Sistema híbrido inteligente para la predicción de tensión de una pila de combustible basada en hidrógeno

Por razones de sostenibilidad y estrategia energética, entre otras, existe en la actualidad una tendencia clara hacia el uso de nuevas formas de obtención, almacenamiento y gestión de energía, más eficientes y con un carácter eminentemente sostenible. Con este fin, se está investigando sobre sistemas de almacenamiento de energía; de los que uno de los más prometedores, en lo que a capacidad y movilidad se refiere, es el basado en hidrógeno. En el presente trabajo se obtiene un modelo para predecir el comportamiento dinámico de una pila de combustible alimentada por hidrógeno, lo cual permitirá mejorar su control entre otras aplicaciones. Las variables usadas en esta investigación se han extraído de un banco de pruebas real, donde se monitoriza una pila de combustible mientras se producen variaciones en una carga programable conectada a la salida de la misma. Para realizar este modelado se opta por estudiar la implementación de un modelo híbrido basado en técnicas de agrupamiento y, posteriormente, técnicas inteligentes de regresión con redes neuronales artificiales sobre cada uno de los grupos. La propuesta se ha probado con dos conjuntos de datos de validación, consiguiendo resultados altamente satisfactorios.Due to some reasons like sustainability and energy strategy, there is a clear trend using new ways to obtain energy, more e cient and, usually, renewables. In addition, with other di erent objectives, many researchs are being carried out on energy storage systems; one of the most promising, in terms of capacity and mobility, is hydrogen-based. In the present work a model is obtained to predict the dynamic behavior of a hydrogen fuel cell, which will improve its control. The variables used in this research have been extracted from a test bench, where a fuel cell is monitored under several load conditions with a programmable load connected to its output. To perform this model, a hybrid intelligent model was chosen. This kind of models use clustering techniques to divide the data set and, after that, intelligent regression algorithm with artificial neural networks are used for each group. The proposal has been tested with two validation data set, obtaining highly satisfactory results.Los autores de este trabajo quieren agradecer el soporte en materia de financiación del Ministerio de Economía, Industria y Competitividad del Gobierno de España a través del proyecto H2SMART- uGRID (DPI2017-85540-R)

SOLAR ENERGY SUPPORTED HYDROGEN PRODUCTION: A THEORETICAL CASE STUDY

Two different units that were connected to each other were modelled and solved numerically in this study. The electrical energy obtained from solar energy via photovoltaic panels were used in order to charge a battery first and then hydrogen was acquired by using aforementioned energy in the electrolysis of water. In the second stage, electricity is generated in a fuel cell by using the generated hydrogen. In this study a more effective way of solar energy utilization was aimed for the periods without sun light. A theoretical analysis was done via computer software by solving the constituted mathematical model. Data containing monthly average insolation values of Konya City according to years were used in this model. Electrolyzer temperature and pressure values and efficiencies of the photovoltaic panels were used as the input parameters. General system efficiency and effectiveness, generated electricity and hydrogen amounts were obtained as the output parameters. Among all, temperature was found to be the most effective parameter according to the obtained results considering the generated hydrogen amount, system effectiveness and efficiency. A wide range of electrical power between 400 W and 1800 W can be harnessed from the PV part of the system. Hydrogen production in the other hand can be attained in the range of 120-130 g/month. Power curve of the fuel cell at the start up of the system yields a 0.001 seconds reaction time. The proposed system can be utilized in rural parts of Konya and climatically similar regions in the world

Experimental and analytical study of an open cathode polymer electrolyte membrane fuel cell.

In this thesis four different fuel cell designs were simulated with consideration for electrochemical effects, reactant species transport, and heat transfer. Simulation results include the mass fraction of hydrogen, oxygen, and water, temperature gradient, pressure gradient, and velocity profile. One of the fuel cell designs was experimentally tested using two different membrane electrolyte assemblies; one high performance and the other high durability. The polarization curve resulting from simulation compares well with the polarization curve produced by experimental work. A 16 cell fuel cell stack was simulated with consideration for stack compression. The same fuel cell stack was tested experimentally for compression using pressure sensitive films. Compression testing was performed in order to find areas of low compression and high compression. Low compression regions lead to high contact resistance which degrades the performance of the fuel cell. High compression regions can cause damage to the thin and brittle membrane electrolyte assemblies. A good correlation was found between the compression pattern resulting from simulation and experimental work

Modelado y validación experimental de una monocelda y un stack de una pila de combustible tipo PEM

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