Electric vehicles/hybrid electric vehicles (EV/HEV) commercialization is still a challenge in industries in terms of performance and cost. The performance along with cost reduction are two tradeoffs which need to be researched to arrive at an optimal solution. This book focuses on the convergence of various technologies involved in EV/HEV. The book brings together the research that is being carried out in the field of EV/HEV whose leading role is by optimization techniques with artificial intelligence (AI). Other featured research includes green drive schemes which involve the possible renewable energy sources integration to develop eco-friendly green vehicles, as well as Internet of Things (IoT)-based techniques for EV/HEVs. Electric vehicle research involves multi-disciplinary expertise from electrical, electronics, mechanical engineering and computer science. Consequently, this book serves as a point of convergence wherein all these domains are addressed and merged and will serve as a potential resource for industrialists and researchers working in the domain of electric vehicles.

This comprehensive reference text discusses simulation with case studies and realworld applications related to energy system models, the large-scale integration of renewable energy systems, electric vehicles, and energy storage systems. The text covers analysis and modeling of the large-scale integration of renewable energy systems, electric vehicles, and energy storage systems. It further discusses economic aspects useful for policy makers and industrial professionals. It covers important topics, including smart grids architectures, wide-area situational awareness (WASA), energy management systems (EMS), demand response (DR), smart grid standardization exertions, virtual power plants, battery degradation modeling, optimization approaches in modeling, and smart metering infrastructure. The book: Discusses the analysis and modeling of the large-scale integration of renewable energy systems, electric vehicles, and energy storage systems Covers issues and challenges encountered in the large-scale integration of electric vehicles, energy storage systems and renewable energy systems into future smart grid design Provides simulation with case studies and real-world applications related to energy system models, electric vehicles, and energy storage systems Discusses the integration of large renewable energy systems, with the presence of a large number of electric vehicles and storage devices/systems Discussing concepts of smart grids, together with the deployment of electric vehicles, energy storage systems and renewable energy systems, this text will be useful as a reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, renewable energy, and clean technologies. It further discusses topics, including electric grid infrastructure, architecture, interfacing, standardization, protocols, security, reliability, communication, and optimal control.

Fast-Charging Infrastructure for Electric and Hybrid Electric Vehicles Comprehensive resource describing fast-charging infrastructure in electric vehicles, including various subsystems involved in the power system architecture needed for fast-charging Fast-Charging Infrastructure for Electric and Hybrid Electric Vehicles presents various aspects of fast-charging infrastructure, including the location of fast-charging stations, revenue models and tariff structures, power electronic converters, power quality problems such as harmonics & supraharmonics, energy storage systems, and wireless-charging, electrical distribution infrastructures and planning. This book serves as a guide to learn recent advanced technologies with examples and case studies. It also considers problems that arise, and the mitigation methods involved, in fast-charging stations in global aspects and provides tools for analysis. Sample topics covered in Fast-Charging Infrastructure for Electric and Hybrid Electric Vehicles include: Selection of fast-charging stations, advanced power electronic converter topologies for EV fast-charging, wireless charging for plug-in HEV/EVs, and batteries for fast-charging infrastructure Standards for fast-charging infrastructure and power quality issues (analysis of harmonic injection and system resonance conditions due to large-scale penetration of EVs and supraharmonic injection) For professionals in electric vehicle technology, along with graduate and senior undergraduates, professors, and researchers in related fields, Fast-Charging Infrastructure for Electric and Hybrid Electric Vehicles is a useful, comprehensive, and accessible guide to gain an overview of the current state of the art.

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

The book is a collection of high-quality, peer-reviewed innovative research papers from the International Conference on Signals, Machines and Automation (SIGMA 2018) held at Netaji Subhas Institute of Technology (NSIT), Delhi, India. The conference offered researchers from academic and industry the opportunity to present their original work and exchange ideas, information, techniques and applications in the field of computational intelligence, artificial intelligence and machine intelligence. The book is divided into two volumes discussing a wide variety of industrial, engineering and scientific applications of the emerging techniques.

Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid is a comprehensive guide that delves into the intricate world of renewable energy integration and its impact on electrical systems. With the current global energy crisis and the urgent need to address climate change, this book explores the latest advancements and research surrounding optimization techniques in the realm of renewable energy. This book has a focus on nature-inspired and meta-heuristic optimization methods, and it demonstrates how these techniques have revolutionized renewable energy problem-solving and their application in real-world scenarios. It examines the challenges and opportunities in achieving a larger utilization of renewable energy sources to reduce carbon emissions and air pollutants while meeting renewable portfolio standards and enhancing energy efficiency. This book serves as a valuable resource for researchers, academicians, industry delegates, scientists, and final-year master's degree students. It covers a wide range of topics, including novel power generation technology, advanced energy conversion systems, low-carbon technology in power generation and smart grids, AI-based control strategies, data analytics, electrified transportation infrastructure, and grid-interactive building infrastructure.

Industry 4.0 Vision for the Supply of Energy and Materials Explore the impact of Industry 4.0 technologies on the supply chain with this authoritative text written by a leader in his field In Industry 4.0 Vision for the Supply of Energy and Materials, distinguished researcher and editor, Dr. Mahdi Sharifzadeh, delivers thematic, analytic, and applied discussions of the Industry 4.0 vision for supply chain design and operation. The book compiles all current aspects and emerging notions of Industry 4.0 into clusters of “enablers” and “analytics” of Supply Chain 4.0. Their multifaceted and highly interconnected nature is discussed at length, as are their diverse range of applications. You will discover uses of these new technologies ranging from the supply of conventional energy networks to renewables, pharmaceuticals, and additive manufacturing. You will also learn about their implications for economic prosperity and environmental sustainability. For each sector, this book scrutinizes current industrial practice and discusses developing concepts. Finally, the book concludes with potential future research directions of interest to industry practitioners and academics alike. Readers will also benefit from the inclusion of: A thorough introduction to connectivity through wireless communications and remote sensors An exploration of blockchains and smart contracts, as well as robotics and automation and cloud computing Practical discussions of supply chain analytics, including big data, machine-learning, and artificial intelligence, as well as supply chain modeling, optimization, and control A concise treatment of Industry 4.0 applications in supply chain design and operation, including the circular economy and the power industry An analysis of the oil, gas, and petrochemical industry, the pharmaceutical industry, and additive manufacturing Perfect for PhD-level and Postdoctoral researchers and industrial researchers, Industry 4.0 Vision for the Supply of Energy and Materials will also earn a place in the libraries of working professionals with an interest in the quantitative analysis of Supply Chain 4.0 concepts and techniques.

This book gathers selected papers from Artificial Intelligence and Industrial Applications (A2IA’2020), the first installment of an annual international conference organized by ENSAM-Meknes at Moulay Ismail University, Morocco. The 29 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as digital twin, multiagent systems, deep learning, image processing and analysis, control, prediction, modeling, optimization and design, as well as AI applications in industry, health, energy, agriculture, and education. The book is intended for AI experts, offering them a valuable overview and global outlook for the future, and highlights a wealth of innovative ideas and recent, important advances in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.

This book, set against the backdrop of huge advancements in artificial intelligence and machine learning within mechatronic systems, serves as a comprehensive guide to navigating the intricacies of mechatronics and harnessing its transformative potential. Mechatronics has been a revolutionary force in engineering and medical robotics over the past decade. It will lead to a major industrial revolution and affect research in every field of engineering. This book covers the basics of mechatronics, computational intelligence approaches, simulation and modeling concepts, architectures, nanotechnology, real-time monitoring and control, different actuators, and sensors. The book explains clearly and comprehensively the engineering design process at different stages. As the historical divisions between the various branches of engineering and computer science become less clearly defined, mechatronics may provide a roadmap for nontraditional engineering students studying within the traditional university structure. This book covers all the algorithms and techniques found in mechatronics engineering, well explained with real-time examples, especially lab experiments that will be very informative to students and scholars. Audience This resource is important for R & D departments in academia, government, and industry. It will appeal to mechanical engineers, electronics engineers, computer scientists, robotics engineers, professionals in manufacturing, automation and related industries, as well as innovators and entrepreneurs.