Dynamic Modeling and Predictive Control in Solid Oxide Fuel Cells - First Principle and Data-Based Approaches

Informationen zum Autor Biao Huang University of Alberta, Canada Yutong Qi Corporate Electronics, Canada AKM Monjur Murshed Shell Canada, Canada Klappentext The high temperature solid oxide fuel cell (SOFC) is identified as one of the leading fuel cell technology contenders to capture the energy market in years to come. However, in order to operate as an efficient energy generating system, the SOFC requires an appropriate control system which in turn requires a detailed modelling of process dynamics.Introducting state-of-the-art dynamic modelling, estimation, and control of SOFC systems, this book presents original modelling methods and brand new results as developed by the authors. With comprehensive coverage and bringing together many aspects of SOFC technology, it considers dynamic modelling through first-principles and data-based approaches, and considers all aspects of control, including modelling, system identification, state estimation, conventional and advanced control.Key features:* Discusses both planar and tubular SOFC, and detailed and simplified dynamic modelling for SOFC* Systematically describes single model and distributed models from cell level to system level* Provides parameters for all models developed for easy reference and reproducing of the results* All theories are illustrated through vivid fuel cell application examples, such as state-of-the-art unscented Kalman filter, model predictive control, and system identification techniques to SOFC systemsThe tutorial approach makes it perfect for learning the fundamentals of chemical engineering, system identification, state estimation and process control. It is suitable for graduate students in chemical, mechanical, power, and electrical engineering, especially those in process control, process systems engineering, control systems, or fuel cells. It will also aid researchers who need a reminder of the basics as well as an overview of current techniques in the dynamic modelling and control of SOFC. Zusammenfassung Bringing together many aspects of SOFC technology, this book introduces readers to state-of-the-art dynamic modeling, estimation, and all aspects of SOFC systems control. Inhaltsverzeichnis Preface xi Acknowledgments xiii List of Figures xv List of Tables xxi 1 Introduction 1 1.1 Overview of Fuel Cell Technology 1 1.1.1 Types of Fuel Cells 2 1.1.2 Planar and Tubular Designs 3 1.1.3 Fuel Cell Systems 4 1.1.4 Pros and Cons of Fuel Cells 5 1.2 Modelling, State Estimation and Control 5 1.3 Book Coverage 6 1.4 Book Outline 6 Part I Fundamentals 2 First Principle Modelling for Chemical Processes 11 2.1 Thermodynamics 11 2.1.1 Forms of Energy 11 2.1.2 First Law 12 2.1.3 Second Law 13 2.2 Heat Transfer 13 2.2.1 Conduction 14 2.2.2 Convection 15 2.2.3 Radiation 17 2.3 Mass Transfer 18 2.4 Fluid Mechanics 20 2.4.1 Viscous Flow 21 2.4.2 Velocity Distribution 21 2.4.3 Bernoulli Equation 21 2.5 Equations of Change 22 2.5.1 The Equation of Continuity 23 2.5.2 The Equation of Motion 23 2.5.3 The Equation of Energy 24 2.5.4 The Equations of Continuity of Species 26 2.6 Chemical Reaction 26 2.6.1 Reaction Rate 26 2.6.2 Reversible Reaction 28 2.6.3 Heat of Reaction 29 2.7 Notes and References 29 3 System Identification I 31 3.1 Discrete-time Systems 31 3.2 Signals 36 3.2.1 Input Signals 36 3.2.2 Spectral Characteristics of Signals 41 3.2.3 Persistent Excitation in Input Signals 44 3.2.4 Input Design 49 3.3 Models 50 3.3.1 Linear Models 50 3.3.2 Nonlinear Models 54 3.4 Notes and References 56 <...

List of contents

Preface xvii
1 Introduction 1

1.1 Overview of Fuel Cell Technology 1

1.1.1 Types of Fuel Cells 2

1.1.2 Planar and Tubular Design 3

1.1.3 Fuel Cell Systems 5

1.1.4 Pros and Cons of Fuel Cells 5

1.2 Modelling, Filtering and Control 6

1.3 Book Coverage 7

1.4 Book Outline 7

Part One Fundamentals 9

2 First Principle Modelling for Chemical Processes 11

2.1 Thermodynamics 11

2.1.1 Forms of Energy 11

2.1.2 First Law 12

2.1.3 Second Law 13

2.2 Heat Transfer 14

2.2.1 Conduction 14

2.2.2 Convection 16

2.2.3 Radiation 17

2.3 Mass Transfer 19

2.4 Fluid Mechanics 21

2.4.1 Viscous Flow 21

2.4.2 Velocity Distributions 22

2.4.3 Bernoulli Equation 22

2.5 Equations of Change 23

2.5.1 The Equation of Continuity 24

2.5.2 The Equation of Motion 24

2.5.3 The Equation of Energy 25

2.5.4 Equations of Continuity of Species 27

2.6 Chemical Reaction 28

2.6.1 Reaction Rate 28

2.6.2 Reversible Reaction 29

2.6.3 Heat of Reaction 30

2.7 Notes and References 31

3 Data Driven Modelling: Preliminaries for System Identification 333.1 Discrete-time Systems 33

3.2 Signals 39

3.2.1 Input signals 39

3.2.2 Spectral Characteristics of Signals 44

3.2.3 Persistent Excitation in Input Signal 48

3.2.4 Input Design 53

3.3 Models 53

3.3.1 Linear Models 53

3.3.2 Nonlinear Models 58

3.4 Notes and References 60

4 Data Driven Modelling: System Identification 61

4.1 Regression Analysis 61

4.1.1 Autoregressive Moving Average with Exogenous Input Models 61

4.1.2 Linear Regression 63

4.1.3 Analysis of Linear Regression 64

4.1.4 Weighted Least Squares Method 65

4.2 Prediction Error Method 68

4.2.1 Optimal Prediction 70

4.2.2 Prediction Error Method 75

4.2.3 Prediction Error Method with Independent Parameterization 79

4.2.4 Asymptotic Variance Property of PEM 80

4.2.5 Nonlinear Identification 82

4.3 Model Validation 84

4.3.1 Model Structure Selection 84

4.3.2 The parsimony principle 86

4.3.3 Comparison of model structures 86

4.4 Practical Consideration 87

4.4.1 Treating nonzero means 88

4.4.2 Treating drifts in disturbances 88

4.4.3 Robustness 89

4.4.4 Model Validation 89

4.5 Closed-loop Identification 90

4.5.1 Direct Closed-loop Identification 91

4.5.2 Indirect Closed-loop Identification 93

4.6 Subspace Identification 98

4.6.1 Notations 98

4.6.2 Subspace Identification via Regression Analysis Approach 104

4.6.3 Example 106

4.7 Notes and References 109

5 State Estimation 111

5.1 Recent Development of Filtering Techniques for Stochastic Dynamic Systems 111

5.2 Problem Formulation 113

5.3 Sequential Bayesian Inference for State Estimation 115

5.3.1 Kalman Filter and Extended Kalman Filter 119

5.3.2 Unscented Kalman Filter 121

5.4 Examples 126

5.5 Notes and References 130

6 Model Predictive Control 131

6.1 Model Predictive Control: State-of-the-Art 131

6.2 General Principle 132

6.2.1 Models for MPC 132

6.2.2 Free and forced response 135

6.2.3 Objective Function 136

6.2.4 Constraints 136

6.2.5 MPC control law 137

6.3 Dynamic Matrix Control 137

6.3.1 The Prediction Model 137

6.3.2 Unconstrained DMC Design 140

6.3.3 Penalizing the Control Action 140

6.3.4 Handling Disturbances in DMC 141

6.4 Nonlinear MPC 144

6.5 General Tuning Guideline of nonlinear MPC 147

6.6 Discretization of Models: Orthogonal Collocation Method 148

6.6.1 Orthogonal Collocation Method with Prediction Horizon 1 149

6.6.2 Orthogonal Collocation Method with Prediction Horizon N 151

6.7 Pros and Cons of MPC 153

6.8 Optimization 154

6.9 Example: Chaotic System 155

6.10 Notes and References 157

Part Two Tubular SOFC 159

7 Dynamic Modelling: First-Principle Approach 161

7.1 SOFC Stack Design 161

7.2 Conversion Process 162

7.2.1 Electrochemical Reactions 162

7.2.2 Electrical Dynamics 165

7.3 Diffusion Dy

Product details

• Authors: B Huang, B. Huang, Bia Huang, Biao Huang, Biao (University of Alberta Huang, Biao Qi Huang, A K M Monjur Murshed, A. K. M. Monjur Murshed, Monjur Murshed, Yuton Qi, Yutong Qi, Yutong (Corporate Electronics Qi, Qi Yutong
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Hardback
• Released: 18.01.2013
• EAN: 9780470973912
• ISBN: 978-0-470-97391-2
• No. of pages: 345
• Subjects: Natural sciences, medicine, IT, technology > Technology > Electronics, electrical engineering, communications engineering; Chemie, Brennstoffzelle, Energie, Regelungstechnik, ENERGY, Elektrochemie, chemistry, electrochemistry, Electrical & Electronics Engineering, Elektrotechnik u. Elektronik, Control Systems Technology, Wasserstoff, Batterien u. Brennstoffzellen, Hydrogen, Batteries & Fuel Cells