A dynamic performance diagnostic method applied to hydrogen powered aero engines operating under transient conditions

Yu-Zhi Chen, Elias Tsoutsanis, Heng-Chao Xiang, Yi-Guang Li, Jun-Jie Zhao

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At present, aero engine fault diagnosis is mainly based on the steady-state condition at the cruise phase, and the gas path parameters in the entire flight process are not effectively used. At the same time, high quality steady-state monitoring measurements are not always available and as a result the accuracy of diagnosis might be affected. There is a recognized need for real-time performance diagnosis of aero engines operating under transient conditions, which can improve their condition-based maintenance. Recent studies have demonstrated the capability of the sequential model-based diagnostic method to predict accurately and efficiently the degradation of industrial gas turbines under steady-state conditions. Nevertheless, incorporating real-time data for fault detection of aero engines that operate in dynamic conditions is a more challenging task. The primary objective of this study is to investigate the performance of the sequential diagnostic method when it is applied to aero engines that operate under transient conditions while there is a variation in the bypass ratio and the heat soakage effects are taken into consideration. This study provides a novel approach for quantifying component degradation, such as fouling and erosion, by using an adapted version of the sequential diagnostic method. The research presented here confirms that the proposed method could be applied to aero engine fault diagnosis under both steady-state and dynamic conditions in real-time. In addition, the economic impact of engine degradation on fuel cost and payload revenue is evaluated when the engine under investigation is using hydrogen. The proposed method demonstrated promising diagnostic results where the maximum prediction errors for steady state and transient conditions are less than 0.006% and 0.016%, respectively. The comparison of the proposed method to a benchmark diagnostic method revealed a 15% improvement in accuracy which can have great benefit when considering that the cost attributed to degradation can reach up to $702,585 for 6000 flight cycles of a hydrogen powered aircraft fleet. This study provides an opportunity to improve our understanding of aero engine fault diagnosis in order to improve engine reliability, availability, and efficiency by online health monitoring.

Original languageEnglish
Article number119148
Number of pages20
JournalApplied Energy
Early online date26 Apr 2022
Publication statusPublished - 1 Jul 2022

Bibliographical note

Funding Information:
This work is supported by the National Science and Technology Major Project under Grant No. 2017-V-0011-0062, and the Nature Science Foundation of Shaanxi under Grant No. NO. 2020JM-149.

Publisher Copyright:
© 2022 The Author(s)


  • Aero Engine Performance
  • Condition Monitoring
  • Economic Impact
  • Model-Based Method
  • Turbofan Engine Diagnostics

ASJC Scopus subject areas

  • Building and Construction
  • Mechanical Engineering
  • Energy(all)
  • Management, Monitoring, Policy and Law


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