Bibliographic Details
| Title: |
LIGHTWEIGHT DESIGN OF FORKLIFT TRUCK BOOM CROSS-SECTION BASED ON MULTI-LEVEL OPTIMISATION. |
| Authors: |
Fang, Zhanpeng1,2, Zhao, Liukai1,2, Xiao, Yanqiu1,2 xiaoyanqiu@zzuli.edu.cn, Qi, Jiaqi1,2, Cui, Guangzhen1,3, Jia, Lianhui1,4, Xiao, Wei1,4 |
| Source: |
Transactions of FAMENA. 2026, Vol. 50 Issue 2, p51-72. 22p. |
| Subjects: |
Structural optimization, Forklift trucks, Optimization algorithms, Multidisciplinary design optimization, Parametric modeling, Genetic algorithms, Structural components |
| Abstract: |
To reduce the material consumption of the telescopic boom of forklift trucks, a multilevel optimisation lightweight design approach for the boom is proposed. Based on actual loading conditions, a mechanical model of the boom cross-section is established, and the design is optimised through topology optimisation. By analysing the impact of element size, volume fraction, and threshold values on the performance of the telescopic boom's cross-section, the optimal topology of its configuration is obtained. The parametric model of the boom is reconstructed based on the topology optimisation result. With the minimisation of the boom mass as the objective, and both stress and deformation as constraints, the cross-sectional parameters of the boom are optimised. The design variables are sampled by the Optimal Space-Filling (OSF) design method, and the Kriging surrogate model is used to construct a high-precision model, thereby enhancing computational efficiency and ensuring accuracy. The Multi-Objective Genetic Algorithm (MOGA) is used to solve the optimisation model and identify the optimal solution. Upon validation, the optimised boom not only reduces the mass by 8.44%, but also improves its torsional stiffness, effectively reduces the material usage, and has important guiding significance for the lightweight design of telescopic booms. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |
