Автор: Johannes Unger; Marcus Quasthoff; Stefan Jakubek Название: Energy Efficient Non-Road Hybrid Electric Vehicles ISBN: 3319297953 ISBN-13(EAN): 9783319297958 Издательство: Springer Рейтинг: Цена: 9141.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a systematic assessment of the performance of electric and hybrid buses in urban areas on a daily basis and presents a complete set of technical scenarios to promote their efficient exploitation.
Автор: Berg Название: Batteries for Electric Vehicles ISBN: 1107085934 ISBN-13(EAN): 9781107085930 Издательство: Cambridge Academ Рейтинг: Цена: 15365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is the first practical guide to optimizing battery usage in electric vehicles. Covering topics ranging from materials and electrochemistry to practical implementation and control, and with guidelines for battery and cell selection, this is an ideal resource for researchers in battery design and practitioners in the automotive industry.
Описание: This book addresses practical issues for commercialization of current and future electric and plug-in hybrid electric vehicles, covering power system architecture, battery technologies, battery management and interface with renewable energy, with examples.
Название: Energy systems for electric and hybrid vehicles ISBN: 1785610082 ISBN-13(EAN): 9781785610080 Издательство: Неизвестно Рейтинг: Цена: 30577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Electric and hybrid vehicles have been globally identified to be the most environmental friendly road transportation. Energy Systems for Electric and Hybrid Vehicles provides comprehensive coverage of the three main energy system technologies of these vehicles - energy sources, battery charging and vehicle-to-grid systems.
Автор: Mart?nez, Clara Marina Название: iHorizon-Enabled Energy Management for Electrified Vehicles ISBN: 0128150106 ISBN-13(EAN): 9780128150108 Издательство: Elsevier Science Рейтинг: Цена: 19370.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
iHorizon-Enabled Energy Management for Electrified Vehicles proposes a realistic solution that assumes only scarce information is available prior to the start of a journey and that limited computational capability can be allocated for energy management. This type of framework exploits the available resources and closely emulates optimal results that are generated with an offline global optimal algorithm. In addition, the authors consider the present and future of the automotive industry and the move towards increasing levels of automation. Driver vehicle-infrastructure is integrated to address the high level of interdependence of hybrid powertrains and to comply with connected vehicle infrastructure.
This book targets upper-division undergraduate students and graduate students interested in control applied to the automotive sector, including electrified powertrains, ADAS features, and vehicle automation.
Addresses the level of integration of electrified powertrains
Presents the state-of-the-art of electrified vehicle energy control
Offers a novel concept able to perform dynamic speed profile and energy demand prediction
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.
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.
Автор: Antonio Sciarretta; Ardalan Vahidi Название: Energy-Efficient Driving of Road Vehicles ISBN: 3030241262 ISBN-13(EAN): 9783030241261 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book elaborates the science and engineering basis for energy-efficient driving in conventional and autonomous cars. After covering the physics of energy-efficient motion in conventional, hybrid, and electric powertrains, the book chiefly focuses on the energy-saving potential of connected and automated vehicles. It reveals how being connected to other vehicles and the infrastructure enables the anticipation of upcoming driving-relevant factors, e.g. hills, curves, slow traffic, state of traffic signals, and movements of nearby vehicles. In turn, automation allows vehicles to adjust their motion more precisely in anticipation of upcoming events, and to save energy. Lastly, the energy-efficient motion of connected and automated vehicles could have a harmonizing effect on mixed traffic, leading to additional energy savings for neighboring vehicles. Building on classical methods of powertrain modeling, optimization, and optimal control, the book further develops the theory of energy-efficient driving. In addition, it presents numerous theoretical and applied case studies that highlight the real-world implications of the theory developed. The book is chiefly intended for undergraduate and graduate engineering students and industry practitioners with a background in mechanical, electrical, or automotive engineering, computer science or robotics.
Описание: This book elaborates the science and engineering basis for energy-efficient driving in conventional and autonomous cars. Lastly, the energy-efficient motion of connected and automated vehicles could have a harmonizing effect on mixed traffic, leading to additional energy savings for neighboring vehicles.
Автор: Sadhan Kumar Ghosh Название: Waste Management and Resource Efficiency ISBN: 9811339333 ISBN-13(EAN): 9789811339332 Издательство: Springer Рейтинг: Цена: 39130.00 р. Наличие на складе: Поставка под заказ.
Описание: The book contains high-quality research papers presented at Sixth International Conference on Solid Waste Management held at Jadavpur University, Kolkata India during November 23-26, 2016. The Conference, IconSWM 2016, is organized by Centre for Quality Management System, Jadavpur University in association with premier institutes and societies of India. The researchers from more than 30 countries presented their work in Solid Waste Management. The book is divided into two volumes and deliberates on various issues related to innovation and implementation in sustainable waste management, segregation, collection, transportation of waste, treatment technology, policy and strategies, energy recovery, life cycle analysis, climate change, research and business opportunities.
Описание: Omar Abu Mohareb proposes a novel dynamic inductor control (DIC) that can be generally applied to various DC?DC converter types. The aim is to improve the converter efficiency throughout controlling the inductance value at all operating points without consequential complexity or increase in the inductor cost and size. The dynamic inductor control implies the maximum energy transfer (MET) concept to improve the DC?DC converter efficiency and preserve a fast system dynamics against load changes at the same time.
About the Author:Omar Abu Mohareb has earned his doctoral degree in Automotive Mechatronics Engineering from University of Stuttgart. He is now active in electromobility field and its efficient and smart infrastructure concepts. He has also earned his first patent on the proposed dynamic inductor control (DIC) concept.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
