Testing of an indirect ice detection methodology in the Horizon 2020 project SENS4ICE

Abstract Supercooled large droplets (SLD) icing conditions have been the cause of severe aircraft accidents over the last decades. Existing countermeasures, even on modern airplanes, are not necessarily effective against the resulting ice formations, which raises a demand for reliable detection of SLD in all conditions for safe operations. The EU-funded Horizon 2020 project SENS4ICE focused on new ice detection approaches and innovative sensor hybridization to target a fast and reliable (SLD-)ice detection. The performance-based (indirect) ice detection methodology is key to this approach and based on the changes of airplane flight characteristics under icing influence. This paper provides a short overview of the development and implementation of the indirect ice detection (IID) algorithms in SENS4ICE. Moreover, it gives and discusses first exemplary results from the IID tests in classical icing conditions during the SENS4ICE North America flight test campaign conducted in February/March 2023 out of St. Louis Regional Airport in Alton (Illinois, USA).