EXPERIMENTAL STUDY AND NUMERICAL MODELLING OF THE DYNAMIC BEHAVIOUR OF TYRE/SUSPENSION WHILE RUNNING OVER AN OBSTACLE

摘要

Simulation tools have been widely used to complement experimentation for suspension design in the automotive industry not only for reducing the development time, but also to allow the optimization of the vehicle performance. Both a test method and a simulation tool are presented for the analysis of Noise-Vibration-Harshness (NVH) performances of road vehicles suspension systems. A single suspension (corner) has been positioned on a rotating drum (2.6 m diameter) installed in the Laboratory for the Safety of Transport of the Politecnico di Milano. The suspension system is excited as the wheel passes over different cleats fixed to the working surface of the drum. The forces and the moments acting at the suspension-chassis joints are measured up to 250 Hz by means of five six-axis load cells. A mathematical representation that can accurately reflect tyre dynamic behaviour while passing over different cleats is fundamental for evaluating the suspension system quality (NVH) and for developing new suspension design and control strategies. Since the phenomenon is highly non-linear, it is rather difficult to predict the actual performance by using a physical model. However universal "black-box" models can be successfully used in the identification and control of non-linear systems. The paper deals with the simulation of the tyre/suspension dynamics by using Recurrent Neural Networks (RNN). RNN are derived from the Multi Layer Feed-forward Neural Networks (MLFNN), by adding feedback connections between output and input layers. The Neural Network (NN) has been trained with the experimental data obtained in the laboratory. The results obtained from the NN demonstrate very good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tyre dynamics behaviour.