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El. knyga: Models for Solid Oxide Fuel Cell Systems: Exploitation of Models Hierarchy for Industrial Design of Control and Diagnosis Strategies

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  • Formatas: PDF+DRM
  • Serija: Green Energy and Technology
  • Išleidimo metai: 07-Mar-2016
  • Leidėjas: Springer London Ltd
  • Kalba: eng
  • ISBN-13: 9781447156581
Kitos knygos pagal šią temą:
Models for Solid Oxide Fuel Cell Systems: Exploitation of Models Hierarchy for Industrial Design of Control and Diagnosis StrategiesDidesnis paveikslėlis
  • Formatas: PDF+DRM
  • Serija: Green Energy and Technology
  • Išleidimo metai: 07-Mar-2016
  • Leidėjas: Springer London Ltd
  • Kalba: eng
  • ISBN-13: 9781447156581
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The book presents methodologies that are suitable for optimal design of control and diagnosis strategies for Solid Oxide Fuel Cell (SOFC) systems. Key feature of the methodologies presented is the exploitation of modelling tools with an optimal balance between accuracy and computational burden. Particular emphasis is given to the useful combination of models within a hierarchical framework, aimed at reducing the experimental efforts required for characterization and testing. Such tools are proven to be highly effective for SOFC systems destined to both residential and transportation applications. Optimality through the book is always conceived in such a way as to let the SOFC systems work efficiently while guaranteeing safe thermal operation as well as extended lifetime. The book is intended for scientists and engineers involved into the design of marketable SOFC systems. It gathers the knowledge and the experience gained in other research and industrial areas, for which control and diagnosis have proven to be the main keys of success and market penetration.

This book presents methodologies for optimal design of control and diagnosis strategies for Solid Oxide Fuel Cell systems. A key feature of the methodologies presented is the exploitation of modelling tools that balance accuracy and computational burden.
1 Introduction
1(26)
1.1 Solid Oxide Fuel Cells
1(3)
1.1.1 Cell Materials
2(1)
1.1.2 Cell Designs
3(1)
1.2 Toward Industrial Deployment of Reliable SOFC Systems
4(3)
1.3 Benefits of Model-Based Approach for Control and Diagnostics
7(4)
1.4 Literature Survey
11(9)
1.4.1 1D Models
12(1)
1.4.2 0D Models
13(3)
1.4.3 Black-Box (Data-Driven) Models
16(1)
1.4.4 Models for Diagnosis and Degradation Monitoring
17(3)
1.5
Chapter Closure
20(7)
References
21(6)
2 Models Hierarchy
27(64)
2.1 From Physical to Synthesis Models
27(4)
2.1.1 Hierarchical Approach to SOFC Modeling
29(2)
2.2 Dimensional Modeling
31(29)
2.2.1 The 1D Model
31(29)
2.3 Lumped (Gray-Box) Modeling
60(18)
2.3.1 Lumped Model of Planar SOFC
61(9)
2.3.2 PostBurner Modeling
70(3)
2.3.3 Heat Exchangers Modeling
73(5)
2.4 Black-Box Modeling
78(5)
2.4.1 Overview on Neural Network Models
78(2)
2.4.2 Development of Neural Networks for Steady-State Modeling of SOFC Performance
80(2)
2.4.3 Development of Neural Networks for Dynamic Modeling of SOFC Performance
82(1)
2.5 Required Experimental Activity
83(3)
2.5.1 Definition of Steady-State Identification Domain
84(1)
2.5.2 Transient Experiments
85(1)
2.6
Chapter Closure
86(5)
References
87(4)
3 Models for Control Applications
91(30)
3.1 Multilevel Control of SOFC Systems
91(7)
3.1.1 Control Variables and Controlled Outputs
94(2)
3.1.2 Which Controllers?
96(2)
3.2 Supervisory Control
98(2)
3.3 Central-Level Control
100(2)
3.4 Low-Level Control
102(9)
3.4.1 Warmed-up Phase
104(3)
3.4.2 Cold-Start Phase
107(4)
3.5 Case Studies
111(7)
3.5.1 Case Study 1: Automotive APU
111(4)
3.5.2 Case Study 2: Residential CHP
115(3)
3.6
Chapter Closure
118(3)
References
118(3)
4 Models for Diagnostic Applications
121
4.1 Model-Based Diagnosis
121(2)
4.2 Residual Generation
123(2)
4.3 Threshold Design
125(3)
4.4 Inferential Process
128(6)
4.4.1 Fault Tree Analysis
130(2)
4.4.2 Fault Signature Matrix
132(2)
4.5 Case Studies
134(18)
4.5.1 Case Study 1: Air Blower Fault
136(9)
4.5.2 Case Study 2: Fuel Pre-reformer Fault
145(7)
4.6
Chapter Closure
152
References
153
Over the past decade Cesare Pianese and Marco Sorrentino concentrated their research interests in the field of model-based control and diagnosis of fuel-cell based energy conversion systems. They transfer to the fuel-cell area the experience gained on the control and optimization of internal combustion engines and other alternative propulsion systems. Most of the modelling approaches and the methodologies presented in the book are derived from those successfully implemented on real systems by industrial companies.
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