Adaptive-Cycle Engine Thermal Management via Real-Time Optimization
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Solution Overview
Problem
Military gas turbine engines face inefficiencies in specific fuel consumption and thermal management, requiring adaptive cycle engines that balance high thrust and power-to-weight ratios with low fuel consumption, while also addressing increased cooling demands due to advanced electronics and thermal loads from electrification in aircraft systems.
Innovation Solution
An adaptive-power thermal management system (APTMS) utilizing real-time optimization solvers and predictive models to control interconnected sub-systems, including Fuel Thermal Management, Directed Energy Weapon thermal management, Vapor Cycle Systems, and Air Cycle Systems, to optimize fuel flow, heat transfer, and cooling power distribution dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If military gas turbine engines use high power to weight ratio design, then high thrust and power-to-weight ratio are achieved, but specific fuel consumption increases
Solution Approach 1:
The patent implements variable cycle engine technology that dynamically adjusts engine operating parameters including bypass ratio, compressor pressure ratio, and turbine inlet temperature based on flight conditions. This allows the engine to adapt between high thrust modes (low bypass ratio) and efficient cruise modes (high bypass ratio), resolving the contradiction between power-to-weight ratio and fuel consumption across different operating regimes
Solution Approach 2:
The engine control system continuously varies critical parameters such as bypass ratio, compression ratio, and thermal management settings to optimize performance. By changing these parameters in real-time, the engine achieves high power output when needed while maintaining lower fuel consumption during sustained operation, directly addressing the technical contradiction
2Adaptability or versatility
If advanced electronics and directed energy weapons are added to military aircraft, then combat capability is enhanced, but cooling power requirements increase to megawatt levels
Solution Approach 1:
The engine's third stream (exhaust bypass flow) serves multiple functions: it provides thrust augmentation, cools the engine components, and acts as a heat sink for thermal management of avionics and directed energy weapons. This multi-functional use of the same thermal resource resolves the contradiction by utilizing existing engine flows for additional cooling purposes without requiring separate dedicated cooling systems
Solution Approach 2:
The engine's own exhaust gases and thermal energy are utilized to provide cooling for the aircraft's electronic systems and weapons. The thermal management system recycles waste heat from the engine to cool sensitive components, allowing the system to serve its own thermal management needs and reducing the burden on external cooling systems
3Productivity
If More Electric Aircraft systems are implemented, then efficiency and capability are improved, but thermal loads from electrification increase
Solution Approach 1:
The engine's third stream and thermal management system act as an intermediary between the electrified aircraft systems and the ambient environment. Electrical components generate heat that is transferred to the engine's cooling flows, which then dissipate this heat through the exhaust and bypass systems, effectively mediating the thermal management of electrified systems without compromising efficiency
Data Source
AI summary
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.