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| 基于Kriging近似模型的碳纤维增强复合 | |
| 引用本文： | 籍庆辉,朱平,卢家海,刘钊. 基于Kriging近似模型的碳纤维增强复合[J]. 上海交通大学学报, 2017, 51(2): 129 |
| 作者姓名： | 籍庆辉 朱平 卢家海 刘钊 |
| 作者单位： | 上海交通大学 机械系统与振动国家重点实验室； 上海市复杂薄板结构数字化制造重点实验室， 上海 200240 |
| 基金项目： | 国家自然科学基金项目（11372181），国汽（北京）轻量化技术研究院开放课题（20130303）资助 |
| 摘 要： | 以平纹机织碳纤维增强树脂基(CFRP)复合材料为研究对象，通过力学试验测试材料的静态力学和疲劳力学性能，结合Kriging插值方法和Basquin疲劳方程建立预测任意载荷下疲劳应力 循环寿命(S N)曲线的恒幅寿命图模型，并以此作为复合材料结构优化设计的性能约束；同时，利用最优拉丁超立方试验设计方法和Kriging近似模型构建优化目标和约束响应的近似模型，采用遗传算法优化得到CFRP复合材料电动汽车电池箱壳体的厚度，并通过台架实验加以验证.结果表明，优化后，电池箱壳体结构的减重率达到34.39%. |
| 关 键 词： | 电动汽车 动力电池箱壳体 碳纤维增强树脂基复合材料 Kriging近似模型 优化设计 |
Carbon Fiber Reinforced Plastic Fatigue Performance Prediction and#br#Application Based on Kriging Surrogate Model |
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| JI Qinghui,ZHU Ping,LU Jiahai,LIU Zhao. Carbon Fiber Reinforced Plastic Fatigue Performance Prediction and#br#Application Based on Kriging Surrogate Model[J]. Journal of Shanghai Jiaotong University, 2017, 51(2): 129 | |
| Authors: | JI Qinghui ZHU Ping LU Jiahai LIU Zhao |
| Affiliation: | State Key Laboratory of Mechanical System and Vibration; Shanghai Key Laboratory of Digital Manufacture for Thin Walled Structures, Shanghai Jiao Tong University, Shanghai 200240, China |
| Abstract: | Mechanical properties of plain weave carbon fiber reinforced plastic (CFRP) composite were studied by static and fatigue experiments. The new Haigh diagram model was established by using Kriging interpolation method and Basquin formulation. The model can predict S N curves under random loading conditions. And those curves were used as constraints of optimization design. The surrogate modes of optimization object and constraint were established using optimal Latin hypercube design (OLHD) of experiment and Kriging model. The shell thicknesses of power battery pack of electric vehicle were obtained by genetic algorithm. The optimized results were verified through fatigue bench testing. The weight of optimized structure reduced 34.39%. |
| Keywords: | electric rehicle shell of power battery pack carbon fiber reinforced plastic (CFRP) composite Kriging model optimization design |
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