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Acta Aeronautica et Astronautica Sinica ›› 2026, Vol. 47 ›› Issue (15): 632797.doi: 10.7527/S1000-6893.2025.32797

• Special Topic: Aeroengine Intelligent Control and Health Management • Previous Articles    

An improved high-to-low method for component characteristics modification towards curved surface smoothness

Zhaolong BAI, Xiaofeng LIU()   

  1. School of Transportations Science and Engineering,Beihang University,Beijing 102206,China
  • Received:2025-09-17 Revised:2025-09-29 Accepted:2025-11-10 Online:2025-11-14 Published:2025-11-13
  • Contact: Xiaofeng LIU E-mail:liuxf@buaa.edu.cn
  • Supported by:
    National Natural Science Foundation of China(52372371)

Abstract:

High-precision aeroengine digital models require well-matched component characteristics data. An improved component characteristics modification method is proposed to address the non-unique results and non-smooth curved surfaces from the traditional high-to-low method. Preliminary scaling modification is carried out through reference points to ensure high accuracy at design point and broad coverage across all operation points. Fitness function constructed from target parameters is optimized by using particle swarm optimization algorithm to determine optimal component correction coefficients for all operation points. Component characteristic maps are expanded by adding characteristic lines corresponding to these conditions. Both the expanded and original lines are scaled using the obtained coefficients, resulting in a fully-matched and continuously smooth characteristic curved surface. A comparative simulation between the improved method and traditional method was conducted on a two-spool mixed-flow engine. The simulation results demonstrate that all the relative errors of the target parameters corrected by the improved method are less than 1%, outperforming the tradition method in overall accuracy while successfully avoiding non-smooth correction results.

Key words: aeroengine, component characteristics modification, component level model, particle swarm optimization, off-design point matching

CLC Number: