Continuous Aircraft Climb Planning Under Altitude and Speed Constraints
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Solution Overview
Problem
Current aircraft trajectory calculation methods, particularly in climb phases, face challenges in efficiently managing altitude and speed constraints, leading to suboptimal climb profiles that can result in non-compliance with safety standards, increased fuel consumption, and passenger discomfort due to abrupt thrust variations.
Innovation Solution
The method determines an optimal continuous climb strategy, adjusts parameters such as energy sharing ratios, thrust, and roll angles to create a smoothed ascent profile that respects altitude and speed constraints, minimizing slope variations and avoiding constant altitude stops, while allowing for real-time adjustments to match selected flight dynamics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If energy sharing mode is used with fixed energy distribution, then climb thrust is maximized, but rate of climb becomes non-adjustable and may cause leveling off to meet future altitude constraints
Solution Approach 1:
The patent applies dynamics by making the energy distribution ratio adjustable rather than fixed. The system dynamically modifies the proportion of excess energy allocated to speed increase versus altitude gain, allowing the rate of climb to be adapted in real-time to meet future altitude constraints while maintaining maximum climb thrust capability.
Solution Approach 2:
The patent changes the parameter of energy distribution ratio from a fixed value to a variable parameter. By adjusting this ratio, the system can control the rate of climb and prevent premature leveling off, while still operating in energy sharing mode to maximize climb thrust.
2Speed
If rate of climb is high, then climb performance is improved, but leveling off occurs to meet future altitude constraints
Solution Approach 1:
The patent applies preliminary action by using predictions of future altitude constraints to adjust the current rate of climb. The system proactively modifies the energy distribution ratio before the aircraft reaches points where leveling off would be necessary, ensuring smooth compliance with altitude constraints without abrupt thrust variations.
Solution Approach 2:
The patent implements feedback by continuously monitoring predicted altitude constraints and adjusting the energy distribution ratio accordingly. The system uses this feedback loop to maintain optimal rate of climb while ensuring compliance with future altitude requirements, preventing both premature leveling off and non-compliance.
3Reliability
If rate of climb is low, then altitude constraints are met, but lateral trajectory length increases and fuel consumption rises
Solution Approach 1:
The patent applies dynamics by dynamically adjusting the energy distribution ratio to optimize the balance between compliance with altitude constraints and fuel efficiency. Rather than using a fixed low rate of climb, the system adaptively modifies the climb profile to achieve the shortest lateral trajectory while meeting all altitude requirements.
4Reliability
If succession of leveling and climbing is used, then altitude constraints are met, but passenger comfort and engine maintenance are degraded due to strong thrust variations
Solution Approach 1:
The patent applies continuity of useful action by maintaining continuous climb without interruption by level flight. The system adjusts the energy distribution ratio to smoothly meet altitude constraints while keeping the aircraft in continuous climb mode, eliminating abrupt thrust variations and improving both passenger comfort and engine maintenance requirements.
Data Source
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AI summary
The document describes methods and devices for optimising the climb of an aircraft or drone. Having determined an optimal continuous climb strategy (110), a lateral trajectory (120) is determined, in particular with regard to speeds and turning radii, based on vertical predictions calculated in the previous step. Subsequently, calculation results are displayed (130) in one or more human-machine interfaces and the climb strategy is actually flown (140). Developments describe the use of altitude and speed constraints and/or of speed and/or thrust and/or level avoidance and/or slope variation minimisation settings, the iterative adjustment of parameters to match the current trajectory profile with the constrained profile in real time according to the selected flight dynamics (e.g. energy sharing, climb slope constraint, climb vertical speed constraint). System (e.g. FMS) and software aspects are described.