Multirotor electric aerial vehicle model identification with flight data with corrections to physics-based models
CEAS Aeronautical Journal
Developing standard, well-vetted methods for modeling and simulation, prediction of flying/handling qualities, and control system design is critical for improving safety and quality control of multirotor electric aerial vehicles. This paper explores two methods for modeling the dynamics of a small (56 cm, 1.56 kg) hexacopter at hover and forward flight. The first modeling method was system identification from flight data, the second method was a physics-based blade element model with 10 state Peter-He inflow. Evaluation of the fidelity for both the system-identification and physics-based models was completed by comparison to flight data at hover and forward flight. The results were used to classify the importance of key dynamic building blocks on the model fidelity, such as motor/rotor lag dynamics, inertia, and dynamic inflow.
Rensselaer Polytechnic Institute
Electric VTOL (eVTOL), Flight mechanics, System identification
Robert Niemiec, Christina Ivler, Farhan Gandhi, and Frank Sanders. "Multirotor electric aerial vehicle model identification with flight data with corrections to physics-based models" CEAS Aeronautical Journal (2022): 575-596. https://doi.org/10.1007/s13272-022-00583-5