Multi-layer diffusion model and error analysis applied to chamber-based gas fluxes measurements

Direct and inverse neural networks model

Direct and inverse neural networks modelling applied to study the influence of the gas diffusion layer properties on PBI-based PEM fuel cells

✍ Justo Lobato; Pablo Cañizares; Manuel A. Rodrigo; Ciprian-George Piuleac; Silvia 📂 Article 📅 2010 🏛 Elsevier Science 🌐 English ⚖ 577 KB

This article shows the application of a very useful mathematical tool, artificial neural networks, to predict the fuel cells results (the value of the tortuosity and the cell voltage, at a given current density, and therefore, the power) on the basis of several properties that define a Gas Diffusion