Dynamic modelling and predictive control in solid oxide fuel cells - Info and Reading Options

The Open Library:

"A timely treatment of the modeling and advanced control of the most promising fuel cell technology - SOFC (solid oxide fuel cells) - from cell to system levelDynamic Modeling and Predictive Control in Solid Oxide Fuel Cells: Delivers comprehensive coverage of SOFC dynamic models and modeling approach from first principles, bringing together many aspects of SOFC technology in one book for the first time Provides parameters for all models developed for easy reference and reproducing of the results Discusses lumped model and distributed model from cell level to system level Applications to the state-of-the-art unscented Kalman filter, model predictive control, and monitoring techniques to SOFC systems Uses NMPC, which is well understood by both industry and academia Essential reading for Graduate students and researchers in the area of fuel cells, process systems engineering, control systems engineering, process control and electrochemical engineering"-- "This is a unique book, dedicated to solid oxide fuel cells; in both cell level and system level, for both planner and tubular structures, with both lumped model and distributed model, and with complete parameters provided for each model developed"--

Open Data:

Intro -- Title Page -- Copyright -- Preface -- Acknowledgments -- List of Figures -- List of Tables -- Chapter 1: Introduction -- 1.1 Overview of Fuel Cell Technology -- 1.2 Modelling, State Estimation and Control -- 1.3 Book Coverage -- 1.4 Book Outline -- Part One: Fundamentals -- Chapter 2: First Principle Modelling for Chemical Processes -- 2.1 Thermodynamics -- 2.2 Heat Transfer -- 2.3 Mass Transfer -- 2.4 Fluid Mechanics -- 2.5 Equations of Change -- 2.6 Chemical Reaction -- 2.7 Notes and References -- Chapter 3: System Identification I -- 3.1 Discrete-time Systems -- 3.2 Signals -- 3.3 Models -- 3.4 Notes and References -- Chapter 4: System Identification II -- 4.1 Regression Analysis -- 4.2 Prediction Error Method -- 4.3 Model Validation -- 4.4 Practical Consideration -- 4.5 Closed-loop Identification -- 4.6 Subspace Identification -- 4.7 Notes and References -- Chapter 5: State Estimation -- 5.1 Recent Developments in Filtering Techniques for Stochastic Dynamic Systems -- 5.2 Problem Formulation -- 5.3 Sequential Bayesian Inference for State Estimation -- 5.4 Examples -- 5.5 Notes and References -- Chapter 6: Model Predictive Control -- 6.1 Model Predictive Control: State-of-the-Art -- 6.2 General Principle -- 6.3 Dynamic Matrix Control -- 6.4 Nonlinear MPC -- 6.5 General Tuning Guideline of Nonlinear MPC -- 6.6 Discretisation of Models: Orthogonal Collocation Method -- 6.7 Pros and Cons of MPC -- 6.8 Optimisation -- 6.9 Example: Chaotic System -- 6.10 Notes and References -- Part Two: Tubular SOFC -- Chapter 7: Dynamic Modelling of Tubular SOFC: First-Principle Approach -- 7.1 SOFC Stack Design -- 7.2 Conversion Process -- 7.3 Diffusion Dynamics -- 7.4 Fuel Feeding Process -- 7.5 Air Feeding Process -- 7.6 SOFC Temperature -- 7.7 Final Dynamic Model -- 7.8 Investigation of Dynamic Properties through Simulations

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