A Kriging-based bi-objective constrained optimization method for fuel economy of hydrogen fuel cell vehicle
A Kriging-based bi-objective constrained optimization method for fuel economy of hydrogen fuel cell vehicle
复制标题
基于克里金法的氢燃料电池汽车燃油经济性双目标约束优化方法
DOI：
10.1016/j.ijhydene.2019.04.094
复制
发表时间：
2019-11
影响因子：
7.2
通讯作者：
Wang Shuting
中科院分区：
文献类型：
--
作者：
Li Yaohui;Wu Yizhong;Zhang Yuanmin;Wang Shuting
基于克立格法的昂贵黑箱问题的单目标优化问题一直是阻碍工程应用的瓶颈。主要的挑战是如何减少时间消耗和提高收敛精度。为此，提出了一种基于克立格的双目标约束优化算法。对于每个周期，KBCO首先使用采样的设计点来建立或连续更新昂贵的目标和约束函数的克立格模型。然后，利用克立格模型产生的预测目标、均方根误差(RMSE)和最大可行概率构造两个目标，并用NSGA-II求解器对这两个目标进行优化，生成帕累托最优解。最后，对帕累托前沿数据进行进一步筛选，得到新的昂贵评价样本点，并将其附加到样本数据中。几个数值试验和氢燃料电池汽车的燃油经济性仿真实例验证了KBCO方法的可行性和有效性。
The Kriging-based single-objective optimization for expensive black-box problems has been preventing the engineering application. The main challenge is how to reduce time consumption and improve convergence accuracy. To this end, a Kriging-based bi-objective constrained optimization (KBCO) algorithm is proposed. For each cycle, KBCO firstly uses the sampled design points to build or consecutively update Kriging models of expensive objective and constraint functions. And then, the predictive objective, root mean square error (RMSE) and maximum feasible probability produced by Kriging models are used to construct two objectives, which will be optimized by the NSGA-II solver to generate the Pareto optimal solutions. Finally, the Pareto front data will be further screened to obtain new expensive-evaluation sampling points and append them to sample data. Several numerical tests and a fuel economy simulation case for hydrogen fuel cell vehicle verify the feasibility and effectiveness of the KBCO method.
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DOI：
--
发表时间：
2014-05
期刊：
--
影响因子：
--
作者：
홍재열;박정술;김성식;백준걸
通讯作者：
홍재열;박정술;김성식;백준걸
影响因子：
2.5
作者：
J. Wisnowski
通讯作者：
J. Wisnowski
影响因子：
1.9
作者：
David P. Montminy;R. Baldwin;M. Temple;Eric D. Laspe
通讯作者：
David P. Montminy;R. Baldwin;M. Temple;Eric D. Laspe
影响因子：
5.7
作者：
S. Koziel;S. Ogurtsov
通讯作者：
S. Koziel;S. Ogurtsov
影响因子：
2.7
作者：
R. Regis
通讯作者：
R. Regis