The amount of current density produced by the stack is the key performance parameter for a fuel cell, given a well-defined quantity of reactants flowing through it. A Proton Exchange Membrane fuel cell (PEMFC) distributed parameters model is considered with all the aspects influencing the cell behavior. A sensitivity analysis is performed through a Monte Carlo Simulation to assess the impact on performances of key parameters. The Pareto plot obtained from such analysis allow to operate design variables reduction, aimed to those parameters that show small impact, so to decrease the problem complexity through an increased orthogonality of the input design matrix. The target of the activity is to obtain and validate a method able to reduce the time needed for a complete simulation, so to be able to realize an effective multi-disciplinary design optimization.

Sensitivity Analysis for a PEM Fuel Cell Model aimed to Optimization / Testa, Enrico; Maggiore, Paolo; Pace, Lorenzo; DALLA VEDOVA, MATTEO DAVIDE LORENZO. - In: WSEAS TRANSACTIONS ON POWER SYSTEMS. - ISSN 1790-5060. - 10:(2015), pp. 171-179.

Sensitivity Analysis for a PEM Fuel Cell Model aimed to Optimization

TESTA, ENRICO;MAGGIORE, Paolo;PACE, LORENZO;DALLA VEDOVA, MATTEO DAVIDE LORENZO
2015

Abstract

The amount of current density produced by the stack is the key performance parameter for a fuel cell, given a well-defined quantity of reactants flowing through it. A Proton Exchange Membrane fuel cell (PEMFC) distributed parameters model is considered with all the aspects influencing the cell behavior. A sensitivity analysis is performed through a Monte Carlo Simulation to assess the impact on performances of key parameters. The Pareto plot obtained from such analysis allow to operate design variables reduction, aimed to those parameters that show small impact, so to decrease the problem complexity through an increased orthogonality of the input design matrix. The target of the activity is to obtain and validate a method able to reduce the time needed for a complete simulation, so to be able to realize an effective multi-disciplinary design optimization.
2015
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2614593
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