This text deals with the simulation of the tyre/suspension dynamics by using recurrent
dynamic neural networks. Recurrent neural networks are based on the multilayer
feedforward neural networks, by adding feedback connections between output and input
layers. The neural network can be trained with data obtained from the simulation of a
physical model created using a multi-body simulation software (SIMPACK). The results
obtained from the neural network demonstrate a good agreement that could be improved, depending on some factors, with the multi-body model simulation results. The
neural network model can be applied as a part of vehicle system model to predict system dynamic behaviour. Although the neural network model does not provide a good insight of the physical behaviour of the system, it is a useful tool to help in vehicle ride dynamics performance due to its good efficiency and accuracy in computational terms.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder. If you wish to make any use of the work not provided for in the law, please contact: firstname.lastname@example.org