United Technologies Corporation

Pratt-whitney Canada Corp

Raytheon Technologies Corporation

Rtx Corporation

Georgia Tech Research Corporation

Manuj Dhingra

Richard P Meisner

Boris Karpman

Timothy J Crowley

Joshua Adams

Martin Richard Amari

Leonid Guerchkovitch

Aaron J Kaufman

David Lei Ma

Sorin Bengea

David Gelwan

Jonnalagadda V R Prasad

Kevin Hendricks

Coy Bruce Wood

Matthew R Feulner

Ramesh Rajagopalan

Patrick D Couture

Brenda J Lisitano

Yedidia Neumeier

Timothy J Gaudet

Stephen A Witalis

Joseph Kehoe

Andrew B Thompson

Christopher L Ho

Assaad Krichene

Gi-Yun Chung

An engine system for an aircraft includes a gas turbine engine and a control system. The control system is configured to motor the gas turbine engine, absent fuel burn, during a taxi mode of the aircraft. The control system is further configured to accelerate a motoring speed of the gas turbine engine, absent fuel burn, above an idle speed of the gas turbine engine to provide propulsion during the taxi mode. The control system is configured to decrease the motoring speed of the gas turbine engine, absent fuel burn, based on a change in a starting mode of the gas turbine engine or the aircraft reaching a targeted new position.

Ground-based aircraft movement

A method of controlling a hybrid-electric aircraft powerplant includes running a first control loop for command of a thermal engine based on error between total response commanded for a hybrid-electric powerplant and total response from the hybrid-electric powerplant. A second control loop runs in parallel with the first control loop for commanding the thermal engine based on error between maximum thermal engine output and total response commanded. A third control loop runs in parallel with the first and second control loops for commanding engine/propeller speed, wherein the third control loop outputs a speed control enable or disable status. A fourth control loop runs in parallel with the first, second, and third control loops for commanding the electric motor with non-zero demand when the second control loop is above control to add response from the electric motor to response from the thermal engine to achieve the response commanded.

Parallel control loops for hybrid electric aircraft

A hybrid electric propulsion system includes a gas turbine engine having at least one compressor section and at least one turbine section operably coupled to a shaft. The hybrid electric propulsion system includes an electric motor configured to augment rotational power of the shaft of the gas turbine engine. A controller is operable to determine hybrid electric propulsion system parameters based on a composite system model and sensor data, determine a prediction based on the hybrid electric propulsion system parameters and the composite system model, determine a model predictive control optimization for a plurality of hybrid electric system control effectors based on the prediction using a plurality of reduced-order partitions of the composite system model, and actuate the hybrid electric system control effectors based on the model predictive control optimization.

Adaptive model predictive control for hybrid electric propulsion

A method of controlling a multi-engine aircraft includes receiving input for commanded thrust and modifying the commanded thrust using a model of an incumbent powerplant to generate a modified commanded thrust for matching aircraft performance with a new powerplant to the aircraft performance with the incumbent powerplant. The method includes applying the modified commanded thrust to the new powerplant.

Engine characteristics matching

A hybrid electric propulsion system includes a gas turbine engine having at least one compressor section and at least one turbine section operably coupled to a shaft. The hybrid electric propulsion system includes an electric motor configured to augment rotational power of the shaft of the gas turbine engine. A controller is operable to determine an estimate of hybrid electric propulsion system parameters based on a composite system model and sensor data, determine a model predictive control state and a prediction based on the hybrid electric propulsion system parameters and the composite system model, determine a model predictive control optimization for a plurality of hybrid electric system control effectors based on the model predictive control state and the prediction using a plurality of reduced-order partitions of the composite system model, and actuate the hybrid electric system control effectors based on the model predictive control optimization.

A method of operating a gas turbine engine includes commanding an acceleration of the gas turbine engine and moving a variable pitch high pressure compressor vane toward an open position thereby reducing an acceleration rate of a high pressure turbine rotor thereby reducing a change in a clearance gap between the high pressure turbine rotor and a blade outer airseal. An active clearance control system of a gas turbine engine includes an engine control system configured to command an acceleration of the gas turbine engine and move a variable pitch high pressure compressor vane toward an open position thereby slowing an acceleration rate of a high pressure turbine rotor thereby reducing a change in a clearance gap between the high pressure turbine rotor and a blade outer airseal located radially outboard of the high pressure turbine rotor.

Active multi-effector control of high pressure turbine clearances

A system for controlling a plurality of hydraulic effectors operably connected to an engine to control engine parameters. The system also includes a plurality of sensors operably connected to measure a state or parameter of each effector, a pump configured to supply fluid to the plurality of effectors, and a controller operably connected to the plurality of sensors, the plurality of effectors, and the pump. The controller executes a method for an adaptive model-based control for controlling each effector, The method includes receiving a request indicative of a desired state for each effector, receiving a weighting associated each request, obtaining information about a current state of each effector, and updating an adaptive model based control (MBC) based upon the information. The method also includes generating a control command for an effector based upon the adaptive MBC and commanding the effector based upon the control command.

Model predictive control sub-system hydraulic flow management

A system for controlling a plurality of electromechanical effectors operably connected to an engine to control engine parameters. The system also includes a plurality of sensors operably connected to measure a state or parameter of each effector, a power supply configured to supply power to the plurality of effectors, and a controller operably connected to the plurality of sensors, the plurality of effectors, and the power supply. The controller executes a method for an adaptive model-based control for controlling each effector, The method includes receiving a request indicative of a desired state for each effector, receiving a weighting associated each request, obtaining information about a current state of each effector, and updating an adaptive model based control (MBC) based upon the information. The method also includes generating a control command for an effector based upon the adaptive MBC and commanding the effector based upon the control command.

Model predictive control sub-system power management

Systems and methods for controlling a fluid based engineering system are disclosed. The systems and methods may include a model processor configured to generate a model output, the model processor including a set state module for setting dynamic states of the model processor, the dynamic states input to an open loop model based on a model operating mode. The model processor may further include an estimate state module configured to determine an estimated state of the model based on at least one of a prior state, current state derivatives, solver state errors, and synthesized parameters, the estimate state module using online linearization and gain calculation to determine estimator gain for determining the estimated state of the model.

Compact aero-thermo model real time linearization based state estimator

Systems and methods for controlling a fluid based engineering system are disclosed. The systems and methods may include a model processor for generating a model output, the model processor including a set state module for setting dynamic states of the model processor, the dynamic states input to an open loop model based on the model operating mode. The model processor may further include an estimate state module for determining an estimated state of the model based on a prior state model output and the current state model of the open loop model the estimate state module using online linearization and gain calculation to determine estimator gain for determining the estimated state of the model.

A method for model-based control of a gas turbine engine is disclosed. An operating point of the gas turbine engine is generated from measured parameters using a component-level model. The component-level model is analytically linearized by taking the first partial derivative of output parameters of each component with respect to input parameters of each component, and evaluating the result at the operating point. Components of the linearized component-level model are combined to form a combined perturbational model of the gas turbine engine, which is inverted to solve for control commands as a function of target parameters and measured parameters.

Real time linearization of a component-level gas turbine engine model for model-based control

Methods for avoiding surge in a compressor are provided. A representative method includes detecting precursor information of the compressor and controlling the compressor based on the precursor information to avoid a surge condition in the compressor. The control scheme for the method uses a real time observer for on-line identification of magnitude and frequency of dominant precursor waves. The observer outputs feed into a fuzzy logic control scheme, and the identified frequency and amplitude of the precursors are used to actuate devices, such as a bleed valve and/or a fuel valve, for active control of compressor surge. Systems and other methods are provided.

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Glastonbury, CT, United States of America

Manuj Dhingra