A parallel Seq2Seq neural architecture for long-horizon performance forecasting and online condition monitoring of fuel cells

Solid Oxide Fuel Cells (SOFCs) are efficient and environmentally friendly power generation technologies that have seen increasing applications in recent years. However, their material instability at high operating temperatures makes them susceptible to degradation and unexpected failures. This demands developing robust monitoring algorithms to predict the onset of degradation, thereby facilitating…