United Technologies Corporation

Raytheon Technologies Corporation

Carrier Corporation

Pratt-Whitney Canada Corp

Rtx Corporation

Boris Karpman

Richard P Meisner

Manuj Dhingra

John L Shade

Ian Michael Dinsmore

Alexander Lifson

Subhradeep Chowdhury

Leonid Guerchkovitch

Matthew Donald

Mark E Lacour

Aaron J Kaufman

Thomas Niemczycki

Thomas E Case

David Sembiante

Robert H Luppold

Serge L Shishkin

Matthew R Feulner

David Lei Ma

Daniel E Kane

Juan A Marcos

Stefan M Poth, Jr

Brian V Winebrenner

John Douglas Lamb

Richard P Neisner

Alexandra I Britten

Thomas J Roadinger

Alex Lifson

Mark A Bushman

Jr Stefan M Poth

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

An engine control system includes an engine controller configured to execute an open-loop model of the engine control system. The open-loop model receives a measured effector and boundary condition parameter vector and generates a synthesized engine operating parameter based on the measured effector and boundary condition parameter vector. The engine controller calculates a corrector error value between the synthesized engine operating parameter and a measured engine operating parameter, and determines an open loop corrector error calculated as a difference between the corrector error and a vector-matrix product of corrector state vector and a gain map/function. The engine controller applies the gain map/function to the open loop corrector error to determine an effector and boundary condition error vector of the measured effector and boundary condition parameter vector.

On-board estimator effector drift detection in engine control

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

An engine control system includes an electronic hardware engine controller in signal communication with at least one engine sensor, which measures an engine operating parameter (Ycrtr_t). The engine controller generates a synthesized engine operating parameter (Ycrtr) calculates an error (ERRcrtr) between the engine operating parameter (Ycrtr_t) and the synthesized engine operating parameter (Ycrtr). The engine controller further determines a corrector error parameter (Xcrtr) and determines a faulty sensor among the at least one engine sensor based on a comparison between the error value (ERRcrtr) and the corrector error parameter (Xcrtr).

On-board estimator sensor drift detection in engine control

An engine control system includes an electronic hardware engine controller in signal communication with an actuator and an engine sensor. The actuator operates at a plurality of different positions to control operation of an engine. The engine sensor measures an engine operating parameter. The engine controller generates a synthesized engine operating parameter, and adjusts the position of the actuator based on the synthesized engine operating parameter in response to detecting a faulty engine sensor.

On-board estimator engine sensor fault accommodation in engine control

Systems and methods for controlling a fluid-based system are disclosed. The systems and methods may include generating a model output using a model processor, processing a model input vector and setting a model operating mode, and setting dynamic states of the model processor, the dynamic states input to an open loop model based on the model operating mode. Synthesized parameters are generated as a function of the dynamic states and the model input vector based on a series of utilities, where at least one of the utilities is a configurable utility including one or more sub-utilities. An estimated state of the model is determined based on at least one of a prior state and the synthesized parameters. An actuator associated with the control device is directed as a function of a model output, where the model output includes an estimated thrust value for the control device.

Compact aero-thermo model based engine power control

Systems and methods for controlling a fluid-based 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, the dynamic states input to an open loop model based on the model operating mode, where the open loop model generates current state derivatives, solver state errors, and synthesized parameters as a function of the dynamic states and a model input vector. A constraint on the current state derivatives and solver state errors is based on mathematical abstractions of physical laws that govern behavior of a component using a material temperature utility. The model processor may further include an estimate state module for determining an estimated state of the model based on at least one of a prior state, the current state derivatives, the solver state errors, and the synthesized parameters.

Compact aero-thermo model based engine material temperature control

Systems and methods for controlling a fluid-based 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, the dynamic states input to an open loop model based on the model operating mode, where the open loop model generates current state derivatives, solver state errors, and synthesized parameters as a function of the dynamic states and a model input vector. A constraint on the current state derivatives and solver state errors is based on mathematical abstractions of physical laws that govern behavior of a component of a cycle of a control device. The model processor may further include an estimate state module for determining an estimated state of the model based on at least one of a prior state, the current state derivatives, the solver state errors, and the synthesized parameters.

Systems and methods for controlling a fluid-based 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, the dynamic states input to an open loop model based on the model operating mode, where the open loop model generates current state derivatives, solver state errors, and synthesized parameters as a function of the dynamic states and a model input vector. A constraint on the state derivatives and solver state errors is based a series of utilities that are based on mathematical abstractions of physical laws that govern behavior of the component. The model processor may include an estimate state module for determining an estimated state of the model based on at least one of a prior state, the current state derivatives, the solver state errors, and the synthesized parameters.

Compact aero-thermo model based control system

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 at least one of a prior state, current state derivatives, solver state errors, and synthesized parameters. The estimate state module determines an estimator gain associated with the current state derivatives and applies the estimator gain to determine the estimated state of the model.

Compact aero-thermo model base point linear system based state estimator

An engine control system includes an electronic hardware engine controller and an actuator that operates at different positions to control operation of an engine. An actuator sensor measures an actuator position, and the engine controller generates a synthesized actuator position. In response to detecting a faulty actuator, a faulty actuator sensor, or both, the engine controller adjusts the position of the actuator based on the synthesized actuator position.

On-board estimator actuator system fault accommodation in engine control

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 include an input object for processing model input and setting a model operating mode, the model operating mode being a starting mode if the model input is within a data range associated with a starting operation of the control device. 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.

Compact aero-thermo model based control system estimator starting algorithm

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, where the open loop model generates current state derivatives, solver state errors, and synthesized parameters as a function of the dynamic states and a model input vector, where a constraint on the current state derivatives and solver state errors is based a series of cycle synthesis modules. The series of cycle synthesis modules may include a flow module for mapping a flow curve relating a compressible flow function to a pressure ratio and for defining a solution point located on the flow curve and a base point located off the flow curve.

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Marlborough, CT, United States of America

Boris Karpman