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Experimental parameter uncertainty in PEM fuel cell modeling. Part II: Sensitivity analysis and importance ranking
Applied Physics · Submitted 25 Nov 2018
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim The top five in this list are, in this order: The membrane hydration isotherm, the electro-osmotic drag coefficient, the membrane thickness, the water diffusivity in the ionomer and its ionic conductivity.
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The abstract, sentence by sentence
Numerical modeling of proton exchange membrane fuel cells is at the verge of becoming predictive. A crucial requisite for this, though, is that material properties of the membrane-electrode assembly and their functional dependence on the conditions of operation are known with high precision. In this bipartite paper series we determine the most critical transport parameters for which accurate experimental characterization is required in order to enable the simulation of fuel cell operation with sufficient confidence from small to large current densities. In Part II, we employ the two-phase model developed in Part I to carry out extensive forward uncertainty propagation analyses. These include the study of local parameter sensitivity in the vicinity of a baseline parameter set, and a global sensitivity analysis in which a broad range of operating conditions and material properties is covered. A comprehensive ranking list of model parameters is presented, sorted by impact on predicted fuel cell properties such as the current-voltage characteristics and water balance. The top five in this list are, in this order: The membrane hydration isotherm, the electro-osmotic drag coefficient, the membrane thickness, the water diffusivity in the ionomer and its ionic conductivity.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | Numerical modeling of proton exchange membrane fuel cells is at the verge of becoming predictive. | background 1.00 | 0.06 | 0.02 | asserted 0.93 |
| s1 | A crucial requisite for this, though, is that material properties of the membrane-electrode assembly and their functional dependence on the conditions of operation are known with high precision. | background 0.77 | 0.06 | 0.04 | asserted 1.00 |
| s2 | In this bipartite paper series we determine the most critical transport parameters for which accurate experimental characterization is required in order to enable the simulation of fuel cell operation with sufficient confidence from small to large current densities. | contribution 0.98 | 0.87 | 0.15 | asserted 1.00 |
| s3 | In Part II, we employ the two-phase model developed in Part I to carry out extensive forward uncertainty propagation analyses. | method 0.93 | 0.91 | 0.03 | asserted 1.00 |
| s4 | These include the study of local parameter sensitivity in the vicinity of a baseline parameter set, and a global sensitivity analysis in which a broad range of operating conditions and material properties is covered. | method 0.91 | 0.92 | 0.05 | asserted 0.98 |
| s5 | A comprehensive ranking list of model parameters is presented, sorted by impact on predicted fuel cell properties such as the current-voltage characteristics and water balance. | result 0.63 | 0.93 | 0.39 | asserted 1.00 |
| s6 | The top five in this list are, in this order: The membrane hydration isotherm, the electro-osmotic drag coefficient, the membrane thickness, the water diffusivity in the ionomer and its ionic conductivity. | result 1.00 | 0.92 | 0.71 | asserted 1.00 |
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Original abstract
Numerical modeling of proton exchange membrane fuel cells is at the verge of becoming predictive. A crucial requisite for this, though, is that material properties of the membrane-electrode assembly and their functional dependence on the conditions of operation are known with high precision. In this bipartite paper series we determine the most critical transport parameters for which accurate experimental characterization is required in order to enable the simulation of fuel cell operation with sufficient confidence from small to large current densities. In Part II, we employ the two-phase model developed in Part I to carry out extensive forward uncertainty propagation analyses. These include the study of local parameter sensitivity in the vicinity of a baseline parameter set, and a global sensitivity analysis in which a broad range of operating conditions and material properties is covered. A comprehensive ranking list of model parameters is presented, sorted by impact on predicted fuel cell properties such as the current-voltage characteristics and water balance. The top five in this list are, in this order: The membrane hydration isotherm, the electro-osmotic drag coefficient, the membrane thickness, the water diffusivity in the ionomer and its ionic conductivity.
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