Based on RBF Neural Network Gasoline Transient Conditions Oil Film Parameter of Gasoline Engine Soft Predicted Measurements Research

It is too difficult to determin oil film parameter in the case of transient conditions, but this paper presents a method, Chaos Radial Basis Function (RBF) neural network gasoline engine transient conditions the film parameter identification method. It shows the chaotic RBF neural network model has stronger nonlinear identification capability,this model can improve the identification accuracy of oil film parameter dynamic effectively, And then come to the oil film parameter dynamic characteristics of the different conditions.