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Multirotor electric aerial vehicle model identification with flight data with corrections to physics-based models

Abstract

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.

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Availability of data and materials

The simulation data used in this study is available upon request.

Code availability

The code used for simulation is not available.

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Acknowledgements

This paper is an extension of the work that was previously presented at the 75th Annual Forum of the Vertical Flight Society as “Multirotor Electric Aerial Vehicle Model Validation with Flight Data: Physics-Based and System Identification Models.” The work has been expanded to include model corrections for the physics-based model.

Funding

This work is carried out at Rensselaer Polytechnic Institute under the Army/ Navy/NASA Vertical Lift Research Center of Excellence (VLRCOE) Program, grant number W911W61120012, with Dr. Mahendra Bhagwat as Technical Monitor.

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Correspondence to Robert Niemiec.

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Previous Publication

This work was presented at the 75th Annual Forum of the Vertical Flight Society as “Multirotor Electric Aerial Vehicle Model Validation with Flight Data: Physics-Based and System Identification Models.” The work has been expanded to include model corrections for the physics-based model.

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Niemiec, R., Ivler, C., Gandhi, F. et al. Multirotor electric aerial vehicle model identification with flight data with corrections to physics-based models. CEAS Aeronaut J (2022). https://doi.org/10.1007/s13272-022-00583-5

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  • DOI: https://doi.org/10.1007/s13272-022-00583-5

Keywords

  • System identification
  • Flight mechanics
  • Electric VTOL (eVTOL)