Based On Fuzzy Neural Algorithm Of Pure Electric Vehicle EPS Control

Pure electric vehicles to achieve zero emissions, can solve the problem of car pollution to the environment, to protect the ecological environment is of great significance. But because of the pure Electric Power bus no motor and oil pump, so can only use Electric Power Steering (EPS). The developing process of steering system has experienced four phases from The Traditional Mechanical Steering System, The Conventional Hydraulic Power Steering System, The Electric-Hydraulic Steering System to The Electric Power Steering System, as well proceeding development tendency of electronic and intelligent. The EPS system is led by its advantages over the traditional steering systems in safety, environmental protection, engine efficiency, flexibility of installation, and easiness on the adjustment, in recent year, it is a hot topic and owns a promising future.Because of the EPS system is non-linear and multi-input and output system, it exist Non-linear, Time-varying and Uncertainty, the accurate mathematic model of the system is established difficulty. The traditional control theory can not solve the present problem on the Electric Power Steering system, so in this paper; the technology of fuzzy control with neural network-based is applied to the EPS system. Through the experiment of Simulink simulation, system performance is studied, such as the effects of synamic characteristic and parameter variations.In the paper, based on the current domestic and abroad research situation of EPS system, characteristics, operational principles, and structures are discussed, by analysis of dynamic, kinematics and load characteristics, a mathematic model of mechanical steering system and EPS is respectively established, the power of features and the turn of followers and the steering feel of features and the system stability is analysised theoretically; and then, a fuzzy controller with neural network-based is designed and applied to the EPS system, the simulation model of the EPS system is established; the final, through the simulation results demonstrates that the benefits of using fuzzy-neural network controller are restraining nonlinearity and parameter changes to the EPS system, improving system robustness, better meet the demands of power-assisted. Compared with the PID control, the fuzzy-neural network control has more merits, such as better robustness, letter overshoot and more powerful self-adapting capability, etc. So that the fuzzy-neural network control has good prospect in Intelligent control.