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Cyber-Physical Vehicle Systems

Methodology and Applications
Buch | Softcover
85 Seiten
2020
Morgan & Claypool Publishers (Verlag)
978-1-68173-731-7 (ISBN)
54,80 inkl. MwSt
Examines the design optimization, state estimation, and advanced control methods for cyber-physical vehicle systems (CPVS) and their applications in real-world automotive systems. The results presented validate the effectiveness of the theoretical methods of design, estimation, control, and optimization for cyber physical vehicle systems.
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.

Chen Lv is currently an Assistant Professor of School of Mechanical and Aerospace Engineering, Nanyang Technological University. He is also a Cluster Director in Future Mobility Solutions at Energy Research Institute at NTU. He received his Ph.D. from Department of Automotive Engineering, Tsinghua University, China in 2016. He was a joint Ph.D. researcher at EECS Dept., University of California, Berkeley, USA during 2014-2015, and worked as a Research Fellow at Advanced Vehicle Engineering Center, Cranfield University, UK during 2016-2018. He joined NTU and founded the Automated Driving and Human-Machine System Research Group since June 2018. His research focuses on automated driving, human-machine intelligence, and intelligent electric vehicles, where he has contributed 2 book chapters, over 90 papers, and obtained 12 granted patents. 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.

Preface
Introductions
Co-Design Optimization for Cyber-Physical Vehicle System
State Estimation of Cyber-Physical Vehicle Systems
Controller Design of Cyber-Physical Vehicle Systems
Conclusions
References
Authors' Biographies

Erscheinungsdatum
Reihe/Serie Synthesis Lectures on Advances in Automotive Technology
Mitarbeit Herausgeber (Serie): Amir Khajepour
Verlagsort San Rafael
Sprache englisch
Maße 191 x 235 mm
Gewicht 333 g
Themenwelt Technik Elektrotechnik / Energietechnik
Technik Fahrzeugbau / Schiffbau
Technik Maschinenbau
ISBN-10 1-68173-731-0 / 1681737310
ISBN-13 978-1-68173-731-7 / 9781681737317
Zustand Neuware
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