Author: Amir Taghavipour
Publisher: Springer
ISBN: 3030003140
Category : Technology & Engineering
Languages : en
Pages : 202
Book Description
Intelligent Control of Connected Plug-in Hybrid Electric Vehicles presents the development of real-time intelligent control systems for plug-in hybrid electric vehicles, which involves control-oriented modelling, controller design, and performance evaluation. The controllers outlined in the book take advantage of advances in vehicle communications technologies, such as global positioning systems, intelligent transportation systems, geographic information systems, and other on-board sensors, in order to provide look-ahead trip data. The book contains simple and efficient models and fast optimization algorithms for the devised controllers to address the challenge of real-time implementation in the design of complex control systems. Using the look-ahead trip information, the authors of the book propose intelligent optimal model-based control systems to minimize the total energy cost, for both grid-derived electricity and fuel. The multilayer intelligent control system proposed consists of trip planning, an ecological cruise controller, and a route-based energy management system. An algorithm that is designed to take advantage of previewed trip information to optimize battery depletion profiles is presented in the book. Different control strategies are compared and ways in which connecting vehicles via vehicle-to-vehicle communication can improve system performance are detailed. Intelligent Control of Connected Plug-in Hybrid Electric Vehicles is a useful source of information for postgraduate students and researchers in academic institutions participating in automotive research activities. Engineers and designers working in research and development for automotive companies will also find this book of interest. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Intelligent Control of Connected Plug-in Hybrid Electric Vehicles
Author: Amir Taghavipour
Publisher: Springer
ISBN: 3030003140
Category : Technology & Engineering
Languages : en
Pages : 202
Book Description
Intelligent Control of Connected Plug-in Hybrid Electric Vehicles presents the development of real-time intelligent control systems for plug-in hybrid electric vehicles, which involves control-oriented modelling, controller design, and performance evaluation. The controllers outlined in the book take advantage of advances in vehicle communications technologies, such as global positioning systems, intelligent transportation systems, geographic information systems, and other on-board sensors, in order to provide look-ahead trip data. The book contains simple and efficient models and fast optimization algorithms for the devised controllers to address the challenge of real-time implementation in the design of complex control systems. Using the look-ahead trip information, the authors of the book propose intelligent optimal model-based control systems to minimize the total energy cost, for both grid-derived electricity and fuel. The multilayer intelligent control system proposed consists of trip planning, an ecological cruise controller, and a route-based energy management system. An algorithm that is designed to take advantage of previewed trip information to optimize battery depletion profiles is presented in the book. Different control strategies are compared and ways in which connecting vehicles via vehicle-to-vehicle communication can improve system performance are detailed. Intelligent Control of Connected Plug-in Hybrid Electric Vehicles is a useful source of information for postgraduate students and researchers in academic institutions participating in automotive research activities. Engineers and designers working in research and development for automotive companies will also find this book of interest. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Publisher: Springer
ISBN: 3030003140
Category : Technology & Engineering
Languages : en
Pages : 202
Book Description
Intelligent Control of Connected Plug-in Hybrid Electric Vehicles presents the development of real-time intelligent control systems for plug-in hybrid electric vehicles, which involves control-oriented modelling, controller design, and performance evaluation. The controllers outlined in the book take advantage of advances in vehicle communications technologies, such as global positioning systems, intelligent transportation systems, geographic information systems, and other on-board sensors, in order to provide look-ahead trip data. The book contains simple and efficient models and fast optimization algorithms for the devised controllers to address the challenge of real-time implementation in the design of complex control systems. Using the look-ahead trip information, the authors of the book propose intelligent optimal model-based control systems to minimize the total energy cost, for both grid-derived electricity and fuel. The multilayer intelligent control system proposed consists of trip planning, an ecological cruise controller, and a route-based energy management system. An algorithm that is designed to take advantage of previewed trip information to optimize battery depletion profiles is presented in the book. Different control strategies are compared and ways in which connecting vehicles via vehicle-to-vehicle communication can improve system performance are detailed. Intelligent Control of Connected Plug-in Hybrid Electric Vehicles is a useful source of information for postgraduate students and researchers in academic institutions participating in automotive research activities. Engineers and designers working in research and development for automotive companies will also find this book of interest. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Intelligent Control for Modern Transportation Systems
Author: Arunesh Kumar Singh
Publisher: CRC Press
ISBN: 1000963462
Category : Technology & Engineering
Languages : en
Pages : 203
Book Description
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.
Publisher: CRC Press
ISBN: 1000963462
Category : Technology & Engineering
Languages : en
Pages : 203
Book Description
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.
Intelligent Control for Electric Power Systems and Electric Vehicles
Author: G. Rigatos
Publisher: CRC Press
ISBN: 104013467X
Category : Technology & Engineering
Languages : en
Pages : 589
Book Description
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.
Publisher: CRC Press
ISBN: 104013467X
Category : Technology & Engineering
Languages : en
Pages : 589
Book Description
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.
Intelligent Control and Smart Energy Management
Author: Maude Josée Blondin
Publisher: Springer Nature
ISBN: 3030844749
Category : Science
Languages : en
Pages : 434
Book Description
This volume aims to provide a state-of-the-art and the latest advancements in the field of intelligent control and smart energy management. Techniques, combined with technological advances, have enabled the deployment of new operating systems in many engineering applications, especially in the domain of transport and renewable resources. The control and energy management of transportation and renewable resources are shifting towards autonomous reasoning, learning, planning and operating. As a result, these techniques, also referred to as autonomous control and energy management, will become practically ubiquitous soon. The discussions include methods, based on neural control (and others) as well as distributed and intelligent optimization. While the theoretical concepts are detailed and explained, the techniques presented are tailored to transport and renewable resources applications, such as smart grids and automated vehicles. The reader will grasp the most important theoretical concepts as well as to fathom the challenges and needs related to timely practical applications. Additional content includes research perspectives and future direction as well as insight into the devising of techniques that will meet tomorrow’s scientific needs. This contributed volume is for researchers, graduate students, engineers and practitioners in the domains of control, energy, and transportation.
Publisher: Springer Nature
ISBN: 3030844749
Category : Science
Languages : en
Pages : 434
Book Description
This volume aims to provide a state-of-the-art and the latest advancements in the field of intelligent control and smart energy management. Techniques, combined with technological advances, have enabled the deployment of new operating systems in many engineering applications, especially in the domain of transport and renewable resources. The control and energy management of transportation and renewable resources are shifting towards autonomous reasoning, learning, planning and operating. As a result, these techniques, also referred to as autonomous control and energy management, will become practically ubiquitous soon. The discussions include methods, based on neural control (and others) as well as distributed and intelligent optimization. While the theoretical concepts are detailed and explained, the techniques presented are tailored to transport and renewable resources applications, such as smart grids and automated vehicles. The reader will grasp the most important theoretical concepts as well as to fathom the challenges and needs related to timely practical applications. Additional content includes research perspectives and future direction as well as insight into the devising of techniques that will meet tomorrow’s scientific needs. This contributed volume is for researchers, graduate students, engineers and practitioners in the domains of control, energy, and transportation.
Intelligent Control in Energy Systems
Author: Anastasios Dounis
Publisher: MDPI
ISBN: 3039214152
Category : Science
Languages : en
Pages : 508
Book Description
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.
Publisher: MDPI
ISBN: 3039214152
Category : Science
Languages : en
Pages : 508
Book Description
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.
Technologies and Applications for Smart Charging of Electric and Plug-in Hybrid Vehicles
Author: Ottorino Veneri
Publisher: Springer
ISBN: 3319436511
Category : Technology & Engineering
Languages : en
Pages : 323
Book Description
This book outlines issues related to massive integration of electric and plug-in hybrid electric vehicles into power grids. Electricity is becoming the preferred energy vector for the next new generation of road vehicles. It is widely acknowledged that road vehicles based on full electric or hybrid drives can mitigate problems related to fossil fuel dependence. This book explains the emerging and understanding of storage systems for electric and plug-in hybrid vehicles. The recharging stations for these types of vehicles might represent a great advantage for the electric grid by facilitating integration of renewable and distributed energy production. This book presents a broad review from analyzing current literature to on-going research projects about the new power technologies related to the various charging architectures for electric and plug-in hybrid vehicles. Specifically focusing on DC fast charging operations, as well as, grid-connected power converters and the full range of energy storage systems. These key components are analyzed for distributed generation and charging system integration into micro-grids. The authors demonstrate that these storage systems represent effective interfaces for the control and management of renewable and sustainable distributed energy resources. New standards and applications are emerging from micro-grid pilot projects around the world and case studies demonstrate the convenience and feasibility of distributed energy management. The material in this unique volume discusses potential avenues for further research toward achieving more reliable, more secure and cleaner energy.
Publisher: Springer
ISBN: 3319436511
Category : Technology & Engineering
Languages : en
Pages : 323
Book Description
This book outlines issues related to massive integration of electric and plug-in hybrid electric vehicles into power grids. Electricity is becoming the preferred energy vector for the next new generation of road vehicles. It is widely acknowledged that road vehicles based on full electric or hybrid drives can mitigate problems related to fossil fuel dependence. This book explains the emerging and understanding of storage systems for electric and plug-in hybrid vehicles. The recharging stations for these types of vehicles might represent a great advantage for the electric grid by facilitating integration of renewable and distributed energy production. This book presents a broad review from analyzing current literature to on-going research projects about the new power technologies related to the various charging architectures for electric and plug-in hybrid vehicles. Specifically focusing on DC fast charging operations, as well as, grid-connected power converters and the full range of energy storage systems. These key components are analyzed for distributed generation and charging system integration into micro-grids. The authors demonstrate that these storage systems represent effective interfaces for the control and management of renewable and sustainable distributed energy resources. New standards and applications are emerging from micro-grid pilot projects around the world and case studies demonstrate the convenience and feasibility of distributed energy management. The material in this unique volume discusses potential avenues for further research toward achieving more reliable, more secure and cleaner energy.
Smart Power Grids 2011
Author: Ali Keyhani
Publisher: Springer
ISBN: 9783642440632
Category : Technology & Engineering
Languages : en
Pages : 0
Book Description
Electric power systems are experiencing significant changes at the worldwide scale in order to become cleaner, smarter, and more reliable. This edited book examines a wide range of topics related to these changes, which are primarily caused by the introduction of information technologies, renewable energy penetration, digitalized equipment, new operational strategies, and so forth. The emphasis will be put on the modeling and control of smart grid systems. The book addresses research topics such as high efficiency transforrmers, wind turbines and generators, fuel cells, or high speed turbines and generators.
Publisher: Springer
ISBN: 9783642440632
Category : Technology & Engineering
Languages : en
Pages : 0
Book Description
Electric power systems are experiencing significant changes at the worldwide scale in order to become cleaner, smarter, and more reliable. This edited book examines a wide range of topics related to these changes, which are primarily caused by the introduction of information technologies, renewable energy penetration, digitalized equipment, new operational strategies, and so forth. The emphasis will be put on the modeling and control of smart grid systems. The book addresses research topics such as high efficiency transforrmers, wind turbines and generators, fuel cells, or high speed turbines and generators.
Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles
Author: Teng Liu
Publisher: Springer Nature
ISBN: 3031015037
Category : Technology & Engineering
Languages : en
Pages : 90
Book Description
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles. Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application. In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Publisher: Springer Nature
ISBN: 3031015037
Category : Technology & Engineering
Languages : en
Pages : 90
Book Description
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles. Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application. In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Integrating Machine Learning Into HPC-Based Simulations and Analytics
Author: Ben Youssef, Belgacem
Publisher: IGI Global
ISBN: 1668437961
Category : Computers
Languages : en
Pages : 494
Book Description
Researchers are increasingly using machine learning (ML) models to analyze data and simulate complex systems and phenomena. Small-scale computing systems used for training, validation, and testing of these ML models are no longer sufficient for grand-challenge problems characterized by large volumes of data generated at a much higher rate than before, surpassing by far the computing capabilities currently available in many cyberinfrastructure platforms. By associating high-performance computing (HPC) with ML environments, scientists and engineers would be able to enhance not only the scalability but also the performance of their predictive ML models. The Handbook of Research on Integrating Machine Learning Into HPC-Based Simulations and Analytics presents recent research efforts in designing and using ML techniques on HPC systems and discusses some of the results achieved thus far by cutting-edge relevant contributions. Covering topics such as data analytics, deep learning, and networking, this major reference work is ideal for computer scientists, academicians, engineers, researchers, scholars, practitioners, librarians, instructors, and students.
Publisher: IGI Global
ISBN: 1668437961
Category : Computers
Languages : en
Pages : 494
Book Description
Researchers are increasingly using machine learning (ML) models to analyze data and simulate complex systems and phenomena. Small-scale computing systems used for training, validation, and testing of these ML models are no longer sufficient for grand-challenge problems characterized by large volumes of data generated at a much higher rate than before, surpassing by far the computing capabilities currently available in many cyberinfrastructure platforms. By associating high-performance computing (HPC) with ML environments, scientists and engineers would be able to enhance not only the scalability but also the performance of their predictive ML models. The Handbook of Research on Integrating Machine Learning Into HPC-Based Simulations and Analytics presents recent research efforts in designing and using ML techniques on HPC systems and discusses some of the results achieved thus far by cutting-edge relevant contributions. Covering topics such as data analytics, deep learning, and networking, this major reference work is ideal for computer scientists, academicians, engineers, researchers, scholars, practitioners, librarians, instructors, and students.
Connected and Autonomous Vehicles in Smart Cities
Author: Hussein T. Mouftah
Publisher: CRC Press
ISBN: 1000259250
Category : Technology & Engineering
Languages : en
Pages : 636
Book Description
This book presents a comprehensive coverage of the five fundamental yet intertwined pillars paving the road towards the future of connected autonomous electric vehicles and smart cities. The connectivity pillar covers all the latest advancements and various technologies on vehicle-to-everything (V2X) communications/networking and vehicular cloud computing, with special emphasis on their role towards vehicle autonomy and smart cities applications. On the other hand, the autonomy track focuses on the different efforts to improve vehicle spatiotemporal perception of its surroundings using multiple sensors and different perception technologies. Since most of CAVs are expected to run on electric power, studies on their electrification technologies, satisfaction of their charging demands, interactions with the grid, and the reliance of these components on their connectivity and autonomy, is the third pillar that this book covers. On the smart services side, the book highlights the game-changing roles CAV will play in future mobility services and intelligent transportation systems. The book also details the ground-breaking directions exploiting CAVs in broad spectrum of smart cities applications. Example of such revolutionary applications are autonomous mobility on-demand services with integration to public transit, smart homes, and buildings. The fifth and final pillar involves the illustration of security mechanisms, innovative business models, market opportunities, and societal/economic impacts resulting from the soon-to-be-deployed CAVs. This book contains an archival collection of top quality, cutting-edge and multidisciplinary research on connected autonomous electric vehicles and smart cities. The book is an authoritative reference for smart city decision makers, automotive manufacturers, utility operators, smart-mobility service providers, telecom operators, communications engineers, power engineers, vehicle charging providers, university professors, researchers, and students who would like to learn more about the advances in CAEVs connectivity, autonomy, electrification, security, and integration into smart cities and intelligent transportation systems.
Publisher: CRC Press
ISBN: 1000259250
Category : Technology & Engineering
Languages : en
Pages : 636
Book Description
This book presents a comprehensive coverage of the five fundamental yet intertwined pillars paving the road towards the future of connected autonomous electric vehicles and smart cities. The connectivity pillar covers all the latest advancements and various technologies on vehicle-to-everything (V2X) communications/networking and vehicular cloud computing, with special emphasis on their role towards vehicle autonomy and smart cities applications. On the other hand, the autonomy track focuses on the different efforts to improve vehicle spatiotemporal perception of its surroundings using multiple sensors and different perception technologies. Since most of CAVs are expected to run on electric power, studies on their electrification technologies, satisfaction of their charging demands, interactions with the grid, and the reliance of these components on their connectivity and autonomy, is the third pillar that this book covers. On the smart services side, the book highlights the game-changing roles CAV will play in future mobility services and intelligent transportation systems. The book also details the ground-breaking directions exploiting CAVs in broad spectrum of smart cities applications. Example of such revolutionary applications are autonomous mobility on-demand services with integration to public transit, smart homes, and buildings. The fifth and final pillar involves the illustration of security mechanisms, innovative business models, market opportunities, and societal/economic impacts resulting from the soon-to-be-deployed CAVs. This book contains an archival collection of top quality, cutting-edge and multidisciplinary research on connected autonomous electric vehicles and smart cities. The book is an authoritative reference for smart city decision makers, automotive manufacturers, utility operators, smart-mobility service providers, telecom operators, communications engineers, power engineers, vehicle charging providers, university professors, researchers, and students who would like to learn more about the advances in CAEVs connectivity, autonomy, electrification, security, and integration into smart cities and intelligent transportation systems.