On-Line Prediction of Resistant Force During Soil–Tool Interaction

Author:

Yu Sencheng1,Song Xingyong23,Sun Zongxuan4

Affiliation:

1. Controls and Mechatronics Research Lab, Department of Mechanical Engineering, Texas A&M University , College Station, TX 77843

2. Controls and Mechatronics Research Lab, Department of Engineering Technology and Industrial Distribution, Texas A&M University , College Station, TX 77843; , College Station, TX 77843

3. Department of Mechanical Engineering, Texas A&M University, College Station, TX 77843; Department of Electrical and Computer Engineering, Texas A&M University , College Station, TX 77843; , College Station, TX 77843

4. Center of Compact and Efficient Fluid Power, Department of Mechanical Engineering, University of Minnesota , Minneapolis, MN 55455

Abstract

Abstract For off-road vehicles such as excavators and wheel loaders, a large portion of energy is consumed to overcome the soil resistant force in the digging process. For optimal control of the digging tool, a high-fidelity model of the soil–tool interaction force is important to reduce energy consumption. In this paper, an on-line soil resistant force prediction method is proposed. In this method, a hybrid model, which combines a physical model and a data-driven model, is used for the force prediction. In addition, the parameters of the hybrid model can be updated on-line based on real-time data. Comparisons with experimental data demonstrate that the proposed prediction method has an average error of around 12.7%.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Reference17 articles.

1. Optimal Control of Wheel Loader Actuators in Gravel Applications;Autom. Construction,2018

2. Bucket Trajectory Optimization Under the Automatic Scooping of LHD;Energies,2019

3. The Fundamental Equation of Earth-Moving Mechanics;Proc. Inst. Mech. Eng.,1964

4. Modeling and Identification of Soil-Tool Interaction in Automated Excavation,1998

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