Ever stringent vehicle safety legislation and consumer expectations inspire the improvement of vehicle dynamic performance, which result in a rising number of control strategies for vehicle dynamics that rely on driving conditions. Road profiles, as the primary excitation source of vehicle systems, play a critical role in vehicle dynamics and also in public transportation. Knowledge of precise road conditions can thus be of great assistance for vehicle companies and government departments to develop proper dynamic control algorithms, and to fix roads in a timely manner and at the minimum cost, respectively. As a result, developing easy-to-use and accurate road estimation methods are of great importance in terms of reducing the cost related to vehicles and road maintenance as well as improving passenger comfort and handling capacity. A few books have already been published on road profile modeling and the influence of road unevenness on vehicle response. However, there is still roomto discuss road assessment methods based on vehicle response and how road conditions can be used to improve vehicle dynamics.

In this book, we use several generalized vehicle models to demonstrate the concepts, methods, and applications of vehicle response-based road estimation algorithms. In addition, necessary tools, algorithms, and methods are illustrated, and the benefits of the road estimation algorithms are evaluated. Furthermore, several case studies of controllable suspension systems to improve vehicle vertical dynamics are presented.

Autorentext

Yechen Qin is currently a Postdoctoral Fellow of mechanical engineering at the Beijing Institute of Technology, where he received his B. Eng and Ph.D. in 2010 and 2016, respectively. From 2013-2014, he studied at Texas A&M University as a visiting Ph.D. student. From 2017-2018, he studied at the University of Waterloo as a visiting scholar. His research interests include vehicle dynamics control, road estimation, and in-wheel motor vibration control.Hong Wang is currently a research associate of Mechanical and Mechatronics Engineering at the University of Waterloo. She received her Ph.D. from the Beijing Institute of Technology in China in 2015. Her research focuses on component sizing, modeling of hybrid powertrains, and energy management control strategies design for hybrid electric vehicles; intelligent control theory and application; and autonomous vehicles.Yanjun Huang is a Postdoctoral Fellow at the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, where he received his Ph.D. in 2016. His research interest is primarily focused on the vehicle holistic control in terms of safety, energy-saving, and intelligence, including vehicle dynamics and control, HEV/EV optimization and control,motion planning and control of connected and autonomous vehicles, and human-machine cooperative driving. He has published several books and over 50 papers in journals and conferences. He currently serves as an associate editor and editorial board member of IET Intelligent Transport System, SAE International Journal of Commercial Vehicles, International Journal of Vehicle Information and Communications, Automotive Innovation, AIME, etc.Xiaolin Tang received a B.S. in mechanics engineering and an M.S. in vehicle engineering from Chongqing University, China, in 2006 and 2009, respectively. He received a Ph.D. in mechanical engineering from Shanghai Jiao Tong University, China, in 2015. He is currently an Associate Professor at theState Key Laboratory of Mechanical Transmissions and at the Department of Automotive Engineering, Chongqing University,Chongqing, China. Heis also acommitteemanof Technical Committee on Vehicle Control and Intelligence of Chinese Association of Automation (CAA). He has led and has been involved in more than 10 research projects, such as National Natural Science Foundation of China, and has published more than 20 papers. His research focuses on Hybrid Electric Vehicles (HEVs), vehicle dynamics, noise and vibration, and transmission control.

Inhalt
Acknowledgments.- Nomenclature.- Introduction.- System Modeling.- Data-Driven Road Classification Algorithms.- Model-Based Road Estimation Algorithms.- Road Adaptive Hybrid Suspension Control.- Suspension Predictive Control Based on Road Estimation.- Conclusions.- References.- Authors' Biographies.