摘要
To better improve the lightweight and fatigue durability performance of the tractor cab,a multi-objective lightweight design of the cab was carried out in this study.First,the finite element model of the cab with counterweight loading was established and then confirmed by the physical testing,and use the inertial reliefmethod to obtain stress distribution under unit load.The cab-frame rigid-flexible couplingmulti-body dynamicsmodelwas built by Adams/car software.Taking the cab airbag mount displacement and acceleration signals acquired on the proving ground as the desired signals and obtaining the fatigue analysis load spectrum through Femfat-Lab virtual iteration.The fatigue simulation analysis is performed in nCode based on the Miner linear fatigue cumulative damage theory.Then,with themass and fatigue damage values as the optimization objectives,the bending-torsional stiffness and first-order bending-torsional mode as constraints,the thickness variables are screed based on the sensitivity analysis.The experimental design was carried out using the Optimal Latin hypercube method,and the multi-objective optimal design of the cab was carried out using theKriging approximationmodel fitting and particle swarmalgorithm.The weight of the optimized cab is reduced by 7.8%on the basis of meeting the fatigue durability performance.Finally,a seven-axis road simulation test rig was designed to verify its fatigue durability.The results show the optimized cab can consider both lightweight and durability.
基金
supported in part by the Science and Technology Major Project of Guangxi under Grants AA18242033 and AA19182004
in part by the Key Research andDevelopment Program of Guangxi AB21196029
in part by the Scientific Research and Technology Development in Liuzhou 2020GAAA0404,2021AAA0104 and 2021AAA0112
in part by the Guangxi Higher Education Undergraduate Teaching Reform Project Grant 2021JGA180
in part by the GUET Education Undergraduate Teaching Reform Project Grant JGB202002
in part by the Innovation Project of GUET Graduate Education (2022YCXS017).
