Modeling and Prediction of Vehicle Tube Hydraulic Shock Absorbers Based on BP Neural Network

Research on modeling the tube hydraulic shock absorbers is always a challenging issue. This paper presents a modeling method through BP (back-propagation) neural network established by training data from experiments. Characteristic parameters of the absorbers are as the inputs of the BP network model, while damping forces as outputs. Numerical simulations are given as examples, which demonstrate that the method is effective to predict the performance of the absorber successfully