Generating Fault Databases Through Simulated and Experimental Multi-Rotor UAV Propulsion Systems

A light-gray-box simulation model is proposed for a multi-rotor propulsion chain designed to inject various faults into the system to generate fault behavior data sets. The model integrates the electrical and thermal characteristics of each component to model the interactions between components when...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2024-04, Vol.73 (4), p.4671-4682
Main Authors: Brulin, Pierre-Yves, Khenfri, Fouad, Rizoug, Nassim
Format: Article
Language:English
Subjects:
Autonomous aerial vehicles
Behavioral sciences
Circuit faults
Controllers
database fault tolerance
Engineering Sciences
Fault detection
fault diagnosis
Faults
Hardware
Overheating
permanent magnet motor
Permanent magnets
Power semiconductor devices
Propellers
Propulsion
Propulsion systems
Redundancy
Rotors
Sensors
Simulation models
Synchronous motors
Unmanned Aerial Vehicle (UAV)
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Summary:A light-gray-box simulation model is proposed for a multi-rotor propulsion chain designed to inject various faults into the system to generate fault behavior data sets. The model integrates the electrical and thermal characteristics of each component to model the interactions between components when faults are introduced. The simulated model is compared with an experimental test bench incorporating real hardware components, on which various faults can be injected to assess the accuracy of the simulated model. The propulsion chain consists of an Electronic Speed Controller, a Permanent Magnet Synchronous Motor, and a propeller. The faults considered are introduced on the three components of the propulsion chain. Electronic Speed Controller faults are applied to the power transistors; motor failures are open circuit, overheating and friction; and propeller failures are blade breakage and propeller loss. Using simulation of components with various failures, the model is designed to generate scalable, systematic, and reproducible behavior datasets for the development of fault detection systems which would eliminate the need for real hardware components.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2024.3352172