Detection and Quantification of Over-Humidification in Polymer Electrolyte Fuel Cells: Insights into Simulation, Imaging, and Sensors

Abstract

Over-humidification is a critical challenge to the performance and durability of polymer electrolyte fuel cells (PEFCs). This review evaluates current methods for detecting and quantifying over-humidification, focusing on simulation, imaging, and sensor technologies. Each method is assessed based on five key criteria: precision, sensitivity, real-time capability, interpretation complexity, and validation strength. Physically grounded modeling approaches such as computational fluid dynamics and the lattice Boltzmann method offer high accuracy but are computationally demanding. Imaging techniques, including neutron imaging and magnetic resonance imaging, provide valuable insight and validation but face limitations regarding scalability and real-time application. Sensor technologies, from commercial sensors to artificial intelligence–enhanced and nanostructured platforms, enable real-time monitoring but require improved robustness and validation under operando conditions. By comparing these techniques individually and collectively, this review identifies promising hybrid strategies and outlines research priorities for achieving intelligent, real-time water management in PEFCs.