Abstract
A novel robust ice detection methodology for the early detection of icing-related flight performance degradation is presented. Based on data of 75,689 flights with modern commercial airliners, a maximum aircraft fleet’s performance variation has been estimated. The evaluation of results indicates that an expected influence of icing could be clearly separated. The developed methodology is energy based and fuses aircraft body and engine influences on flight performance, which allows to reliably calculate a deviation from an available reference. This difference in flight performance is consequently used to detect an aerodynamic degradation. The novel methodology provides large capabilities and shows a good detection reliability with no false alarm even within maneuvering flight, wind shear, turbulence, and sideslip as well as for several sensor error cases. The methodology was evaluated during various simulator trials. The results show a very high potential in supporting pilots with adequate information about the current aircraft status in icing conditions.
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