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

Authors :
Sencheng Yu
Xingyong Song
Zongxuan Sun
Source :
Journal of Dynamic Systems, Measurement, & Control. Aug2023, Vol. 145 Issue 8, p1-8. 8p.
Publication Year :
2023

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%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00220434
Volume :
145
Issue :
8
Database :
Academic Search Index
Journal :
Journal of Dynamic Systems, Measurement, & Control
Publication Type :
Academic Journal
Accession number :
169934921
Full Text :
https://doi.org/10.1115/1.4062513