Probabilistic aircraft trajectory prediction in cruise flight considering ensemble wind forecasts
The problem of aircraft trajectory prediction subject to wind uncertainty is addressed. In particular, a probabilistic analysis of aircraft flight time and fuel consumption in cruise flight is presented. The wind uncertainty is obtained from ensemble weather forecasts. The cruise is composed of a gi...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/180812 |
| Acceso en línea: | https://hdl.handle.net/11441/180812 https://doi.org/10.1016/j.ast.2018.09.020 |
| Access Level: | acceso abierto |
| Palabra clave: | Stochastic trajectory prediction Fuel consumption uncertainty Flight predictability Wind uncertainty Ensemble weather forecasting |
| Sumario: | The problem of aircraft trajectory prediction subject to wind uncertainty is addressed. In particular, a probabilistic analysis of aircraft flight time and fuel consumption in cruise flight is presented. The wind uncertainty is obtained from ensemble weather forecasts. The cruise is composed of a given number of segments subject to uncertain winds (both along-track winds and crosswinds). The resulting average ground speed of each segment is modeled as a random variable, assuming a Log-Normal distribution. The probabilistic trajectory predictor developed is based on the Probabilistic Transformation Method; the input is the probability density functions of the average ground speeds of the cruise segments, and the output is the probability density functions of the flight time and the fuel consumption. Results are presented for several aircraft of different categories (medium and heavy), for a given trans-oceanic route and a real ensemble weather forecast. The effects of wind uncertainty on flight predictability and on fuel loading are analyzed. A fuel penalty parameter is defined, and the cost of flight unpredictability is quantified. The sample variability of all the results has been quantified by means of standard errors. |
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