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Advanced Controls for Fuel Consumption and Time-on-Wing Optimization in Commercial Aircraft Engines

[+] Author Affiliations
Daniel Viassolo, Aditya Kumar, Brent Brunell

General Electric Global Research Center, Niskayuna, NY

Paper No. GT2007-27214, pp. 539-548; 10 pages
  • ASME Turbo Expo 2007: Power for Land, Sea, and Air
  • Volume 1: Turbo Expo 2007
  • Montreal, Canada, May 14–17, 2007
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 0-7918-4790-X | eISBN: 0-7918-3796-3
  • Copyright © 2007 by ASME


This paper introduces an architecture that improves the existing interface between flight control and engine control. The architecture is based on an on-board dynamic engine model, and advanced control and estimation techniques. It utilizes a Tracking Filter (TF) to estimate model parameters and thus allow a nominal model to match any given engine. The TF is combined with an Extended Kalman Filter (EKF) to estimate unmeasured engine states and performance outputs, such as engine thrust and turbine temperatures. These estimated outputs are then used by a Model Predictive Control (MPC), which optimizes engine performance subject to operability constraints. MPC objective and constraints are based on the aircraft operation mode. For steady-state operation, the MPC objective is to minimize fuel consumption. For transient operation, such as idle-to-takeoff, the MPC goal is to track a thrust demand profile, while minimizing turbine temperatures for extended engine time-on-wing. Simulations at different steady-state conditions over the flight envelope show important fuel savings with respect to current control technology. Simulations for a set of usual transient show that the TF/EKF/MPC combination can track a desired transient thrust profile and achieve significant reductions in peak and steady-state turbine gas and metal. These temperature reductions contribute heavily to extend the engine time-on-wing. Results for both steady state and transient operation modes are shown to be robust with respect to engine-engine variability, engine deterioration, and flight envelope operating point conditions. The approach proposed provides a natural framework for optimal accommodation of engine faults through integration with fault detection algorithms followed by update of the engine model and optimization constraints consistent with the fault. This is a potential future work direction.

Copyright © 2007 by ASME



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