fSDE: efficient evolutionary optimisation for many-objective aero-engine calibration

Liu, Jialin1; Zhang, Qingquan1; Pei, Jiyuan1; Tong, Hao1; Feng, Xudong2,4; Wu, Feng3,4

2021-05-01

10.1007/s40747-021-00374-1

Complex & Intelligent Systems   影响因子和分区

2199-4536

2198-6053

Engine calibration aims at simultaneously adjusting a set of parameters to ensure the performance of an engine under various working conditions using an engine simulator. Due to the large number of engine parameters to be calibrated, the performance measurements to be considered, and the working conditions to be tested, the calibration process is very time-consuming and relies on the human knowledge. In this paper, we consider non-convex constrained search space and model a real aero-engine calibration problem as a many-objective optimisation problem. A fast many-objective evolutionary optimisation algorithm with shift-based density estimation, called fSDE, is designed to search for parameters with an acceptable performance accuracy and improve the calibration efficiency. Our approach is compared to several state-of-the-art many- and multi-objective optimisation algorithms on the well-known many-objective optimisation benchmark test suite and a real aero-engine calibration problem, and achieves superior performance. To further validate our approach, the studied aero-engine calibration is also modelled as a single-objective optimisation problem and optimised by some classic and state-of-the-art evolutionary algorithms, compared to which fSDE not only provides more diverse solutions but also finds solutions of high-quality faster.

Engine calibration Many-objective optimisation Multi-objective optimisation Constrained optimisation Evolutionary algorithm

SCI

英语

第一

National Natural Science Foundation of China[61906083,61976111]

Computer Science

Computer Science, Artificial Intelligence

WOS:000650060700001

SPRINGER HEIDELBERG

Web of Science

1.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Guangdong Prov Key Lab Brain Inspired Intelligent, Shenzhen, Peoples R China
2.Xidian Univ, Xian, Peoples R China
3.Northwestern Polytech Univ, Sch Power & Energy, Xian, Peoples R China
4.AECC, Chengdu, Peoples R China

Liu, Jialin,Zhang, Qingquan,Pei, Jiyuan,et al. fSDE: efficient evolutionary optimisation for many-objective aero-engine calibration[J]. Complex & Intelligent Systems,2021.

Liu, Jialin,Zhang, Qingquan,Pei, Jiyuan,Tong, Hao,Feng, Xudong,&Wu, Feng.(2021).fSDE: efficient evolutionary optimisation for many-objective aero-engine calibration.Complex & Intelligent Systems.

Liu, Jialin,et al."fSDE: efficient evolutionary optimisation for many-objective aero-engine calibration".Complex & Intelligent Systems (2021).