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

  • Casteleiro-Roca, José-Luis [1] ; Barragán, Antonio Javier [2] ; Segura, Francisca [2] ; Calvo-Rolle, José Luis [1] ; Andújar, José Manuel [2]
    1. [1] Universidade da Coruña

      Universidade da Coruña

      A Coruña, España

    2. [2] Universidad de Huelva

      Universidad de Huelva

      Huelva, España

  • Localización: Revista iberoamericana de automática e informática industrial ( RIAI ), ISSN-e 1697-7920, Vol. 16, Nº. 4, 2019, págs. 492-501
  • Idioma: español
  • DOI: 10.4995/riai.2019.10986
  • Títulos paralelos:
    • Intelligent hybrid system for the prediction of the voltage-current characteristic curve of a hydrogen-based fuel cell
  • Enlaces
  • Resumen
    • español

      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.

    • English

      Due to some reasons like sustainability and energy strategy, there is a clear trend using new ways to obtain energy, more efficient and, usually, renewables. In addition, with other dierent 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.

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