摘要
以某款车型的前保险杆为研究对象,在保持前保险杠结构不变的情况下,改变横梁和吸能盒的厚度值。以入侵量、横梁和保险杠总质量为优化目标,采用优化拉丁超立方进行抽样,建立高拟合精度的二次响应面近似模型。通过非支配排序遗传算法得出最终优化方案与仿真值相近。研究表明,此优化方案增强前保险杠耐撞性的同时实现了轻量化。
Taking the front bumper of a certain car model as the research object,the thickness values of the beam and the energy absorbing box are changed while keeping the structure of the front bumper unchanged.The intrusion volume,the total mass of the beam and the bumper are the optimization targets,and the optimized Latin hypercube is used for sampling to establish a quadratic response surface approximate model with high fitting accuracy.Through the non-dominated sorting genetic algorithm,the final optimization scheme is close to the simulation value.Studies have shown that this optimization scheme enhances the crashworthiness of the front bumper while achieving lightweight.
作者
孙江
常高爽
Sun Jiang;Chang Gaoshuang(University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《农业装备与车辆工程》
2021年第10期148-152,共5页
Agricultural Equipment & Vehicle Engineering
关键词
前保险杠
近似模型
优化
耐撞性
轻量化
front bumper
approximate model
optimization
crashworthiness
lightweight
