Design of mode transition control system for tandem TBCC engine based on direct performance parameters closed-loop control

Zhihua Xi; Cheng Chen; Ming Chen; Haibo Zhang

doi:10.1515/tjj-2023-0069

Article

Design of mode transition control system for tandem TBCC engine based on direct performance parameters closed-loop control

Zhihua Xi , Cheng Chen , Ming Chen and Haibo Zhang

Published/Copyright: October 12, 2023

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From the journal International Journal of Turbo & Jet-Engines Volume 41 Issue 3

Abstract

This paper conducts a study on closed-loop control of engine performance parameters during mode transition process of TBCC engine based on artificial intelligence method. Firstly, a composite modeling method based on stepwise regression analysis and batch normalization-depth neural network is proposed to establish the on-board model during mode transition to estimate the thrust and inlet airflow in real-time. Secondly, based on the hybrid penalty function-particle swarm optimization algorithm, a mode transition control schedule applicable to the closed-loop control of thrust and inlet airflow is developed. Finally, a data processing method based on similarity conversion is proposed to extend the applicable envelope range of the mode transition control system. The transition time is shortened by 33.3 %, and the fluctuations of thrust and inlet airflow are reduced by 1.33 % and 10.77 %, respectively. When the control system is applied to the off-design mode transition process, a satisfactory mode transition performance is also obtained.

Keywords: turbine-based combined cycle; on-board model; mode transition control schedule; direct performance parameters; similarity conversion

Corresponding author: Zhihua Xi, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China, E-mail: shanexzh@yeah.net

Abbreviation

TBCC: turbine-based combined cycle
MSV: mode selector valve
VABI: variable area bypass injector
BN–DNN: batch normalization–depth neural network
HP–PSO: hybrid penalty function–particle swarm optimization
HPT: high-pressure turbine
LPT: low-pressure turbine

Nomenclature

Ma: mach number
H: flight height (m)
A _C: inlet capture area (m²)
σ: total pressure recovery coefficient
φ: discharge coefficient
q(λ): mass flow parameter
MR: opening of MSV
VR: opening of VABI
RM: recirculation margin
n _f: fan speed (%)
n _c: compressor speed (%)
W _f: fuel flow (kg/s)
W _a: airflow (kg/s)
F: thrust (kN)
s _ml: fan surge margin
s _mh: compressor surge margin
t _mt: mode transition time (s)

Research ethics: Not applicable.
Author contributions: The author(s) have (has) accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interests: The author(s) state(s) no conflict of interest.
Research funding: This study was supported in part by National Science and Technology Major Project under Grant 2017-V-0004-0054; in part by Research on the Basic Problem of Intelligent Aero-engine under Grant 2017-JCJQ-ZD-047-21; in part by Natural Science Foundation of Jiangsu Province University under No: 20KJB470017.
Data availability: The raw data can be obtained on request from the corresponding author.

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Received: 2023-08-02

Accepted: 2023-09-18

Published Online: 2023-10-12

Published in Print: 2024-08-27

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Articles in the same Issue

https://doi.org/10.1515/tjj-2023-0069

Keywords for this article

turbine-based combined cycle; on-board model; mode transition control schedule; direct performance parameters; similarity conversion