摘要
氢燃料电池无人机发展迅速,但无人机结构紧凑气源容量有限,如何提高氢气利用率,进一步增强续航能力是一个亟待解决的问题。针对该问题,本文设计了引射循环系统,将排空的氢气进行回收利用,以提高氢气利用率。以典型的1.7 kW无人机燃料电池为例,采用计算流体力学方法设计了氢循环引射器,并进行性能分析,揭示了不同工况下内部流场特性。结果表明在二次流压力与出口压力压差为10 kPa时,一次流压力在300~700 kPa的范围内具有良好的引射性能。同时研究了关键结构参数喉嘴面积比(AR)和不同工况对引射性能的影响,研究表明,最佳AR随一次流压力变化而变化,统筹考虑本文选择AR=16,满足了不同工况下的全局最优引射性能,氢气利用率最高提升了30.3%,进一步延长了无人机的续航能力。
The PEMFC driven unmanned aerial vehicle(UAV)is developing rapidly.However,the UAV has a compact structure and limited air source capacity.It is an urgent problem to improve the utilization rate of hydrogen that will further enhance the UAV endurance.In this paper,a hydrogen recirculation system based on the ejector is designed to recycle the drained hydrogen to improve the utilization rate of fuel.For the 1.7 kW fuel cell used in UAV,a hydrogen cycle ejector is designed by using the computational fluid dynamics method,and the performance analysis is implemented to reveal the internal flow field characteristics under different working conditions.The results show that the primary flow pressure has a good ejecting performance in the range of 300~700 kPa when the pressure difference between the secondary flow pressure and the back pressure is 1o kPa.Then,the influence of key structural parameters of area ratio(AR)and different working conditions on the ejecting performance is studied.The research shows that the optimal AR varies with the change of primary flow pressure,and the AR is selected as 16 in this paper to meet the global optimal ejecting performance under different working conditions.The maximum hydrogen utilization rate of the proposed system is increased by 30.3%outperforming that of the traditional UAV's system.
作者
徐好进
王辰
王雷
Xu Haojin;Wang Chen;Wang Lei(School of Control Science and Engineering,Shandong University,Jinan 250061,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2023年第3期49-57,共9页
Chinese Journal of Scientific Instrument
基金
国家重点研发计划(2019YFB1504700)项目资助。
关键词
氢燃料电池
引射器
计算流体力学
流场分析
结构优化
proton exchange membrane fuel cell
ejector
computational fluid dynamics
fluid analysis
structure optimization
