Abstract
dc:description.abstractIn the design of tyres, rolling resistance and wear resistance cannot be optimized at the same time. Tyres with high rolling resistance have good wear performance and good adhesion, whereas tyres with low resistance have poor wear performance and poor adhesion. It is therefore necessary to understand wear in order to design better tyres so as to reduce rolling resistance. Tyre wear is more serious for trucks as the tyres of multi-axle suspensions are subjected to severe abrasive wear caused by large slip angles resulted from the turning geometry. In Chapter 1, studies about tyre wear are reviewed. Most of the studies focused on car tyre wear. No systematic study of severe abrasive truck tyre wear has been found in the open literature. A model needs to be developed and validated to accurately predict severe abrasive truck tyre wear. In this project, a conventional trailer tyre, Goodyear KMax T Gen 2, and a low-rolling-resistance trailer tyre, Goodyear FuelMax T, are studied and compared. In Chapter 2, a tyre wear model is developed by combining physical models of tyre rolling contact, including the ‘brush’ model and the ‘string’ model, with a local wear law. The physical models simulate the contact conditions of tyres subjected to large slip angles. Surface tractions and sliding speeds are calculated. Combining these outputs with a local wear law - which describes the wear rate as a function of surface tractions, sliding speed, contact temperature, surface roughness, etc, - wear of a single tyre is calculated. Contact pressure distributions used in the models are measured in Chapter 3 and the necessary tyre tread-band stiffness parameters are simulated in Chapter 5. In Chapter 4, a laboratory test rig to measure the local wear law on different surfaces is designed. Rubber samples are pressed against a rough moving platen at various vertical pressures and sliding speeds. Contact temperatures are monitored using an infrared camera and controlled within a range by intermittent loading. The mass loss of each sample is measured to determine the wear rate. It is found that wear rate is proportional to vertical pressure, and increases linearly with sliding speed with a positive intercept. Wear rate is found not to be sensitive to temperature up to 80⁰C. Two microscopic models are developed to explain different aspects of the observed local wear behaviour. In Chapter 6, a test track test using a special trailer with steerable axles is presented for the verification of the tyre wear model. Two axles of the trailer are steered at the same angle but opposite directions and the trailer is towed along to form two trails of rubber wear particles. The rubber particles deposited over a fixed area are collected and weighted. The wear model simulation results are found to fit well with measurements with a scale factor accounting for the difference between the abrasion characteristics of the asphalt surface and the laboratory test rig. An empirical model is also summarized using the measurement data. In Chapter 7, an in-service vehicle test is presented. Two identical tractors and trailers are equipped with new tyres of each type and are instrumented to measure their motion, driver inputs, tyre pressures and temperatures, engine performance, and many other quantities. All journeys of the two vehicles are recorded for a period of about 18 months and regular measurements of tread depths of each tyre are carried out. A vehicle wear model is developed to simulate the tyre-related variables and tyre wear during the journeys. The simulated wear is converted into tread depths and compared with the tread depth measurements. Both the tyre wear model and the empirical law are used with the vehicle model for wear calculations, and both results fit the measured tread depths well, with scale factors accounting for differences in the abrasive properties of the road surfaces. The scale factors for the tyre wear model are closer than the empirical law, indicating the model predicts more consistent results. Finally, conclusions are drawn in Chapter 8 and recommendations are made for future work.
Degree
thesis:*- Name dc:type.qualificationname
- Doctor of Philosophy (PhD)
- Level dc:type.qualificationlevel
- Doctoral
- Grantor dc:publisher.institution
- University of Cambridge
- Year dc:date.issued
- 2024
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Liu, Chen
- Advisor dc:contributor.advisor
-
- Cebon, David
Subjects
dc:subject × 6Rights
dc:rightsIdentifiers
dc:identifier.*- DOI dc:identifier.doi
- https://doi.org/10.17863/CAM.111100
- OAI identifier oai:identifier
- oai:www.repository.cam.ac.uk:1810/372218