Systems and methods for control of an adaptive-cycle engine with power-thermal management system

• US 9,354,621 B2
• Filed: 06/16/2014
• Issued: 05/31/2016
• Est. Priority Date: 06/16/2014
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Westervelt, Eric Richard, Breig, Benjamin Paul, Dokucu, Mustafa Tekin, Garrigan, Neil Richard, Gerstler, William Dwight, Parrilla, Javier Armando
• Primary Examiner(s): Nguyen, Nga X
• Application Number:
  US14/305,063
• Publication Number:
  US 20150362923A1
• Time in Patent Office: 715 Days
• Field of Search: 701/3, 700287-289
• US Class Current: 1/1
• CPC Class Codes: G05B 13/026 using a predictor
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05D 23/1917 using digital means

Abstract

A control system for an adaptive-power thermal management system of an aircraft having at least one adaptive cycle gas turbine engine includes a real time optimization solver that utilizes a plurality of models of systems to be controlled, the plurality of models each being defined by algorithms configured to predict changes to each system caused by current changes in input to each system. The real time optimization solver is configured to solve an open-loop optimal control problem on-line at each of a plurality of sampling times, to provide a series of optimal control actions as a solution to the open-loop optimal control problem. The real time optimization solver implements a first control action in a sequence of control actions and at a next sampling time the open-loop optimal control problem is re-posed and re-solved.

Claims

1. A control system for an adaptive-power thermal management system of an aircraft having at least one adaptive cycle as turbine engine, the control system comprising:

a real time optimization solver that utilizes a plurality of models of systems to be controlled, the plurality of models each being defined by algorithms configured to predict changes to each system caused by current changes in input to each system and configured to solve an open-loop optimal control problem on-line at each of a plurality of sampling times, to provide a series of optimal control actions as a solution to the open-loop optimal control problem,

wherein the real time optimization solver implements a first control action in a sequence of control actions and at a next sampling time the open-loop optimal control problem is re-posed and re-solved and is coupled to a model-based estimator that is configured to receive signals from a sensor suite, the signals being indicative of parameters of the engine systems of the aircraft, and the adaptive-power thermal management system, and estimate at least one parameter on-line in order to improve the predictive capability of the plurality of models of the systems representing the overall adaptive-power thermal management system by either estimating at least one parameter as an initial state of at least one of the predictive models or as an uncertain parameter of these system models, and wherein the plurality of models includes a fuel thermal management system model, a directed energy weapon thermal management system model, a vapor cycle system model, and an air cycle system model.

2. The control system of claim 1, wherein the fuel thermal management system model comprises an internal fuel tank of the aircraft, a fuel pump, a plurality of heat exchangers, a condenser, and a combustor of the at least one engine.

3. The control system of claim 2, wherein the vapor cycle system model includes a compressor, a plurality of condensers, and a plurality of heat exchangers, and one condenser of the vapor cycle system model corresponds to one condenser of the fuel thermal management system model.

4. The control system of claim 3, wherein air cycle system model includes a condenser and a heat exchanger, and the condenser of the air cycle system corresponds to one of the condensers of the vapor cycle system and the heat exchanger of the air cycle system corresponds to one of the heat exchangers of the fuel thermal management system.

5. The control system of claim 1, wherein inputs to the real time optimization solver include a mission profile of the aircraft that is a forecast of profiles of mission states including engine states, aircraft states, and adaptive-power thermal management system states.

6. The control system of claim 5, wherein the engine states include third-stream temperatures of the at least one engine and/or fuel flow, the aircraft states include altitude, mach number, and/or ambient temperature, and the adaptive-power thermal management system states include heat-sink temperatures, fuel flow rates, and/or coolant flow rates.

7. The control system of claim 1, wherein the control action comprises bleed flow commands, electrical system load commands, cooling load commands, and/or valve position commands.

8. The control system of claim 7, wherein the solution comprises fuel consumption reduction, flight range increase, and/or thermal heat sink availability.

9. A method of controlling an adaptive-power thermal management system of an aircraft having at least one adaptive cycle gas turbine engine, the method comprising:

receiving signals indicative of parameters of the engine, systems of the aircraft, and the adaptive-power thermal management system;

estimating at least one parameter;

solving in real time an open-loop optimal control problem at each of a plurality of sampling times using the at least one parameter as an initial state of each system to be controlled;

providing a series of control actions as a solution to the open-loop optimal finial control problem, wherein a plurality of models of systems to be controlled are each defined by algorithms configured to predict changes to each system caused by current changes in input to each system, wherein the method further comprises

implementing a first control action in a sequence of control actions; and

at a next sampling time, re-posing and solving the open-loop optimal control problem, wherein the plurality of models includes a fuel thermal management system model, a directed energy weapon thermal management system model, a vapor cycle system model, and an air cycle system model, and wherein the fuel thermal management system model comprises an internal fuel tank of the aircraft, a fuel pump, a plurality of heat exchangers, a condenser, and a combustor of the at least one engine.

10. The method of claim 9, wherein the directed energy weapon thermal management system model includes a hot fuel tank, a cold fuel tank, a hot to cold pump, a cold to hot pump, and a plurality of heat exchangers.

11. The method of claim 10, wherein the vapor cycle system model includes a compressor, a plurality of condensers, and a plurality of heat exchangers, and one condenser of the vapor cycle system model corresponds to one condenser of the fuel thermal management system model.

12. The method of claim 11, wherein air cycle system model includes a condenser and a heat exchanger, and the condenser of the air cycle system corresponds to one of the condensers of the vapor cycle system and the beat exchanger of the air cycle system corresponds to one of the heat exchangers of the fuel thermal management system.

13. The method of claim 9, further comprising further comprising generating a mission profile of the aircraft as input to the open-loop optimal control problem that is a forecast of profiles of mission states including, engine states, aircraft states, and adaptive-power thermal management system states.

14. The method of claim 13, wherein the engine states include third-stream temperatures of the at least one engine and/or fuel flow, the aircraft states include altitude, mach number, and/or ambient temperature, and the adaptive-power thermal management system states include heat-sink temperatures, fuel flow rates, and/or coolant flow rates.

15. The method of claim 9, wherein the control action comprises bleed flow commands, electrical system load commands, cooling load commands, and/or valve position commands.

16. The method of claim 15, wherein solving comprises determining fuel consumption reduction, flight range increase, and/or thermal heat sink availability.