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隐式参数化白车身多目标协同优化设计

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隐式参数化白车身多目标协同优化设计
Multi-Objective Lightweight Collaborative Optimization and Design for Latent Parametric BIW Structure
投稿时间：2018-12-04
DOI：10.15918/j.tbit1001-0645.2019.05.002
中文关键词:白车身参数化轻量化全自动优化
English Keywords:body in white (BIW)parametriclightweightoptimization automation
基金项目:国家重点研发计划项目（2016YFB0101601）
作者单位
吕天佟吉林大学 汽车仿真与控制国家重点实验室, 吉林, 长春 130022
王登峰吉林大学 汽车仿真与控制国家重点实验室, 吉林, 长春 130022
王传青北京汽车股份有限公司研究院, 北京 101300
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中文摘要:
利用参数化建模软件SFE-CONCEPT建立了某轿车白车身的参数化模型，用仿真方法分析了白车身的静态弯扭刚度、主要低阶模态频率并与试验对比，再将白车身与动力总成、底盘连接后，对整车正碰性能进行仿真分析，并与试验对比，验证了所建参数化白车身的有效性.由于安全性分析属于非线性分析，传统优化方法通常需要人工介入，无法实现优化流程的全自动化.通过编写批处理文件，提取安全性能指标，实现白车身结构轻量化优化流程的自动化.白车身结构轻量化优化后弯曲刚度提升0.15%，扭转刚度降低0.03%，一阶扭转模态频率提高1.30%，一阶弯曲模态频率提高0.09%，碰撞安全性能基本不变的情况下，白车身质量降低24.17kg，减重率高达7.42%，取得了显著的轻量化效果.
English Summary:
A parametric model was established with SFE-CONCEPT software for a BIW (body in white). Firstly, the static bending-torsion stiff and the lower-order modal of BIW were simulated based on finite element method, and the results were compared with tests. Then connecting the parametric BIW with power train and chassis, the crash safety performances were simulated based on finite element method and compared with tests. The comparison results between simulation and test validate the parametric model of BIW. Secondly, the lightweight and safety of BIW structure were optimized. Due to the safety simulation analysis belongs to non-linear analysis, the optimization process can't fully achieve automatic, needing manual intervention to extract safety performances in tradition way. In order to achieve the optimization process automation, a batch file was compiled to extract safety performances. The lightweight optimization results show that, the bending stiff can increase 0.15%, the torsion stiff can reduce 0.03%, torsion modal frequency can increase 1.30%, bending modal frequency increased 0.09%. And under the condition that the crash safety performances keep no changing, the weight of lightweight optimization BIW can reduce 24.17 kg, the reduction rate reaches 7.63%. The multi-objective collaborative optimization can provide obvious lightweight effect for BIW.
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