轿车悬架控制臂参数化建模及轻量化多目标优化设计

Research on Parameterization Modeling and Multi-Objective Lightweight Optimization for Car Suspension Control Arm

提取了汽车在加速、制动、稳态回转和最高车速行驶4种工况下前悬架控制臂的载荷,建立了控制臂的拓扑优化分析模型。以控制臂质量最轻、最大变形最小为目标函数,以控制臂的1阶弹性模态频率不低于轻量化前的频率及控制臂最大米塞斯应力小于材料的许用应力为约束条件,以控制臂参数化模型的11个参数为设计变量,建立了控制臂轻量化多目标优化设计数学模型。用第二代非劣排序遗传算法(NSGA-Ⅱ)对控制臂进行轻量化多目标优化设计结果表明,在保持控制臂低阶固有振动特性、强度和刚度基本不变的条件下,轻量化后控制臂质量从2.62kg减少到2.21kg,减重15.6%,轻量化效果明显。

The front suspension control arm loads are extracted in four working conditions, i.e. acceleration,braking, steady static circular and maximum speed running, and a topology optimization analysis model is set up.Lightweight multi-objective optimization design model of control arm is established with the minimal mass and maximum deformation of control arm as objective function, the first order elastic modal frequency of control arm not less than its original value and maximum Mises stress less than permissible stress as constraint condition, and eleven parameters of control arm parameterization model as design variables. The second generation of non dominated sorting genetic algorithm（NSGA-Ⅱ） is used for lightweight multi- objective optimization design model of control arm, the results indicate that mass of the lightweight control arm is reduced by 15.6 % to 2.21 kg from 2.62 kg with the low-order natural vibration characteristic, strength and stiffness of control arm remain unchanged. Obvious lightweight effects are achieved.