Development and optimization of a wide base FEA truck tire model for prediction of tire-road interactions

The most important aspect of any land-type vehicle is the efficiency in which it can translate energy from an engine, motor, or external source to the ground in an effort to move. Currently, the most efficient way to do so is through the use of pneumatic tires, which are the only link between the chassis and the ground interface. With recent advancements in the computational efficiency of modern computers, there has been a dynamic movement towards virtual modeling and experimentation of pneumatic tires. This thesis provides a detailed analysis of the selection, construction, validation, and possible applications for a Finite Element Analysis (FEA) based tire model. Through the use of an Adaptive Response Surface Method (ARSM) optimization algorithm, the newly constructed wide base FEA truck tire model underwent a parameter-tuning procedure of its materials until the behaviour of the virtual model closely matched the behaviour of the physical tire. The optimized tire model achieved a minimum of 1.78% error in the amount of rolling resistance force measured during steady-state driving conditions between the physical and simulated experiments. In addition, the static vertical deflection of the virtual tire model was able to be minimized to only 0.42% error in comparison to the physical tire. After the optimization process was completed, the FEA wide base truck tire model was used in virtual isolation experiments to populate an analytical in-plane and out-of-plane rigid ring model for use on rigid surfaces. This process has been completed in an effort to aid in the study, understanding and experimentation related to pneumatic tire dynamics.

Name thesis:degree_name

Master of Applied Science (MASc)

Discipline thesis:degree_discipline

Automotive Engineering

Grantor

University of Ontario Institute of Technology

Year dc:date.issued

2015

Author dc:creator

• Reid, Adam Cameron

Advisor dc:contributor.advisor

• El-Gindy, Moustafa

• FEA
• Wide-base
• Automotive
• Engineering
• Optimization

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10155/523

OAI identifier oai:identifier

oai:ontariotechu.scholaris.ca:10155/523