2019
DOI: 10.1109/tmech.2019.2890901
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An Analytical Design-Optimization Method for Electric Propulsion Systems of Multicopter UAVs With Desired Hovering Endurance

Abstract: Multicopters are becoming increasingly important in both civil and military fields. Currently, most multicopter propulsion systems are designed by experience and trial-anderror experiments, which are costly and ineffective. This paper proposes a simple and practical method to help designers find the optimal propulsion system according to the given design requirements. First, the modeling methods for four basic components of the propulsion system including propellers, motors, electric speed controls, and batter… Show more

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Cited by 54 publications
(39 citation statements)
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References 17 publications
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“…The electric model is also validated against experimental data from Ref. (53) ; the results are presented in Table 2.…”
Section: Propulsion Model Validationmentioning
confidence: 99%
See 1 more Smart Citation
“…The electric model is also validated against experimental data from Ref. (53) ; the results are presented in Table 2.…”
Section: Propulsion Model Validationmentioning
confidence: 99%
“…In Ref. (53) , a model corrected with experimental data, which shows the relation between the efficiency and the number of blades, is developed:…”
Section: Number Of Bladesmentioning
confidence: 99%
“…The key parameters of them are demonstrated in Table 2. Further design optimization can be carried out by using mathematical models [32] established based on these parameters. V and cruising required thrust req T which equals to cruising drag that can obtain from Eq.…”
Section: Propulsion Components Selectionmentioning
confidence: 99%
“…In [4], through considering the machine-interactions and operational context, a hybrid data-driven and physics-based framework was derived for modelling manufacturing equipment to improve anomaly detection and diagnosis. For battery applications, numerous data-driven models have been derived to estimate operational states [5]- [8], predict service life [9]- [12], diagnose faults [13], achieve effective charging [14]- [16] and energy managements [17], [18]. However, all these researches mainly focus on the in-situ operation of battery performance without considering the microscopic properties of its production.…”
Section: Introductionmentioning
confidence: 99%