Adaptive extended kalman filter for PEMFC membrane water content estimation.

Proton Exchange Membrane Fuel Cells are a favorite technology for decarbonizing the transportation sector. However, their large-scale democratization is hampered by their high cost compounded by their unsatisfactory lifespan. To anticipate potential degradation while keeping improving performance, it is essential to maintain an acceptable humidity range inside the cells, especially at the membrane level. However, membrane humidity level is not directly measurable, alternative techniques must be considered to recover this key variable. Here, we develop a real-time software sensor of the membrane water content at the fuel cell's heart. We build a model describing the membrane water balance, electrochemical behavior, and species mass balance. We then reduce the model and perform an Adaptive Extended Kalman Filter. We perform sensitivity analyses in both steady-state and transient conditions. We validate the filter on a "Worldwide Harmonized Light Vehicles Test Cycles" test procedure. Finally, we obtain a fast and accurate model-based software sensor. • Real-time capable software sensor for PEMFC membrane water content. • Observer based on membrane model accounting for most of major transport phenomena. • Adaptive Extended Kalman filter applied to differential-algebraic equations. • Sensitivity analysis of membrane water content shows a 5% coefficient of variation.<textboxend⟩. [ABSTRACT FROM AUTHOR]