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

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 con...

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Published in:Complex & intelligent systems Vol. 8; no. 4; pp. 2731 - 2747
Main Authors: Liu, Jialin, Zhang, Qingquan, Pei, Jiyuan, Tong, Hao, Feng, Xudong, Wu, Feng
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 01.08.2022
Springer Nature B.V
Subjects:
Aerospace engines
Algorithms
Calibration
Complexity
Computational Intelligence
Data Structures and Information Theory
Engineering
Evolutionary algorithms
Mathematical models
Multiple objective analysis
Optimization
Original Article
Parameters
Working conditions
Constrained optimisation
Engine calibration
Evolutionary algorithm
Many-objective optimisation
Multi-objective optimisation
ISSN:2199-4536, 2198-6053
Online Access:Get full text
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Abstract 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.
AbstractList 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.
Author Liu, Jialin
Wu, Feng
Pei, Jiyuan
Tong, Hao
Zhang, Qingquan
Feng, Xudong
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CitedBy_id crossref_primary_10_3390_aerospace11020140
crossref_primary_10_1016_j_swevo_2023_101405
crossref_primary_10_1109_JIOT_2023_3292369
crossref_primary_10_1007_s40747_022_00714_9
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Keywords Constrained optimisation
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Evolutionary algorithm
Many-objective optimisation
Multi-objective optimisation
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Snippet Engine calibration aims at simultaneously adjusting a set of parameters to ensure the performance of an engine under various working conditions using an engine...
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SubjectTerms Aerospace engines
Algorithms
Calibration
Complexity
Computational Intelligence
Data Structures and Information Theory
Engineering
Evolutionary algorithms
Mathematical models
Multiple objective analysis
Optimization
Original Article
Parameters
Working conditions
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Title fSDE: efficient evolutionary optimisation for many-objective aero-engine calibration
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