Detection and Isolation of Propeller Icing and Electric Propulsion System Faults in Fixed-Wing UAVs

Abstract

This thesis presents a fault detection and isolation (FDI) framework for detecting propeller icing, and other propulsion faults of unmanned aerial vehicles (UAVs). Such faults are among the main causes for incidents and loss of equipment. A theoretical framework for the proposed FDI is covered extensively. A tuning methodology and an implementation guide are also covered in detail. The method has been tested extensively using a software–in–the–loop simulator. The simulation results have proven to be very successful and this motivates future testing on real data sets.