Modelling polymer electrolyte membrane fuel cells for dynamic reliability assessment

Tackling climate change is arguably the biggest challenge humanity faces in the 21st century. Rising average global temperatures threaten to destabilize the fragile ecosystem of the Earth and bring unprecedented changes to human lives if nothing is done to prevent it. This phenomenon is caused by the anthropogenic greenhouse effect due to the increasing atmospheric concentrations of carbon dioxide (CO2). One way to avert the disaster is to drastically reduce the consumption of fossil fuels in all spheres of human activities, including transportation. To do this, research and development of electric vehicles (EVs) to make them more efficient, reliable and accessible is essential. [Continues.

Investigation of an indicator for on-line diagnosis of polymer electrolyte membrane (PEM) fuel cell flooding using model based techniques

The durability and reliability of producing high quality power for long periods of time have the potential to be the leading marketing factors for future hydrogen and fuel cell power sources. In the past few decades, several researchers have been devoted to investigating diagnostic techniques for fuel cell systems. However, in commercial fuel cell applications, on-line diagnosis is urgently required so that fuel cell degradation can be detected at its early stage, and mitigation strategies can be performed to recover fuel cell performance. In this paper, on-line diagnosis of fuel cell flooding is investigated. For this purpose, a generalised fuel cell stack model is developed, and water mass balance equations are used to study water balance inside the fuel cell stack. Moreover, with these equations, the flooding indicator is proposed and its relationship with liquid water inside the stack is evaluated. Results demonstrate that the proposed indicator is sensitive to the liquid water in the stack, thus can be used for flooding diagnosis. Furthermore, the expectation of the proposed indication in the cell flooding case is also presented. The advantage of this method is that parameters in the flooding indicator can be determined with measurements from tests, thus quick diagnosis can be made during the practical fuel cell operation

Model-based fault detection and isolation of PEM fuel cells using Bond Graphs

Polymer Electrolyte Membrane (PEM) fuel cell powered vehicles are only beginning to enter the automotive market and currently significantly more expensive than conventional vehicles. Therefore it is important to reduce their manufacturing and maintenance costs in order to secure their position and aid with market penetration. Improved durability and reliability of PEM fuel cells is crucial to cost reduction and can be achieved via implementation of effective control strategies. Such control algorithms will incorporate accurate Fault Detection and Isolation (FDI) procedures to ensure system robustness and fault tolerance. This ongoing research project is focused on model-based FDI for fuel cells with qualitative diagnosis using Bond Graphs (BG). BG is a graphical modelling approach which represents interactions between system components as exchanges of energy across multiple physical domains. A bond graph model of a PEM fuel cell is introduced in this paper and its application to FDI is considered