Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164036
Title: A comprehensive review of electrochemical hybrid power supply systems and intelligent energy managements for unmanned aerial vehicles in public services
Authors: Zhang, Caizhi
Qiu, Yuqi
Chen, Jiawei
Li, Yuehua
Liu, Zhitao
Liu, Yang
Zhang, Jiujun
Chan, Siew Hwa
Keywords: Engineering::Mechanical engineering
Issue Date: 2022
Source: Zhang, C., Qiu, Y., Chen, J., Li, Y., Liu, Z., Liu, Y., Zhang, J. & Chan, S. H. (2022). A comprehensive review of electrochemical hybrid power supply systems and intelligent energy managements for unmanned aerial vehicles in public services. Energy and AI, 9, 100175-. https://dx.doi.org/10.1016/j.egyai.2022.100175
Journal: Energy and AI
Abstract: The electric unmanned aerial vehicles (UAVs) are rapidly growing due to their abilities to perform some difficult or dangerous tasks as well as many public services including real-time monitoring, wireless coverage, search and rescue, wildlife surveys, and precision agriculture. However, the electrochemical power supply system of UAV is a critical issue in terms of its energy/power densities and lifetime for service endurance. In this paper, the current power supply systems used in UAVs are comprehensively reviewed and analyzed on the existing power configurations and the energy management systems. It is identified that a single type of electrochemical power source is not enough to support a UAV to achieve a long-haul flight; hence, a hybrid power system architecture is necessary. To make use of the advantages of each type of power source to increase the endurance and achieve good performance of the UAVs, the hybrid systems containing two or three types of power sources (fuel cell, battery, solar cell, and supercapacitor,) have to be developed. In this regard, the selection of an appropriate hybrid power structure with the optimized energy management system is critical for the efficient operation of a UAV. It is found that the data-driven models with artificial intelligence (AI) are promising in intelligent energy management. This paper can provide insights and guidelines for future research and development into the design and fabrication of the advanced UAV power systems.
URI: https://hdl.handle.net/10356/164036
ISSN: 2666-5468
DOI: 10.1016/j.egyai.2022.100175
Rights: © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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