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

Sencheng Yu, Xingyong Song, Zongxuan Sun

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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%.

Original languageEnglish (US)
Article number081004
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume145
Issue number8
DOIs
StatePublished - Aug 1 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
Copyright © 2023 by ASME.

Keywords

  • data-driven model
  • fundamental earthmoving equation
  • off-road vehicle
  • soil–tool interaction forces

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