| In order to better meet the needs for external load adaptability, Construction Vehicle hydraulic drive system used in mechanical transmission, however, Hydro-mechanical transmission of the transmission efficiency is relatively lower than mechanical transmission, especially when the load needs high-intensity transient powertrain, transmission efficiency will be significantly decreased, make the operating efficiency, resulted in the waste of energy. In order to solve this problem, in this paper, controlling strategy of NNC for RBF neural network to controlling automatic energy-saving shift for Construction Vehicle.Research control theory and learning algorithm of the RBF neural network based on the energy shift of four parameters in Construction vehicle in this paper, controlling strategy of NNC for RBF neural networkcontrol strategy, the working oil pressure, torque converter turbine speed and wheel speed as the input pump, shift in the output of the RBF neural network model, training samples used to study the model training, in the MATLAB simulation environment for the conduct of the examination, vehicles through the work electronically controlled automatic transmission test bench tests carried out, simulation and experimental results verify the construction vehicle automatic transmission nearest neighbor clustering algorithm for RBF neural network control strategy is feasible, Strategy based on the automatic transmission control system to solve the problem to identify the best gear, timely and accurately meet the requirements of automatic shift of vehicles, and transmission system to ensure efficient working, so as to achieve energy-saving purpose. The full text is divided into five chapters, including the following:1,Put forward the purpose of research. Research project on automatic transmission vehicles practical significance. Research on automatic transmission vehicles engineering principles, analysis of the engineering vehicle and the vehicle's automatic transmission links and the difference between, pointed out that the construction vehicle automatic transmission in key technologies. Introduced the automatic transmission vehicle engineering technology research at home and abroad. Put forward the main research contents of this article.2,Introduced the structure of the transmission system for ZL50 wheel loader. Research project the characteristics of the vehicle torque converter, working principle, torque converter on a mathematical model, analysis of its original features, hydraulic torque converter to find out the causes of inefficiency. Research on the construction vehicles of the principle of shifting the four parameters, the optimum shift points and control parameters, work in combination with hydraulic torque converter efficiency when the two areas, put forward a solution to inefficient torque converter program.3,Researched the theory controlled and learning algorithm for RBF neural network in-depth, NNC for RBF neural network control strategy, its automatic transmission vehicles for engineering feasibility of the theoretical analysis, demonstrates the feasibility of such a control strategy. The establishment of a construction vehicle automatic transmission nearest neighbor clustering algorithm for RBF neural network control model, training samples used for training the network model of learning, and in the MATLAB environment to test the simulation model, the simulation results show the network model built for construction vehicles to control automatic transmission has a strong feasibility, accuracy and reliability, In order to show that the nearest neighbor-clustering algorithm for RBF neural network control strategy to automatic transmission vehicles to carry out the project under control.4,The use of works electronically controlled automatic transmission vehicle test-bed for the four parameters of energy-saving strategies and work-shift automatic transmission vehicles nearest neighbor clustering algorithm for RBF neural network control strategy was tested to verify. ECU test is divided into test and self-learning automatic transmission ECU controlled trial of two parts. Concluded by the test: Engineering Vehicles shift four-parameter energy-saving strategy is feasible; Nearest neighbor clustering algorithm for RBF neural network control strategy can be used to control automatic transmission, timely and accurately meet the requirements of automatic shift of vehicles, and to ensure high efficiency torque converter area often work, so as to achieve the purpose of energy conservation. |
