Estimating Aircraft Fuel Consumption using Radar Tracks Data

Liu, Fangzi

doi:10.23940/ijpe.18.10.p1.22492260

Cited by 2 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The fuel flow prediction accuracy during climb and level-flight phases is relatively satisfactory with the average relative errors 9.6% and 7.1%, respectively. The overall estimation accuracy is within the acceptable range [48]. Therefore, the accuracy of the BADA fuel consumption model used in this study meets the requirements for trajectory optimization.…”

Section: Verification Of Fuel Consumption Modelmentioning

confidence: 58%

Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints

Liu

Xie

et al. 2021

Sustainability

Self Cite

View full text Add to dashboard Cite

Investigating potential ways to improve fuel efficiency of aircraft operations is crucial for the development of the global air traffic management (ATM) performance target. The implementation of trajectory-based operations (TBOs) will play a major role in enhancing the predictability of air traffic and flight efficiency. TBO also provides new means for aircraft to save energy and reduce emissions. By comprehensively considering aircraft dynamics, available route limitations, sector capacity constraints, and air traffic control restrictions on altitude and speed, a “runway-to-runway” four-dimensional trajectory multi-objective planning method under loose-to-tight heterogeneous constraints is proposed in this paper. Taking the Shanghai–Beijing city pair as an example, the upper bounds of the Pareto front describing potential fuel consumption reduction under the influence of flight time were determined under different airspace rigidities, such as different ideal and realistic operating environments, as well as fixed and optional routes. In the congestion-free scenario with fixed route, the upper bounds on fuel consumption reduction range from 3.36% to 13.38% under different benchmarks. In the capacity-constrained scenario, the trade-off solutions of trajectory optimization are compressed due to limited available entry time slots of congested sectors. The results show that more flexible route options improve fuel-saving potentials up to 8.99%. In addition, the sensitivity analysis further illustrated the pattern of how optimal solutions evolved with congested locations and severity. The outcome of this paper would provide a preliminary framework for predicting and evaluating fuel efficiency improvement potentials in TBOs, which is meaningful for setting performance targets of green ATM systems.

show abstract

Section: Verification Of Fuel Consumption Modelmentioning

confidence: 58%