TY - JOUR
T1 - Integrated Energy-Efficient Planning and Management Framework for Autonomous Long-Endurance Flight of Hydrogen Fuel Cell/Battery Hybrid UAVs
AU - Guo, Xiaoyu
AU - Song, Xiaowei
AU - Zeng, Dan
AU - Dong, Zhen
AU - Yu, Xiang
AU - Liu, Lu
AU - Fang, Yuguang
PY - 2025/1/23
Y1 - 2025/1/23
N2 - 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.
AB - 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.
KW - energy efficiency
KW - energy management
KW - Fuel cell (FC)
KW - trajectory planning
KW - unmanned aerial vehicle (UAV)
UR - http://www.scopus.com/inward/record.url?scp=85216392354&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85216392354&origin=recordpage
U2 - 10.1109/TMECH.2024.3524751
DO - 10.1109/TMECH.2024.3524751
M3 - RGC 21 - Publication in refereed journal
SN - 1083-4435
JO - IEEE/ASME Transactions on Mechatronics
JF - IEEE/ASME Transactions on Mechatronics
ER -