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Belfort, France

Placca L.,FC Laboratory | Placca L.,University of Technology of Belfort - Montbeliard | Placca L.,CEA Grenoble | Kouta R.,FC Laboratory | And 7 more authors.
International Journal of Hydrogen Energy | Year: 2010

Polarisation curves performed at the Fuel Cell System Laboratory (FC LAB) at Belfort on a PEM fuel cell stack using a homemade fully instrumented test bench led to more than 100 variables depending on time. Visualising and analysing all the different test variables are complex. In this work, we show how the Principal Component Analysis (PCA) method helps to explore correlations between variables and similarities between measurements at a specific sampling time (individuals). To complete this method, an empirical model of the PEM fuel cell is proposed by linking the different input parameters to the cell voltage using Multiple Linear Regression. © 2010 Professor T. Nejat Veziroglu. Source

Placca L.,FC Laboratory | Placca L.,University of Technology of Belfort - Montbeliard | Kouta R.,FC Laboratory | Kouta R.,University of Technology of Belfort - Montbeliard
International Journal of Hydrogen Energy | Year: 2011

For transportation applications, Proton Exchange Membrane fuel cells (PEMFC) are considered to be the most promising fuel cell technology due to their low operating temperature and pressure resulting in a possible quick start-up. However, to implement them in transportation systems, their reliability should be improved. In the present work, a single fuel cell is considered. It is composed of a membrane, catalyst layers (anode and cathode electrodes) and diffusion layers (anode and cathode electrodes). Those layers are considered as the critical components of the cell. Modelling the process degradations of those components is a great issue. In this work, Fault Tree (FT) is used for this modelling for two main reasons. At first, FT helps to model clearly and intuitively the different causal relations of the degradation mechanisms. Secondly, FT allows quantifying components specific degradations, and their effects on the global degradation of the cell. The cell is considered non repairable. Degradation modelling needs knowledge about mechanisms involving components failures. For 1000 simulations of 100 h operation in cycling conditions, the results of the FT show the most important degradations effects on the global degradation of the cell. This work also proposes degradation probability estimates for some specific events. © 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved. Source

Paclisan D.,FC Laboratory | Paclisan D.,University of Technology of Belfort - Montbeliard | Charon W.,FC Laboratory | Charon W.,University of Technology of Belfort - Montbeliard
Engineering Applications of Artificial Intelligence | Year: 2013

Modelling complex dynamic mechanical systems, such as PEMFC, without any physical models is a difficult challenge but it could allow the monitoring of endurance tests of fuel cell systems. Neural networks are recognised as powerful numerical tools for predicting complex and nonlinear dynamic behaviours. They require only data limited to experimental inputs and outputs but the choice of an adapted architecture is critical. This paper presents a method for defining a neural network architecture optimised for the fuel cell systems. The associated experimental conditions specifying the vibration tests to train and validate were defined. They consist of swept sinus as well as random excitation forces. The resulting simulations are presented and analysed. © 2012 Elsevier Ltd. Source

Onanena R.,FC Laboratory | Onanena R.,University of Franche Comte | Onanena R.,INRETS | Oukhellou L.,INRETS | And 8 more authors.
International Journal of Hydrogen Energy | Year: 2011

This paper deals with a pattern-recognition-based diagnosis approach, which aim is to estimate the Fuel Cell (FC) operating time, and consequently its remaining duration life. With the method proposed, both static and dynamic information extracted from the stack (i.e. polarization curve records and Electrochemical Impedance Spectroscopy (EIS) measurements) can be used. The complete diagnosis method consists of several steps. First, features are extracted from EIS measurements and polarization curves independently. This enables us to simplify the extracted information without losing relevant information, and to remove noise. For the polarization curves, an empiric model is exploited to ensure the feature extraction. For the impedance spectra, both expert knowledge and parametric modeling are used to extract features. In particular, a latent regression model is used to split automatically the imaginary part of the spectra into several segments that are approximated by polynomials. The next step of the method consists in selecting the most relevant features from the whole set of extracted features. This helps us to estimate the operating time, while adjusting the complexity of the model. The final step of the approach is a linear regression that uses the selected subset of features to estimate the FC operating time. The performances of the proposed approach are evaluated on a dataset made up of EIS measurements and polarization curves extracted from two FC lifetime tests. A mean error of about 2 h over a global operating duration of 1000 h can be obtained. Moreover, the portability of the method is shown by considering another FC ageing test conducted on a different FC stack type. © 2010 Professor T. Nejat Veziroglu. Published by Elsevier Ltd. All rights reserved. Source

Begot S.,FC Laboratory | Begot S.,University of Franche Comte | Harel F.,FC Laboratory | Harel F.,INRETS | And 7 more authors.
Energy Conversion and Management | Year: 2010

The implementation of Fuel Cell (FC) systems in transportation systems, as aircrafts, requires some better understanding and mastering of the new generator behaviours in low temperature environments. To this end, a PEMFC stack is tested and characterised in a climatic chamber. The impacts of the low temperatures over different FC operation and start-up conditions are estimated using a specific test bench developed in-lab. Some descriptions concerning the test facilities and the experimental set-up are given in the paper, as well as some information about the test procedures applied. Some examples of test results are shown and analysed. The experiments are derived from aircraft requirements and are related with different scenarios of airplane operation. Finally, some assessments concerning the FC system behaviour in low temperature conditions are made, especially with regard to the constraints to be encountered by the next embedded FC generators. © 2010 Elsevier Ltd. All rights reserved. Source

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