摘要
为提高氢燃料电池引射器的性能,以额定工况下氢燃料电池引射器为研究对象,提出一种基于椭球基(EBF)神经网络模型和非线性序列二次规划(NLPQL)算法的引射器结构参数优化方法。基于正交试验,建立EBF神经网络模型,描述引射器结构参数与引射系数间的非线性关系;通过引射系数模拟值与代理模型预测值的对比以及复相关系数,验证了代理模型的精度;最后,应用NLPQL算法进行全局寻优,获得使引射系数最大的结构参数组合,并进行模拟验证。研究结果表明:基于EBF神经网络和NLPQL算法,提高了燃料电池引射器的引射系数,相对于正交试验方案最大值,引射系数提高了3.9%。基于正交试验设计和EBF神经网络的方法,可以扩大引射器结构参数研究范围和水平,节约CFD模拟计算时间。
In order to improve the performance of hydrogen fuel cell ejector,the hydrogen fuel cell ejector under rated operating conditions was taken as the research object,an optimization method of ejector structure parameters based on EBF neural network model and NLPQL algorithm was proposed.Based on orthogonal test,the EBF neural network model was established,the nonlinear relationship between the structural parameters of the ejector and the ejection coefficient was described.The precision of the proxy model was verified by comparing the simulated value of the ejection coefficient with the predicted value of the proxy model and the complex correlation coefficient.The NLPQL algorithm was applied to make global optimization,and the structure parameter combination with the maximum ejection coefficient was obtained and verified by simulation.The results indicate that,based on EBF neural network and NLPQL algorithm,the ejection coefficient of fuel cell ejector is improved,compared with the maximum value of the orthogonal test scheme,the ejection coefficient is increased by 3.9%.The method based on orthogonal test and EBF neural network can expand the research scope and level of ejector structural parameters,save the time of CFD simulation calculation.
作者
么大锁
赵凯芳
吴国鹏
季宁
裴毅强
YAO Dasuo;ZHAO Kaifang;WU Guopeng;JI Ning;PEI Yiqiang(School of Mechanical Engineering,Tianjin Renai College,Tianjin 301636,China;State Key Laboratory of Engines,Tianjin University,Tianjin 300072,China;Department of Mathematics,Tianjin Renai College,Tianjin 301636,China)
出处
《机床与液压》
北大核心
2023年第21期144-149,共6页
Machine Tool & Hydraulics
基金
天津市教委科研计划项目(2021KJ081)。
关键词
氢燃料电池引射器
正交试验
引射系数
神经网络
非线性序列二次规划
Hydrogen fuel cell ejector
Orthogonal test
Ejection coefficient
Neural network
Non-linear programming by quadratic lagrangian
