Feasibility Study Using FE Model for Tire Load Estimation

For virtual simulation of the vehicle attributes such as handling, durability, and ride, an accurate representation of pneumatic tire behavior is very crucial. With the advancement in autonomous vehicles as well as the development of Driver Assisted Systems (DAS), the need for an Intelligent Tire Model is even more on the increase. Integrating sensors into the inner liner of a tire has proved to be the most promising way in extracting the real-time tire patch-road interface data which serves as a crucial zone in developing control algorithms for an automobile. The model under development in Kettering University (KU-iTire), can predict the subsequent braking-traction requirement to avoid slip condition at the interface by implementing new algorithms to process the acceleration signals perceived from an accelerometer installed in the inner liner on the tire. Abaqus® FEA has been used to develop the tire model and subjected to Abaqus/Explicit® analysis to study the non-linear behavior executed by a rolling tire. The strain variation at the contact under the three major situations of acceleration, braking and free rolling have been studied to develop a robust algorithm which could provide real-time contact patch situation to the vehicle GPU in order to generate the optimum traction or braking force required thus avoiding the slip situation.