Energy Management Strategy for Hybrid-Electric Propulsion UAVs

IF 0.2 Q4 AREA STUDIES
Hongwei Zhao, Xue Jiang, Li-quan He, Yu Wu, Fengming Ai, Xingzhuang Liang, Weilin Li
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引用次数: 0

Abstract

Compared with traditional unmanned aerial vehicles(UAVs) powered by fuel, pure electric UAVs are more environmentally friendly, but due to the low energy density of lithium batteries, the UAVs have a short sailing time, which has also become a fatal disadvantage of UAVs. Fuel cells are considered to be an ideal power generation device to improve the endurance and cruising distance of UAVs due to their high specific energy, non-polluting, and high conversion efficiency. However, the flight tasks of UAVs are complex and changeable, and fuel cells need to use energy storage batteries as auxiliary power sources. This paper focuses on the energy management system (EMS) of the UAV hybrid power system based on fuel cells-lithium battery-supercapacitor. The EMS in the paper is divided into an upper decision-making layer and a lower control layer. The upper decision-making layer obtains the optimal power distribution scheme of each power source through the model predictive control (MPC) energy management strategy based on the equivalent consumption minimization strategy (ECMS) of hydrogen; The lower control layer obtains the power proportional relationship of each power supply from the decision-making layer and controls the output voltage and current of the relevant power supply modules to achieve stable operation of the whole system and reasonable power distribution.
混合动力推进无人机的能量管理策略
纯电动无人机与传统燃油驱动的无人机相比,更加环保,但由于锂电池能量密度低,无人机的航行时间较短,这也成为无人机的致命劣势。燃料电池具有高比能、无污染、转换效率高等特点,被认为是提高无人机续航能力和巡航距离的理想发电装置。然而,无人机的飞行任务复杂多变,燃料电池需要使用储能电池作为辅助动力源。研究了基于燃料电池-锂电池-超级电容器的无人机混合动力系统能量管理系统。本文中的环境管理系统分为上层决策层和下层控制层。上层决策层通过基于氢气等效消耗最小化策略(ECMS)的模型预测控制(MPC)能量管理策略获得各电源的最优功率分配方案;下控制层从决策层获取各电源的功率比例关系,并控制相关电源模块的输出电压和电流,以实现整个系统的稳定运行和合理的功率分配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.20
自引率
0.00%
发文量
8
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