Predictions of Motion Sickness Incidence for EVTOL Passengers

Predictions of Motion Sickness Incidence for EVTOL Passengers

Sîrghi, Florina (TU Delft Aerospace Engineering)

Pavel, M.D. (mentor)
van Paassen, M.M. (mentor)
Stroosma, O. (mentor)

Delft University of Technology

Aerospace Engineering

2022-12-02

The interest in developing electric vertical takeoff and landing (eVTOL) vehicles has increased sharply in recent years. A concern for passenger acceptance of the new type of vehicle is that people may experience motion sickness. This is because eVTOL flight profiles are different from the motion conditions that people have previously experienced. The aim of this study was to predict the incidence of motion sickness amongst eVTOL passengers. To achieve this, a two degrees of freedom (2DOF) lateral theoretical motion sickness model was developed, with lateral acceleration and roll rate as inputs. The model parameters were tuned with data collected from flight simulator experiments performed in the SIMONA Research Simulator at the TU Delft. The participants (N=20) completed five trials, each time being exposed to one of five flight profiles: four eVTOL profiles (1—nominal condition, 2—high turbulence, 3—alternative control law, 4—seats turned 180°; t=24 min) and one helicopter profile (5—helicopter, t=31 min). Motion sickness severity in participants was measured using verbal ratings on the MIsery SCale (MISC). A significant difference was found between the MISC data for Profiles 1 and 2, showing that turbulence worsens motion sickness severity for passengers. No significant difference was found between Profiles 1 and 3 and between Profiles 1 and 4. The difference between the data from Profiles 1 and 5 was found to be statistically significant. However, given the discrepancy in how the two profiles were generated, further studies are needed to conclude whether flying in a helicopter in general induces more motion sickness than flying in an eVTOL. The 2DOF model was extended to 3DOF by adding vertical acceleration as input. After tuning both models with experimental data (mean MISC scores per participant), it was concluded that the 3DOF motion sickness predictions followed the trend of the measurements better than the ones of the 2DOF model. The developed models can be used for eVTOL design optimisation. To further improve the accuracy of the predictions, the 3DOF model will be extended to 6DOF in future studies.

eVTOL
Motion Sickness
Motion Sickness Modelling

http://resolver.tudelft.nl/uuid:957d5888-cd4a-4b00-9277-62c27a24f5b5

2027-11-21

Student theses

master thesis

© 2022 Florina Sîrghi