Development of a tire model based on an analysis of tire strain obtained by an intelligent tire system

Tires perform important roles, such as supporting weight and generating forces during accelerating or braking. However, the direct acquisition of valuable data from tires is limited because of the nonlinearity and complex composition of tires. Recently, an intelligent tire system was developed to obtain tire-related variables directly from tire strain. The strain of the tire is measured using a strain sensor; strain is then transformed to other valuable variables, such as the vertical load and the road friction coefficient. However, to develop the conversion logic needed to obtain tire-related variables from the strain, costly and extensive experiments are needed. In this study, we propose a novel tire model and an intelligent tire simulation to reduce the effort and cost for developing an intelligent tire system. Based on experimental data, a tire model, one that can reflect the relationships between driving conditions and tire strain, was derived. And, using a set of polynomial equations comprised of the decisive parameters, a simple algebraic model was developed to yield light computational load. Finally, it was verified that the proposed tire model can correctly estimate not only the tire strain but also the 1st differential values of tire strain.