The road surface friction is an important characteristic that must be measured accurately to navigate vehicles effectively under different conditions. This parameter is very difficult to estimate correctly as it can take up a value from a broad spectrum of possibilities and the knowledge of this characteristic is of utmost significance in modern day automotive applications. The possible real-time knowledge of friction opens a new range of improvements to the active safety systems such as the Electronic Stability Control (ESC) and Anti-lock Braking Systems (ABS) in addition to providing computerized support to safety applications. The aim of the research is to take an engineering approach to the problem and design a simple and a robust algorithm that can be implemented in any automotive application of choice. After integrating the load transfer model with the four wheel vehicle model, the Dugoff tire models are combined with the aforementioned model to represent the plant model. Using the plant model to design an emulator, the sensor measurements are created and these measurements are then used by a non linear estimator such as the Unscented Kalman Filter to predict the forces at the tires. Friction is then calculated for every iteration and then passed back into the loop.In the end, a comparison of different design methodologies, implementation techniques and performance along with design decisions are discussed so that the current work can be implemented on a real-time controller. In addition to this, a section is dedicated towards highlighting the difference that prior friction information has on the stopping distance of a vehicle. For this purpose, a demonstration is made by creating an ABS control system that uses the predicted friction information and the performance improvement is documented. / Master of Science / The goal of the research is to identify methods in which the road surface friction can be detected by the on board computers present on modern day cars. Drivers have the ability to determine the grip on the road surface through various mechanisms, for instance if a driver sees a patch of ice on the road when driving, their normal response is to take the foot off the gas and drive without giving much steering input to avoid a slide. Another input that the driver can use to assess the grip is through the 'steering feel', which is the ability to differentiate different driving conditions through the force feedback from the steering wheel.
There have been numerous approaches to help teach the computer to detect these road conditions so that it can operate other computerized systems such as the ABS(Anti-lock Braking System) and ESC( Electronic Stability Control) programs with better accuracy. This work is an attempt to contribute to this vital area of study.
At the end of the study, an algorithm to predict the dynamic estimate of friction has been developed and the improvement in the performance of the Anti-lock braking system using this friction estimate has been demonstrated
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/106643 |
| Date | 12 November 2021 |
| Creators | Rajasekaran, Darshan |
| Contributors | Mechanical Engineering, Taheri, Saied, Sandu, Corina, Akbari Hamed, Kaveh |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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