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Optimization model for endurance performance of electric rotorcraft transport drones and its application prospects
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The operational parameter configuration and performance optimization of electric rotorcraft transport unmanned aerial vehicles (UAVs) currently lack comprehensive guiding theory, impacting UAV endurance and efficiency, thereby limiting industry growth. This paper analyzes factors affecting UAV endurance and establishes a hover endurance model for electric rotorcraft transport UAVs through theoretical derivation and testing. Based on this model, we introduce the concepts of thrust redundancy coefficient and load cut-off line, proposing an optimal endurance configuration theory. This theory categorizes the parameter configuration range into light load, ideal configuration, load cut-off, and endurance saturation zones. Using current operational parameters, we evaluate and optimize UAV performance. Verification results demonstrate high model accuracy, with error rates ranging from 1.89% to 5.69%. After optimization, the payload capacities of two transport UAVs increased by 6.25%, and their endurance improved by 6.97% and 9.5%, respectively, enhancing overall efficiency. This model provides a solid framework for assessing endurance capabilities and offers targeted optimization suggestions, making it crucial for improving UAV performance.
Institute of Advanced Engineering and Science
Title: Optimization model for endurance performance of electric rotorcraft transport drones and its application prospects
Description:
The operational parameter configuration and performance optimization of electric rotorcraft transport unmanned aerial vehicles (UAVs) currently lack comprehensive guiding theory, impacting UAV endurance and efficiency, thereby limiting industry growth.
This paper analyzes factors affecting UAV endurance and establishes a hover endurance model for electric rotorcraft transport UAVs through theoretical derivation and testing.
Based on this model, we introduce the concepts of thrust redundancy coefficient and load cut-off line, proposing an optimal endurance configuration theory.
This theory categorizes the parameter configuration range into light load, ideal configuration, load cut-off, and endurance saturation zones.
Using current operational parameters, we evaluate and optimize UAV performance.
Verification results demonstrate high model accuracy, with error rates ranging from 1.
89% to 5.
69%.
After optimization, the payload capacities of two transport UAVs increased by 6.
25%, and their endurance improved by 6.
97% and 9.
5%, respectively, enhancing overall efficiency.
This model provides a solid framework for assessing endurance capabilities and offers targeted optimization suggestions, making it crucial for improving UAV performance.
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