Cyber-Physical Vehicle Systems: Methodology and Applications (Synthesis Lectures on Advances in Automotive Technology, 10)
Language: English
Published by Morgan & Claypool Publishers, 2020
- Softcover
- New

Condition: New
£ 45.85
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- Title
- Cyber-Physical Vehicle Systems: Methodology and Applications (Synthesis Lectures on Advances in Automotive Technology, 10)
- Author
- Lv, Chen; Xing, Yang; Zhang, Junzhi
- Publisher
- Morgan & Claypool Publishers
- Publication year
- 2020
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1681737310
- ISBN 13
- 9781681737317
- Item weight
- 12 ounces
This book studies the design optimization, state estimation, and advanced control methods for cyber-physical vehicle systems (CPVS) and their applications in real-world automotive systems.
First, in Chapter 1, key challenges and state-of-the-art of vehicle design and control in the context of cyber-physical systems are introduced. In Chapter 2, a cyber-physical system (CPS) based framework is proposed for high-level co-design optimization of the plant and controller parameters for CPVS, in view of vehicle's dynamic performance, drivability, and energy along with different driving styles. System description, requirements, constraints, optimization objectives, and methodology are investigated. In Chapter 3, an Artificial-Neural-Network-based estimation method is studied for accurate state estimation of CPVS. In Chapter 4, a high-precision controller is designed for a safety-critical CPVS. The detailed control synthesis and experimental validation are presented. The application results presented throughout the book validate the feasibility and effectiveness of the proposed theoretical methods of design, estimation, control, and optimization for cyber physical vehicle systems.
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About the Author
Yang Xing received his Ph.D. from Cranfield University, UK, in 2018. He is currently a research fellow with the department of mechanical and aerospace engineering at Nanyang Technological University, Singapore. His research interests include machine learning, driver behavior modeling, intelligent multiagent collaboration, and intelligent/autonomous vehicles. His work focuses on the understanding of driver behaviors using machine-learning methods and intelligent and automated vehicle design. He received the IV2018 Best Workshop/Special Issue Paper Award. Dr. Xing serves as a Guest Editor for IEEE Internet of Things, and he is an active reviewer for IEEE Transactions on Vehicular Technology, Industrial Electronics, and Intelligent Transportation Systems.
Junzhi Zhang received his B.E. in Transportation Engineering and his M.S. and Ph.D. in Vehicle Engineering from the Jiliin University of Technology, Changchun, China in 1992, 1995, and 1997, respectively. From 1998–1999, Dr. Zhang was a Research Associate in Department of Automotive Engineering in Tsinghua University, Beijing, China. In 1999, Dr. Zhang joined Tsinghua University and founded the Hybrid Powertrain Systems Laboratory whose major research interests include modeling, control and diagnosis of hybrid, electric vehicle. Dr. Zhang become a full professor in Department of Automotive Engineering in Tsinghua University in 2008. Dr. Zhang is the author or co-author of more than 50 peer-reviewed publications and 20 Chinese patents.
Dongpu Cao received his Ph.D. from Concordia University, Canada, in 2008. He is currently an Associate Professor at Mechanical and Mechatronics Engineering, University of Waterloo, Canada. His research focuses on vehicle dynamics and control, automated driving and parallel driving, where he has contributed more than 100 publications and 1 US patent. He received the ASME AVTT'2010 Best Paper Award and 2012 SAE Arch T. Colwell Merit Award. Dr. Cao serves as an Associate Editor for IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Vehicular Technology, IEEE Transactions on Industrial Electronics, IEEE/ASME Transactions on Mechatronics, and ASME Journal of Dynamic Systems, Measurement, and Control. He has been a Guest Editor for Vehicle System Dynamics, and IEEE Transactions on Human-Machine Systems. He serves on the SAE International Vehicle Dynamics Standards Committee and a few ASME, SAE, and IEEE technical committees.
Amir Khajepour is a professor of mechanical and mechatronics engineering at the University of Waterloo. He holds the Canada Research Chair in Mechatronic Vehicle Systems, and NSERC/General Motors Industrial Research program that applies his expertise in several key multidisciplinary areas including system modeling and control of dynamic systems. His research has resulted in many patents and technology transfers. He is the author of more than 400 journal and conference publications as well as several books. He is a Fellow of the Engineering Institute of Canada, the American Society of Mechanical Engineers, and the Canadian Society of Mechanical Engineering.
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