Development of new test instruments and protocols for the diagnostic of fuel cell stacks

In the area of fuel cell research, most of the experimental techniques and equipments are still devoted to the analysis of single cells or very short stacks. However, the diagnosis of fuel cell stacks providing significant power levels is a critical aspect to be considered for the integration of fuel cell systems into real applications such as vehicles or stationary gensets. In this article, a new instrument developed in-lab is proposed in order to satisfy the requirements of electrochemical impedance studies to be led on large FC generators made of numerous individual cells. Moreover, new voltammetry protocols dedicated to PEMFC stack analysis are described. They enable for instance the study of membrane permeability and loss of platinum activity inside complete PEMFC assemblies. Keywords: PEMFC; Stack; Characterization; Electrochemical Impedance Spectroscopy; Cyclic Voltammetry; Linear Sweep Voltammetry

Experiments of a twenty cell PEFC operating under fault conditions with diode by-pass circuit for uninterrupted power delivery

International audienceThe work presents the results of experiments related to the electrical and dynamical behaviour of a 500W, twenty cell Polymer Electrolyte Fuel Cell (PEFC) stack operated under fault condition and connected to an anti-parallel diode acting as a by-pass. The stack is placed in an experimental set-up that reproduces the electrical coupling in series of two fuel cells. The results allow the evaluation of the by-pass diode solution in the case of specific degraded working modes such as the break of the gas reactant feeding. The experiments presented in this article constitute an extrapolation and a complementary investigation of the preliminary results already achieved on a two cell PEFC stack and which had demonstrated the capability of the reverse diode to electrically isolate a fuel cell stack under fault. The proposed experiments focus on the dynamic behaviour of the stack under degraded working modes and point out the key-role of the fuel cell stack impedance in the triggering of the anti-parallel diode switching

Fuel cells static and dynamic characterizations as tools for the estimation of their ageing time

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

Dynamic modeling of hydrogen desorption from a metal hydride tank using the electrical fluidic analogy

WHEC 2016, World Hydrogen Energy Conference, Saragosse, ESPAGNE, 13-/06/2016 - 16/06/2016International audienceThe current work presents a modeling study of the thermal behavior during discharge of a hydride hydrogen tank. In a thermal coupling between a fuel cell and its associated hydride hydrogen tank, the hydrogen desorption kinetics depends on temperature, nature of the hydride, the tank design, but also on the hydrogen demand from the fuel cell in terms of mass flow and pressure. The objective of the study is to demonstrate the dynamic response of hydrogen discharge from a metal hydride tank by using the fluidic electrica

Proton exchange membrane fuel cell operation and degradation in short-circuit

This paper presents an experimental study dealing with operation and degradation during an electrical short circuit of a proton exchange membrane fuel cell stack. The physical quantities in the fuel cell (electrical voltage and current, gas stoichiometry, pressures, temperatures and gas humidity) are studied before, during and after the failure. After a short circuit occurs, a high peak of current appears but decreases to stabilize in a much lower value. The voltage drops in all the cells and even some cells presents reversal potentials. The degradation is quantified by using electrochemical impedance spectroscopy

Study of temperature, air dew point temperature and reactant flow effects on PEMFC performances using electrochemical spectroscopy and voltammetry techniques

A single PEMFC has been operated by varying the assembly temperature, the air dew point temperature and the anode/cathode stoichiometry rates with the aim to identify the parameters and combinations of factors affecting the cell performance. Some of the experiments were conducted with low humidified reactants (relative humidity of 12%). The FC characterizations tests have been conducted using in-situ electrochemical methods based on load current and cell voltage signal analysis, namely: polarization curves, EIS measurements, cyclic and linear sweep voltammetries (CV and LSV). The impacts of the parameters on the global FC performances were observed using the polarization curves whereas EIS, CV and LSV test results were used to discriminate the different voltage loss sources. The test results suggest that some parameter sets allow maximal output voltages but can also induce material degradation. For instance, higher FC temperature and air flow values can induce significant electrical efficiency benefits, notably by increasing the reversible potential and the reaction kinetics. However, raising the cell temperature can also gradually dry the FC and increase the risk of membrane failure. LSV has also shown that elevated FC temperature and relative humidity can also accelerate the electrolyte degradation (i.e. slightly higher fuel crossover rate) and reduce the lifetime consequently. PEMFC; Characterization; Electrochemical Impedance Spectroscopy; Cyclic Voltammetry; Linear Sweep Voltammetr

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks encountered by the deployed systems will not be limited to the original training context, and systems will instead need to adapt to novel distributions and tasks while deployed. This critical gap may be addressed through the development of "Lifelong Learning" systems that are capable of 1) Continuous Learning, 2) Transfer and Adaptation, and 3) Scalability. Unfortunately, efforts to improve these capabilities are typically treated as distinct areas of research that are assessed independently, without regard to the impact of each separate capability on other aspects of the system. We instead propose a holistic approach, using a suite of metrics and an evaluation framework to assess Lifelong Learning in a principled way that is agnostic to specific domains or system techniques. Through five case studies, we show that this suite of metrics can inform the development of varied and complex Lifelong Learning systems. We highlight how the proposed suite of metrics quantifies performance trade-offs present during Lifelong Learning system development - both the widely discussed Stability-Plasticity dilemma and the newly proposed relationship between Sample Efficient and Robust Learning. Further, we make recommendations for the formulation and use of metrics to guide the continuing development of Lifelong Learning systems and assess their progress in the future.Comment: To appear in Neural Network

An Open Resource for Non-human Primate Imaging.

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets

Fuel cell diagnosis based on stack voltage multifractal analysis. The question of the method portability

Battery Tech 2016, Dubaï, EMIRATS ARABES UNIS, 08-/12/2016 - 09/12/2016In the era of renewable and clean energies, the demand for less polluting energy generation technologies has increased rapidly. Among these technologies, the Proton Exchange Membrane Fuel Cell (PEMFC) receives much attention, as it can convert the hydrogen chemical energy into electricity with high efficiency, and also produce water and heat. However, to make this technology commercially viable, some challenges still remain. Especially the extension of the fuel cell lifespan and reliability are identified as major concerns in the research and industry sectors. The lifetime and reliability objectives can notably be achieved by implementing a diagnosis tool capable of high performances, whatever the stack design and the operating environment. In this context, we propose a new tool based on the investigation of singularity measurements stamped in fuel cell stack voltage signals. Indeed, measuring local singularities on voltage signals provides suitable information about the evolving dynamics of non-stationary and non-linear processes involved in fuel cell systems. In our study, two PEMFC stacks are experimented to evaluate the portability of our diagnosis tool. The first one is an 8 cell stack designed for automotive applications and manufactured by CEA LITEN, France. The second one is an 12 cell stack dedicated to stationary application (micro combined heat and power - µCHP application). It is designed and marketed by Riesaer Brennstoffzellentechnik GmbH and Inhouse Engineering GmbH, Germany. The steps of our diagnosis strategy are the following ones: - Two PEMFC stacks are operated under a variety of conditions (nominal, and faults i.e. more or less severe deviations from the nominal conditions) using characterization testbenches developed in lab. The deviations from the nominal conditions refer either to single fault types or to combinations of different faults. - The recorded stack voltages are analyzed using a Wavelet Leader based Multifractal Analysis (WLMA) in order to identify their singularity spectra as fault signatures. - A feature selection method is used to select the most relevant singularity features and to remove the redundant ones. - The selected singularity features are classified using Support Vector Machine (SVM) classifier according to the considered operating situations (faults and combinations of faults). The obtained results show that the proposed PEMFC diagnosis tool allows identifying simple operating failures and even more complicated situations that contain several failure types, for different stack sizes, powers and technologies for different power application environments. Framework of the 'Decentralized energy production' project, directed by EFFICACITY, the French R&D Institute for urban energy transition