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The present monograph offers a detailed and in-depth analysis of the topic of Intelligent Control for Electric Power Systems and Electric Vehicles. First, Nonlinear optimal control and Lie algebra-based control (Control based on approximate linearization and Global linearization-based control concepts) is analyzed. Next, Differential flatness theory and flatness-based control methods (Global linearization-based control with the use of differential flatness theory and Flatness-based control of nonlinear dynamical systems in cascading loops) is treated. Following the control theoretic part Control of DC and PMBLDC electric motors (Control of DC motors through a DC-DC converter and Control of Per- manent Magnet Brushless DC motors) is presented. Besides, Control of VSI-fed three-phase and multi- phase PMSMs (Nonlinear optimal control VSI-fed three-phase PMSMs and Nonlinear optimal control VSI-fed six-phase PMSMs) is explained. Additionally, Control of energy conversion chains based on PMSMs (Control of wind-turbine and PMSM-based electric power unit and Control of a PMSM-driven gas-compression unit) is studied. Besides, Control of energy conversion chains based on Induction Ma- chines (Control of the VSI-fed three-phase induction motor, Control of an induction motor-driven gas compressor and Control of induction generator-based shipboard microgrids) is explained. Next, Control of multi-phase machines in gas processing and power units (Control of gas-compressors actuated by 5-phase PMSMs and Control of 6-phase induction generators in renewable energy units) is introduced, Moreover, Control of Spherical Permanent Magnet Synchronous Motors and Switched Reluctance Mo- tors (Control of spherical permanent magnet synchronous motors, Control of switched reluctance motors for electric traction and Adaptive control for switched reluctance motors) is analyzed, Furthermore, Control of traction and powertrains in Electric Vehicles and Hybrid Electric Vehicles (Control of multi- phase motors in the traction system in electric vehicles and Control of synchronous machines and converters in power-chains of hybrid electric vehicles) is explained, Finally, Control of renewable power units and heat management units (Control of residential microgrids with Wind Generators, Fuel Cells and PVs and Control of heat pumps for thermal management in electric vehicles) it treated. The new control methods which are proposed by the monograph treat the control problem of the complex nonlinear dynamics of electric power systems and electric vehicles without the need for complicated state-space model transformations and changes of state variables. The proposed control schemes are modular and scalable and can be applied to a large class of dynamic models of electric power systems and electric vehicles. They have a clear and easy-to- implement algorithmic part, while they also exhibit a moderate computational load. The proposed control schemes foster the optimized exploitation of renewable energy sources and the reliable integration of renewable energy units in the power grid. Besides, they support the transition to electromotion and the deployment of the use of electric vehicles. The manuscript is suitable for teaching nonlinear control, estimation and fault diagnosis topics with emphasis to electric power systems and to electric vehicle traction and propulsion systems both at late undergraduate and postgraduate levels.
This book provides a basis for full integration of electric vehicles into the smart grid, through the use of ICT tools. It looks at transport and energy system modelling, simulation and optimisation processes; vehicle on-line optimal control, estimation and prediction; energy system strategic planning; and services such as smart charging.
Build state-of-the-art intelligent omnidirectional HEVs Engineer high-performance, low-emission automobiles by overcoming traditional obstacles and efficiently harnessing energy from multiple sources. Hybrid Electric Vehicle Design and Control features complete coverage of all electrical, mechanical, and software components. Find out how to develop fast-charging battery systems, efficiently manage power, implement independent steering and force control, and enhance driving stability and controllability. This comprehensive guide offers detailed modeling, testing, and tuning techniques and provides an overview of emerging developments in hybrid technologies. Coverage includes: 4WIS and 4WID hardware and software Hybrid vehicle design structures Zero-radius turning and lateral parking Steer-by-wire and extended steering Behavior-based and zero-radius steering Traction force distribution and stability Battery, energy, and power management systems Cell equalization and fast-charging control MPC, load forecasting, and neural network classifi cation Best performance techniques
Because society depends greatly on electric energy, power system control and protection focuses on ensuring a secure and reliable supply of power. To operate the electric systems in safe mode, the power system component should be equipped with intelligent controllers. The Handbook of Research on Smart Power System Operation and Control is a collection of innovative research on the theoretical and practical developments in smart power system operation and control that takes into account both smart grid and micro-grid systems. While highlighting topics including cybersecurity, smart grid, and wide area monitoring, this book is ideally designed for researchers, students, and industry professionals.
This book compiles the best selected research papers presented during the 2nd International Conference on Intelligent Computing Techniques for Smart Energy Systems (ICTSES 2021), held at Manipal University, Jaipur, Rajasthan, India. It presents the diligent work of the research community where intelligent computing techniques are applied in allied fields of engineering ranging from engineering materials to electrical engineering to electronics and communication engineering- to computer-related fields. The theoretical research concepts are supported with extensive reviews highlighting the trends in the possible and real-life applications of computational intelligence. The high-quality content with broad range of the topics is thoroughly peer-reviewed and published on suitable recommendations.
The editors of this Special Issue titled “Intelligent Control in Energy Systems” have attempted to create a book containing original technical articles addressing various elements of intelligent control in energy systems. In response to our call for papers, we received 60 submissions. Of those submissions, 27 were published and 33 were rejected. In this book, we offer the 27 accepted technical articles as well as one editorial. Authors from 15 countries (China, Netherlands, Spain, Tunisia, United Sates of America, Korea, Brazil, Egypt, Denmark, Indonesia, Oman, Canada, Algeria, Mexico, and the Czech Republic) elaborate on several aspects of intelligent control in energy systems. The book covers a broad range of topics including fuzzy PID in automotive fuel cell and MPPT tracking, neural networks for fuel cell control and dynamic optimization of energy management, adaptive control on power systems, hierarchical Petri Nets in microgrid management, model predictive control for electric vehicle battery and frequency regulation in HVAC systems, deep learning for power consumption forecasting, decision trees for wind systems, risk analysis for demand side management, finite state automata for HVAC control, robust μ-synthesis for microgrids, and neuro-fuzzy systems in energy storage.
This book aims to systematically review and design different intelligent control algorithms for the small-signal stability assessment of HPS. With the growing consciousness of global warming and the fast depletion of natural power generation resources, the existing power system is on the verge of transitions to a “hybrid power system (HPS)” integrated with distributed energy resources. The recent results and requirements for the developments of intelligent control algorithms have motivated the authors to introduce this book for extensively analyzing the performance of HPS against unknown/uncertain disturbances. This book introduces fractional-order resilient control methodologies for arresting small-signal instability of HPS. The prospective investigation has been performed on the MATLAB platform. This book is helpful for undergraduate, postgraduate students, and research scholars working in power system stability, control applications, and soft computing in particular.
The book comprehensively discusses concepts of artificial intelligence in green transportation systems. It further covers intelligent techniques for precise modeling of complex transportation infrastructure, forecasting and predicting traffic congestion, and intelligent control techniques for maximizing performance and safety. It further provides MATLAB® programs for artificial intelligence techniques. It discusses artificial intelligence-based approaches and technologies in controlling and operating solar photovoltaic systems to generate power for electric vehicles. Highlights how different technological advancements have revolutionized the transportation system. Presents core concepts and principles of soft computing techniques in the control and management of modern transportation systems. Discusses important topics such as speed control, fuel control challenges, transport infrastructure modeling, and safety analysis. Showcases MATLAB® programs for artificial intelligence techniques. Discusses roles, implementation, and approaches of different intelligent techniques in the field of transportation systems. It will serve as an ideal text for professionals, graduate students, and academicians in the fields of electrical engineering, electronics and communication engineering, civil engineering, and computer engineering.
Electric vehicles are changing transportation dramatically and this unique book merges the many disciplines that contribute research to make EV possible, so the reader is informed about all the underlying science and technologies driving the change. An emission-free mobility system is the only way to save the world from the greenhouse effect and other ecological issues. This belief has led to a tremendous growth in the demand for electric vehicles (EV) and hybrid electric vehicles (HEV), which are predicted to have a promising future based on the goals fixed by the European Commission's Horizon 2020 program. This book brings together the research that has been carried out in the EV/HEV sector and the leading role of advanced optimization techniques with artificial intelligence (AI). This is achieved by compiling the findings of various studies in the electrical, electronics, computer, and mechanical domains for the EV/HEV system. In addition to acting as a hub for information on these research findings, the book also addresses the challenges in the EV/HEV sector and provides proven solutions that involve the most promising AI techniques. Since the commercialization of EVs/HEVs still remains a challenge in industries in terms of performance and cost, these are the two tradeoffs which need to be researched in order to arrive at an optimal solution. Therefore, this book focuses on the convergence of various technologies involved in EVs/HEVs. Since all countries will gradually shift from conventional internal combustion (IC) engine-based vehicles to EVs/HEVs in the near future, it also serves as a useful reliable resource for multidisciplinary researchers and industry teams.