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Intelligent Tire Systems [electronic resource] / by Nan Xu, Hassan Askari, Amir Khajepour.

By: Xu, Nan [author.].
Contributor(s): Askari, Hassan [author.] | Khajepour, Amir [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Advances in Automotive Technology: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2022Edition: 1st ed. 2022.Description: XV, 166 p. 168 illus., 130 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031102684.Subject(s): Automotive engineering | Mechanical engineering | Vehicles | Automotive Engineering | Mechanical Engineering | Vehicle EngineeringAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 629.2 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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.
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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.

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.

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