Skip to main content

A Review on Unmanned Aerial Vehicle Energy Sources and Management

  • Conference paper
  • First Online:
International Conference on Emerging Applications and Technologies for Industry 4.0 (EATI’2020) (EATI 2020)

Abstract

Unmanned Aerial vehicle (UAV) systems have an insufficient amount of onboard energy which is being shared for mobility, transmission, data processing, control and payload related applications. Different energy sources have been investigated and applied to solve unmanned aerial vehicle energy limitations. These energy sources were either used as single sources or hybrid for the reason of UAV weight budget or miniaturization. To achieve the aforementioned designed criteria, researchers around the globe are continuously investigating different energy sources and hybridization techniques while others focus on the Energy Management System (EMS) such to achieve optimal energy sources utilization. Such energy sources and supplying techniques are battery swapping, wireless Power Transfer (WPT), tethering methods, Fuel Cells (FC), and SuperCapacitors (SC). While, the hybridization technique is based on the combination of single energy source with either renewable energy sources, Internal Combustion Engine (ICE) to save fuel or WPT. Example of such hybridization techniques are solar and battery storage, Fuel Cell (FC) and Battery Storage (BS) etc. This article presents an in-depth review of UAV energy sources, hybridization techniques and EMS. Their challenges and methods adopted by researchers to mitigate such UAV energy challenges.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Cord, T.: Skytote advanced cargo delivery system. In: AIAA International Air and Space Symposium and Exposition: The Next 100 Years (2003)

    Google Scholar 

  2. Woodworth, A., Peverill, J.: Tethered aerial system for data gathering. Google Patents (2013)

    Google Scholar 

  3. Lin, Z.L., Liu, H.H.T., Wotton, M.: Kalman filter-based large-scale wildfire monitoring with a system of UAVs. IEEE Trans. Ind. Electr. 66(1), 606–615 (2018)

    Google Scholar 

  4. Valavanis, K.P.V., George, J.: Handbook of Unmanned Aerial Vehicles, pp. 2639–2641. Springer, Dordrecht (2015)

    Google Scholar 

  5. Mozaffari, M., et al.: A tutorial on UAVs for wireless networks: applications, challenges, and open problems (2019)

    Google Scholar 

  6. Hu, X., Wong, K.-K., Yang, K.: Wireless powered cooperation-assisted mobile edge computing. IEEE Trans. Wireless Commun. 17(4), 2375–2388 (2018)

    Article  Google Scholar 

  7. Cwojdziński, L., Adamski, M.: Power units and power supply systems in UAV. Aviation 18(1), 1–8 (2014)

    Google Scholar 

  8. Iqbal, J., Khan, Z.H.: The potential role of renewable energy sources in robot’s power system: a case study of Pakistan. Renew. Sustain. Energy Rev. 75, 106–122 (2017)

    Article  Google Scholar 

  9. Aneke, M., W.M.: Energy storage technologies and real life applications–a state of the art review. Appl. Energy 179, 350–77 (2018)

    Google Scholar 

  10. Buticchi, G., et al.: On-board microgrids for the more electric aircraft—technology review. IEEE Trans. Industr. Electron. 66(7), 5588–5599 (2018)

    Article  Google Scholar 

  11. Lei, T., et al.: The state of art on energy management strategy for hybrid-powered unmanned aerial vehicle. Chinese J. Aeronaut. (2019)

    Google Scholar 

  12. Nadir, B.M., Zhibin, Z., Benbouzid, M.: A critical review on unmanned aerial vehicles power supply and energy management: solutions, strategies, and prospects. Appl. Energy 255, 113823 (2019)

    Google Scholar 

  13. Chung, P.-H., Ma, D.-M., Shiau, J.-K.: Design, manufacturing, and flight testing of an experimental flying wing UAV. Appl. Sci. 9(15), 3043 (2019)

    Article  Google Scholar 

  14. Freeman, P., Balas, G.J.: Actuation failure modes and effects analysis for a small UAV. In: 2014 American Control Conference. IEEE (2014)

    Google Scholar 

  15. Hung, J., Gonzalez, L.F.: On parallel hybrid-electric propulsion system for unmanned aerial vehicles. Prog. Aerosp. Sci. 51, 1–17 (2012)

    Article  Google Scholar 

  16. Jansen, R., et al.: Overview of NASA electrified aircraft propulsion (EAP) research for large subsonic transports. In: 53rd AIAA/SAE/ASEE Joint Propulsion Conference (2017)

    Google Scholar 

  17. El-Sayed, A.F.: Aircraft Propulsion and Gas Turbine Engines. CRC Press, Boca Raton (2017)

    Google Scholar 

  18. Fahlstrom, P., Gleason, T.: Introduction to UAV Systems. Wiley, Hoboken (2012)

    Google Scholar 

  19. King, D.W., Bertapelle, A., Moses, C.: UAV failure rate criteria for equivalent level of safety. In: International Helicopter Safety Symposium, Montreal (2005)

    Google Scholar 

  20. Petritoli, E., Leccese, F., Ciani, L.: Reliability assessment of UAV systems. In: 2017 IEEE International Workshop on Metrology for AeroSpace (MetroAeroSpace). IEEE (2017)

    Google Scholar 

  21. Bongermino, E., et al.: Hybrid aeronautical propulsion: control and energy management. IFAC-PapersOnLine 50(2), 169–174 (2017)

    Article  Google Scholar 

  22. Huang, Y., et al.: Energy-optimal path planning for solar-powered UAVs monitoring stationary target. In: Proceedings of the 4th ACM SIGSPATIAL International Workshop on Safety and Resilience. ACM (2018)

    Google Scholar 

  23. Chin, C.K.: Extending the endurance, missions and capabilities of most UAVs using advanced flexible/ridged solar cells and new high power density batteries technology. Naval Postgraduate School Monterey CA (2011)

    Google Scholar 

  24. Adam, P., Leachman, J.: Design of a reconfigurable liquid hydrogen fuel tank for use in the Genii unmanned aerial vehicle. In: AIP Conference Proceedings. AIP (2014)

    Google Scholar 

  25. Saha, B., et al.: Battery health management system for electric UAVs. In: 2011 Aerospace Conference. IEEE (2011)

    Google Scholar 

  26. Sastry, A.M., et al.: Energy storage system. Google Patents (2019)

    Google Scholar 

  27. Koster, J., et al.: Hybrid electric integrated optimized system (HELIOS)-design of a hybrid propulsion system for aircraft. In: 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition (2011)

    Google Scholar 

  28. Zandi, M., Payman, A., Martin, J.P., Pierfederici, S., Davat, B.: Energy management of a fuel cell/supercapacitor/battery power sources for electric vehicular applications. IEEE Trans. Veh. Technol. 60, 433–443 (2011)

    Article  Google Scholar 

  29. Yang, Z., et al.: The testing platform of hybrid electric power system for a fuel cell unmanned aerial vehicle. In: IEEE International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC), pp. 1–8. IEEE, Nottingham (2018)

    Google Scholar 

  30. Xu, J., Zeng, Y., Zhang, R.: UAV-enabled wireless power transfer: trajectory design and energy optimization. IEEE Trans. Wireless Commun. 17(8), 5092–5106 (2018)

    Article  Google Scholar 

  31. Traub, L.W.: Range and endurance estimates for battery-powered aircraft. J. Aircraft 48(2), 703–707 (2011)

    Article  Google Scholar 

  32. Hwang, S.-J., Kim, S.-G., Kim, C.-W., Lee, Y.-G.: Aerodynamic design of the solar-powered high altitude long endurance (HALE) unmanned aerial vehicle (UAV). Int. J. Aeronaut. Space Sci. 17(1), 132–138 (2016)

    Google Scholar 

  33. Morton, S., D’Sa, R., Papanikolopoulos, N.: Solar powered UAV: design and experiments. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE (2015)

    Google Scholar 

  34. Belmonte, N., et al.: Fuel cell powered octocopter for inspection of mobile cranes: design, cost analysis and environmental impacts. Appl. Energy 215, 556–565 (2018)

    Article  Google Scholar 

  35. Gong, A., et al.: Analysis of a fuel-cell/battery/supercapacitor hybrid propulsion system for a UAV using a hardware-in-the-loop flight simulator. In: 2018 AIAA/IEEE Electric Aircraft Technologies Symposium (EATS). IEEE (2018)

    Google Scholar 

  36. Gong, A., Verstraete, D.: Role of battery in a hybrid electrical fuel cell UAV propulsion system (2014)

    Google Scholar 

  37. Lubkowski, S., et al.: Trade-off analysis of regenerative power source for long duration loitering Airship. In: 2010 IEEE Systems and Information Engineering Design Symposium. IEEE (2010)

    Google Scholar 

  38. Hasvold, O., Johansen, K.H., Mollestad, O., Forseth, S., Størkersen, N.: The alkaline aluminium/hydrogen peroxide power source in the Hugin II unmanned underwater vehicle. J. Power Sources 80(1–2), 254–260 (1999)

    Google Scholar 

  39. Thackeray, M.M., Wolverton, C., Isaacs, E.D.: Electrical energy storage for transportation—approaching the limits of, and going beyond, lithium-ion batteries. Energy Environ. Sci. 5(7), 7854–7863 (2012)

    Article  Google Scholar 

  40. Mansouri, S.S., et al.: Remaining useful battery life prediction for UAVs based on machine learning. IFAC-PapersOnLine 50(1), 4727–4732 (2017)

    Article  Google Scholar 

  41. Morbidi, F., Cano, R., Lara, D.: Minimum-energy path generation for a quadrotor UAV. In: 2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE (2016)

    Google Scholar 

  42. Donateo, T., et al.: A new approach to calculating endurance in electric flight and comparing fuel cells and batteries. Appl. Energy 187, 807–819 (2017)

    Article  Google Scholar 

  43. Jacobsen, R., Ruhe, N., Dornback, N.: Autonomous UAV Battery Swapping (2018)

    Google Scholar 

  44. Wang, M.: Systems and methods for UAV battery exchange. Google Patents (2016)

    Google Scholar 

  45. Gentry, N.K., Hsieh, R., Nguyen, L.K.: Multi-use UAV docking station systems and methods. US Patent App. 15/159,859 (2018)

    Google Scholar 

  46. Michini, B., et al.: Automated battery swap and recharge to enable persistent UAV missions. In: Infotech@ Aerospace 2011, p. 1405 (2011)

    Google Scholar 

  47. Kemper, F.P., Suzuki, K.A., Morrison, J.R.: UAV consumable replenishment: design concepts for automated service stations. J. Intell. Rob. Syst. 61(1–4), 369–397 (2011)

    Article  Google Scholar 

  48. Swieringa, K.A., et al.: Autonomous battery swapping system for small-scale helicopters. In: 2010 IEEE International Conference on Robotics and Automation. IEEE (2010)

    Google Scholar 

  49. Ure, N.K., et al.: An automated battery management system to enable persistent missions with multiple aerial vehicles. IEEE/ASME Trans. Mechatron. 20(1), 275–286 (2014)

    Article  Google Scholar 

  50. Liu, Z.-N., et al.: QUADO: an autonomous recharge system for quadcopter. In: 2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM). IEEE (2017)

    Google Scholar 

  51. Achtelik, M.C., et al.: Design of a flexible high performance quadcopter platform breaking the MAV endurance record with laser power beaming. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE (2011)

    Google Scholar 

  52. Sun, B., Tan, X., Tsang, D.H.: Optimal charging operation of battery swapping stations with QoS guarantee. In: 2014 IEEE International Conference on Smart Grid Communications (SmartGridComm). IEEE (2014)

    Google Scholar 

  53. Tan, X., et al.: Optimal scheduling of battery charging station serving electric vehicles based on battery swapping. IEEE Trans. Smart Grid 10(2), 1372–1384 (2017)

    Article  Google Scholar 

  54. Junaid, A., et al.: Autonomous wireless self-charging for multi-rotor unmanned aerial vehicles. Energies 10(6), 803 (2017)

    Article  Google Scholar 

  55. Griffin, B.: Automated resonant wireless power transfer to remote sensors from an unmanned aerial vehicle (2012)

    Google Scholar 

  56. Kausar, A.Z., et al.: Energizing wireless sensor networks by energy harvesting systems: scopes, challenges and approaches. Renew. Sustain. Energy Rev. 38, 973–989 (2014)

    Article  Google Scholar 

  57. Vega‐Garita, V., et al.: Integrating a photovoltaic storage system in one device: a critical review. Progr. Photovol. Res. Appl. 27(4), 346–370 (2019)

    Google Scholar 

  58. Shiau, J.-K., et al.: Design of a solar power management system for an experimental UAV. IEEE Trans. Aerosp. Electron. Syst. 45(4), 1350–60 (2009)

    Google Scholar 

  59. Muttin, F.: Umbilical deployment modeling for tethered UAV detecting oil pollution from ship. Appl. Ocean Res. 33(4), 332–343 (2011)

    Article  Google Scholar 

  60. Gu, B.W., et al.: Novel roaming and stationary tethered aerial robots for continuous mobile missions in nuclear power plants. Nuclear Eng. Technol. 48(4), 982–996 (2016)

    Article  Google Scholar 

  61. Nicotra, M.M., Naldi, R., Garone, E.: Taut cable control of a tethered UAV. IFAC Proc. Vol. 47(3), 3190–3195 (2014)

    Article  Google Scholar 

  62. Kiribayashi, S., Yakushigawa, K., Nagatani, K.: Design and development of tether-powered multirotor micro unmanned aerial vehicle system for remote-controlled construction machine. In: Hutter, M., Siegwart, R. (eds.) Field and Service Robotics. SPAR, vol. 5, pp. 637–648. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-67361-5_41

    Chapter  Google Scholar 

  63. Kim, T., Kwon, S.: Design and development of a fuel cell-powered small unmanned aircraft. Int. J. Hydrogen Energy 37(1), 615–622 (2012)

    Article  Google Scholar 

  64. Sharaf, O.Z., Orhan, M.F.: An overview of fuel cell technology: fundamentals and applications. Renew. Sustain. Energy Rev. 32, 810–853 (2014)

    Article  Google Scholar 

  65. Swider-Lyons, K., et al.: Hydrogen fule cell propulsion for long endurance small UVAs. In: AIAA Centennial of Naval Aviation Forum. 100 Years of Achievement and Progress (2011)

    Google Scholar 

  66. Lee, B., et al.: Active power management system for an unmanned aerial vehicle powered by solar cells, a fuel cell, and batteries. IEEE Trans. Aerosp. Electron. Syst. 50(4), 3167–3177 (2014)

    Article  Google Scholar 

  67. Williams, M.C., Suzuki, A., Miyamoto, A.: Assessment of the performance of fuel cells and batteries. ECS Trans. 51(1), 183–192 (2013)

    Article  Google Scholar 

  68. Lee, B., Park, P., Kim, C.: Power managements of a hybrid electric propulsion system powered by solar cells, fuel cells, and batteries for UAVs. In: Handbook of Unmanned Aerial Vehicles, pp. 495–524 (2015)

    Google Scholar 

  69. Gao, L., Jiang, Z., Dougal, R.A.: Evaluation of active hybrid fuel cell/battery power sources. IEEE Trans. Aerosp. Electron. Syst. 41(1), 346–355 (2005)

    Article  Google Scholar 

  70. González, E.L., et al.: Experimental evaluation of a passive fuel cell/battery hybrid power system for an unmanned ground vehicle. Int. J. Hydrogen Energy 44(25), 12772–12782 (2019)

    Article  Google Scholar 

  71. Gang, B.G., Kwon, S.: Design of an energy management technique for high endurance unmanned aerial vehicles powered by fuel and solar cell systems. Int. J. Hydrogen Energy 43(20), 9787–9796 (2018)

    Article  Google Scholar 

  72. Rapinett, A.: Zephyr: a high altitude long endurance unmanned air vehicle. Doctor, Department of Physics, University of Surrey (2009)

    Google Scholar 

  73. Donateo T., Spedicato, L.: Fuel economy of hybrid electric flight. Appl. Energy 206, 723–38 (2019)

    Google Scholar 

  74. Khayyam, H., Bab-Hadiashar, A.: Adaptive intelligent energy management system of plug-in hybrid electric vehicle. Energy 69(5), 319–35 (2014)

    Google Scholar 

  75. Sikeridis, D., et al.: Wireless powered Public Safety IoT: A UAV-assisted adaptive-learning approach towards energy efficiency. J. Netw. Comput. Appl. 123, 69–79 (2018)

    Article  Google Scholar 

  76. Larsson, V., Johannesson, L., Egardt, B.: Analytic solutions to the dynamic programming sub-problem in hybrid vehicle energy management. IEEE Trans. Veh. Technol. 64(4), 1458–1467 (2014)

    Article  Google Scholar 

  77. Chen, Q., Gao, L., Dougal, R.A., Quan, S.: Multiple model predictive control for a hybrid proton exchange membrane fuel cell system. J. Power Sources. 191(2), 473–82 (2009)

    Google Scholar 

  78. Glassock, R., et al.: Design, modelling and measurement of a hybrid powerplant for unmanned aerial systems. Austr. J. Mech. Eng. 6(2), 69–78 (2008)

    Article  Google Scholar 

  79. Peng, L., et al.: A novel tangent error maximum power point tracking algorithm for photovoltaic system under fast multi-changing solar irradiances. Appl. Energy 2018(210), 303–316 (2018)

    Article  Google Scholar 

  80. Xie, Y., Savvaris, A., Tsourdos, A.: Fuzzy logic based equivalent consumption optimization of a hybrid electric propulsion system for unmanned aerial vehicles. Aerosp. Sci. Technol. 85, 13–23 (2019)

    Google Scholar 

  81. Karunarathne, L., Economou, J.T., Knowles, K.: Model based power and energy management system for PEM fuel cell/Li-Ion battery driven propulsion system (2010)

    Google Scholar 

  82. Zhang, X., Liu, L., Xu, G.: Energy management strategy of hybrid PEMFC-PV-battery propulsion system for low altitude UAVs. In: 52nd AIAA/SAE/ASEE Joint Propulsion Conference (2016)

    Google Scholar 

  83. Kuroki, Y., Young, G.S., Haupt, S.E.: UAV navigation by an expert system for contaminant mapping with a genetic algorithm. Expert Syst. Appl. 37(6), 4687–4697 (2010)

    Article  Google Scholar 

  84. Todd, R., Forsyth, A.: DC-bus power quality for UAV systems during generator fault conditions (2010)

    Google Scholar 

  85. Logic, F.: Foundations of fuzzy logic and semantic web languages (2014)

    Google Scholar 

  86. Smith, J.F., Nguyen, T.: Fuzzy logic based resource manager for a team of UAVs. In: NAFIPS 2006–2006 Annual Meeting of the North American Fuzzy Information Processing Society. IEEE (2006)

    Google Scholar 

  87. Zhang, X., et al.: Experimental investigation on the online fuzzy energy management of hybrid fuel cell/battery power system for UAVs. Int. J. Hydrogen Energy 43(21), 10094–10103 (2018)

    Article  Google Scholar 

  88. Wang, A., Yang, W.: Design of energy management strategy in hybrid electric vehicles by evolutionary fuzzy system part II: tuning fuzzy controller by genetic algorithms. In: 2006 6th World Congress on Intelligent Control and Automation. IEEE (2006)

    Google Scholar 

  89. Wang, A., Yang, W.: Design of energy management strategy in hybrid vehicles by evolutionary fuzzy system part I: fuzzy logic controller development. In: 2006 6th World Congress on Intelligent Control and Automation. IEEE (2006)

    Google Scholar 

  90. Lakhmi Jain, P.D., Anna Maria Fanelli, P.D.: Recent Advances in Artificial Neural Networks Design and Applications, vol. 315. CRC Press (2000). ed. P.D. L.C. Jain, M.E., B.E. (Hons), Fellow I.E. (Australia)

    Google Scholar 

  91. Xu, L., et al.: Multi-objective component sizing based on optimal energy management strategy of fuel cell electric vehicles. Appl. Energy 157, 664–674 (2015)

    Article  Google Scholar 

  92. Eren, U., et al.: Model predictive control in aerospace systems: current state and opportunities. J. Guid. Contr. Dyn. 40(7), 1541–1566 (2017)

    Article  Google Scholar 

  93. Geng, B., Mills, J.K., Sun, D.: Energy management control of microturbine-powered plug-in hybrid electric vehicles using the telemetry equivalent consumption minimization strategy. IEEE Trans. Veh. Technol. 60, 4238–4248 (2011)

    Google Scholar 

  94. Han, J., Kum, D., Park, Y.: Synthesis of predictive equivalent consumption minimization strategy for hybrid electric vehicles based on closed-form solution of optimal equivalence factor. IEEE Trans. Veh. Technol. 66, 5604–5616 (2017)

    Google Scholar 

  95. Choi, Y., Jimenez, H., Mavris, D.N.: Two-layer obstacle collision avoidance with machine learning for more energy-efficient unmanned aircraft trajectories. Robot. Auton. Syst. 98, 158–173 (2017)

    Article  Google Scholar 

  96. Bellingham, J., et al.: Multi-task allocation and path planning for cooperating UAVsl. In: Butenko, S., Murphey, R., Pardalos, P.M. (eds.) Cooperative Control: Models, Applications and Algorithms, vol. 1, pp. 23–41. Springer, Boston (2003). https://doi.org/10.1007/978-1-4757-3758-5_2

  97. Amoiralis, E.I., Tsili, M.A., Spathopoulos, V., Hatziefremidis, A.: Energy efficiency optimization in UAVs: a review. Mater. Sci. Forum 792, 281–286 (2014)

    Google Scholar 

  98. Leonard, J., Savvaris, A., Tsourdos, A.: Energy management in swarm of unmanned aerial vehicles. J. Intell. Rob. Syst. 74(1–2), 233–250 (2013). https://doi.org/10.1007/s10846-013-9893-8

    Article  Google Scholar 

  99. Zhang, X., Liu, L., Dai, Y.: Fuzzy state machine energy management strategy for hybrid electric UAVs with PV/fuel cell/battery power system. Int. J. Aerosp. Eng. 2018 (2018)

    Google Scholar 

  100. Panagiotou, P., Tsavlidis, I., Yakinthos, K.: Conceptual design of a hybrid solar MALE UAV. Aerosp. Sci. Technol. 53, 207–219 (2016)

    Google Scholar 

  101. Hajianmaleki, M.: Conceptual design method for solar powered aircrafts. In: AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ibrahim Abdullahi Shehu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Shehu, I.A., Mohammed, M., Sulaiman, S.H., Abdulkarim, A., Alhassan, A.B. (2021). A Review on Unmanned Aerial Vehicle Energy Sources and Management. In: Abawajy, J.H., Choo, KK.R., Chiroma, H. (eds) International Conference on Emerging Applications and Technologies for Industry 4.0 (EATI’2020). EATI 2020. Lecture Notes in Networks and Systems, vol 254. Springer, Cham. https://doi.org/10.1007/978-3-030-80216-5_14

Download citation

Publish with us

Policies and ethics