Aircraft Performance Model Development for Low SWaP UAS
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current Aircraft Performance Models (APMs) are inadequate for low SWaP (Size, Weight, and Power) aircraft, leading to reduced accuracy in flight simulation and trajectory prediction, particularly for Unmanned Air Systems, due to simplifications and increased costs associated with generating accurate 6DOF APMs.
Innovation Solution
A method and system for efficiently modeling the six degrees of freedom of a fixed-wing aerial vehicle, involving data collection through controlled maneuvers and mathematical modeling to determine fuel consumption, thrust, aerodynamic forces, and inertia properties, allowing for improved accuracy and reduced costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If generic APMs are used for low SWaP UAS, then costs and complexity are reduced, but simulation accuracy and trajectory prediction precision significantly deteriorate
Solution Approach 1:
The APM development process is segmented into distinct phases: initial generic model creation, automated flight data collection through structured maneuvers, and iterative refinement cycles. This segmentation allows the system to start with a simple model and progressively add accuracy where needed based on actual flight performance data, rather than requiring full complexity from the outset.
Solution Approach 2:
The system enables the aircraft itself to generate the test data needed for APM validation and refinement through automated flight maneuvers. The aircraft performs self-tested flight patterns that automatically collect performance data, eliminating the need for external test facilities and expert intervention, thereby reducing costs while improving model accuracy specific to that aircraft type.
2Measurement precision
If accurate 6DOF APMs are generated through traditional methods, then simulation fidelity and trajectory prediction accuracy are improved, but time consumption and development costs significantly increase
Solution Approach 1:
The methodology performs preliminary automated data collection through structured flight maneuvers before final APM validation. By pre-collecting performance data across the flight envelope using automated test sequences, the system prepares all necessary information in advance, eliminating the need for time-consuming iterative testing and validation during later development stages.
Solution Approach 2:
Traditional manual flight testing and expert analysis are replaced with automated flight control systems that execute predetermined maneuvers and automatically process performance data. This substitution of manual mechanical processes with automated electronic systems dramatically reduces the time required for APM development while maintaining or improving accuracy.
3Ease of manufacture
If simplified APM assumptions are made for low SWaP aircraft, then model complexity and testing requirements are reduced, but aerodynamic accuracy and control precision deteriorate
Solution Approach 1:
The system dynamically adjusts model complexity parameters based on the specific aircraft type and available data. Rather than using fixed simplified assumptions for all low SWaP aircraft, the methodology modifies aerodynamic parameters, control surface effectiveness, and environmental factors to match actual flight characteristics, achieving both ease of implementation and aerodynamic accuracy for each specific platform.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Computer-implemented method and system for modelling performance of a fixed-wing aerial vehicle (AV) with six degrees of freedom. The system comprises a collecting unit (330) to collect data from a plurality of modelling measures and modelling maneuvers; a processing unit (340) to communicate with a collecting unit (330). The processing unit (340) further sequentially processes data sets from a plurality of modelling measures and to determine models to generate an accurate aircraft performance model (APM). Modelling measures and modelling maneuvers are designed to modify an influence on the AV of variables of a model of the AV (100) to be determined.