摘要
对电动大客车底架利用第二代非支配排序遗传算法(NSGA-Ⅱ)进行了拓扑优化,在保证所有梁单元最大应力不超过屈服强度的条件下,以整车扭转刚度和质量作为优化目标,最终得到底架拓扑后的帕累托前沿.对结果进行筛选,得到的拓扑方案扭转刚度与原模型接近,质量降低89kg,占原模型底架的6.4%,拓扑效果显著.
The non-dominated genetic algorithm Ⅱ was introduced to topology optimization of electric bus underframe, where the objectives were to maximize torsional stiffness and minimize total mass under the constraint of the maximum stress of all the beam elements within the yield strength, finally the Pareto front of optimization result was obtained. The results show that the torsional stiffness of the proposed scheme is close to that of the original model, and the quality is reduced by 89kg, which is 6. 4% of that of the original model underframe and the topological effect is remarkable.
出处
《同济大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2017年第11期1664-1669,共6页
Journal of Tongji University:Natural Science
基金
国家自然科学基金(51575399)
"十三五"国家科技支撑计划(2016YFB0101600)
关键词
离散拓扑优化
非支配排序
遗传算法
多目标优化
应力约束
discrete topology optimization
non-dominatedsorting
genetic algorithm
multi-objective optimization
stress constraints
