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Multidisciplinary Design Optimization of BEV Body Structure

机译：BEV车身结构的多学科设计优化

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Blade Electric Vehicle (BEV) with a light body plays an important role in saving the energy and reducing the exhaust emission. However, reducing the body weight need to meet the heterogeneous attributes such as structural, safety and NVH (Noise, Vibration and Harshness) performance. With the rapid development of finite element (FE) analysis technology, simulation analysis is widely used for researching the complex engineering design problem. Multidisciplinary Design Optimization (MDO) of a BEV body is a challenging but meaningful task in the automotive lightweight. In present research, the MDO is introduced to optimize a BEV Body-in-White (BIW). The goal of optimization is to minimize the mass of the BIW while meeting the following requirements: structural performance (the bending and torsion stiffness is increased), NVH performance (the first overall torsion frequency is increased), and safety performance (the roof crush resistance is improved). The sample points were obtained by using Design of Experiment (DOE) with optimal Latin hypercube. The approximation models of mass, bending stiffness, torsion stiffness, modal and safety were established with the polynomial response surface method (RSM). The thicknesses of nine parts of the BIW were selected to be optimized by Muti-island Genetic Algorithm (MGA) method. After the MDO of the BIW, the paper drew the following conclusions: 1. The predictive values of the approximation and the results of FE simulation had a good agreement with an error less than 5.00% and the former met the engineering requirements; 2. The weight of the BIW was reduced by 2.00% and the optimized BIW met all prescribed requirements about structural, NVH and safety performance.
机译：刀片电动车（BEV）与轻体发挥着重要作用，可节省能量并减少排气。然而，降低体重需要满足异构属性，例如结构，安全和NVH（噪音，振动和严格）性能。随着有限元（FE）分析技术的快速发展，仿真分析广泛用于研究复杂的工程设计问题。 BEV机身的多学科设计优化（MDO）是汽车轻量级中的一个具有挑战性但有意义的任务。在目前的研究中，介绍了MDO以优化BEV机身（BIW）。优化的目标是最小化BIW的质量，同时满足以下要求：结构性能（弯曲和扭转刚度增加），NVH性能（第一整体扭转频率增加），安全性能（屋顶挤压是改进的）。通过使用具有最佳拉丁杂交型实验（DOE）的设计获得的采样点。用多项式响应表面法（RSM）建立了质量，弯曲刚度，扭转刚度，模态和安全性的近似模型。选择九个部分的厚度由Muti-Island遗传算法（MGA）方法进行优化。在BIW的MDO之后，该论文提出了以下结论：1。近似值的预测值和FE模拟的结果与小于5.00％的误差良好，并且前者达到了工程要求; 2. BIW的重量减少了2.00％，优化的BIW符合结构，NVH和安全性能的所有规定要求。

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