使用可持续航空燃料的飞机发动机气体交换优化:实验设计和遗传算法方法

IF 9.6 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Energy and AI Pub Date : 2024-07-14 DOI:10.1016/j.egyai.2024.100396
Zheng Xu , Jinze Pei , Shuiting Ding , Longfei Chen , Shuai Zhao , Xiaowei Shen , Kun Zhu , Longtao Shao , Zhiming Zhong , Huansong Yan , Farong Du , Xueyu Li , Pengfei Yang , Shenghui Zhong , Yu Zhou
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引用次数: 0

摘要

以可持续航空燃料为燃料的动阀二冲程(PV2S)航空发动机具有功率重量比高、扭矩输出均匀、气门正时灵活等优点,是通用航空和无人机推进的理想选择。然而,其高空气体交换性能仍有待探索,这为通过人工智能(AI)技术进行优化提供了新的机遇。本研究使用经过验证的一维+三维模型来评估 PV2S 飞机发动机的高空气体交换性能。PV2S 发动机的气门定时具有相当大的灵活性,因此采用了拉丁超立方实验设计(DoE)方法来拟合响应面模型。应用遗传算法(GA)对不同高度的气门正时进行迭代优化。优化过程表明,增加进气持续时间,同时减少排气持续时间和气门重叠角,可以显著提高高海拔地区的气体交换性能。最佳气门重叠角在海平面为 93 °CA,海拔 4000 米为 82 °CA。进一步研究了发动机转速、负荷和排气背压等运行参数对不同海拔高度气体交换过程的影响。在不同海拔高度,发动机转速越高,捕集效率越高,但输送比和充气效率却越低。这种影响在高海拔地区尤为明显。排气背压的增加会显著降低输送比,提高捕集效率。这项研究表明,将 DoE 与人工智能算法相结合可以提高飞机发动机的高空性能,为进一步的优化工作提供有价值的参考。
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Gas exchange optimization in aircraft engines using sustainable aviation fuel: A design of experiment and genetic algorithm approach

The poppet valves two-stroke (PV2S) aircraft engine fueled with sustainable aviation fuel is a promising option for general aviation and unmanned aerial vehicle propulsion due to its high power-to-weight ratio, uniform torque output, and flexible valve timings. However, its high-altitude gas exchange performance remains unexplored, presenting new opportunities for optimization through artificial intelligence (AI) technology. This study uses validated 1D + 3D models to evaluate the high-altitude gas exchange performance of PV2S aircraft engines. The valve timings of the PV2S engine exhibit considerable flexibility, thus the Latin hypercube design of experiments (DoE) methodology is employed to fit a response surface model. A genetic algorithm (GA) is applied to iteratively optimize valve timings for varying altitudes. The optimization process reveals that increasing the intake duration while decreasing the exhaust duration and valve overlap angles can significantly enhance high-altitude gas exchange performance. The optimal valve overlap angle emerged as 93 °CA at sea level and 82 °CA at 4000 m altitude. The effects of operating parameters, including engine speed, load, and exhaust back pressure, on the gas exchange process at varying altitudes are further investigated. The higher engine speed increases trapping efficiency but decreases the delivery ratio and charging efficiency at various altitudes. This effect is especially pronounced at elevated altitudes. The increase in exhaust back pressure will significantly reduce the delivery ratio and increase the trapping efficiency. This study demonstrates that integrating DoE with AI algorithms can enhance the high-altitude performance of aircraft engines, serving as a valuable reference for further optimization efforts.

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来源期刊
Energy and AI
Energy and AI Engineering-Engineering (miscellaneous)
CiteScore
16.50
自引率
0.00%
发文量
64
审稿时长
56 days
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