

Cited by 21 publications

(1 citation statement)

References 13 publications

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“…Wu et al [14] employed a multi-resolution approach and the radial basis function (RBF) surrogate model for simulation and optimization of operating conditions for hydrogen polymer electrolyte fuel cells. Zervas et al [15] performed a phosphoric acid fuel cell (PAFC) system optimization study based on meta-models that were derived by applying the linear regression and the RBF neural network methodology on the results produced by a CFD model. The optimization of different operating and design parameters on PEMFC using the Taguchi method was performed by Karthikeyan et al [16], Solehati et al [17], and Sasmito et al [18].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Membrane Electrode Assembly of PEM Fuel Cell by Response Surface Method

Vuppala

Chaedir²,

Jiang

et al. 2019

Molecules

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The membrane electrode assembly (MEA) plays an important role in the proton exchange membrane fuel cell (PEMFC) performance. Typically, the structure comprises of a polymer electrolyte membrane sandwiched by agglomerate catalyst layers at the anode and cathode. Optimization of various parameters in the design of MEA is, thus, essential for reducing cost and material usage, while improving cell performance. In this paper, optimization of MEA is performed using a validated two-phase PEMFC numerical model. Key MEA parameters affecting the performance of a single PEMFC are determined from sensitivity analysis and are optimized using the response surface method (RSM). The optimization is carried out at two different operating voltages. The results show that membrane thickness and membrane protonic conductivity coefficient are the most significant parameters influencing cell performance. Notably, at higher voltage (0.8 V per cell), the current density can be improved by up to 40% while, at a lower voltage (0.6 V per cell), the current density may be doubled. The results presented can be of importance for fuel cell engineers to improve the stack performance and expedite the commercialization.

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