The contact between the tire and the road is the key enabler of vehicle acceleration, deceleration and steering. However, under the circumstances of sudden changes to the road conditions, the driver`s ability to maintain control of the vehicle maybe at risk. In many cases, this requires intervention from the chassis control systems onboard the vehicle. Although these systems perform well in a variety of situations, their performance can be improved if a real-time estimate of the tire-road contact parameters (ranging from kinematic conditions of the tire to its dynamic properties) are available. At the present stage of development, tire-road contact parameters are indirectly estimated using observers based on vehicle dynamics measurements (acceleration, yaw and roll rates, suspension deflections, etc). Although these methods present a relatively accurate solution, they rely heavily on tire and vehicle kinematic formulations and break down in case of abrupt changes in the measured quantities.
To address this problem, researchers have been developing certain sensor based advanced tire concepts for direct measurement of the tire-road contact parameters. Thus the new terms "Intelligent Tire" and "Smart Tire", which mean online tire monitoring are thus enjoying increasing popularity among automotive manufacturers and formed the motivation for this thesis to explore the possibility of developing an intelligent tire system. The development of the so called "intelligent tire/ smart tire system" is expected to spur the development of a new generation of vehicle control system with modified control strategies, leveraging information directly coming from the interface between the tire and the road, and in turn significantly reducing the risk of accidents.
The specific contributions of this thesis include the following:
• Development of an intelligent tire system, with a special attention to development of measurement and sensor feature extraction methodologies of acceleration signals coming from sensors fixed to the tire innerliner
• Design of an integrated vehicle state estimator for application to global chassis control
• Development of a model-based tire-road friction estimation algorithm
• Development of an intelligent tire based adaptive wheel slip controller for anti-lock brake system (ABS)
• Development of a piezoelectric vibration energy harvesting system with an adaptive frequency tuning mechanism for intelligent tires / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/76959 |
| Date | 27 January 2012 |
| Creators | Singh, Kanwar Bharat |
| Contributors | Mechanical Engineering, Taheri, Saied, Priya, Shashank, Ferris, John B. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Type | Thesis, Text |
| Format | application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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