基于网格变形技术的白车身多目标形状优化

Multi-Objective Shape Optimization of Body-in-White Based on Mesh Morphing Technology

市场的竞争压力促使汽车厂商致力于加快车身开发的进程,而基于计算机辅助工程(Computer aided engineering,CAE)的车身结构优化技术由此而成为业内的研究热点。与传统的尺寸优化不同,形状优化在工程优化中具有更大的潜力。将网格变形技术引入形状优化,提出基于近似模型的多目标形状优化方法。利用网格变形技术定义形状变量,并根据灵敏度信息筛选优化变量;采用优化拉丁方试验设计对设计空间均匀分布样本点,进一步拟合高精度的Kriging模型;运用多目标粒子群算法,保持其余性能指标满足预期的前提下,以白车身弯曲刚度和质量为目标进行优化。研究表明,所提出的优化方法成功用于白车身的多目标优化,设计者可根据优化结果权衡各个目标,以指导最终的决策。

The fierce competition within the automotive industry requires manufacturers to shorten their development time for a new body,and the CAE-based optimization techniques are arousing wide attention.Compared with traditional size optimization,shape optimization in engineering optimization has greater potential.As a result,mesh morphing technology is first introduced into shape optimization,and a metamodel-based multi-objective shape optimization methodology is presented.Mesh morphing technology is employed to define the shape variables which are then screened through sensitivity analysis.An optimal Latin hypercube sampling is utilized to generate uniformly distributed sample points for fitting the Kriging models with high accuracies.A multi-objective particle swarm algorithm is adopted to perform the optimization where the mass and bending stiffness are defined as the objective functions while maintaining other performance indicators.The conclusion can be drawn that the proposed methodology is used to perform the multi-objective optimization for body-in-white successfully,and engineers can handle the trade-off between the objectives for guiding the decision-making.