Noise-Adaptive Multi-Mode Online Energy Management for PEMFC/Battery Hybrid UAVs

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

1 Scopus Citations
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Author(s)

  • Xiaoyu Guo
  • Dan Zeng
  • Zhen Dong
  • Jiabin Shen
  • Yixing Liu
  • Xiang Yu

Related Research Unit(s)

Detail(s)

Original languageEnglish
Journal / PublicationIEEE Transactions on Transportation Electrification
Publication statusOnline published - 10 Jul 2024

Abstract

Hydrogen/battery hybrid UAV flights present unique challenges to the adaptability of energy management strategy (EMS) due to dynamic operating conditions (altitude, temperature, humidity, etc.) and diverse flight modes (takeoff, cruising, maneuvering, etc.). In this paper, a novel multi-mode energy management strategy is proposed. First, inspired by the variational Bayesian approach, a noise-adaptive parameter identification method is introduced to monitor the fuel cell characteristics in-flight. The identification results provide an online reference for energy management. Subsequently, a case recognition logic categorizes the flight mode into cruising and non-cruising based on flight power variation. An online rule-based method is deployed for the non-cruising case to prioritize system response, and a novel equivalent consumption minimization strategy (ECMS) is used to maximize system endurance during cruising. Extensive ground tests are conducted with a fuel cell in a constant temperature and humidity chamber, and a flight test is carried out on a self-developed 3 kW fuel cell/battery hybrid UAV. Experimental results show that the proposed method outperforms classic EMSs in terms of system efficiency and reduced system stress. © 2024 IEEE.

Research Area(s)

  • energy management, Fuel cell, multi-mode, system identification, unmanned aerial vehicle

Citation Format(s)

Noise-Adaptive Multi-Mode Online Energy Management for PEMFC/Battery Hybrid UAVs. / Guo, Xiaoyu; Zeng, Dan; Dong, Zhen et al.
In: IEEE Transactions on Transportation Electrification, 10.07.2024.

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