Modeling and Control Optimization of the Shaft Driven Lift Fan Engagement

Tianmu Jiang, Xiaobo Zhang, Zhanxue Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper presents the modeling and control optimization of the shaft driven lift fan (SDLF) engagement. The SDLF propulsion system is a key component for short takeoff and vertical landing (STOVL) aircraft. Through lift fan engagement, the propulsion system can obtain high levels of thrust augmentation required for STOVL. Coordination of control of the lift fan, the cruise engine, and the clutch during SDLF engagement is essential for STOVL aircraft control. The dynamic performance model of the SDLF propulsion system is built to design the control law during the SDLF engagement. The dynamic model of the clutch is obtained by analyzing the working principle of the clutch. According to the different working states of the clutch, the balance equations of the propulsion system, namely its dynamic performance model, are set up. A pointwise optimization method is proposed to optimize the control law during the SDLF engagement. The method establishes a control law optimization problem at each control time step. Each optimization problem adaptively establishes an objective function to minimize the transition time according to the clutch working state and the relationship between lift fan speed, engine speed and expected lock-up speed. Some control optimizations are carried out to verify the proposed control optimization method. The results show that the proposed method can realize fast and safe engagement without violating the constraints. The clutch lock-up speed greatly influences the transition performance of the engagement. A higher clutch lock-up speed leads to a shorter transition time, more clutch heat generation due to a longer slipping time, and requires a larger clutch size due to an enormous friction torque.

Original languageEnglish
Title of host publication2023 IEEE Aerospace Conference, AERO 2023
PublisherIEEE Computer Society
ISBN (Electronic)9781665490320
DOIs
StatePublished - 2023
Event2023 IEEE Aerospace Conference, AERO 2023 - Big Sky, United States
Duration: 4 Mar 202311 Mar 2023

Publication series

NameIEEE Aerospace Conference Proceedings
Volume2023-March
ISSN (Print)1095-323X

Conference

Conference2023 IEEE Aerospace Conference, AERO 2023
Country/TerritoryUnited States
CityBig Sky
Period4/03/2311/03/23

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