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Differences between theoretical and real operating conditions can occur during fuel cell operation, which can affect the fuel cell voltage. In the aging campaign studied in this work, an atypical behavior was observed on the voltage. The aim was then to understand if the voltage drop could have been caused by differences in operating conditions throughout the test campaign. To this end, a model expressing the voltage of a fuel cell cycling a mission profile for 2030h as a function of the related operating conditions was implemented. A voltage law was tested and improved by taking into account several different sets of operating conditions. A comparison of the coefficients associated with the parameters was also carried out. The results obtained with the model convinced us that the early voltage unusual behavior seen on the aging campaign was probably not related to the operating conditions. • This paper aims to develop a fuel cell stack voltage model based on an aging campaign depending on the operating conditions. • A voltage law was developed, tested and improved by taking into account several different sets of operating conditions. • The model accuracy depended on the chosen configuration, with a better prediction when all parameters were considered. • We concluded that the early life voltage fluctuations observed were not caused by differences in operating conditions. [ABSTRACT FROM AUTHOR]

In this work, three commercially available Membrane Electrode Assemblies (MEAs) from Advent Technology Inc. and Danish Power Systems, developed for a use in High Temperature Proton Exchange Membrane Fuel Cell (HT-PEMFC), were tested under various Operating Conditions (OCs): over-stoichiometry of hydrogen gas (1.05, 1.2, 1.35), over-stoichiometry of air gas (1.5, 2, 2.5), gas oxidant (O2 or air) and temperature (140 °C, 160 °C, 180 °C). For each set of operating conditions, a polarization curve (V–I curve) was performed. A semi-empirical and macroscopic (0D) model of the fuel cell voltage was established in steady state conditions in order to model some of these experimental data. The proposed parameterization approach for this model (called here the "multi-VI" approach) is based on the sensitivity to the operating conditions specific to each involved physicochemical phenomenon. According to this method, only one set of parameters is used in order to model all the experimental curves (optimization is performed simultaneously on all curves). A model depending on air over-stoichiometry was developed. The main objective is to validate a simple (0D) and fast-running model that considers the impact of air over-stoichiometry on cell voltage regarding all commercially available MEAs. The obtained results are satisfying with AdventPBI MEA and Danish Power Systems MEA: an average error less than 1.5% and a maximum error around 15% between modelled and measured voltages with only nine parameters to identify. However, the model was not as adapted to Advent TPS® MEA: average error and maximum error around 4% and 21%, respectively. Most of the obtained parameters appear consistent regardless of the OCs. The predictability of the model was also validated in the explored domain during the sensibility study with an interesting accuracy for 27 OCs after being trained on only nine curves. This is attractive for industrial application, since it reduces the number of experiments, hence the cost of model development, and is potentially applicable to all commercial HT-PEMFC MEAs. [ABSTRACT FROM AUTHOR]

High-Temperature Proton Exchange Membrane Fuel Cell constant current ageing tests highlighted that the characterizations used to monitor the state of health of single cells could be potentially degrading. An experimental campaign to analyze potential degradation due to polarization curves was carried out. More exactly, four methodologies to generate a polarization curve including Electrochemical Impedance Spectroscopies (EIS) were cycled 30 times. The tested single cells were based on a commercial PBI Membrane Electrodes Assembly (MEA) with an active surface of 45 cm2 (BASF Celtec®-P 1100 type). Before the first cycling test and after the last cycling one, complete characterizations, composed by a voltammetry and a polarization curve including EIS, were performed. The results show that one of the MEA has a voltage which increased for one of the four methods to obtain the polarization curve. This growth is linked to a decrease of ohmic losses: in an unexpected way, it could be considered as a way to improve the break-in period. Similarly, the monitoring of CO2 emission (as corrosion has been suspected to be involved at high voltage, i.e. low current density) confirms the potential degradation of the electrodes during the measurement of the polarization curve.

In this paper, the authors face the problem of wind speed processing as environmental variable of a wind turbine system. Generally, the information on wind speed measurements is processed over long periods of time to be relevant with respect to the site characteristics (average and maximum speeds, statistics). Subsequent large scale profiles of wind speed lead to long processing time for simulation analysis and especially for optimization design that penalises the search of optimal solutions. An original synthesis approach of a compact and representative wind speed profile using an Evolutionary Algorithm (EA) is proposed. This approach is compared to a purely statistical approach based on random number generators. It allows reducing the actual wind profile duration with compression ratios greater (two months of wind speed measurements are compressed in only 1 h). Then, the synthesis approach by EA is applied to the sizing of an autonomous hybrid system based on wind turbine with battery storage for stand-alone energy systems. It has proven its effectiveness in reducing 200 days of wind speed measurements in only 10 days, allowing sizing the storage system with a significant gain in terms of computing time in the framework of the optimization process. [ABSTRACT FROM AUTHOR]