Using Neural Networks to Modeling Vehicle Dynamics

Abstract

This paper is the result of a research program which focused on the statistical dynamics of vehicles. Most of the inputs of man-machine-field system have a random variation, so a systemic and statistical analysis of vehicle dynamics is obvious. In our study, data were obtained by measuring the dynamic parameters of vehicles and engines. Testing program aimed to capture a large range of operating regimes. To analyze the data the authors have used neural networks. There was adopted a NNARX (Neural Network Auto-Regressive with eXogene inputs) model with 4 inputs, 5 hidden units and 1 output. It can be concluded that the development of mathematical modeling using non-linear neural network can ensure the desired accuracy, conveniently is obtained by increasing the number of neurons in the hidden laws.

The simulation of the dynamic behaviour for an elastic mechanical transmission of passenger car

“…The maximum acceleration performances are obtained when the engine is working at the total load [6]. Similar researches of the dynamic performances simulation are presented in the papers [2,8]. The friction modelling constitutes the base of all clutch models.…”