Aircraft Energy Management Iterative Optimization
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Solution Overview
Problem
Current aircraft energy management during flight approaches, particularly for landing, relies heavily on pilot expertise and manual control of energy-controlling means, leading to suboptimal energy distribution and increased pilot workload, as existing automation levels do not fully address non-nominal situations or provide precise energy state feedback.
Innovation Solution
An automated method and device that iteratively determine and apply optimized command orders for energy control means, such as slats, flaps, landing gear, and engines, based on real-time and predicted energy states, using predetermined models and strategies to ensure the aircraft reaches a given operational state while reducing pilot workload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated energy management system is implemented, then energy distribution optimization is improved, but device complexity increases
Solution Approach 1:
The energy management system automatically determines current airplane parameters, calculates predicted energy states, and generates optimized command orders without continuous pilot intervention. The system serves itself by using onboard sensors and computers to monitor and control energy-controlling means, reducing the need for external manual control while optimizing energy distribution throughout the approach phase.
Solution Approach 2:
The system continuously monitors current values of airplane parameters and uses this feedback to iteratively calculate predicted energy states at the given point. The feedback loop compares actual energy state with predicted state and adjusts command orders accordingly, enabling dynamic optimization of energy distribution while maintaining system stability despite increased complexity.
2Manufacturing precision
If iterative calculation of predicted energy state is performed, then energy management precision is improved, but loss of time increases
Solution Approach 1:
The system performs iterative calculations of predicted energy state in advance during the approach phase, using predetermined models and strategies to determine optimal command orders before reaching the given point. By calculating energy trajectories ahead of time and continuously refining them through iteration, the system achieves high precision without causing time delays during critical landing moments.
Solution Approach 2:
The iterative calculation process operates continuously throughout the approach phase, constantly updating predicted energy states based on current airplane parameters. This continuous refinement maintains high precision by accounting for changing flight conditions while distributing calculation workload over time rather than concentrating it, thus minimizing time loss.
3Reliability
If multiple energy controlling means are coordinated, then energy management effectiveness is improved, but device complexity increases
Solution Approach 1:
The system merges control of multiple energy-controlling means (engines, airbrakes, slats, flaps, landing gear) into a unified automated management system. By combining these previously separate control functions under a single iterative optimization framework, the system improves overall energy management effectiveness while the integration itself manages the complexity through centralized coordination rather than multiple independent control loops.
Solution Approach 2:
The automated energy management system performs multiple functions simultaneously: monitoring airplane parameters, calculating energy states, generating command orders, and coordinating various energy-controlling means. This multi-functional approach improves effectiveness by ensuring all energy means work together coherently while the universal control algorithm manages complexity through a single integrated decision-making process.
Data Source
AI summary
Method and device for an optimal management of the energy of an aircraft.The device (1) includes means (5) for determining, in an iterative manner, according to a predicted energy state and according to a management strategy, optimal commands of means (S1,S2, S3, S4, S5, S6) for controlling the energy of the aircraft, which allow the aircraft to reach a given point of a trajectory in a given operational state.