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Intelligent Tire Systems - Nan XU, Hassan Askari, Amir Khajepour

Intelligent Tire Systems

Buch | Hardcover
XV, 166 Seiten
2022 | 1st ed. 2022
Springer International Publishing (Verlag)
978-3-031-10267-7 (ISBN)
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Vehicle performance is largely controlled by the tire dynamic characteristics mediated by forces and moments generated at the tire-road contact patch. The tire may undergo deformations that increase the longitudinal and lateral forces within the contact patch. It is crucial to develop a model for the accurate prediction of tire characteristics, as this will enable optimization of the overall performance of vehicles. Research has been conducted to identify new strategies for tire measurement and modeling vehicle dynamics analysis. Autonomous vehicles (AVs), electric vehicles (EVs), shared sets, and connected vehicles have further revolutionized interdisciplinary research on vehicle and tire systems. The performance and reliability of vehicle active safety and advanced driver assistance systems (ADASs) are primarily influenced by the tire force capacity, which cannot be measured. High active safety and optimized ADAS are particularly crucial for automated driving systems (ADS) to guarantee passenger safety in intelligent transportation settings. The establishment of online measurement or estimation tools for tire states, especially for autonomous vehicles, is critical.

NAN XU: Nan Xu received his B.Sc. and M.Sc. degrees from Harbin Institute of Technology in 2007 and 2009, respectively, and the Ph.D. degree in vehicle engineering from Jilin University in 2012. He is currently an Associate Professor with the State Key Laboratory of Automotive Simulation and Control, Jilin University of China. In 2019, he was a Visiting Scholar with the Department of Mechanical and Mechatronics Engineering, University of Waterloo. His current research focuses on tire dynamics and control, intelligent tires, vehicle state estimation, and motion control of electric vehicles and autonomous vehicles. HASSAN ASKARI: Hassan Askari was born in Rasht, Iran. He received his B.Sc., M.Sc., and Ph.D. degrees from the Iran University of Science and Technology, Tehran, Iran, University of Ontario Institute of Technology, Oshawa, Canada, and the University of Waterloo, Waterloo, Canada, in 2011, 2014, and 2019, respectively. He published more than 75 journals and conference papers in the areas of nonlinear vibrations, applied mathematics, nanogenerators, intelligent tires, and self-powered sensors. He co-authored one book and one book chapter both published by Springer. He is an active reviewer for more than 50 journals and an editorial board member of several scientific and international journals. AMIR KHAJEPOUR: Amir Khajepour is a Professor of mechanical and mechatronics engineering at the University of Waterloo, Waterloo, ON, Canada, where he is also the Canada Research Chair in mechatronic vehicle systems and senior NSERC/General Motors Industrial Research Chair in Holistic Vehicle Control. He has developed an extensive research program that applies his expertise in several key multidisciplinary areas. He is a fellow of The Engineering Institute of Canada, The American Society of Mechanical Engineers, and The Canadian Society of Mechanical Engineering.

Chapter 1 - Introduction to Intelligent Tires.- Chapter 2 - Tire Modeling.- Chapter 3 - Sensing Systems in Intelligent Tires.- Chapter 4 - Tire Forces Estimation in Intelligent Tire.- Chapter 5 - Machine Learning for Slip Angle and Slip Ratio Prediction.- Chapter 6 - Tire-Road Friction Estimation.

Erscheinungsdatum
Reihe/Serie Synthesis Lectures on Advances in Automotive Technology
Zusatzinfo XV, 166 p. 168 illus., 130 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 168 x 240 mm
Gewicht 481 g
Themenwelt Technik Fahrzeugbau / Schiffbau
Technik Maschinenbau
Schlagworte Autonomous Vehicles • Intelligent tire • machine learning • Sensing Systems • tire characteristics • tire force estimation • Vehicle system dynamics
ISBN-10 3-031-10267-3 / 3031102673
ISBN-13 978-3-031-10267-7 / 9783031102677
Zustand Neuware
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