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A Novel Real-Time Mechanism Modeling Approach for Turbofan Engine

Author

Listed:
  • Qianjing Chen

    (Jiangsu Province Key Laboratory Power Systems, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Jinquan Huang

    (Jiangsu Province Key Laboratory Power Systems, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Muxuan Pan

    (Jiangsu Province Key Laboratory Power Systems, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Feng Lu

    (Jiangsu Province Key Laboratory Power Systems, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Abstract

Nonlinear component level model (NCLM) is a widely used model for aeroengines. However, it requires iterative calculation and is, therefore, time-consuming, which restricts its real-time application. This study aims at developing a simplified real-time modeling approach for turbofan engines. A mechanism modeling approach is proposed based on linear models to avoid the iterative calculation in NCLM so as to effectively reduce the computational complexity. Linear local models, of which the outputs are the solution of the balance equations in NCLM, are established at the ground operating points and are combined into a linear parameter varying (LPV) state-space model. Then, the model is extended throughout the full flight envelope in a polytopic expression and is integrated with the flow path calculation to obtain satisfactory real-time performance. In order to ensure the accuracy of the integrated model, the upper bound of convergence residual of the iteration is strictly set and consideration on the interpolation method is taken. The simulation results demonstrate that the integrated model requires much less computational resources than the NCLM does. Meanwhile, it maintains an acceptable accuracy performance and, therefore, is suitable for real-time application.

Suggested Citation

  • Qianjing Chen & Jinquan Huang & Muxuan Pan & Feng Lu, 2019. "A Novel Real-Time Mechanism Modeling Approach for Turbofan Engine," Energies, MDPI, vol. 12(19), pages 1-18, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:19:p:3791-:d:274021
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    References listed on IDEAS

    as
    1. Yirop Kim & Myoungsoo Kim & Sechul Oh & Woojae Shin & Seokwon Cho & Han Ho Song, 2019. "A New Physics-Based Modeling Approach for a 0D Turbulence Model to Reflect the Intake Port and Chamber Geometries and the Corresponding Flow Structures in High-Tumble Spark-Ignition Engines," Energies, MDPI, vol. 12(10), pages 1-24, May.
    2. Muxuan Pan & Hao Wang & Jinquan Huang, 2019. "T–S Fuzzy Modeling for Aircraft Engines: The Clustering and Identification Approach," Energies, MDPI, vol. 12(17), pages 1-15, August.
    3. Junjie Lu & Feng Lu & Jinquan Huang, 2018. "Performance Estimation and Fault Diagnosis Based on Levenberg–Marquardt Algorithm for a Turbofan Engine," Energies, MDPI, vol. 11(1), pages 1-18, January.
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    Cited by:

    1. Zeyang Zhou & Jun Huang, 2020. "Study of the Radar Cross-Section of Turbofan Engine with Biaxial Multirotor Based on Dynamic Scattering Method," Energies, MDPI, vol. 13(21), pages 1-20, November.
    2. Ziyu Gu & Shuwei Pang & Wenxiang Zhou & Yuchen Li & Qiuhong Li, 2022. "An Online Data-Driven LPV Modeling Method for Turbo-Shaft Engines," Energies, MDPI, vol. 15(4), pages 1-19, February.

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