Ground crash area estimation of quadrotor aircraft under propulsion failure

• Main Authors: Mohd Hasrizam Che Man, Sivakumar, Anush Kumar, Hu, Haoliang, Low, Kin Huat
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Aeronautical engineering::Accidents and air safety; Engineering::Aeronautical engineering::Aircraft motors and engines; Engineering::Aeronautical engineering::Flight simulation; Unmanned Aerial Vehicle; Aircraft Flight Control System; Quad Rotor; Unmanned Aircraft Systems; Propulsion System Failure; Crash Trajectory Prediction; Risk Analysis; Safety Analysis; High-Fidelity Modelling
• Online Access: https://hdl.handle.net/10356/167368
• Institution: Nanyang Technological University

Small unmanned aircraft systems or drones are expected to be used for different applications, such as parcel delivery, inspection, and aerial photography, in urban areas. However, drones usually use an electric system to power up the propulsion, communications, navigation, and flight control system, which means that it is not as reliable as the manned aircraft system and may result in failure during operation and then crash to the ground. At present, there is almost no extensive publication about the high-fidelity modeling used by drones to calculate the crash trajectory and point of crash. The experimental data for modeling and simulation verification of multirotor aircraft are limited. So far, crash trajectory prediction has been limited to point mass or ballistic methods, and these methods are usually only suitable for complete power failure and without any control system. This study intends to investigate the effects of different multirotor drones’ failure modes on its crash trajectory and crash area compared to the ballistic model by using ADAMS and MATLAB co-simulation methods. Conclusions from the study show the crash trajectory, flight distance, and impact speed of the drones under four failure modes, which are quite different from the ballistic trajectory. The findings can potentially contribute to better risk assessment of the multirotor drones for the urban environment operation.