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Advanced Methods of Solid Oxide Fuel Cell Modeling

  • Jarosław Milewski
  • Konrad Świrski
  • Massimo Santarelli
  • Pierluigi Leone

Part of the Green Energy and Technology book series (GREEN)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Jarosław Milewski
    Pages 1-16
  3. Jarosław Milewski
    Pages 17-39
  4. Konrad Świrski
    Pages 41-62
  5. Massimo Santarelli, Pierluigi Leone
    Pages 63-90
  6. Jarosław Milewski
    Pages 91-200
  7. Back Matter
    Pages 201-217

About this book

Introduction

Fuel cells are widely regarded as the future of the power and transportation industries. Intensive research in this area now requires new methods of fuel cell operation modeling and cell design. Typical mathematical models are based on the physical process description of fuel cells and require a detailed knowledge of the microscopic properties that govern both chemical and electrochemical reactions. Advanced Methods of Solid Oxide Fuel Cell Modeling proposes the alternative methodology of generalized artificial neural networks (ANN) solid oxide fuel cell (SOFC) modeling.

Advanced Methods of Solid Oxide Fuel Cell Modeling provides a comprehensive description of modern fuel cell theory and a guide to the mathematical modeling of SOFCs, with particular emphasis on the use of ANNs. Up to now,  most of the equations involved in SOFC models have required the addition of numerous factors that are difficult to determine. The artificial neural network (ANN) can be applied to simulate an object’s behavior without an algorithmic solution, merely by utilizing available experimental data.

The ANN methodology discussed in Advanced Methods of Solid Oxide Fuel Cell Modeling can be used by both researchers and professionals to optimize SOFC design. Readers will have access to detailed material on universal fuel cell modeling and design process optimization, and will also be able to discover comprehensive information on fuel cells and artificial intelligence theory.

Keywords

Artificial Intelligence Artificial Neural Network CP8059 Empirical Methods Fuel Cell Mathematical Modelling Solid Oxide

Authors and affiliations

  • Jarosław Milewski
    • 1
  • Konrad Świrski
    • 2
  • Massimo Santarelli
    • 3
  • Pierluigi Leone
    • 4
  1. 1.Institute of Heat EngineeringWarsaw University of TechnologyWarsawPoland
  2. 2.Institute of Heat EngineeringWarsaw University of TechnologyWarsawPoland
  3. 3.Dipto. EnergeticaPolitecnico di TorinoTorinoItaly
  4. 4.Dipto. EnergeticaPolitecnico di TorinoTorinoItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-85729-262-9
  • Copyright Information Springer-Verlag London Limited 2011
  • Publisher Name Springer, London
  • eBook Packages Engineering
  • Print ISBN 978-0-85729-261-2
  • Online ISBN 978-0-85729-262-9
  • Series Print ISSN 1865-3529
  • Series Online ISSN 1865-3537
  • Buy this book on publisher's site