Evaluating Fuel Consumption for Continuous Descent Approach Based on QAR Data

Abstract

Fuel savings are a significant aspect for evaluating the current and future technologies of civil aviation. Continuous-Descent Approach (CDA), as a representative of new concepts, requires a method for evaluating its fuel benefits. However, because of unavailability of the practical operational data, it is difficult to validate whether the previous fuel consumption mechanisms are suitable. This paper presents a unique method for quantifying potential fuel benefits. This permits an easy evaluation for the new procedures without modelling before implementing field tests. The proposed method is detailed in this paper. It derives from the inherent mechanical characteristic of aircraft engine, and utilizes historical flight data, rather than modelling, to predict fuel flow rates by matching flight conditions from Quick Access Recorder (QAR) data. The result has been shown to predict fuel consumption for conventional descent with the deviation of ±0.73%. To validate such method, a case study for our designed CDA procedure is presented. Fuel consumptions in baseline scenarios are estimated to analyse the variable impacts on fuel consumption. The estimated fuel benefits are consistent with the results in the previous field tests. This analysis helps support Air Traffic Management decisions on eventual field test by reducing the validation time and cost.

Calculation and analysis of pollutants during takeoff and landing based on airborne data

“…The improvement of this method is based on the sum or average of all data for each model. The standard LTO mode and ICAO time data are listed in Table 2 13 …”

A Review of the Research of Quick Access Recorder data

“…The establishment of fuel consumption model can better estimate engine performance, control fuel saving flow, and make more accurate prediction of fuel consumption, but there are also time consuming and workload problems. Different from the above modeling and simulation analysis methods, Ye [22] et al proposed a method based on the inherent mechanical characteristics of the engine without modeling. By using QAR data to match flight conditions, fuel flow prediction is carried out.…”