Modeling and simulative analysis of shifting schedule for the automatic transmission vehicle

The estimation methods of best shift schedule based on fuzzy neural network was advanced, and the shift schedule model for automatic transmission vehicle based on fuzzy neural network with Takagi-Sugeno model was established. Fuzzy logic rules with two input parameters and membership functions of the shift schedule based on the skilled driver´s experience and expert´s knowledge were established, which were modified through train mechanism of artificial neural network based on test sample. The fuzzy-BangBang control model of engine was established by utilizing difference between the real and target speed and difference changing speed. Shift schedule of automatic transmission vehicle was simulated based on fuzzy neural network and the result indicated that this shift schedule based on fuzzy neural network of Takagi-Sugeno model was established exactly and feasibility.