锻压技术

汽车B柱加强板热冲压工艺的遗传算法多目标优化

英文标题：Multi-objective optimization on hot stamping process for vehicle B-pillar reinforced plate based on genetic algorithm

作者：王泌宝

单位：潍坊工商职业学院潍坊市经济学校

关键词：B柱加强板热冲压 BP神经网络非支配排序遗传算法 Pareto前沿解

分类号：TG386

出版年,卷(期):页码：2021,46(5):46-52

摘要：

为了提高汽车B柱加强板热冲压件的厚度均匀性，提出了非支配排序遗传算法的工艺参数多目标优化方法。分析了B柱加强板的热冲压过程，选择板料加热温度、冲压速度、摩擦系数和模具间隙作为优化参数。以减小最大减薄率和最大增厚率作为优化目标，建立多目标优化模型。使用最优拉丁超立方抽样法在优化空间内设计实验点，并依据Autoform有限元软件得到实验值。基于BP神经网络拟合工艺参数与质量参数之间的关系，并依据预测均方根误差验证了拟合的精确性。使用非支配排序遗传算法搜索多个优化目标的Pareto前沿解。经生产验证，与厂家工艺相比，优化后的热冲压件最大减薄率减小了22.25%，最大增厚率减小了7.34%，说明优化后冲压件的质量得到了提高；且优化后最大减薄率和最大增厚率的标准差均减小，说明优化工艺的生产稳定性更好。

In order to improve the thickness uniformity of hot stamping part for B-pillar reinforced plate, a multi-objective optimization method of process parameters based on the non-dominated sorting genetic algorithm was proposed, and the hot stamping process of B-pillar reinforced plate was analyzed. Then, taking plate heating temperature, stamping speed, friction factor and die clearance as optimization parameters and the reduction of the maximum thinning rate and the maximum thickening rate as the optimization goals, the multi-objective optimization model was built. In the optimized space, the experiment points were designed by the optimal Latin hypercube sampling method, and the experimental values were obtained by finite element software Autoform. Furthermore, the relationship between process parameters and quality parameters was fitted by BP neutral network, the fitting accuracy was verified based on the predicted root mean square error, and Pareto front solutions of multiple optimization objectives were searched by the non-dominated sorting genetic algorithm. After production verification, compared with the thoriginal process used by manufacturer, the maximum thinning rate and the maximum thickening rate of the optimized hot stamping part are decreased by 22.25% and 7.34% respectively, indicating that the quality of stamping part is improved after optimization, and after optimization, the standard deviations of the maximum thinning rate and the maximum thickening rate are both reduced, indicating that the production stability of the optimized process is better.

基金项目：

山东省职业教育教学改革研究项目（2017647）

王泌宝（1969-），男，硕士，副教授 E-mail：niu666222@126.com

参考文献：

[1]陈泽中, 李响,刘欢,等.基于Dynaform的SUV汽车B柱热冲压成形仿真分析与工艺研究[J].塑性工程学报,2019,26(4):113-119.

Chen Z Z, Li X, Liu H, et al. Simulation analysis and process research of hotstamped SUV Bpillar based on Dynaform [J]. Journal of Plasticity Engineering, 2019, 26(4):113-119.

[2]王功, 沈辉.基于JSTAMP/NV的汽车B柱热冲压仿真分析[J].热加工工艺,2019,48(5):158-160.

Wang G, Shen H. Hot stamping simulation analysis of automobile bpillar based on JSTAMP/NV [J]. Hot Working Technology, 2019, 48(5):158-160.

[3]陈菲. 含钒1500 MPa热冲压成型钢的组织与性能研究[D].唐山：华北理工大学,2019.

Chen F. Study on Microstructure and Properties of 1500 MPa Stamping Steel Containing Vanadium [D]. Tangshan: North China University of Science and Technology, 2019.

[4]林浩波, 刘军辉,吴立国.基于遗传算法的防撞钢梁热冲压成形工艺优化[J].塑性工程学报,2019,26(5):65-69.

Lin H B, Liu J H, Wu L G, et al. Optimization of hot stamping process for anticollision beam based on genetic algorithms [J].Journal of Plasticity Engineering, 2019, 26(5):65-69.

[5]刘雪飞, 黄馨阅,向相,等.基于Dynaform的B柱加强件热冲压全流程仿真及优化[J].锻压技术,2019,44(6):46-52.

Liu X F, Huang X Y, Xiang X, et al. Simulation and optimization on B pillar reinforcing parts during hot stamping process based on Dynaform [J]. Forging & Stamping Technology, 2019, 44(6):46-52.

[6]王凯, 朱彬,王义林,等. 热冲压钢AlSi镀层形貌动态演化及形变开裂特征[J].塑性工程学报,2020,27(9):181-185.

Wang K, Zhu B, Wang Y L, et al. Dynamic morphology evolution and deformation cracking characteristics of AlSi coating on hot stamping steel [J]. Journal of Plasticity Engineering, 2020,27(9):181-185.

[7]易红亮, 常智渊,才贺龙,等.热冲压成形钢的强度与塑性及断裂应变[J].金属学报,2020,56(4):429-443.

Yi H L, Chang Z Y, Cai H L, et al. Strength, ductility and fracture strain of presshardening steels [J]. Acta Metallur Gica Sinica, 2020, 56(4):429-443.

[8]刘树帅, 王新洪,于童.DP780/B1500HS异种钢脉冲穿孔等离子弧焊工艺研究[J].热加工工艺,2018,47(1):83-87.

Liu S S, Wang X H, Yu T. Study on keyhole pulse plasma arc welding of DP780/B1500HS dissimilar steels [J]. Hot Working Technology, 2018,47(4):83-87.

[9]杨振朝, 林允博,刘三娃,等.基于BoxBehnken设计的高速铣削TC11钛合金切削力预测模型研究[J].航空精密制造技术,2018,54(4):14-18.

Yang Z C, Lin Y B, Liu S W, et al. Cutting force prediction models based on BoxBehnken design in highspeed milling of titanium alloy TC11 [J]. Aviation Precision Manufacturing Technology, 2018, 54(4):14-18.

[10]熊杰, 魏勇,严丹.基于BP神经网络的超声波温湿度补偿算法研究与应用[J].现代电子技术,2020,43(9):113-116.

Xiong J, Wei Y, Yan D. Research and application of ultrasonic temperaturehumidity compensation algorithm base on BP neural network [J]. Modern Electronics Technique, 2020, 43(9):113-116.

[11]王乐, 李冬,余慕春,等.基于动态加权系数和多目标进化的模型修正方法[J].振动与冲击,2020,39(4):284-290.

Wang L, Li D, Yu M C, et al. A method of model updating based on dynamic weighting coefficients and multiobjective evolution [J]. Journal of Vibration and Shock, 2020, 39(4):284-290.

[12]赵志彪, 刘浩然,刘彬,等.改进非支配排序精英遗传算法的篦冷机参数优化[J].控制与决策,2020,35(5):1217-1225.

Zhao Z B, Liu H R, Liu B,et al. Optimization of grate cooler parameters based on improved nodominated sorting genetic algorithm II [J]. Control and Decision, 2020, 35(5):1217-1225.

服务与反馈：

【本网站尚未开通全文下载服务】【加入收藏】