Study on tire-ice traction using a combined neural network and secondary development finite element modelingmethod

摘要

Research on tire-ice traction theory is still in the basic stage, and there are large differencesbetween the current theoretical calculation and engineering practice. Because testing of pneumatictire performance on icy road is very expensive, and testing conditions are complex andvariable, testing does not have higher repeatability. In this paper, a tire-ice tractionmodel is establishedbased on a neural network and the finite-element method. Through themodel calculations,the traction characteristics of tires on ice can be well-simulated. The method of combining theLevenberg-Marquardt (LM) optimizing algorithm with the neural network is used to predict thefriction between tires and ice. The attributive characteristics of tires based on testing results arethen measured.Anonlinear finite-elementmodel of a 37×12.5R16.5 tire is established by adoptingtheYeoh model of rubber and researching existing tire-ice driving tractionmodels. This tire-icefinite-element model can predict the changes of drawbar pull and torque when driving on icyroads, and two different tire working conditions, ie, straight line and turning, are taken into considerationsimultaneously. The influence of slip ratio, speed, load on drawbar pull, and torque arealso explored.