Comparison of Two Ground-based Mass Estimation Methods on Real Data - ENAC - École nationale de l'aviation civile Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

## Comparison of Two Ground-based Mass Estimation Methods on Real Data

Richard Alligier
David Gianazza
• Fonction : Auteur
• PersonId : 955966
Nicolas Durand

#### Résumé

This paper focuses on the estimation of the aircraft mass in ground-based applications. Mass is a key parameter for climb prediction. It is currently not available to groundbased trajectory predictors because it is considered a competitive parameter by many airlines. There is hope that the aircraft mass might become widely available someday, but in the meantime it is possible to estimate an equivalent mass from the data already available, assuming the thrust to be known (maximum or reduced climb thrust for example). In a previous paper ([1]), two mass estimation methods were compared using simulated data. In this paper, we compare these two mass estimation methods using Mode-C radar data. Both methods estimate the aircraft mass by fitting the modeled energy rate (i.e. the power of the forces acting on the aircraft) with the energy rate observed at several points of the past trajectory. The first method, proposed by Schultz et al. ([2]), dynamically adjusts the weight parameter so as to fit the energy rate, using an adaptive sensitivity parameter to weight each observation. The second method, introduced in one of our previous publications ([1]), estimates the mass by minimizing the quadratic error on the observed energy rate, taking advantage of the polynomial expression of the modeled power when using the BADA model. The actual mass is unavailable in our radar data. However, we can use the estimated mass to compute a trajectory prediction. This prediction is then compared to the actual trajectory giving us some insight on the accuracy of the estimated mass. We have compared the obtained predictions with the ones obtained using the BADA reference mass. The root mean square error on the predicted altitude is reduced by 45 % using the least squares method. With the adaptive method this error is divided by two.

#### Domaines

Optimisation et contrôle [math.OC]

### Dates et versions

hal-01002401 , version 1 (06-06-2014)

### Identifiants

• HAL Id : hal-01002401 , version 1

### Citer

Richard Alligier, David Gianazza, Mohammad Ghasemi Hamed, Nicolas Durand. Comparison of Two Ground-based Mass Estimation Methods on Real Data. ICRAT 2014, 6th International Conference on Research in Air Transportation, May 2014, Istanbul, Turkey. pp xxxx. ⟨hal-01002401⟩

### Exporter

BibTeX TEI Dublin Core DC Terms EndNote Datacite

### Collections

350 Consultations
193 Téléchargements