Fuzzy-based optimal energy management strategy of series hybrid-electric propulsion system for UAVs

汽车工程 推进 模糊逻辑 燃料效率 工程类 能源管理 能源消耗 荷电状态 电池(电) 计算机科学 功率(物理) 能量(信号处理) 航空航天工程 电气工程 统计 物理 量子力学 人工智能 数学
作者
Mingliang Bai,Wenjiang Yang,Ruopu Zhang,Marek Košuda,Peter Korba,Michal Hovanec
出处
期刊:Journal of energy storage [Elsevier BV]
卷期号:68: 107712-107712 被引量:12
标识
DOI:10.1016/j.est.2023.107712
摘要

Hybrid-electric propulsion system (HEPS) has gained significant attention in unmanned aerial vehicles (UAVs) due to its potential to significantly reduce fuel consumption and pollutant emissions. Effective energy management strategies are crucial in ensuring the efficient operation of HEPS in UAVs, as they involve multiple power and energy sources. While conventional equivalent consumption minimum strategy (ECMS) is effective in distributing engine and battery output power, it struggles to maintain the battery’s state of charge (SOC) within desired levels in case of engine failure. The present study introduced the fuzzy logic control-equivalent consumption minimum strategy (FLC-ECMS), a fuzzy-based composite energy management strategy that incorporates the robustness and adaptability of fuzzy logic control. Through simulation tests under general aviation cruise flight and cargo transport flight scenarios, the results indicated that hybrid UAV equipped with the HEPS can decrease fuel consumption and CO2 emissions by at least 18.6% and NOx emissions by 10.1% in the first profile and by 23.6% and 11.2% in the second profile, compared to conventional oil-powered UAV. The FLC-ECMS method not only reduces fuel consumption and emissions, but also maintains the battery SOC within permitted range and minimizes the difference between front and back SOC. This study provides new insights into the optimal energy management of HEPS for complex profiles in UAVs, highlighting the significance of UAVs in reducing environmental impacts, and has the potential for broader application in other electric propulsion systems.
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