基于飞行轨迹估算飞机耗油量的综合框架

Linfeng Zhang, Alex Bian, Changmin Jiang, Lingxiao Wu
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摘要

准确计算飞机燃油消耗量在飞行运行、优化和污染物核算方面发挥着不可替代的作用。由于飞机油耗会随着不同飞行条件和物理因素的变化而变化,因此准确计算飞机油耗非常困难。本研究利用飞行监控数据,建立了一个全面的数学框架,并在飞行动力学和燃油消耗之间建立了联系,提供了一套高精度、高分辨率的燃油计算方法。通过这一框架,其他从业人员也可以根据具体需要选择数据源。该方法首先解决了区间燃油消耗的功能问题。我们应用光谱变换技术挖掘自动监控广播(ADS-B)数据,识别飞行剖面的关键方面,并建立其与燃油消耗的理论关系。随后,使用参数可调的深度神经网络来拟合这一多元函数,从而方便地计算出高精度的区间油耗。此外,还构建了一种二阶平滑单调插值法和一种瞬时燃料消耗量估算方法。数值结果验证了模型的有效性。使用ADS-B和飞机通信寻址与报告系统(ACARS)2023年的数据进行测试,区间油耗的平均误差可降至3.31%$,瞬时油耗的积分误差为8.86%$。这些结果确立了该模型的先进性,实现了迄今为止飞机油耗计算中最低的估计误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comprehensive Framework for Estimating Aircraft Fuel Consumption Based on Flight Trajectories
Accurate calculation of aircraft fuel consumption plays an irreplaceable role in flight operations, optimization, and pollutant accounting. Calculating aircraft fuel consumption accurately is tricky because it changes based on different flying conditions and physical factors. Utilizing flight surveillance data, this study developed a comprehensive mathematical framework and established a link between flight dynamics and fuel consumption, providing a set of high-precision, high-resolution fuel calculation methods. It also allows other practitioners to select data sources according to specific needs through this framework. The methodology begins by addressing the functional aspects of interval fuel consumption. We apply spectral transformation techniques to mine Automatic Dependent Surveillance-Broadcast (ADS-B) data, identifying key aspects of the flight profile and establishing their theoretical relationships with fuel consumption. Subsequently, a deep neural network with tunable parameters is used to fit this multivariate function, facilitating high-precision calculations of interval fuel consumption. Furthermore, a second-order smooth monotonic interpolation method was constructed along with a novel estimation method for instantaneous fuel consumption. Numerical results have validated the effectiveness of the model. Using ADS-B and Aircraft Communications Addressing and Reporting System (ACARS) data from 2023 for testing, the average error of interval fuel consumption can be reduced to as low as $3.31\%$, and the error in the integral sense of instantaneous fuel consumption is $8.86\%$. These results establish this model as the state of the art, achieving the lowest estimation errors in aircraft fuel consumption calculations to date.
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