journal article·2025-03Open access

Analysis and Optimisation of Obstacle‐Crossing Performance of Electric Shovel Based on DEM‐MBD Coupling Method

Zeren Chen, Wei Guan, Ruibin Li, Guang Li, Duomei Xue, Zhengbin Liu, Guoqiang Wang

Abstract

ABSTRACT To study and enhance the obstacle‐crossing performance of the electric shovel, an obstacle‐crossing model that employs a coupling methodology integrating the discrete element method (DEM) and multi‐body dynamics (MBD) is constructed. Secondly, the influence of grouser height (GH), track velocity (TV), slope inclination (SI) and slope height (SH) on obstacle‐crossing performance is investigated through DEM‐MBD simulation, with the objective of obtaining an obstacle‐crossing surrogate model through the Kriging method and Box‐Behnken experimental design. On this basis, two optimisation solutions for the obstacle‐crossing performance of the electric shovel are proposed based on a genetic algorithm (GA), and the corresponding obstacle‐crossing performances are analysed. The results demonstrate that the coupling effect between SI and SH exerts a considerable influence on the ground pressure coefficient (GPC), power and disturbance potential energy (DPE). When the optimal TV and GH are set at 0.1 m/s and 9.38 mm, the GPC, power and disturbance kinetic energy (DKE) are observed to diminish to varying degrees, thereby indicating that the obstacle‐crossing performance of the electric shovel has been enhanced.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Soil Mechanics and Vehicle Dynamics · Granular flow and fluidized beds · Agricultural Engineering and Mechanization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Mechanical Engineering Taiyuan University of Technology Taiyuan PR China

School of Mechanical and Aerospace Engineering Jilin University Changchun PR China

Taiyuan Heavy Industry Co LTD Taiyuan PR China

College of Chemical Engineering and Technology Taiyuan University of Science and Technology Taiyuan PR China

Funding

National Natural Science Foundation of China

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