Application of Robustness and Lightweight in Optimal Design of Door Structure
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摘要: 目前多数的轻量化研究，通常基于尺寸、形状、位置等某一单方面的设计因素展开，而忽略了各因素之间的交互性。另外，设计变量在制造生产过程中不可避免的存在一定范围内的波动。针对现有车门产品，结合多种类的设计因素，并考虑设计变量的波动对产品性能的影响，采用试验设计方法构造高精度的响应面模型，结合多岛遗传算法、蒙特卡罗模拟技术，对车门结构进行6σ稳健性与轻量化改进设计。结果表明，本研究在减轻车门质量的同时显著提高了产品性能及性能的稳健性。Abstract: Most of the current lightweight studies are usually based on a single design factor, such as size, shape, position, and so on, while ignoring the interactivity between the factors. In addition, design variables inevitably fluctuate in a certain range in the manufacturing process. For the existing door products, combining the variety of design factors, and the effect of the fluctuation of design variables on the performance of the product is considered. The high precision response surface model is constructed by the experimental design method, and the six sigma robust and lightweight design of the door structure is improved by combining the multi-island genetic algorithm and Monte Carlo simulation technology. As a result, the quality of the door is reduced and the robustness of the product is improved.
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Key words:
- door /
- response surface /
- six sigma robustness /
- lightweight
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表 1 车门下沉刚度数据对比
F/N 200 400 600 800 1 000 卸载 试验值/mm 1.46 2.86 4.33 5.91 7.47 0.36 仿真值/mm 1.46 2.92 4.37 5.83 7.29 0.36 
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表 2 窗框侧向刚性数据对比
F/N 40 80 120 160 200 卸载 试验值/mm 1.00 2.12 3.21 4.35 5.52 5.52 仿真值/mm 1.06 2.11 3.17 4.26 5.28 5.22
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表 3 侧面碰撞工况门内板侵入量数据对比
编号 测量项 侵入量/mm 试验 CAE 1 门内板对应假人上肋骨 117.7 110.8 2 门内板对应假人下肋骨 131.7 129.8 3 门内板对应假人腹部 162.5 151 4 门内板对应假人H点 175.2 159.9 5 门内板对应假人骨盆 177.9 175.1
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表 4 考核性能的约束条件
性能 考核点 约束条件 下沉刚度 加载1 000 N时加载点位置Z向弹性位移d1 d1≤7 mm 窗框侧向刚度 加载200 N时加载点位置Y向弹性位移d2 d2≤5 mm 耐撞性能 骨盆对应门内板Y向侵入量y >y≤170 mm
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表 5 设计变量
参数名称 下限 初始值 上限 分布类型 标准差 拼焊线前侧
内板T1/mm0.65 1.4 2.0 正态分布 0.016 外后视镜安
装板T2/mm0.65 1.6 2.0 正态分布 0.016 内板上加
强板T3/mm0.65 1.6 2.0 正态分布 0.016 防撞杆管
厚T4/mm1.4 2.0 2.8 正态分布 0.05 防撞杆的
管径D/mm22.0 32.0 36.0 正态分布 0.05 防撞杆的
长度l/mm778.0 788.0 851.6 正态分布 1.0 防撞杆的
角度α/(°)-7.0 9.0 15.0 正态分布 0.5 防撞杆的
高度h/mm0.0 0.0 106.0 正态分布 1.0 拼焊线X
向坐标/mm622.0 672.0 722.0 正态分布 0.5
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表 6 响应面系数
对应变量 m d1 d2 y a0 常数项 21.310 -108.362 12.080 -884.116 D -0.068 0.294 0.076 -0.237 T1 -0.273 -16.290 -6.398 26.084 T2 0.193 -2.156 -0.962 31.230 T3 0.921 0.616 0.402 57.181 ai T4 0.486 0.389 -0.437 -9.403 X -0.009 0.096 0.003 0.812 α 0.519 13.191 2.564 -22.334 h -0.089 9.182 2.214 22.219 l 0.05 -12.576 -3.812 -7.475 D2 0.000 -0.005 -0.001 -0.020 aii ⋮ ⋮ ⋮ ⋮ ⋮ l2 -0.0001 0.0084 0.002 0.0185 D×T1 0.003 -0.014 -0.001 -0.155 aij ⋮ ⋮ ⋮ ⋮ ⋮ h*l 0.0002 -0.012 -0.002 -0.045
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表 8 初始值、确定性最优解和稳健性最优解
参数 初始值 确定性最优解 6σ稳健性最优解 6σ稳健性最优解(圆整后) 结果 标准差 σ水平 结果 标准差 σ水平 RSM 有限元 D/mm 32 22.5 — 8 26.3 — 8 26 — T1/mm 1.4 1.5 — 8 1.7 — 8 1.7 — T2/mm 1.6 1.9 — 2.8 1.9 — 8 1.9 — T3/mm 1.6 1.1 — 2.8 0.9 — 8 0.9 — T4/mm 2 1.4 — 1 1.7 — 8 1.7 — X/mm 672 680.7 — 6 631.7 — 8 632 — α/(°) 9 5 — 8 5 — 8 5 — h/mm 0 34.4 — 8 23.8 — 8 24 — l/mm 788 803.1 — 8 796.2 — 8 796 — d1/mm 7.29 6.38 0.135 8 6.25 0.022 8 6.29 6.83 d2/mm 5.28 4.98 0.014 1.38 4.97 0.005 6 4.98 5.08 y/mm 175.1 170.6 0.16 2.87 168.8 0.14 8 169.3 170.5 m/kg 17.9 16.4 0.037 — 16.6 0.036 — 16.6 16.6
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