Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles

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Author :
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1636393020
Total Pages : 135 pages
Book Rating : 4.6/5 (363 download)

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Book Synopsis Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles by : Yeuching Li

Download or read book Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles written by Yeuching Li and published by Morgan & Claypool Publishers. This book was released on 2022-02-14 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: The urgent need for vehicle electrification and improvement in fuel efficiency has gained increasing attention worldwide. Regarding this concern, the solution of hybrid vehicle systems has proven its value from academic research and industry applications, where energy management plays a key role in taking full advantage of hybrid electric vehicles (HEVs). There are many well-established energy management approaches, ranging from rules-based strategies to optimization-based methods, that can provide diverse options to achieve higher fuel economy performance. However, the research scope for energy management is still expanding with the development of intelligent transportation systems and the improvement in onboard sensing and computing resources. Owing to the boom in machine learning, especially deep learning and deep reinforcement learning (DRL), research on learning-based energy management strategies (EMSs) is gradually gaining more momentum. They have shown great promise in not only being capable of dealing with big data, but also in generalizing previously learned rules to new scenarios without complex manually tunning. Focusing on learning-based energy management with DRL as the core, this book begins with an introduction to the background of DRL in HEV energy management. The strengths and limitations of typical DRL-based EMSs are identified according to the types of state space and action space in energy management. Accordingly, value-based, policy gradient-based, and hybrid action space-oriented energy management methods via DRL are discussed, respectively. Finally, a general online integration scheme for DRL-based EMS is described to bridge the gap between strategy learning in the simulator and strategy deployment on the vehicle controller.

Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles

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Author :
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1681736195
Total Pages : 99 pages
Book Rating : 4.6/5 (817 download)

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Book Synopsis Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles by : Teng Liu

Download or read book Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles written by Teng Liu and published by Morgan & Claypool Publishers. This book was released on 2019-09-03 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Hybrid Electric Vehicles

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Author :
Publisher : Springer
ISBN 13 : 1447167813
Total Pages : 121 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Hybrid Electric Vehicles by : Simona Onori

Download or read book Hybrid Electric Vehicles written by Simona Onori and published by Springer. This book was released on 2015-12-16 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief deals with the control and optimization problem in hybrid electric vehicles. Given that there are two (or more) energy sources (i.e., battery and fuel) in hybrid vehicles, it shows the reader how to implement an energy-management strategy that decides how much of the vehicle’s power is provided by each source instant by instant. Hybrid Electric Vehicles: •introduces methods for modeling energy flow in hybrid electric vehicles; •presents a standard mathematical formulation of the optimal control problem; •discusses different optimization and control strategies for energy management, integrating the most recent research results; and •carries out an overall comparison of the different control strategies presented. Chapter by chapter, a case study is thoroughly developed, providing illustrative numerical examples that show the basic principles applied to real-world situations. The brief is intended as a straightforward tool for learning quickly about state-of-the-art energy-management strategies. It is particularly well-suited to the needs of graduate students and engineers already familiar with the basics of hybrid vehicles but who wish to learn more about their control strategies.

Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles

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Author :
Publisher : Springer Nature
ISBN 13 : 3031792068
Total Pages : 123 pages
Book Rating : 4.0/5 (317 download)

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Book Synopsis Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles by : Li Yeuching

Download or read book Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles written by Li Yeuching and published by Springer Nature. This book was released on 2022-06-01 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: The urgent need for vehicle electrification and improvement in fuel efficiency has gained increasing attention worldwide. Regarding this concern, the solution of hybrid vehicle systems has proven its value from academic research and industry applications, where energy management plays a key role in taking full advantage of hybrid electric vehicles (HEVs). There are many well-established energy management approaches, ranging from rules-based strategies to optimization-based methods, that can provide diverse options to achieve higher fuel economy performance. However, the research scope for energy management is still expanding with the development of intelligent transportation systems and the improvement in onboard sensing and computing resources. Owing to the boom in machine learning, especially deep learning and deep reinforcement learning (DRL), research on learning-based energy management strategies (EMSs) is gradually gaining more momentum. They have shown great promise in not only being capable of dealing with big data, but also in generalizing previously learned rules to new scenarios without complex manually tunning. Focusing on learning-based energy management with DRL as the core, this book begins with an introduction to the background of DRL in HEV energy management. The strengths and limitations of typical DRL-based EMSs are identified according to the types of state space and action space in energy management. Accordingly, value-based, policy gradient-based, and hybrid action space-oriented energy management methods via DRL are discussed, respectively. Finally, a general online integration scheme for DRL-based EMS is described to bridge the gap between strategy learning in the simulator and strategy deployment on the vehicle controller.

Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles

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Author :
Publisher : Synthesis Lectures on Advances
ISBN 13 : 9781681736204
Total Pages : 99 pages
Book Rating : 4.7/5 (362 download)

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Book Synopsis Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles by : Teng Liu

Download or read book Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles written by Teng Liu and published by Synthesis Lectures on Advances. This book was released on 2019-09-03 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Proceedings of China SAE Congress 2020: Selected Papers

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Author :
Publisher : Springer Nature
ISBN 13 : 9811620903
Total Pages : 1670 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Proceedings of China SAE Congress 2020: Selected Papers by : China Society of Automotive Engineers

Download or read book Proceedings of China SAE Congress 2020: Selected Papers written by China Society of Automotive Engineers and published by Springer Nature. This book was released on 2022-01-13 with total page 1670 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings gather outstanding papers presented at the China SAE Congress 2020, held on Oct. 27-29, Shanghai, China. Featuring contributions mainly from China, the biggest carmaker as well as most dynamic car market in the world, the book covers a wide range of automotive-related topics and the latest technical advances in the industry. Many of the approaches in the book will help technicians to solve practical problems that affect their daily work. In addition, the book offers valuable technical support to engineers, researchers and postgraduate students in the field of automotive engineering.

Deep Reinforcement Learning

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Author :
Publisher : Springer Nature
ISBN 13 : 9811540950
Total Pages : 526 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Deep Reinforcement Learning by : Hao Dong

Download or read book Deep Reinforcement Learning written by Hao Dong and published by Springer Nature. This book was released on 2020-06-29 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine, and famously contributed to the success of AlphaGo. Furthermore, it opens up numerous new applications in domains such as healthcare, robotics, smart grids and finance. Divided into three main parts, this book provides a comprehensive and self-contained introduction to DRL. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation. The second part covers selected DRL research topics, which are useful for those wanting to specialize in DRL research. To help readers gain a deep understanding of DRL and quickly apply the techniques in practice, the third part presents mass applications, such as the intelligent transportation system and learning to run, with detailed explanations. The book is intended for computer science students, both undergraduate and postgraduate, who would like to learn DRL from scratch, practice its implementation, and explore the research topics. It also appeals to engineers and practitioners who do not have strong machine learning background, but want to quickly understand how DRL works and use the techniques in their applications.

Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management

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Author :
Publisher : Elsevier
ISBN 13 : 0443131902
Total Pages : 348 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management by : Jili Tao

Download or read book Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management written by Jili Tao and published by Elsevier. This book was released on 2024-06-07 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management presents the state-of-the-art in hybrid electric vehicle system modelling and management. With a focus on learning-based energy management strategies, the book provides detailed methods, mathematical models, and strategies designed to optimize the energy management of the energy supply module of a hybrid vehicle.The book first addresses the underlying problems in Hybrid Electric Vehicle (HEV) modeling, and then introduces several artificial intelligence-based energy management strategies of HEV systems, including those based on fuzzy control with driving pattern recognition, multi objective optimization, fuzzy Q-learning and Deep Deterministic Policy Gradient (DDPG) algorithms. To help readers apply these management strategies, the book also introduces State of Charge and State of Health prediction methods and real time driving pattern recognition. For each application, the detailed experimental process, program code, experimental results, and algorithm performance evaluation are provided.Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management is a valuable reference for anyone involved in the modelling and management of hybrid electric vehicles, and will be of interest to graduate students, researchers, and professionals working on HEVs in the fields of energy, electrical, and automotive engineering. Provides a guide to the modeling and simulation methods of hybrid electric vehicle energy systems, including fuel cell systems Describes the fundamental concepts and theory behind CNN, MPC, fuzzy control, multi objective optimization, fuzzy Q-learning and DDPG Explains how to use energy management methods such as parameter estimation, Q-learning, and pattern recognition, including battery State of Health and State of Charge prediction, and vehicle operating conditions

Data-driven Reinforcement Learning-based Real-time Energy Management System for Plug-in Hybrid Electric Vehicles

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Author :
Publisher :
ISBN 13 :
Total Pages : 23 pages
Book Rating : 4.:/5 (982 download)

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Book Synopsis Data-driven Reinforcement Learning-based Real-time Energy Management System for Plug-in Hybrid Electric Vehicles by :

Download or read book Data-driven Reinforcement Learning-based Real-time Energy Management System for Plug-in Hybrid Electric Vehicles written by and published by . This book was released on 2016 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: Plug-in hybrid electric vehicles (PHEVs) show great promise in reducing transportation-related fossil fuel consumption and greenhouse gas emissions. Designing an efficient energy management system (EMS) for PHEVs to achieve better fuel economy has been an active research topic for decades. Most of the advanced systems rely either on a priori knowledge of future driving conditions to achieve the optimal but not real-time solution (e.g., using a dynamic programming strategy) or on only current driving situations to achieve a real-time but nonoptimal solution (e.g., rule-based strategy). This paper proposes a reinforcement learning-based real-time EMS for PHEVs to address the trade-off between real-time performance and optimal energy savings. The proposed model can optimize the power-split control in real time while learning the optimal decisions from historical driving cycles. Here, a case study on a real-world commute trip shows that about a 12% fuel saving can be achieved without considering charging opportunities; further, an 8% fuel saving can be achieved when charging opportunities are considered, compared with the standard binary mode control strategy.

Vehicle Power Management

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Publisher : Springer Science & Business Media
ISBN 13 : 0857297368
Total Pages : 353 pages
Book Rating : 4.8/5 (572 download)

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Book Synopsis Vehicle Power Management by : Xi Zhang

Download or read book Vehicle Power Management written by Xi Zhang and published by Springer Science & Business Media. This book was released on 2011-08-12 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vehicle Power Management addresses the challenge of improving vehicle fuel economy and reducing emissions without sacrificing vehicle performance, reliability and durability. It opens with the definition, objectives, and current research issues of vehicle power management, before moving on to a detailed introduction to the modeling of vehicle devices and components involved in the vehicle power management system, which has been proven to be the most cost-effective and efficient method for initial-phase vehicle research and design. Specific vehicle power management algorithms and strategies, including the analytical approach, optimal control, intelligent system approaches and wavelet technology, are derived and analyzed for realistic applications. Vehicle Power Management also gives a detailed description of several key technologies in the design phases of hybrid electric vehicles containing battery management systems, component optimization, hardware-in-the-loop and software-in-the-loop. Vehicle Power Management provides graduate and upper level undergraduate students, engineers, and researchers in both academia and the automotive industry, with a clear understanding of the concepts, methodologies, and prospects of vehicle power management.

Vehicle Propulsion Systems

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Publisher : Springer Science & Business Media
ISBN 13 : 3540746927
Total Pages : 345 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Vehicle Propulsion Systems by : Lino Guzzella

Download or read book Vehicle Propulsion Systems written by Lino Guzzella and published by Springer Science & Business Media. This book was released on 2007-09-21 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors of this text have written a comprehensive introduction to the modeling and optimization problems encountered when designing new propulsion systems for passenger cars. It is intended for persons interested in the analysis and optimization of vehicle propulsion systems. Its focus is on the control-oriented mathematical description of the physical processes and on the model-based optimization of the system structure and of the supervisory control algorithms.

Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019

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Publisher : Springer Nature
ISBN 13 : 9811528624
Total Pages : 869 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019 by : Limin Jia

Download or read book Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019 written by Limin Jia and published by Springer Nature. This book was released on 2020-04-07 with total page 869 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reflects the latest research trends, methods and experimental results in the field of electrical and information technologies for rail transportation, which covers abundant state-of-the-art research theories and ideas. As a vital field of research that is highly relevant to current developments in a number of technological domains, the subjects it covered include intelligent computing, information processing, Communication Technology, Automatic Control, etc. The objective of the proceedings is to provide a major interdisciplinary forum for researchers, engineers, academicians as well as industrial professionals to present the most innovative research and development in the field of rail transportation electrical and information technologies. Engineers and researchers in academia, industry, and the government will also explore an insight view of the solutions that combine ideas from multiple disciplines in this field. The volumes serve as an excellent reference work for researchers and graduate students working on rail transportation, electrical and information technologies.

Intelligent Renewable Energy Systems

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Publisher : John Wiley & Sons
ISBN 13 : 1119786274
Total Pages : 484 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Intelligent Renewable Energy Systems by : Neeraj Priyadarshi

Download or read book Intelligent Renewable Energy Systems written by Neeraj Priyadarshi and published by John Wiley & Sons. This book was released on 2022-01-19 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.

Advances in Theoretical and Computational Energy Optimization Processes

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Author :
Publisher : MDPI
ISBN 13 : 3039366386
Total Pages : 422 pages
Book Rating : 4.0/5 (393 download)

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Book Synopsis Advances in Theoretical and Computational Energy Optimization Processes by : Ferdinando Salata

Download or read book Advances in Theoretical and Computational Energy Optimization Processes written by Ferdinando Salata and published by MDPI. This book was released on 2020-12-29 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paradigm in the design of all human activity that requires energy for its development must change from the past. We must change the processes of product manufacturing and functional services. This is necessary in order to mitigate the ecological footprint of man on the Earth, which cannot be considered as a resource with infinite capacities. To do this, every single process must be analyzed and modified, with the aim of decarbonising each production sector. This collection of articles has been assembled to provide ideas and new broad-spectrum contributions for these purposes.

Connected and Autonomous Vehicles in Smart Cities

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Author :
Publisher : CRC Press
ISBN 13 : 1000258971
Total Pages : 517 pages
Book Rating : 4.0/5 (2 download)

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Book Synopsis Connected and Autonomous Vehicles in Smart Cities by : Hussein T. Mouftah

Download or read book Connected and Autonomous Vehicles in Smart Cities written by Hussein T. Mouftah and published by CRC Press. This book was released on 2020-12-17 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems

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Author :
Publisher : Elsevier
ISBN 13 : 0443238154
Total Pages : 552 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems by : Aparna Kumari

Download or read book Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems written by Aparna Kumari and published by Elsevier. This book was released on 2024-06-01 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems: Fundamentals, Technologies, and Solutions is an essential reference for energy researchers, graduate students and engineers who aim to understand the opportunities offered by artificial intelligence for the integration of electric vehicles into smart grids. This book begins by building foundational knowledge for the reader, covering the essentials of artificial intelligence and its applications for electric vehicles in a clear and holistic manner. Next, it breaks down two essential areas of application in more detail: energy management (from to energy harvesting to demand response and complex forecasting), and market strategies (including peer-to-peer, vehicle-to-vehicle, and vehicle-to-everything trading, plus the cyber-security implications). A final part provides detailed case studies and close consideration of challenges, including code and data sets for replication of techniques. Providing a clear pathway from fundamentals to practical implementation, Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems will provide multidisciplinary guidance for implementing this cutting-edge technology in the energy systems of the future. Supports fundamental understanding of artificial intelligence and its opportunities for energy system specialists Collects the real-world experiences of global experts Enables practical implementation of artificial intelligence strategies that support renewable energy integration across energy systems, markets, and grids

Recent Evolutions in Energy, Drives and e-Vehicles

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Author :
Publisher : Springer Nature
ISBN 13 : 9819707633
Total Pages : 671 pages
Book Rating : 4.8/5 (197 download)

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Book Synopsis Recent Evolutions in Energy, Drives and e-Vehicles by : Nitin K. Dhote

Download or read book Recent Evolutions in Energy, Drives and e-Vehicles written by Nitin K. Dhote and published by Springer Nature. This book was released on with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: