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Estimation of aircraft fuel consumption by modeling flight data from avionics systems

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  • Huang, Chenyu
  • Cheng, Xiaoyue

Abstract

Accurate and economic estimation of aircraft fuel consumption is fundamental for optimizing aviation operations, including emission reduction, flight route planning, and fuel management. Numerous literature presented mathematical models to estimate aircraft fuel consumption but often neglected the challenges of applying those methods in aviation operations. This paper explores a novel strategy to estimate aircraft fuel consumption by modeling flight data from onboard flight data recorder (FDR) and automatic dependent surveillance – broadcast (ADS-B). The Classification and Regression Tree (CART) and Neural Networks (NNs) are adopted for modeling. CART and NN models are developed using FDR data; ADS-B data are used to assess the model performance. The result indicates that the CART model performs better when inputs contain errors and missing values, and the ADS-B data could be used to estimate aircraft fuel consumption as a less-expensive and more convenient strategy compared to the FDR data.

Suggested Citation

  • Huang, Chenyu & Cheng, Xiaoyue, 2022. "Estimation of aircraft fuel consumption by modeling flight data from avionics systems," Journal of Air Transport Management, Elsevier, vol. 99(C).
    • Handle: RePEc:eee:jaitra:v:99:y:2022:i:c:s0969699722000023
    DOI: 10.1016/j.jairtraman.2022.102181
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    References listed on IDEAS

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    1. Merkert, Rico & Swidan, Hassan, 2019. "Flying with(out) a safety net: Financial hedging in the airline industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 206-219.
    2. Brueckner, Jan K. & Abreu, Chrystyane, 2017. "Airline fuel usage and carbon emissions: Determining factors," Journal of Air Transport Management, Elsevier, vol. 62(C), pages 10-17.
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    Cited by:

    1. Zheng Zhang & Dongyue Guo & Shizhong Zhou & Jianwei Zhang & Yi Lin, 2023. "Flight trajectory prediction enabled by time-frequency wavelet transform," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Hamdan, Sadeque & Jouini, Oualid & Cheaitou, Ali & Jemai, Zied & Granberg, Tobias Andersson & Josefsson, Billy, 2022. "Air traffic flow management under emission policies: Analyzing the impact of sustainable aviation fuel and different carbon prices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 14-40.

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