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Technologies and technical equipment for agriculture and food industry

Volume

Volume 76 / No. 2 / 2025

Pages : 1074-1091

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LIGHTWEIGHT RESEARCH OF FORESTRY UNMANNED VEHICLE SWING ARMS BASED ON MULTI-CONDITION TOPOLOGY OPTIMIZATION OF CONTINUUM STRUCTURES

基于连续体结构多工况拓扑优化的林业无人车辆摆臂轻量化研究

DOI : https://doi.org/10.35633/inmateh-76-91

Authors

Yihan QIN

The School of Technology, Beijing Forestry University, Beijing, China

Yilu ZHAO

The School of Technology, Beijing Forestry University, Beijing, China

Qiang CHEN

The School of Technology, Beijing Forestry University, Beijing, China

Ji WU

The School of Technology, Beijing Forestry University, Beijing, China

Zhongjia CHEN

The School of Technology, Beijing Forestry University, Beijing, China

Qingchun WANG

The School of Technology, Beijing Forestry University, Beijing, China

(*) Xiangyue YUAN

The School of Technology, Beijing Forestry University, Beijing, China

(*) Corresponding authors:

yuanxiangyue@bjfu.edu.cn |

Xiangyue YUAN

Abstract

To meet the demanding terrain of China’s forest regions—characterized by obstacles, gullies, and uneven ground—a wheel-leg hybrid chassis is proposed for a three-axle unmanned electric forestry vehicle. Parametric modelling in SolidWorks and dynamic simulations in MSC Adams quantified the critical load cases on the swing arms during obstacle negotiation. The Analytic Hierarchy Process (AHP) assigned optimal weights for multi-scenario topology optimisation. A finite-element model of the arms was built in HyperMesh/OptiStruct; post-optimisation analyses confirmed structural integrity. Masses of the front and rear arms converged to 31.3 kg each, and the middle arm to 39.44 kg, realising weight reductions of 29.1 % and 21.7 %, respectively, with no loss in performance.

Abstract in Chinese

为应对中国大陆林区存在众多障碍物和沟壑等林业作业条件所带来的挑战,本文提出了一种适用于林业三轴无人电动车辆的轮腿式混合行走机构。利用SolidWorks和MSC Adams软件进行了参数化建模和动力学仿真,以分析车辆摆臂在越障过程中所经历的多种典型载荷工况,运用层次分析法(AHP)确定了多工况拓扑优化的最优权重系数分配。使用Hypermesh-Optistruct软件建立了摆臂的有限元模型,并对优化后的摆臂进行了有限元分析。优化后的前、后摆臂重量均为31.3千克,中摆臂重量为39.44千克,重量分别降低了29.1%和21.7%,取得了良好的轻量化效果。

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