An artificial neural network ensemble method for fault diagnosis of proton exchange membrane fuel cell system
- 1 April 2014
- journal article
- Published by Elsevier BV in Energy
- Vol. 67, 268-275
- https://doi.org/10.1016/j.energy.2014.01.079
Abstract
No abstract availableThis publication has 18 references indexed in Scilit:
- A passive method of water management for an air-breathing proton exchange membrane fuel cellEnergy, 2013
- Water droplet accumulation and motion in PEM (Proton Exchange Membrane) fuel cell mini-channelsEnergy, 2012
- Fault tree analysis for PEM fuel cell degradation process modellingInternational Journal of Hydrogen Energy, 2011
- Diagnosis of polymer electrolyte fuel cells failure modes (flooding & drying out) by neural networks modelingInternational Journal of Hydrogen Energy, 2011
- A review of polymer electrolyte membrane fuel cell stack testingJournal of Power Sources, 2011
- Design of experiment study of the parameters that affect performance of three flow plate configurations of a proton exchange membrane fuel cellEnergy, 2010
- Fuel cells: History and updating. A walk along two centuriesRenewable and Sustainable Energy Reviews, 2009
- A Bayesian network fault diagnostic system for proton exchange membrane fuel cellsJournal of Power Sources, 2007
- Dynamic modeling of a methanol reformer—PEMFC stack system for analysis and designJournal of Power Sources, 2006
- A new dynamic model for predicting transient phenomena in a PEM fuel cell systemRenewable Energy, 2004