基于非支配解优选的自卸车车厢轻量化设计
Lightweight design of dump truck's compartment based on non-dominant solution optimization
龚青山 1吴东雨 1孙章栋 1张光国 1洪波2
作者信息
- 1. 湖北汽车工业学院机械工程学院,湖北十堰 442002
- 2. 东风商用车技术中心,湖北十堰 442002
- 折叠
摘要
为设计出性能优良且满足轻量化需求的自卸车车厢,基于响应面法对自卸车车厢进行多目标优化设计,文中提出一种混合灰色关联与熵权法的非支配解(Pareto解)优选方法作为最优解决策.首先,对车厢进行有限元仿真分析,发现原车厢结构在满足现有设计需要下具有一定优化空间;然后,采用Plackett-Burman试验方法求出车厢厚度输入变量对输出响应影响敏感程度(Pareto图),进而选出优化设计变量,采用拉丁超立方试验方法进行样本点采集,通过最小二乘法拟合响应面近似模型并进行精度检验;最后,运用响应面模型对车厢进行多目标优化并混合灰色关联与熵权法对Pareto解进行优选,求得全局最优解.结果表明,在满足自卸车车厢性能要求下,整体质量减小24％,模态频率上升了0.2％,具有较好的轻量化效果.
Abstract
In this article,in order to develop a dump truck's compartment characterized by excellent performance and light-weight design,the response surface method is used for multi-objective optimization design;a non-dominant solution(the Pareto solution)optimization method is proposed for optimal solution decision-making,which combines the grey correlation method and the entropy weight method.Firstly,the compartment is subject to the finite-element simulation and analysis;it is found that the carriage's original structure needs to be optimized while meeting the current design requirements.Secondly,the Plackett-Burman test method is used to identify the sensitivity of the compartment's thickness input variable to the output response(the Pareto fig-ure);then,the optimized design variables are selected and the Latin hypercube test method is adopted to collect sample points;next,the least square method is used to fit the response-surface approximate model,and the accuracy is tested.Finally,the re-sponse surface model is adopted to conduct the multi-objective optimization on the compartment;a combination of the gray relation method and the entropy weight method is used to optimize the Pareto solution and then work out the global optimal solution.The results show that while meeting the performance requirement,the dump truck's compartment has its overall mass reduced by 24％,and the modal frequency increases by 0.2％,thus achieving a desirable effect of lightweight design.
关键词
灰色关联法/熵权法/轻量化/响应面模型/多目标优化Key words
grey correlation method/entropy weight method/lightweight/response surface model/multi-objective optimization引用本文复制引用
出版年
2024
NETL
NSTL
万方数据