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Charging Optimization with an Improved Dynamic Programming for Electro-Gasoline Hybrid Powered Compound-Wing Unmanned Aerial Vehicle

Author

Listed:
  • Siqi An

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

  • Yuantao Gan

    (Institute of Electronic and Electrical Engineering, Civil Aviation Flight University of China, Deyang 618307, China)

  • Xu Peng

    (Institute of Electronic and Electrical Engineering, Civil Aviation Flight University of China, Deyang 618307, China)

  • Songyi Dian

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

Abstract

For a longer endurance of vertical and level cruise flight, an electro-gasoline hybrid power system is introduced on a compound-wing unmanned aerial vehicle (UAV). After discharging during vertical flight, the battery pack is charged by a piston engine-driven generator, which simultaneously powers the UAV for level cruise flight. A charging model is established based on the configuration of the hybrid power system. Considering fuel consumption and battery attenuation within the typical flight profile of a compound-wing UAV, an optimized charging plan is developed using dynamic programming to determine the trajectory of the generated power sequence. To address deviations between ideal and practical flight conditions in terms of charging performance, a feedforward compensation is introduced to improve optimal tracking control within the dynamic programming framework. Simulations validate the effectiveness of the optimized charging plan, while testbench experiments confirm improvements achieved through compensation enhancement. The results demonstrate practicality with minimal overall cost compared to other conventional control plans.

Suggested Citation

  • Siqi An & Yuantao Gan & Xu Peng & Songyi Dian, 2024. "Charging Optimization with an Improved Dynamic Programming for Electro-Gasoline Hybrid Powered Compound-Wing Unmanned Aerial Vehicle," Energies, MDPI, vol. 18(1), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:18:y:2024:i:1:p:30-:d:1553196
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    References listed on IDEAS

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    1. Mingliang Bai & Wenjiang Yang & Dongbin Song & Marek Kosuda & Stanislav Szabo & Pavol Lipovsky & Afshar Kasaei, 2020. "Research on Energy Management of Hybrid Unmanned Aerial Vehicles to Improve Energy-Saving and Emission Reduction Performance," IJERPH, MDPI, vol. 17(8), pages 1-24, April.
    2. Tang, Wenbin & Wang, Yaqian & Jiao, Xiaohong & Ren, Lina, 2023. "Hierarchical energy management strategy based on adaptive dynamic programming for hybrid electric vehicles in car-following scenarios," Energy, Elsevier, vol. 265(C).
    3. Stefan Milićević & Ivan Blagojević & Saša Milojević & Milan Bukvić & Blaža Stojanović, 2024. "Numerical Analysis of Optimal Hybridization in Parallel Hybrid Electric Powertrains for Tracked Vehicles," Energies, MDPI, vol. 17(14), pages 1-19, July.
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