Dynamic Neural Networks for Multi-‐Body Simulation in Mechanical Systems
Tutor / director / evaluadorJ. Wiedemann, J. Neubeck
Tipo de documentoProyecto/Trabajo final de carrera
Condiciones de accesoAcceso abierto
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.