PEM fuel cell fault detection and identification using differential method: simulation and experimental validation
نویسندگان
چکیده
PEM fuel cell performance and lifetime strongly depend on the polymer membrane and MEA hydration. As the internal moisture is very sensitive to the operating conditions (temperature, stoichiometry, load current, water management. . . ), keeping the optimal working point is complex and requires real-time monitoring. This article focuses on PEM fuel cell stack health diagnosis and more precisely on stack fault detection monitoring. This paper intends to define new, simple and effective methods to get relevant information on usual faults or malfunctions occurring in the fuel cell stack. For this purpose, the authors present a fault detection method using simple and non-intrusive on-line technique based on the space signature of the cell voltages. The authors have the objective to minimize the number of embedded sensors and instrumentation in order to get a precise, reliable and economic solution in a mass market application. A very low number of sensors are indeed needed for this monitoring and the associated algorithm can be implemented on-line. This technique is validated on a 20-cell PEMFC stack. It demonstrates that the developed method is particularly efficient in flooding case. As a matter of fact, it uses directly the stack as a sensor which enables to get a quick feedback on its state of health.
منابع مشابه
Water Management in the Cathode Side of a PEM Fuel Cell
A one dimensional isothermal mathematical modeling of cathode side of a Proton Exchange Membrane (PEM) fuel cell is developed for the water management problem. Water transport is investigated in both cathode Gas Diffusion Layer (GDL) and membrane through solving appropriate equations for fluid flow and mass transport in GDL and water transport within the membrane. The gaseous mixture flowing in...
متن کاملFault Detection and Isolation using RBF Networks for Polymer Electrolyte Membrane Fuel Cell
This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC s...
متن کاملFault Detection and Isolation using RBF Networks for Polymer Electrolyte Membrane Fuel Cell
This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC s...
متن کاملFinite Element Simulation and ANFIS Prediction of Dimensional Error Effect on distribution of BPP/GDL Contact Pressure in PEM Fuel Cell
Distribution of contact pressure between the bipolar plate and gas diffusion layer considerably affect the performance of proton exchange membrane fuel cell. In this regard, an adaptive neuro-fuzzy inference system (ANFIS) is developed to predict the contact pressure distribution on the gas diffusion layer due to dimensional errors of the bipolar plate ribs in a proton exchange membrane fuel ce...
متن کاملNear-Optimal Controls of a Fuel Cell Coupled with Reformer using Singular Perturbation methods
A singularly perturbed model is proposed for a system comprised of a PEM Fuel Cell(PEM-FC) with Natural Gas Hydrogen Reformer (NG-HR). This eighteenth order system is decomposedinto slow and fast lower order subsystems using singular perturbation techniques that provides tools forseparation and order reduction. Then, three different types of controllers, namely an optimal full-order,a near-opti...
متن کامل