Research On Drag Reduction Strategy And Trajectory Control Of Loader Working Device

Loaders are now widely used in various industrial scenarios.With the development of modern science and technology,and the progress of people’s ideological concepts,the demand for loaders in the market is also increasing.It is particularly important to protect the environment,save energy consumption,and increase efficiency.Through investigation and analysis of the operation process of loaders,it is known that the power consumed during the shovel loading process of loaders is the highest,and the power is mainly consumed by the working device of loaders overcoming resistance to do work.Therefore,it is necessary to study the drag reduction and shovel loading of loaders;During the shovel loading operation of a loader,the vibration of its working device caused by various complex interferences can also consume energy and reduce work efficiency.Therefore,studying the trajectory control of the working device is one of the effective ways to reduce energy consumption and improve efficiency.This article mainly uses the discrete element method to analyze the simulation cost of loader shovel loading operation process,and studies the trajectory control of the working device using intelligent control methods to reduce drag shovel loading and improve efficiency.The main research content is as follows:(1)Research on the shovel loading mechanism and shovel loading resistance of loaders.Based on summarizing the shovel loading methods and material characteristics,analyze the shovel loading resistance using the principles of sliding surface and dense core.And based on soil mechanics theory,calculate the shovel loading resistance,and analyze the influencing factors of shovel loading resistance in combination with relevant theories.(2)Based on the influencing factors of shovel loading resistance,simulation experiments were conducted using EDEM software to obtain the variation pattern of shovel loading resistance.Establish a three-dimensional solid model of the loader working device using Solid Works software,and then import it into EDEM software for simulation experiments.Analyze and study the working conditions of different materials loaded with the same shovel loading method and the same material loaded with different shovel loading methods,and obtain the influence law of shovel loading method and shovel loading material on shovel loading resistance,providing a certain foundation for determining shovel loading resistance reduction strategies in the future.(3)Based on the variation law of resistance during the shovel loading process,a shovel loading trajectory is proposed to avoid dense nuclei during the horizontal shovel loading stage,and the proposed trajectory is verified.The feasibility of two drag reduction trajectories was verified using Monte Carlo method and spatial coordinate position,and the full bucket rate of the drag reduction trajectory was obtained using discrete element method and real vehicle experimental method.Determine the optimal shovel loading trajectory by analyzing and comparing the full bucket rate of simulation and actual vehicle experiments.Laying the foundation for the research on trajectory tracking control of loader working devices in the following text.(4)Aiming at the characteristics of strong coupling of loader working device system and variable shoveling resistance,a nonsingular fast terminal Sliding mode control control method based on resistance compensation is proposed to conduct trajectory tracking control research.Design a controller based on the system model and analyze its stability and convergence.Build a simulation model in Matlab/Simulink,with tracking the determined optimal trajectory as the control objective,and conduct simulation experiments.Set up a control group to conduct simulation experiments on working conditions with and without interference.The experimental results show that the proposed control method can effectively track the target trajectory.The root mean square error of trajectory tracking error is reduced to 8% and 22% of the control group data,respectively,effectively reducing shovel loading resistance and having certain robustness against external interference.