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    Abstract:

    Road surface excitation is an important factor in the research of vehicle riding and maneuver stability. Based on radial basis function (RBF) neural networks, a simulation research method of road surface power spectrum density (PSD) identification was put forward. A four-degree-of-freedom vehicle vibration model was set up and the PSDs for vertical acceleration and pitching angular acceleration of vehicle body centroid were got through Matlab simulation. The nonlinear mapping relation among the PSD of vehicle body centroid vertical acceleration, pitching angular acceleration and the road surface were found by RBF neural networks. The simulation results show that the proposed method has the feature of a good anti-noise performance and high identification accuracy.

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