Abstract: Aiming at the complexity and nonlinear characteristics of FlexRay vehicle network control system, the limited network bandwidth resources result in the uncertainty of data transmission and the delay of data transmission, which makes the FlexRay network control performance degrade when the data is transmitted at high speed. Neural network has the ability of self-learning, adaptive and global approximation. In order to improve the performance of FlexRay vehicle network control, a neural network control method based on network bandwidth utilization is proposed. First, the structure of the neural network model reference control system is analyzed. Secondly, the neural network model reference controller of the FlexRay vehicle network is designed.In the case of load, the performance of the controller is simulated by using Simulink in Matlab software. The simulation results show that the controller can effectively improve the performance of FlexRay vehicle network control and have good adaptability to the change of the parameters of the control object.

Key words: FlexRay, neural network, model reference control, Simulink