Sensor-embedded tires, known as intelligent tires, have been widely studied because they are believed to provide reliable and crucial information on tire-road contact characteristics e.g., slip, forces and deformation of tires. Vehicle control systems such as ABS and VSP (Vehicle Stability Program) can be enhanced by leveraging this information since control algorithms can be updated based on directly measured parameters from intelligent tire rather than estimated parameters based on complex vehicle dynamics and on-board sensor measurements. Moreover, it is also expected that intelligent tires can be utilized for the purpose of the analysis of tire characteristics, taking into consideration that the measurements from the sensors inside the tire would contain considerable information on tire behavior in the real driving scenarios. In this study, estimation methods for the tire-road contact features by utilizing intelligent tires are investigated. Also, it was discussed how to identify key tire parameters based on the fusion technology of intelligent tire and tire modeling. To achieve goals, extensive literature reviews on the estimation methods using the intelligent tire system was conducted at first. Strain-based intelligent tires were introduced and tested in the laboratory for this research.
Based on the literature review and test results, estimation methods for diverse tire-road contact characteristics such as slippages and contact forces have been proposed. These estimation methods can be grouped into two categories: statistical regressions and model based methods. For statistical regressions, synthetic regressors were proposed for the estimation of contact parameters such as contact lengths, rough contact shapes, test loads and slip angles. In the model-based method, the brush type tire model was incorporated into the estimation process to predict lateral forces. Estimated parameters using suggested methods agreed well with measured values in the laboratory environment.
By utilizing sensor measurements from intelligent tires, the tire physical characteristics related to in-plane dynamics of the tire, such as stiffness of the belt and sidewall, contact pressure distribution and internal damping, were identified based on the combination of strain measurements and a flexible ring tire model. The radial deformation of the tread band was directly obtained from strain measurements based on the strain-deformation relationship. Tire parameters were identified by fitting the radial deformations from the flexible ring model to those derived from strain measurements. This approach removed the complex and repeated procedure to satisfy the contact3 constraints between the tread and the road surface in the traditional ring model. For tires with different specifications, identification using the suggested method was conducted and their results are compared with results from conventional methods and tests, which shows good agreements. This approach is available for the tire standing still or rolling at low speeds. For tires rolling at high speeds, advanced tire model was implemented and associated with strain measurements to estimate dynamic stiffness, internal damping effects as well as dynamic pressure distributions. Strains were measured for a specific tire under various test conditions to be used in suggested identification methods. After estimating key tire parameters step by step, dynamic pressure distributions was finally estimated and used to update the estimation algorithm for lateral forces. This updated estimation method predicted lateral forces more accurately than the conventional method.
Overall, this research will serve as a stepping stone for developing a new generation of intelligent tire capable of monitoring physical tire characteristics as well as providing parameters for enhanced vehicle controls. / PHD / Tires are very crucial components in a vehicle because they are only objects in contact with the road surface on which the vehicle drive. They support the weight of the vehicle and generate forces which make the vehicle drive, stop and turn. Thus, the improvement of vehicle performances such as handling, ride quality and braking can be achieved by understanding and by optimizing tire properties as well as improving the design of the vehicle itself.
These days, diverse vehicle control systems such as anti-lock braking and cornering stability control systems have been widely adopted to improve the stability of the vehicle when it is braked or turned. These stability controls usually require information about slippages and forces occurring between the tire and the road surface. These quantities can be indirectly estimated by monitoring vehicle motions, which are measured by sensors installed on the vehicle frame. Although these traditional methods have worked successively, the control algorithms can be improved further by directly sensing the tire behaviors using sensors embedded in the tire. These sensor-embedded tires are often called as ‘intelligent tire’ because tires themselves serve as the monitoring device on driving conditions as well as conduct traditional functions. Also, the measured quantities inside the tire can be effectively used to understand tire characteristics because they have valuable information on tires, especially, mechanism how the tire deforms and generate contact forces when it rolls over the road surface.
In this research, strains are measured at the inner surface of the tire during it rolling and cornering on the flat road surface under different loads on the indoor test rig. A strain represents the relative displacement between particles. Based on experimental results, estimation algorithms for test loads, contact lengths, cornering angles and cornering forces are developed. These estimation methods can be incorporated in the vehicle control algorithm in the real driving scenario for improved vehicle controls.
A tire is a complex system comprising various composite materials, so their behaviors or characteristics show sever non-linearity which difficult to understand. They have been simplified and modeled in a various way based on diverse physical principles to understand how they are deflected and generate forces and moments during rolling on the road surface under a vertical load. These models are called ‘physical tire model’. To extract and analyze tire physical characteristics, measured strains at the inner surface are combined with these tire models. In this research, tires are modeled as a flexible ring which is supported by viscoelastic materials and this tire model called as a ‘flexible ring model’ which have been utilized to analyze vibration properties and contact phenomena of tires. Strain measurements were fed into the model and crucial tire characteristics are extracted such as tire stiffness, pressure distributions and internal damping. These properties can be used to analyze the tire performance like wear, rolling resistance, ride qualities and the capacity of cornering forces. Since intelligent tire systems are applied for the real driving situation, tire characteristics extracted in this way would have closer links to vehicle performances rather than those measured in the laboratory.
Overall, this research will serve as a stepping stone for developing a new generation of intelligent tire capable of monitoring physical tire characteristics as well as providing parameters for enhanced vehicle controls.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/88829 |
| Date | 11 October 2017 |
| Creators | Lee, Hojong |
| Contributors | Mechanical Engineering, Taheri, Saied, Sandu, Corina, Tarazaga, Pablo Alberto, Kennedy, Ronald H., Li, Kejing |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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