Aerial Vehicle Power Reachability Control Using Historical Flight Data
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Solution Overview
Problem
Existing technologies fail to accurately determine whether a movable platform, particularly logistics aerial vehicles, can reach its destination due to insufficient power energy, leading to potential mission failures and resource wastage.
Innovation Solution
A control method that utilizes historical flight data of similar missions to predict energy consumption and combines it with real-time power data to determine if the vehicle can reach its destination, allowing for accurate control strategies to avoid failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional control methods are used without historical flight data, then the control system is simple, but the accuracy of destination reach predictions is insufficient
Solution Approach 1:
The system performs preliminary actions by collecting and storing historical flight data before actual flight missions. This historical data includes energy consumption patterns, flight parameters, and mission outcomes from previous flights. By having this data prepared in advance, the system can accurately predict destination reachability without adding complex real-time computation requirements during actual flights.
Solution Approach 2:
The system implements feedback mechanisms by continuously comparing actual flight data with historical flight data to improve prediction accuracy. The control apparatus analyzes the difference between predicted energy consumption based on historical data and actual energy consumption, then uses this feedback to refine future predictions and adjust flight control strategies accordingly.
2Reliability
If real-time energy monitoring and historical data analysis are implemented, then mission failure is avoided, but energy and computational resources are consumed
Solution Approach 1:
The system applies partial action by selectively analyzing only the most critical flight parameters and historical data points necessary for destination reach prediction, rather than processing all possible flight data. This approach ensures sufficient reliability for mission completion while minimizing the energy and computational resources required for control operations.
3Ease of operation
If historical flight data is used for prediction, then appropriate control strategies can be adopted, but data processing time increases
Solution Approach 1:
The system performs preliminary processing of historical flight data during idle periods or between missions, organizing and pre-analyzing the data so that during actual flight operations, only quick comparisons and predictions are needed. This reduces real-time data processing time while maintaining comprehensive analysis capabilities for control strategy selection.
Data Source
AI summary
A control method includes obtaining a current mission parameter of a current flight mission and historical flight data of a historical flight mission related to the current mission. The current mission parameter is related to an energy consumption of a current aerial vehicle performing the current flight mission, the historical flight data includes a historical mission parameter and a historical energy consumption in the historical flight mission, and the historical mission parameter is related to an energy consumption of a historical aerial vehicle performing the historical mission. The method further includes obtaining a current remaining power energy of the current aerial vehicle in real time, and determining whether the current aerial vehicle is able to reach a destination of the current flight mission based at least one on the current mission parameter, the historical flight data, and the current remaining power energy, to obtain a determination result.