High temperature proton exchange membrane fuel cells (HT-PEMFCs) are one type of
promising energy device with the advantages of fast reaction kinetics (high energy …

Artificial neural networks (ANN) provide a range of powerful new techniques for solving
problems in sensor data analysis, fault detection, process identification, and control and …

Fault diagnosis and durability of Polymer Electrolyte Fuel Cells (PEFCs) have been
identified among the critical issues that need to be overcome for a commercial viability of …

Two data-driven models are presented to predict and analyze the performance of a PEM fuel
cell operating on pure oxygen that can be used as an effective power source for air …

In this work, a three-dimensional half-cell model for a 50 cm2 high temperature
polyelectrolyte membrane fuel cell (HTPEMFC) has been implemented in a Computational …

Polymer electrolyte membrane (PEM) fuel cells produce water as a byproduct, which, if not
properly managed, will cause electrode “flooding” and consequently performance loss …

Fuel cells are expected to soon become a source of low-to zero-emission power generation
for applications in portable technologies and electric vehicles. Allowing development of high …

In this work, the feasibility of a 150 cm 2 high-temperature proton exchange membrane fuel
cell (HT-PEMFC) stack operated with modified proton exchange membranes is …

Artificial neural networks (ANNs) are comparatively straightforward to understand and use in
the analysis of scientific data. However, this relative transparency may encourage their use …

The modeling of fuel cells requires the coupling of fluid transport with electro-chemical
reactions. There are two approaches commonly used. Firstly, the electrodes can be treated …