Study On The Energy-saving Control Technology Of Hydraulic Excavator Based On Fuzzy RBF Neural Networks

Hydraulic excavator work load changes frequently, leading to frequent fluctuations of engine speed, fuel consumption increased dramatically, seriously affecting the machine efficiency of excavators. With the rapid development of mechanical-electrical-hydraulic integration technology, the application of new control theories and techniques, overall control of hydraulic excavator and gradually become smarter roads, improved its energy efficiency and productivity. This paper used the existing hydraulic excavator test prototype, proposed has based on FCM model of fuzzy RBF Neural Network control algorithm on the basis of analyzing engine and variable pump power matching principle and work features; based on the method of combination between experiment and theory analysis, established the dynamics simulation model of engine and variable pump,validated the effectiveness of energy control algorithm by combining the proposed control algorithm theory model; after completed related vehicle experiment, the result of vehicle verification showed that engine speed can be stable on target speed by adopting energy saving control algorithm in the change of load, and also improved the working stability and reduces effectively fuel consumption.This essay finished the following tasks:(1) Analyzed the present status and development trend of energy-saving technology of hydraulic excavators, proposed fuzzy control based on neural network technology on the basis of analyzing engine and power matching for hydraulic system principle and working features to save energy and reduce fuel consumption.(2) Analyzed the energy-saving control method of engine, variable pump and hydraulic system; proposed the solution based on power matching and energy saving control method, and then analyze the strategy of engine speed control and variable pump with constant power.(3) Based on experimental and theoretical analysis, mathematical models with variable pump and engine-related parts were established; simulation model of the system transfer function were established; set the main parameters of the model for dynamic simulation; found the joint control requires a certain amount of correction to the system by analyzed the step signal in response to curves and root locus diagrams.(4) Analyzed typical Neural Network and fuzzy logic control; fuzzy RBF Neural Network algorithm based on FCM model were proposed; design specifically the fuzzy RBF Neural Network controller.(5) Built a simulation model of the engine used SIMULINK; verified the accuracy of simulation model of the engine based on analysis and comparison of simulation results with experimental results; built energy-saving control simulation models of the machine based on constructed variable pump and engine simulation models, which verified the validity of fuzzy RBF Network energy saving control algorithm, and finally took an experiment by used prototype.