HIGHLIGHTS
- who: Safa Meraghni and collaborators from the University of Bourgogne Franche-Comte, France have published the research work: A data-driven digital-twin prognostics method for proton exchange membrane fuel cell remaining useful life prediction, in the Journal: (JOURNAL)
- what: Bourgogne Franche-Comte France. __NEWPAGE__limited due to the shortage of solutions to collect connect and control sensor data and preprocess it through efficient numerical models so that the models that are used for RUL prediction are rarely updated over time. The degradation behaviour of the PEMFC is captured by stacked autoencoders, while the online prognostics . . .
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