Investigating Aerodynamics in RC Vehicles: Comparing Sensor Data Across Diverse Shapes
Iona, Michalis (2025-11-21)
Investigating Aerodynamics in RC Vehicles: Comparing Sensor Data Across Diverse Shapes
Iona, Michalis
(21.11.2025)
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
avoin
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe202601227853
https://urn.fi/URN:NBN:fi-fe202601227853
Tiivistelmä
This thesis investigates different shapes with various angles on front and rear placed on top of a robot, aiming to gather different data from various sensors placed around the shape, while experiencing considerable air resistance in different trajectories it travels. Each shape has a definitive incline and slope angle which was chosen according to the popular day-to day vehicles used. A total of eight sensors were used by placing them in key positions surrounding the robot, with each in purpose of tracking the aerodynamic behaviour depending on the terrain and air friction it faces. One flow sensor on each side of the vehicle, two pressure sensors placed on top and front and one force sensor in the frontal area of the vehicle. Subject to the angular use of incline and slope of each shape, all these sensors output various data, while also taking into consideration the current environmental and weather condition when testing. A track with various turns and straights, which would be taken in different speeds, was chosen for the output of different data, depending on how tight the turns would be. The vehicle would be able to accompany results and understand how much drag, lift and grip each shape would have when taking those specific corners. As a result, printed shapes were designed and put on top of the vehicle with sensors connected to the Jetson Nano, where live data can be seen through a terminal and saved into spreadsheet format. The data around the track is captured in a graphical manner by timestamping each corner whilst simultaneously comparing all angles. Therefore, the knowledge can be used to reconfigure the robot based on what track it would be suitable for. The results obtained by the experiments of different applied angles, output a huge difference in airflow, depending on what part of the track the vehicle is at. The 90° provided much more downforce to the vehicles flow, whereas the lowest angle at 22.5° showed a minimal drag, which was advantageous in top speed straights. An increase of 62% of air friction can be found when comparing the 22.5° and 90°, respectively.
