The current energy situation is dominated by fossil fuels, especially oil. This dependency is turning critical due its reducing reserves, political and economical ramificationsto and environmental impact. This situation has caused an increase in the research and development of electrochemical energy systems, such as fuel cells, batteries and ultracapacitors and its application to stationary or transport applications. This book presents the nonlinear dynamic per-unit modelling of electrochemical systems through frequency domain tests. The per-unit approach is a useful tool for comparison and design, due to the great disparity of voltages and capacities, e.g. in batteries, which can be found. The book also includes the description of the experimental setup needed to allow electrochemical impedance spectroscopy on supercapacitors during high current loads. The modelling results are applied to a hardware-in-the-loop simulation, which allows to test complex systems in an easy way. This book can be useful to electric, electronic and electrochemical researchers who wish to model and simulate energy systems.

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 systems The 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.

This thesis introduces (i) amendments to basic electrochemical measurement techniques in the time and frequency domain suitable for electrochemical energy conversion systems like fuel cells and batteries, which enable shorter measurement times and improved precision in both measurement and parameter identification, and (ii) a modeling approach that is able to simulate a technically relevant system just by information gained through static and impedance measurements of laboratory size cells.

The only book available on fuel cell modeling and control with distributed power generation applications The emerging fuel cell (FC) technology is growing rapidly in its applications from small-scale portable electronics to large-scale power generation. This book gives students, engineers, and scientists a solid understanding of the FC dynamic modeling and controller design to adapt FCs to particular applications in distributed power generation. The book begins with a fascinating introduction to the subject, including a brief history of the U.S. electric utility formation and restructuring. Next, it provides coverage of power deregulation and distributed generation (DG), DG types, fuel cell DGs, and the hydrogen economy. Building on that foundation, it covers: Principle operations of fuel cells Dynamic modeling and simulation of PEM and solid-oxide fuel cells Principle operations and modeling of electrolyzers Power electronic interfacing circuits for fuel cell applications Control of grid-connected and stand-alone fuel cell power generation systems Hybrid fuel cell–based energy system case studies Present challenges and the future of fuel cells MATLAB/SIMULINK-based models and their applications are available via a companion Web site. Modeling and Control of Fuel Cells is an excellent reference book for students and professionals in electrical, chemical, and mechanical engineering and scientists working in the FC area.

Fuel cells can produce electricity with high efficiency, low pollutants, and low noise. With the advent of fuel cell technologies, fuel cell systems have since been demonstrated as reliable power generators with power outputs from a few watts to a few megawatts. With proper equipment, fuel cell systems can produce heating and cooling, thus increased its overall efficiency. To increase the acceptance from electrical utilities and building owners, fuel cell systems must operate more dynamically and integrate well with renewable energy resources. This research studies the dynamic performance of fuel cells and the integration of fuel cells with other equipment in three levels: (i) the fuel cell stack operating on hydrogen and reformate gases, (ii) the fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit, and (iii) the hybrid energy system consisting of photovoltaic panels, fuel cell system, and energy storage.In the first part, this research studied the steady-state and dynamic performance of a high temperature PEM fuel cell stack. Collaborators at Aalborg University (Aalborg, Denmark) conducted experiments on a high temperature PEM fuel cell short stack at steady-state and transients. Along with the experimental activities, this research developed a first-principles dynamic model of a fuel cell stack. The dynamic model developed in this research was compared to the experimental results when operating on different reformate concentrations. Finally, the dynamic performance of the fuel cell stack for a rapid increase and rapid decrease in power was evaluated. The dynamic model well predicted the performance of the well-performing cells in the experimental fuel cell stack.The second part of the research studied the dynamic response of a high temperature PEM fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit with high thermal integration. After verifying the model performance with the obtained experimental data, the research studied the control of airflow to regulate the temperature of reactors within the fuel processor. The dynamic model provided a platform to test the dynamic response for different control gains. With sufficient sensing and appropriate control, a rapid response to maintain the temperature of the reactor despite an increase in power was possible.The third part of the research studied the use of a fuel cell in conjunction with photovoltaic panels, and energy storage to provide electricity for buildings. This research developed an optimization framework to determine the size of each device in the hybrid energy system to satisfy the electrical demands of buildings and yield the lowest cost. The advantage of having the fuel cell with photovoltaic and energy storage was the ability to operate the fuel cell at baseload at night, thus reducing the need for large battery systems to shift the solar power produced in the day to the night. In addition, the dispatchability of the fuel cell provided an extra degree of freedom necessary for unforeseen disturbances. An operation framework based on model predictive control showed that the method is suitable for optimizing the dispatch of the hybrid energy system.

The series Topics in Current Chemistry Collections presents critical reviews from the journal Topics in Current Chemistry organized in topical volumes. The scope of coverage is all areas of chemical science including the interfaces with related disciplines such as biology, medicine and materials science. The goal of each thematic volume is to give the non-specialist reader, whether in academia or industry, a comprehensive insight into an area where new research is emerging which is of interest to a larger scientific audience. Each review within the volume critically surveys one aspect of that topic and places it within the context of the volume as a whole. The most significant developments of the last 5 to 10 years are presented using selected examples to illustrate the principles discussed. The coverage is not intended to be an exhaustive summary of the field or include large quantities of data, but should rather be conceptual, concentrating on the methodological thinking that will allow the non-specialist reader to understand the information presented. Contributions also offer an outlook on potential future developments in the field. The chapters “Assessment of Simple Models for Molecular Simulation of Ethylene Carbonate and Propylene Carbonate as Solvents for Electrolyte Solutions” and “Elucidating Solvation Structures for Rational Design of Multivalent Electrolytes—A Review” are available open access under a CC BY 4.0 License via link.springer.com.

Lithium-ion batteries have revolutionized our everyday lives by laying the foundation for a wireless, interconnected and fossil-fuel-free society. Additionally, the demand for Li-ion batteries has seen a dramatic increase, as the automotive industry shifts up a gear in its transition to electric vehicles. To optimize the power and energy that can be delivered by a battery, it is necessary to predict the behavior of the cell under different loading conditions. However, electrochemical cells are complicated energy storage systems with nonlinear voltage dynamics. There is a need for accurate dynamic modeling of the battery system to predict behavior over time when discharging. The study conducted in this work develops an intuitive model for electrochemical cells based on a mechanical analogy. The mechanical analogy is based on a three degree of freedom spring-mass-damper system which is decomposed into modal coordinates that represent the overall discharge as well as the mass transport and the double layer effect of the electrochemical cell. The dynamic system is used to estimate the cells terminal voltage, open-circuit voltage and the mass transfer and boundary layer effects. The modal parameters are determined by minimizing the error between the experimental and simulated time responses. Also, these estimated parameters are coupled with a thermal model to predict the temperature profiles of the lithium-ion batteries. To capture the dynamic voltage and temperature responses, hybrid pulse power characterization (HPPC) tests are conducted with added thermocouples to measure temperature. The coupled model estimated the voltage and temperature responses at various discharge rates within 2.15% and 0.40% standard deviation of the error. Additionally, to validate the functionality of the developed dynamic battery model in a real system, a battery pack is constructed and integrated with a brushless DC motor (BLDC) and a load. Moreover, because of the unique pole orientation that a BLDC motor possesses, it puts a pulsing dynamic load on the battery pack of the system. HPPC testing was conducted on the cell that is used in the battery pack to calibrate the model parameters. After the battery model is calibrated, the rotation experiment is conducted at which a battery pack is used to drive a benchtop BLDC motor with a magnetorheological brake as a programable load at varying running speeds. The voltage and current of the battery and the BLDC motor driver are recorded. Meanwhile, the speed and the torque of the motor are recorded. These data are compared to the predicted voltage of the battery pack using the mechanical analogy model. The model estimated the voltage response of a battery pack within 0.0385% standard deviation of the error.

This book is for anyone interested in renewable energy for a sustainable future of mankind. Batteries, fuel cells, capacitors, electrolyzers and solar cells are explained at the molecular level and at the power plant level, in their historical development, in their economical and political impact, and social change. Cases from geophysics and astronomy show that electrochemistry is not confined to the small scale. Examples are shown and exercised.

This book addresses the core issues involved in the dynamic modeling, simulation and control of a selection of energy systems such as gas turbines, wind turbines, fuel cells and batteries. The principles of modeling and control could be applied to other non-convention methods of energy generation such as solar energy and wave energy. A central feature of Dynamic Modeling, Simulation and Control of Energy Generation is that it brings together diverse topics in thermodynamics, fluid mechanics, heat transfer, electro-chemistry, electrical networks and electrical machines and focuses on their applications in the field of energy generation, its control and regulation. This book will help the reader understand the methods of modelling energy systems for controller design application as well as gain a basic understanding of the processes involved in the design of control systems and regulators. It will also be a useful guide to simulation of the dynamics of energy systems and for implementing monitoring systems based on the estimation of internal system variables from measurements of observable system variables. Dynamic Modeling, Simulation and Control of Energy Generation will serve as a useful aid to designers of hybrid power generating systems involving advanced technology systems such as floating or offshore wind turbines and fuel cells. The book introduces case studies of the practical control laws for a variety of energy generation systems based on nonlinear dynamic models without relying on linearization. Also the book introduces the reader to the use nonlinear model based estimation techniques and their application to energy systems.

The aim of this book is to review innovative physical multiscale modeling methods which numerically simulate the structure and properties of electrochemical devices for energy storage and conversion. Written by world-class experts in the field, it revisits concepts, methodologies and approaches connecting ab initio with micro-, meso- and macro-scale modeling of components and cells. It also discusses the major scientific challenges of this field, such as that of lithium-ion batteries. This book demonstrates how fuel cells and batteries can be brought together to take advantage of well-established multi-scale physical modeling methodologies to advance research in this area. This book also highlights promising capabilities of such approaches for inexpensive virtual experimentation. In recent years, electrochemical systems such as polymer electrolyte membrane fuel cells, solid oxide fuel cells, water electrolyzers, lithium-ion batteries and supercapacitors have attracted much attention due to their potential for clean energy conversion and as storage devices. This has resulted in tremendous technological progress, such as the development of new electrolytes and new engineering designs of electrode structures. However, these technologies do not yet possess all the necessary characteristics, especially in terms of cost and durability, to compete within the most attractive markets. Physical multiscale modeling approaches bridge the gap between materials’ atomistic and structural properties and the macroscopic behavior of a device. They play a crucial role in optimizing the materials and operation in real-life conditions, thereby enabling enhanced cell performance and durability at a reduced cost. This book provides a valuable resource for researchers, engineers and students interested in physical modelling, numerical simulation, electrochemistry and theoretical chemistry.