Modeling and Identification of Lubricated Polymer Friction Dynamics

Abstract

A systematic approach is proposed to model the dynamics of lubricated polymer friction. It starts with the development of a physical model to describe the fundamental mechanisms of the friction. The physical model then serves as the basic structure for the development of a complex model able to capture a wider spectrum of the deterministic and stochastic dynamics of friction. To assess the accuracy of the complex model, two estimation algorithms are formulated to estimate the unknown parameters in the model and to test the model against experimental data. One algorithm is based on the maximum likelihood principle to estimate the constant parameters for stationary friction dynamics, and the other based on the extended Kalman filter to estimate the time-varying parameters for nonstationary friction dynamics. The model and the algorithms are all validated through experiments. [S0022-0434(00)00601-8]