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

Siqi An, Yuantao Gan, Xu Peng and Songyi Dian ()
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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

Energies, 2024, vol. 18, issue 1, 1-18

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.

Keywords: hybrid power; compound-wing VTOL; power management; dynamic programming; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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