复合材料科学与工程 ›› 2022, Vol. 0 ›› Issue (5): 66-70.DOI: 10.19936/j.cnki.2096-8000.20220528.009

• 应用研究 • 上一篇    下一篇

碳纤维复合材料电池箱轻量化研究

康元春1,2, 刘俊峰1, 孟紫薇1   

  1. 1.湖北汽车工业学院,十堰 442002;
    2.汽车动力传动与电子控制湖北省重点实验室,十堰 442002
  • 收稿日期:2021-05-07 出版日期:2022-05-28 发布日期:2022-07-19
  • 作者简介:康元春(1981-),女,硕士,副教授,主要从事结构及材料轻量化方面的研究。
  • 基金资助:
    汽车动力传动与电子控制湖北省重点实验室创新基金(2015xtzx0407)

Study on lightweight of carbon fiber composite battery box

KANG Yuan-chun1,2, LIU Jun-feng1, MENG Zi-wei1   

  1. 1. Hubei University of Automotive Technology, Shiyan 442002, China;
    2. Key Laboratory of Automotive Power Train and Electronics, Shiyan 442002, China
  • Received:2021-05-07 Online:2022-05-28 Published:2022-07-19

摘要: 为减轻电池箱下箱体重量,采用轻质材料铝合金和碳纤维复合材料替换原Q235钢制材料。材料替换后,为得到新材料的最佳厚度尺寸,提出以神经网络为代理模型,同时优化铝合金和碳纤维部件厚度尺寸的方法。通过拉丁超立方试验得到尺寸变量对应的响应,基于神经网络进行优化,得到铝合金支架和加强梁最佳厚度以及碳纤维各角度厚度;最后在Optistruct中对碳纤维下箱体铺层顺序进行优化。优化结果表明,所采用的方案在减轻电池箱重量的同时,强度刚度和一阶模态频率也得到了提高。

关键词: 碳纤维复合材料, 电池箱, 神经网络

Abstract: In order to reduce the weight of the lower box of the battery box, the light material aluminum alloy and carbon fiber composite were used to replace the original Q235 steel material. After material replacement, in order to get the best thickness of new materials, a method of optimizing the thickness of aluminum alloy and carbon fiber parts is proposed by using neural network as the proxy model. The response of dimension variable was obtained by Latin hypercube test, and the optimum thickness of aluminum alloy support and reinforced beam and the thickness of carbon fiber angle were obtained based on neural network optimization. Finally, the optimal laying sequence of the box under carbon fiber is carried out in Optistruct. The optimization results show that the strength stiffness and the first mode frequency are improved while the weight of the battery box is reduced.

Key words: carbon fiber composite, battery box, neural network

中图分类号: