Nouveau mode de représentation graphique de l'équilibre calco-carbonique Application au traitement des eaux

Cet article traite des problèmes liés à l'étude des équilibres calco-carboniques en limitant leur présentation à l'aspect purement graphique. Dans cette optique, on a développé un nouvel abaque original en choisissant comme coordonnées pH et [CO3 total].La construction d'un tel abaque ne fait appel qu'à 2 lois fondamentales, à savoir : a) la relation du produit de solubilité du carbonate calcique :Ks=Y22[Ca2+[CO2-3]Cette dernière peut, moyenant l'introduction d'une variable auxiliaire :∆=[Ca2+]-[CO3 total]se transformer en une relation équivalente plus commode pour le calcul des courbes constitutives de l'abaque.b) une deuxième relation, prenant en compte les ions H+ soit libres, soit engagés dans des combinaisons avec le groupe carbonate ou avec le solvant H2 O. Dans ce but, on introduit une concentration totale appelée acidité potentielle totale (en abrégé APT) définie de la sorte :APT=2[H2CO3]+[HCO-3]+[H2O]+[H+]En outre, on utilise une variable dérivée de APT à laquelle on a donné le nom d'acidité potentielle carbonatée et le symbole. Sa définition est la suivante :δ=2[H2CO3]+[HCO-3]Les 2 variables et APT jouissent en commun de la propriété intéressante de rester invariantes lors de la mise en équilibre de l'eau selon l'équation :CaCO3+H+⇌Ca2++HCO-3La variable peut également être considérée comme pratiquement invariante dans le domaine des eaux naturelles.Cette propriété est mise à profit pour construire 2 réseaux de courbes constitutives de l'abaque, à savoir :a) celles satisfaisant à la condition : APT=constante. Ces dernières seront appelées "courbes d'iso-aciditéb) celles répondant à la condition : ∆=constante.On les désignera sous le nom de "courbes d'iso-équilibre"L'article s'attache à décrire le mode d'utilisation de cet abaque tout en mettant en valeur sa facilité d'emploi pour l'évaluation, tant qualitative que quantitative du comportement d'une eau à l'égard du carbonate calcique.En particulier, la technique permet de visualiser les caractéristiques essentielles de l'eau telles que pH équilibrant, pH stabilisant et indice de stabilisation, caractéristiques dont la signification est précisée dans l'article.L'abaque en question, en parallèle avec un logiciel qui peut lui être associé, constitue ainsi un outil précieux tant pour caractériser une eau que pour procéder ensuite aux traitements chimiques les plus connus.Le cas du mélange d'eaux peut également être avantageusement traité par le biais de cet abaque. De nombreux exemples d'application aux traitements de l'eau sont également largement développés dans la publication. Ceux-ci devraient aider grandement ceux qui sont confrontés aux divers problèmes de l'industrie de l'eau.L'analyse graphique constitue par ailleurs une excellente introduction à la gestion informatisée plus complète de ces problèmes et dont le traitement ne pouvait trouver place dans le cadre limité de cette publication.Le lecteur désireux de poursuivre ces développements ou d'avoir accès au programme informatique complémentaire à cette étude, trouvera les indications nécessaires dans les références bibliographiques figurant en fin de l'article.Although many good methods exist for computing calcium-carbonate equilibria, we considered that it was still possible to improve the representation to the problem and for this reason we have developed a new method of calculation. In this paper we have restricted ourselves to the graphical aspect of the question, referring the reader to the original bibliography at the end of the paper and as well we have not taken into account the kinetic aspects of the reactions involving the dissolution or precipitation of CaCO3.From this perspective, an original graph has been designed choosing for co-ordinates the pH (abscissa) and [CO3 total] (ordinate). The construction of such a graph requires only two fundamental laws, i.e.1) The solubility product relationship of calcium carbonate. This relationship, with the introduction of an auxiliary variable:∆=[Ca2+] - [CO3 total]can be transformed itself into an équivalent relationship, more convenient for the computation of the various curves composing the graph.2) A second relationship, taking into account the H+-ions in their free or bound state (with the C03 group or the H20 solvent). For this purpose, one introduces a total concentration, called potential total acidity (in abbreviated form PTA), the définition of which is:PTA=2[H2CO3]+[HCO-3]+[H2O]+[H+]In addition, one uses also another variable derived from PTA to which we gave the name : carbonated potential acidity with the following definition:δ=2[H2CO3]+[HCO-3]Both variables PTA and ∆ have jointly the interesting property of remaining constant during the evolution of the water towards equilibrium according to the equation: CaCO3+H+⇌Ca2++HCO-3The variable may also be considered as practically constant in the field of natural waters. We have taken advantage of this property to build up two networks of curves that make up the overall graph, i.e., a) the curves satisfying the condition : PTA=constant (these curves are named " iso-acidity curves "), and b) the curves whose characteristics are : =constant, and which are named " iso-equilibrium curves ".The paper describes how to use the graph and brings out its ease of use for both the qualitative and quantitative prediction of the behaviour of water in contact with calcium carbonate. In particular, the graph illustrates such essential water characteristics as equilibrium pH, stabilisation pH and stabilisation index, characteristics whose meanings are defined in the paper. The graph is shown to be a useful tool for the characterisation of waters as well as for the evaluation of most chemical treatments. The case of the mixture of different waters is also treated. Numerous examples for using the graph under different circumstances are developed in the paper, which should be useful for those whose job is connected with industrial water treatment. The graphical method here described, in conjunction with an associated computer programme, also constitutes an excellent introduction to the more complete computing methods developed elsewhere but which could not be treated in the limited frame of this publication.The graph turns out to be a useful tool for the characterisation of waters as well as for the evaluation of different chemical treatments, such as softening, carbonation, decarbonation, acidification, alkalinisation, aeration, etc. The case of the mixture of different waters is also treated. Numerous examples for using the graph under different circumstances are developed. The paper shows how it is possible, on the basis of the diagram, to predict the evolution of the water when different reagents are added, when the temperature changes or when one mixes different waters. The diagram should be a useful aid for those people whose job is connected with industrial water treatment.A computing program is necessary to draw the curves, to obtain the water characteristics with a better accuracy than can be read from the graphs. This programme, named Carbeq+, is commercially available (see below for the bibliographical reference). The values necessary for the computation and the drawing of the curves are :1. temperature of analysis and temperature of computation2. pH, alkalinity, calcium concentration3. the ionic strength, which can be calculated either from the knowledge of the complete analysis of the water, or if that one is not available, by using an empirical relation based on either the conductivity or the salt content. The program computes then the equilibrium pH, the stabilisation pH and the stabilisation index and draws the graphs described in the paper. The graphical method here described, in conjunction with the associated computer programme, constitutes also an excellent introduction to the more complete computing methods developed elsewhere but which could not be treated in the limited frame of this publication. Note that the case of the influence of the gaseous carbon dioxide phase on the equilibrium is not treated in this paper, but it is taken into account in the Carbeq+ programme mentioned above

Nonlinear predictive control for durability enhancement and efficiency improvement in a fuel cell power system

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/In this work, a nonlinear model predictive control (NMPC) strategy is proposed to improve the efficiency and enhance the durability of a proton exchange membrane fuel cell (PEMFC) power system. The PEMFC controller is based on a distributed parameters model that describes the nonlinear dynamics of the system, considering spatial variations along the gas channels. Parasitic power from different system auxiliaries is considered, including the main parasitic losses which are those of the compressor. A nonlinear observer is implemented, based on the discretised model of the PEMFC, to estimate the internal states. This information is included in the cost function of the controller to enhance the durability of the system by means of avoiding local starvation and inappropriate water vapour concentrations. Simulation results are presented to show the performance of the proposed controller over a given case study in an automotive application (New European Driving Cycle). With the aim of representing the most relevant phenomena that affects the PEMFC voltage, the simulation model includes a two-phase water model and the effects of liquid water on the catalyst active area. The control model is a simplified version that does not consider two-phase water dynamics.Peer ReviewedPostprint (author's final draft

Predicting the Remaining Useful Lifetime of a Proton Exchange Membrane Fuel Cell using an Echo State Network

International audienceOne remaining technological bottleneck to develop industrial Fuel Cell (FC) applications resides in the system limited useful lifetime. Consequently, it's important to develop failure diagnostic and prognostic tools enabling the optimization of FC. The Prognostic and Heath Management (PHM) is a discipline involved in the process of industrial maintenance. The objective, in PHM, is to estimate the Remaining Useful Life (RUL) of a system by predicting its future behavior. The RUL enables to predict the moment when a fault could occur on a system. It also allows identifying the relevant part of the system where a fault could happen. Then, a preventive maintenance could be performed to avoid non-reversible degradations. Three main prognosis approaches can be distinguished: model-based, data-based and hybrid methods. Data-based methods such as Artificial Neural Network (ANN), aim to estimate the ageing behavior of the process without specific knowledges related to the physical system phenomenon. Nevertheless, the deployment of such an approach can be a tedious work, mainly due to the trial and error algorithm method, which represents a real problem for industrial applications where real-time complying algorithms must be developed. Among the various methods of this area, the tool chosen here is called Echo State Network (ESN). An ESN consists in the use of a dynamical neurons reservoir where the training step consists in performing a linear regression. The computation time of this algorithm is thus shorter while keeping the same modeling capability of a Recurrent Neural Network (RNN). Created in 2001 by H. Jaeger, an ESN proposes a better human brain paradigm than traditional ANN, and are based on a reservoir of neurons randomly connected to each other. The aim of this paper is to study the application of ESN as a prognostics system enabling the estimation of the Remaining Useful Life of a Proton Exchange Membrane Fuel Cell using an iterative predictive structure, which is the most common approach performing a one-step prediction. This estimation output value is used in the next step as one of the input regressor and these operations can be repeated until the desired prediction horizon. The results obtained thanks to this method exhibits good prediction and they will be detailed in this paper

Tolérance aux défauts de type court-circuit d'interrupteurs de puissance en SiC utilisés dans un convertisseur DC/DC entrelacé

International audienceL'optimisation de la fiabilité des convertisseurs DC-DC est cruciale pour que la chaine de traction d'un véhicule à pile à combustible puisse fournir, sans interruption, la puissance énergétique demandée par la charge. Pour atteindre cet objectif, un algorithme de détection du défaut est requis afin de l'identifier et le localiser avant que ses effets ne causent l'arrêt du système. Les composants, passifs ou actifs, qui constituent les convertisseurs statiques sont l'une des sources à l'origine de ces défauts. Dans cet article, le défaut de type court-circuit d'interrupteurs de puissance est considéré et un contrôle tolérant aux fautes est proposé. Une architecture modulaire est, par ailleurs, suggérée qui associe plusieurs briques génériques « Pile à Combustible + Convertisseur DC-DC » dans le but d'augmenter l'opérabilité et la disponibilité du système même en mode dégradé. Ainsi, pour améliorer d'avantage les performances du convertisseur, la technologie en carbure de silicium est adoptée

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

Data-driven diagnosis of PEM fuel cell: A comparative study

International audienceThis paper is dedicated to data-driven diagnosis for Polymer Electrolyte Membrane Fuel Cell (PEMFC). More precisely, it deals with water related faults (flooding and membrane drying) by using pattern classification methodologies. Firstly, a method based on physical considerations is defined to label the training data. Secondly, a feature extraction procedure is carried out to pick up the significant features from vectors constructed by individual cell voltages. Finally, a classification is adopted in the feature space to realize the fault diagnosis. Various feature extraction and classification methodologies are employed on a 20-cell PEMFC stack. The performances of these methodologies are compared

Remaining useful life estimates of a PEM fuel cell stack by including characterization-induced disturbances in a particle filter model.

International audienceProton Exchange Membrane Fuel Cells (PEMFC) are available for a wide variety of applications such as transportation, micro-cogeneration or powering of portable devices. However, even if this technology becomes close to competitiveness, it still suffers from too short life duration to pretend to a large scale deployment. In a perspective of a longer lifetime, prognostics aims at tracking and anticipating degradation and failure, and thereby enables deciding mitigation actions to increase life duration. Yet, the complexity of degradation phenomena in PEMFC can make prognostic implementation really tough. Indeed, a PEMFC implies multiphysics and multiscale phenomena making the construction of a physics-based aging model very complex. Moreover, prognostics should also take into account external events influencing the aging. Among them, characterization techniques such as electrochemical impedance spectroscopies and polarization curves introduce disturbances in the stack behavior, and a voltage recovery is observed at the end of characterizations process. It means that irreversible degradation and reversible decrease of performances have to be considered. This work proposes to tackle this problem by setting a prognostics system that includes disturbances' effects. We propose a hybrid prognostics approach by combining the use of empirical models and available data. In an evolving system like a fuel stack, a particle filtering framework seems to be really appropriate for life prediction as it offers the possibility to compute models with time varying parameters and to update them all along the prognostics process. Moreover, it offers a great adaptability to include characterization effects and allows giving prediction with a quantified uncertainty. The logic of the work is the following. First, it is shown that simple empirical models only taking into account the aging are very limited in terms of prognostics performances. Then, some features describing the impact of characterization on the stack behavior and aging are extracted and a more complete prognostics model is built. Finally, the new prognostic framework is used to perform remaining useful life estimation and the whole proposition is illustrated with a long term experiment data set in constant current solicitation and stable operating conditions

Fuel Cells prognostics using Echo State Network

International audienceOne remaining technological bottleneck to develop industrial Fuel Cell (FC) applications resides in the system limited useful lifetime. Consequently, it is important to develop failure diagnostic and prognostic tools enabling the optimization of the FC. Among all the existing prognostics approaches, datamining methods such as artificial neural networks aim at estimating the process' behavior without huge knowledge about the underlying physical phenomena. Nevertheless, this kind of approach needs huge learning dataset. Also, the deployment of such an approach can be long (trial and error method), which represents a real problem for industrial applications where realtime complying algorithms must be developed. According to this, the aim of this paper is to study the application of a reservoir computing tool (the Echo State Network) as a prognostics system enabling the estimation of the Remaining Useful Life of a Proton Exchange Membrane Fuel Cell. Developments emphasize on the prediction of the mean voltage cells of a degrading FC. Accuracy and time consumption of the approach are studied, as well as sensitivity of several parameters of the ESN. Results appear to be very promising