UAV dynamics and electric power system modeling and visualization using modelica and FMI

Meaghan Podlaski, Luigi Vanfretti, Hamed Nademi, Hao Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


This paper presents an object-oriented, equation-based framework for multi-engineering modeling of a quadrotor UAV, which includes the rigid body dynamics, simplified aerodynamics, gyroscopic effects, electrical power system and battery losses, and DC motor dynamics. An open-source drone modeling library is introduced by explaining the mathematical models and multi-domain components used to model the drone. Animation and visualization techniques for the drone using CAD models are also introduced and explained. The proposed drone model is simulated under different flight scenarios using motor and power system models with different levels of detail, aiming to provide better means for design and understanding, of multi-engineering aspects of UAVs. This model provides a foundation for future UAV open-source model development, electrified power propulsion design, visualization and interaction, and system identification.
Original languageEnglish (US)
Title of host publicationVertical Flight Society's 76th Annual Forum and Technology Display
PublisherVertical Flight Society
StatePublished - Jan 1 2020
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-30
Acknowledgements: This work was supported in whole or in part by the National Aeronautics and Space Administration through the University Leadership Initiative award for the Center for Cryogenic High-Efficiency Electrical Technologies for Aircraft (CHEETA), in part by Dominion Energy, in part by the ECSE Department at RPI, and in part by the Center of Excellence for NEOM Research at King Abdullah University of Science and Technolog. The first author is supported through a Rensselaer Graduate Fellowship. The authors would like to thank Dr. Farhan Gandhi and Dr. Robert Niemiec for their invaluable input in shaping the work presented in this paper.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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