Development of a multi-physical 2-D model of PEM fuel cell for real-time control

International audienceIn this paper, a two-dimensional modeling approach for a proton exchange membrane fuel cell (PEMFC) for real-time control implementation. The proposed model considers multi-physical domains in both electrochemical and fluidic. The developed 2-D model considers in particular the fuel cell flow field geometric form. The characteristics of reactant gas flow in the serpentine pipeline and diffusion phenomena through the gas diffusion layer (GDL) are thoroughly considered in the proposed model, based on which the spatial quantity distribution can be further obtained in real-time, for example the current density distribution. An implicit iterative solver has been developed and implemented in C language in real-time processor for real-time control purpose. The developed real-time model is then experimentally validated using a 1.2kW Ballard NEXA 47-cells PEMFC system. The practical feasibilities for real-time model-based diagnostic of PEMFC have been demonstrated by experimental results

Development of a Multi-physical 2-D model of PEM Fuel Cell for Real-Time Control

International audienceThis paper presents a computationally efficient 2-D steady-state model for fuel cell real-time control implementation. Both the fluid and electrochemical physical domains are considered in the proposed real-time model. The fuel cell under-rib convection is fully described by considering the geometry of serpentine channel. In addition, in order to solve the implicit activation voltage loss, and further explore the computational performance, three numerical root-searching algorithms: bisection, secant and Newton-Raphson methods are respectively applied to the proposed implicit iterative solver and compared. The preferred secant method has been proven to effectively improve both the efficiency and robustness performance of the proposed real-time fuel cell model. Moreover, a CFD-based COMSOL fuel cell model is used to validate the calculation accuracy. Furthermore, the practical feasibility of the presented real-time model has been verified using a RT-LAB simulator platform from Opal-RT