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工程设计学报
Chinese Journal of Engineering Design  2024, Vol. 31 Issue (6): 725-732    DOI: 10.3785/j.issn.1006-754X.2024.03.402
【Special Column】Key Technologies of Design, manufacture, operation and maintenance for New Energy Equipment and Their Applications under the Carbon Peaking and Carbon Neutrality Goals     
Propeller-motor matching design and efficiency improvement for high-altitude unmanned aerial vehicle
Wenyi ZHONG,Shizhe LIANG,Bin ZHANG,Peng TANG,Kena LIU
AVIC Chengdu Aircraft Industrial (group) Co. , Ltd. , Chengdu 610031, China
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Abstract  

The propeller-motor matching design of electric propulsion system is a key link for high-altitude unmanned aerial vehicle (UAV) to achieve long-endurance flight. According to the full-profile power requirements of the high-altitude UAV, the overall parameter matching design for the motor and propeller of the electric propulsion system was carried out by using the power loss method and the single-point method, respectively, and the tensile force and power characteristics of the electric propulsion system were measured through ground static test. At the same time, the surrogate model based on BP (back propagation) neural network was established on the basis of the confirmed motor selection, in order to carry out the propeller-motor matching design and efficiency improvement for the electric propulsion system. The test results showed that the measured tensile force was consistent with the calculated tensile force, which indicated that the adopted overall parameter matching design method for the motor and propeller had high accuracy. Taking the climb profile with elevation angle of 5° as an example, the efficiency of the new propeller obtained by optimized matching through the surrogate model was improved by about 0.1, and the energy saving effect was remarkable. The relevant surrogate model can provide a powerful tool for the propeller-motor matching and optimization design of the UAV electric propulsion system in the scheme design and later engineering use stage, as well as the improvement of dynamics characteristics and economy.

Key words： high-altitude unmanned aerial vehicle      electric propulsion system      propeller-motor matching      surrogate model      efficiency improvement      ground static test     
Received: 15 November 2023      Published: 31 December 2024
CLC:  V 279  
Corresponding Authors: Peng TANG   
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Wenyi ZHONG
Shizhe LIANG
Bin ZHANG
Peng TANG
Kena LIU
Cite this article:

Wenyi ZHONG,Shizhe LIANG,Bin ZHANG,Peng TANG,Kena LIU. Propeller-motor matching design and efficiency improvement for high-altitude unmanned aerial vehicle. Chinese Journal of Engineering Design, 2024, 31(6): 725-732.

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https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2024.03.402     OR     https://www.zjujournals.com/gcsjxb/Y2024/V31/I6/725


高空无人机桨发匹配设计及效率提升

电推进系统的桨发匹配设计是高空无人机实现长航时飞行的关键环节。根据高空无人机全剖面的动力需求，分别采用功率损失法和单点法开展了电推进系统电动机与螺旋桨的总体参数匹配设计，并通过地面静态试验对电推进系统的拉力、功率特性进行了测试。同时，在确定电动机选型的基础上，基于BP（back propagation，反向传播）神经网络建立代理模型，以开展电推进系统桨发匹配设计及效率提升工作。试验结果表明，电推进系统的实测拉力与计算拉力相吻合，说明所采用的电动机、螺旋桨总体参数匹配设计方法具有较高的精度。以仰角为5°的爬升剖面为例，经代理模型优化匹配后得到的新螺旋桨的效率约提升了0.1，节能效果显著。相关代理模型可为无人机电推进系统方案设计及后期工程使用阶段的桨发匹配优化设计、动力特性及经济性提升提供有力工具。


关键词： 高空无人机,  电推进系统,  桨发匹配,  代理模型,  效率提升,  地面静态试验 
Fig.1 Relationship between required thrust of unmanned aerial vehicle and flight altitude and climb angle (for a single propulsion device)
Fig.2 Power distribution of permanent magnet synchronous motor
Fig.3 Efficiency distribution of permanent magnet synchronous motor
Fig.4 Drag and lift characteristic curve of propeller
Fig.5 Distribution of paddle chord length and blade angle
Fig.6 Ground static test system and its cross-linking relationship
Fig.7 Comparison of measured results and calculated results of tensile force of electric propulsion system
Fig.8 Comparison of measured results and calculated results of power of electric propulsion system
Fig.9 Propeller-motor matching surrogate model architecture for electric propulsion system
Fig.10 Topology structure of BP neural network with multi-hidden layers
Fig.11 Relative error in predicting required power of propeller
Fig.12 Comparison of paddle chord length distribution before and after optimized matching
Fig.13 Comparison of propeller efficiency before and after optimized matching
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