Integrated Energy-Efficient Planning and Management Framework for Autonomous Long-Endurance Flight of Hydrogen Fuel Cell/Battery Hybrid UAVs

Xiaoyu Guo, Xiaowei Song, Dan Zeng, Zhen Dong, Xiang Yu, Lu Liu*, Yuguang Fang

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

The fuel cell/battery hybrid energy topology can enable autonomous long-endurance flight of multirotor unmanned aerial vehicles (UAVs) for persistent missions. Aiming at further enhancing flight endurance, energy-efficient trajectory planning, and energy management (power allocation between the hydrogen fuel cell and battery) have been widely investigated. However, existing studies mostly design the trajectory planning and energy management separately, largely neglecting the shared information and objectives between planning and management layers. This article introduces an integrated planning and energy management framework be leveraging the trajectory planning results to provide an optimized reference for online energy management. A B-spline parameterized flight trajectory is first generated based on a cost function that balances energy efficiency and dynamic feasibility. Then, an optimal state-of-charge (SOC) trajectory is constructed based on the predictive flight information. Finally, an adaptive equivalent consumption minimization strategy is designed to track the optimal SOC trajectory and distribute power online. In addition, parameter identification is introduced to update the fuel cell characteristics according to flight conditions, enhancing environmental adaptability. Experimental results on a self-developed fuel cell/battery hybrid UAV validate the performance of the proposed method. © 2024 IEEE.
Original languageEnglish
JournalIEEE/ASME Transactions on Mechatronics
Online published23 Jan 2025
DOIs
Publication statusOnline published - 23 Jan 2025

Funding

This work was supported in part by the Hong Kong SAR Government under the Global STEM Professorship, the Hong Kong Jockey Club under the Hong Kong JC STEM Lab of Smart City (Ref.: 2023-0108), in part by the Research Grants Council of Hong Kong under Grant CityU-11210222, in part by the General Research Fund under Grant 11207323, in part by the National Natural Science Foundation of China under Grant 62425302, and in part by the Young Scientists Fund (Hong Kong and Macao) under Grant 62222318.

Research Keywords

  • energy efficiency
  • energy management
  • Fuel cell (FC)
  • trajectory planning
  • unmanned aerial vehicle (UAV)

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