Multi-Surrogates Based Modelling and Optimization Algorithm Suitable for Aero-Engine

被引：0
|
作者：
Ye Y.-F. [1 ]
Wang Z.-X. [1 ]
Zhang X.-B. [1 ]
机构：
[1] Shaanxi Key Laboratory of Internal Aerodynamics in Aero-Engine, School of Power and Energy, Northwestern Polytechnical University, Xi'an
来源：
Tuijin Jishu/Journal of Propulsion Technology | 2021年 / 42卷 / 12期
关键词：
Gas turbine engine; Modelling approach; Multiple-surrogate model technique; Optimization method; Optimization of fuel control schedule; Steady performance modelling;
D O I：
10.13675/j.cnki.tjjs.200817
中图分类号：
学科分类号：
摘要：
In order to improve the performance of aero-engine modelling and optimization algorithm, a new average ensemble model is proposed and used to assist the ego optimization method. By using six well-known mathematical functions with varying dimensions and numbers of training points, it is proved that the proposed ensemble model is more accurate than the other ensemble models, and the convergence of the proposed optimization algorithm is better than that of the classic optimization algorithm. Meanwhile, the steady performance modelling problem of the variable cycle engine and the optimization problem of the variable cycle engine acceleration fuel control schedule are also considered, it is proved that the proposed algorithms perform well in solving a complex engineering problem. © 2021, Editorial Department of Journal of Propulsion Technology. All right reserved.
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页码：2684 / 2693
页数：9
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