Issues of designing power supply units for multicopters

Аuthors

Huseynov O. A., Fatullayev A. A.

National Aerospace Agency of Azerbaijan Republic, NASA, 1, Suleyman Sani Akhundov str., Baku, AZ1115, Azerbaijan Republic

Abstract

The power supply of unmanned aerial vehicles is the most important problem in solving the problem of increasing the efficiency of such systems. At the same time, both promising and modern solutions in the field of energy supply should be tied to the real design features of established typical drone construction options. The limited flight time of multicopters remains one of the important problems waiting to be solved and analytical methods make it possible to successfully solve some problems of designing multicopters. The purpose of this article is to determine the optimal relationship between the volume of the battery type used and the number of DC traction motors. The above problem can be posed and solved in a forward and reverse form. The reverse formulation of the above problem is formulated as follows: At what relationship between the battery capacity and the consumed current of the copter, the extreme battery discharge time is achieved. At the same time, such requirements for the drone power supply system as (a) low weight, and (b) high operating efficiency must be met. Results. The problem of choosing a battery for a copter with i number of DC motors at which the battery discharge time would reach an extreme value is formulated and solved. In this case, it is assumed that there are  set of  batteries with different energy volume. The negative order of battery selection for multicopters, in which the current consumption is proportional to the number of engines available in them, has been revealed, at which the average discharge time over the entire set of copters can reach a minimum. A recommendation is given to avoid such a distribution of available energy resources across a variety of multicopters.

Keywords:

multicopter, power consumption, optimization, DC motor, flight time

References

1. Bowen D. Encyclopedia of war machines: an historical survey of the world’s great weapons, Peerage books, London, UK, 1977, 368 p.
2. Hannavy J. Encyclopedia of nineteenth-century photography, Routledge, Taylor & Francis group, 2007, 828 p.
3. Ambrosia V. G., Wegener S., Zajkowski T. et al. The Ikhana UAS western states fire imaging missions: from concept to reality (2006-2011), Geocarto International, 2011. DOI: 10.1080/10106049.2010.539302
4. Torres-Sanchez J., Lopez-Granados F., Pena J. M. An automatic object-based method for optimal thresholding in UAV images: application for vegetation detection in herbaceous crops, Computers and electronics in agriculture, 2015, vol. 114, pp. 43-52. DOI: 10.1016/j.compag.2015.03.019
5. Primicerio J., Gennaro S. F., Fiorillo E., Genesio L., Lugato E. A flexible unmanned aerial vehicle for precision agriculture, Precision Agriculture, 2012, vol. 13 (4), pp. 517-523. DOI: 10.1007/s11119-012-9257-6
6. Aslanova A.B. Trudy MAI, 2022, no. 122. URL: https://trudymai.ru/eng/published.php?ID=164287. DOI: 10.34759/trd-2022-122-21
7. Aslanova A.B. Trudy MAI, 2021, no. 119. URL: http://trudymai.ru/eng/published.php?ID=159794. DOI: 10.34759/trd-2021-119-16
8. Dzhakhidzade Sh.N. Trudy MAI, 2019, no. 108. URL: http://trudymai.ru/eng/published.php?ID=109570. DOI: 10.34759/trd-2019-108-17
9. Betancourth N.J.P., Villamarin J.E.P., Rios J.J.V. Bravo-Mosquera P.D., Ceron-Munoz H.D. Design and manufacture of a solar-powered unmanned aerial vehicle for civilian surveillance missions, Journal of Aerospace Technology and Management, 2016, vol. 8 (4), pp. 385-396. DOI: 10.5028/jatm.v8i4.678
10. Lee J.S., Yu K.H. Optimal Path Planning of solar-powered UAV using gravitational potential energy, IEEE Transactions on Aerospace and Electronic Systems, 2017, vol. 53, no. 3, pp. 1442-1451. DOI: 10.1109/TAES.2017.2671522
11. Makki B., Svensson T., Bruisman K., Perez J., Alouini M-S. Wireless energy and information transmission in FSO and Rf-FSO links, IEEE Wireless Communication Letters, 2018, vol. 7 (1), pp. 90-93. DOI: 10.1109/LWC.2017.2755658
12. Bogushevskaya V.A., Zayats O.V., Maslyakov Ya.N., Matsak I.S., Nikonov A.A., Savel'ev V.V., Sheptunov A.A. Trudy MAI, 2012, no. 51. URL: http://trudymai.ru/eng/published.php?ID=29047
13. Dai X., Quan Q., Ren J., Cai K. Y. An analytical design-optimization method for electric propulsion systems of multicopter UAVs with desired hovering endurance, IEEE/ASME transactions on mechatronics, 2019, vol. 24, no. 1. DOI: 10.1109/TMECH.2019.2890901
14. Oktay T., Sultan C. Simultaneous helicopter and control-system design, Journal of Aircraft, 2013, vol. 50, no. 3, pp. 911–925. DOI: 10.2514/1.C032043
15. Oktay T., Konar M., Onay M., Aydin M., Mohamed M.A. Simultaneous small uav and autopilot system design, Aircraft Engineering and Aerospace Technology, 2016, vol. 88, no. 6, pp. 818–834. DOI: 10.1108/AEAT-04-2015-0097
16. Harrington A.M. Optimal propulsion system design for a micro quad rotor, Master’s thesis, University of Maryland, College Park, 2011.
17. Shi D., Dai X., Zhang X., Quan Q. A practical performance evaluation method for electric multicopters, IEEE/ASME Transactions on Mechatronics, 2017, vol. 22, no. 3, pp. 1–10. DOI: 10.1109/TMECH.2017.2675913
18. McCrink M., Gregory J.W. Blade element momentum modeling of low-re small uas electric propulsion systems, 33rd AIAA Applied Aerodynamics Conference, 2015. DOI: 10.2514/6.2015-3296
19. Lawrence D., Mohseni K. Efficiency analysis for long duration electric mavs, Infotech@Aerospace Conferences, 2005. DOI: 10.2514/6.2005-7090
20. Stepaniak M.J., Graas F.V., De Haag M.U. Design of an Electric Propulsion System for a Quadrotor Unmanned Aerial Vehicle, Journal of Aircraft, 2009. vol. 46, no. 3, pp. 1050–1058. DOI: 10.2514/1.38409

Download