首页|基于粒子群-细菌觅食混合优化算法的汽车碳纤维复合材料地板铺层设计

基于粒子群-细菌觅食混合优化算法的汽车碳纤维复合材料地板铺层设计

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为提高白车身地板复合材料铺层优化设计的精度、效率及结构轻量化水平,提出了一种碳纤维复合材料地板铺层优化设计方法.首先建立了白车身有限元模型并验证了其有效性,然后通过力学性能测试获取了碳纤维复合材料的参数,并进行了地板铺层的概念设计和建模.接着,采用连续变量优化设计方法确定了地板的铺层厚度、铺块形状和铺层层数,并使用离散化圆整策略获得了各铺向角的离散铺层层数.优化结果表明,所提出的粒子群-细菌觅食混合优化(PSO-BFO)算法对地板质量、静态弯曲刚度和白车身轻量化系数的改善率分别为34.4%、6.0%和5.3%.
Ply Design of Automotive Carbon Fiber Composite Floor Based on PSO-BFO Algorithm
A method for optimizing the layout of carbon fiber composite floorings for BIW was proposed to enhance precision,efficiency,and structural lightweight.Initially,BIW finite element model was established and its efficiency was validated.Subsequently,material parameters for the carbon fiber composite were obtained through mechanical performance testing,followed by conceptual designing and modeling of the flooring layout.Subsequent utilization of continuous variable optimization determined the thickness,block shapes,and layers of the flooring,employing a discretization and rounding strategy to achieve discrete layer numbers for each layup angle.The optimization results show that the Particle Swarm Optimization-Bacteria Foraging Optimization(PSO-BFO)algorithm proposed herein improves flooring quality,static bending stiffness and BIW lightweight coefficient by 34.4%,6.0%and 5.3%,respectively.

Composite floorComposite ply design methodParticle Swarm Optimization-Bacteria Foraging Optimization(PSO-BFO)algorithmMulti-objective optimization

杨海洋、丁娟、蔡珂芳、王军年、胡爱成

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嘉兴南湖学院,嘉兴 314001

嘉兴市智能计算与数据科学重点实验室,嘉兴 314001

吉林大学,汽车仿真与控制国家重点实验室,长春 130022

零束科技有限公司,上海 201800

戴姆勒大中华区投资有限公司上海分公司,上海 200080

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复合材料地板 铺层设计方法 粒子群-细菌觅食混合优化方法 多目标优化

国家自然科学基金面上项目吉林省自然科学基金项目吉林省中青年科技创新创业卓越人才(团队)项目2023嘉兴市重点研发计划项目2024年嘉兴市公益性研究计划项目

5197524420220101200JC20230508050RC2023BZ100022024AY10033

2024

汽车技术
中国汽车工程学会 长春汽车研究所

汽车技术

CSTPCD北大核心
影响因子:0.522
ISSN:1000-3703
年,卷(期):2024.(8)