Speed effect to a Quarter car ARX model based on system identification

Abstract

This paper presents the effect of car speeds on a quarter car passive suspension system model dynamics. The model is identified using system identification technique, in which the input-output data are collected by running a test car on an artificial road surface with two different speeds i.e., 10 km/h and 20 km/h. The quarter car passive suspension system dynamics is assumed to have an ARX model structure and identified using linear least-square estimation algorithm. The car vertical body acceleration, which is the output variable, is measured by installing an accelerometer sensor on the car body, above the suspension. On the other hand, the car shaft acceleration, which is the input variable, is measured by installing an accelerometer sensor at the lower arm of the car suspension. The best model for the 10 km/h car speed gives the output order (na) = 4, the input order (nb) = 2, delay (d) = 1, the best fit = 90.65%, and the Akaike's Final Prediction Error (FPE) = 5.315e-06. In contrast, the 20 km/h speed results in 4th output order (na), 1st the input order (nb), 1st delay (d), the best fit of 91.05%, and 7.503e-05 Akaike's FPE. These results show that the higher speed reduces the effect of the road surface to car dynamics, which is indicated by the order of the model.