Aero-engine dynamic model based on an improved compact propulsion system dynamic model

Abstract

The modern advanced aero-engine control methods are onboard dynamic model–based algorithms. In this article, a novel aero-engine dynamic modeling method based on improved compact propulsion system dynamic model is proposed. The aero-engine model is divided into inlet, core engine, surge margin and nozzle models for establishing sub-model in the compact propulsion system dynamic model. The model of core engine is state variable model. The models of inlet, surge margin and nozzle are nonlinear models which are similar to the component level model. A new scheduling scheme for basepoint control vector, basepoint state vector and basepoint output vector which considers the change of engine total inlet temperature is proposed to improve engine model accuracy especially the steady. The online feedback correction of measurable parameters is adopted to improve the steady and dynamic accuracy of model. The modeling errors of improved compact propulsion system dynamic model remain unchanged when engine total inlet temperature of different conditions are the same or changes small. The model accuracy of compact propulsion system dynamic model, especially the measurable parameters, is improved by online feedback correction. Moreover, the real-time performance of compact propulsion system dynamic model and improved compact propulsion system dynamic model are much better than component level model.

Keywords

Aero-engine onboard real time compact propulsion system dynamic model dynamic model

Get full access to this article

View all access options for this article.

References

Arkov

Kulikov

Breikin

TV.

Application of Markov chains to identification of turbine engine dynamic models. Int J Syst Sci 2006; 37(3): 197–205.

Zheng

Zhang

, et al. A turboshaft engine NMPC scheme for helicopter autorotation recovery maneuver. Aerosp Sci Tech 2018; 76: 421–432.

Zheng

Zhang

Miao

, et al. On-board real-time optimization control for turbo-fan engine life extending. Int J Turbo Jet Engine 2017; 34(4): 321–332.

Abdulnagimov

Trushin

Kulikov

GG.

Concept of monitoring for thermostressed state and service life of aircraft gas turbine engine blades. Russian Aeronaut 2016; 59(1): 77–83.

Zheng

Wang

Sun

, et al. Aero-engine direct thrust control with nonlinear model predictive control based on linearized DNN Predictor. Proc IMechE, Part I: J Systems and Control Engineering 2019; 234: 726–733.

Kulikov

Thompson

HA.

Dynamic modelling of gas turbines: identification, simulation, condition monitoring and optimal control. New York: Springer, 2004, p. 52.

Yuan

Lin

. Fault diagnosis and remaining useful life estimation of aero engine using LSTM neural network. In: 2016 IEEE international conference on aircraft utility systems (AUS), Beijing, China, 10–12 October 2016, pp.135–140. New York: IEEE.

Kisszölgyémi

Beneda

Faltin

. Linear quadratic integral (LQI) control for a small scale turbojet engine with variable exhaust nozzle. In: 2017 international conference on military technologies (ICMT), Brno, 31 May–2 June 2017, pp.507–513. New York: IEEE.

Montazeri-Gh

Abyaneh

Kazemnejad

Hardware-in-the-loop simulation of two-shaft gas turbine engine’s electronic control unit. Proc IMechE, Part I: J Systems and Control Engineering 2016; 230(6): 512–521.

10.

Kulikov

Ar’kov

Abdulnagimov

AI.

Hardware-in-the-loop testing technology for integrated control and condition monitoring systems of aircraft gas turbine engines. Russian Aeronaut 2008; 51(1): 47–52.

11.

Zheng

Wang

, et al. A study on global optimization and deep neural network modeling method in performance-seeking control. Proc IMechE, Part I: J Systems and Control Engineering 2019; 234: 46–59.

12.

Brotherton

Volponi

Luppold

, et al. eSTORM: Enhanced self-tuning on-board real-time engine model. In: 2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652), Big Sky, MT, 8–15 March 2003. New York: IEEE.

13.

Vloponi

Enhanced self-tuning on-board real-time model (eSTORM) for aircraft engine performance health tracking (NASA/CR-2008-215272). Columbus, OH: Biblio publishing, 2008.

14.

Connolly

Csank

Chicatelli

, et al. Model-based control of a nonlinear aircraft engine simulation using an optimal tuner Kalman filter approach. In: 49Th AIAA/ASME/SAE/ASEE joint propulsion conference, San Jose, CA, 14–17 July 2013. New York: IEEE.

15.

Zheng

Miao

Zhang

, et al. On-board real-time optimization control for turbofan engine thrust under flight emergency condition. Proc IMechE, Part I: J Systems and Control Engineering 2017; 231(7): 554–566.

16.

Zheng

Zhang

A global optimization control for turbo-fan engine acceleration schedule design. Proc IMechE, Part G: J Aerospace Engineering 2018; 232(2): 308–316.

17.

Zheng

Juan

, et al. Aero-engine on-board model based on batch normalize deep neural network. IEEE Access 2019; 7: 54855–54862.

18.

Zheng

Zhang

, et al. Aero-engine on-board dynamic adaptive MGD neural network model within a large flight envelope. IEEE Access 2018; 6(1): 45755–45761.

19.

Chen

Zhang

, et al. Modeling of the turbofan with an ejector nozzle based on infrared prediction. Appl Therm Eng 2019; 159: 113910.

20.

Volponi

. Use of hybrid engine modeling for on-board module performance tracking. In: ASME Turbo Expo 2005: power for land, sea, and air, Reno, NV, 6–9 June 2005, pp.525–533. New York: ASME.

21.

Maine

Gilyard

Lambert

. A preliminary evaluation of an F100 engine parameter estimation process using flight data. In: 26th joint propulsion conference, Orlando, FL, 16–18 July 1990, p.1921. Reston, VA: AIAA.

22.

Nobbs

Jacobs

Donahue

. Development of the full-envelope Performance Seeking Control algorithm. In: 28th joint propulsion conference and exhibit, Nashville, TN, 6–8 July 1992, p.3748. Reston, VA: AIAA.

23.

Orme

Conners

. Supersonic flight test results of a performance seeking control algorithm on a NASA-15 spacecraft. In: 30th joint propulsion conference and exhibit, Indianapolis, IN, 27–29 June 1994, p.3210. Reston, VA: AIAA.

24.

Volponi

AJ.

Gas turbine parameter corrections. J Eng Gas Turbin Power 1999; 121(4): 613–621.

25.

Malloy

Webb

Kidman

. F-22/f119 Propulsion system ground and flight test analysis using modeling and simulation techniques. In: ASME Turbo Expo 2002: power for land, sea, and air, Amsterdam, 3–6 June 2002, pp.1–8. New York: ASME.