Inspired by magnetic/electron physics class applications in real life. Maglev trains have always been a study topic I wanted to explore. The 3rd prompt about sustainable transportation really empowered us to think outside of the box.
What it does
This project is meant to find the minimum needed force to hover for unique masses, which in return requires less energy as the electromagnets do not need to output a constant force all the time. Our system first gets the reading from the Sonar Sensor, which it interrupts the raw data and turns into tangible distances. It than uses the given optimal maglev hover distance to see if it is hovering in optimal space, if it is it will provide a 0N additional force based off of its displacement away from the optimal point. If it detects it is off the optimal point, our file calculates based on mass and the magnetic distance relation which is a 2nd power inverse relation, which provides how much force is needed to maintain optimal height. This reading allows us to know know the minimum force needed for load without ever knowing the mass of our load.
How we built it
We constructed the circuit using resistors in series to reach our desired resistance. We than incorporated the sonar sensor which translates info into into the raspberry pi through GPIO pins. We than wrote our code in VScode written in Python.
Challenges we ran into
•Sonar sensor inaccurate readings •Python Errors •Magnetic/Distance relationship formula integration •Display errors •Video File errors
Accomplishments that we're proud of
We are very proud we completed this project just as we envisioned. We’re very proud of the teamwork and all we accomplished. At first we were skeptical if this was possible but it was! All the learning in a short time span was impressive for everyone.
What we learned
Our team learned multiple new Python libraries, visuals for live data, sonar sensor file integration, and much more!
What's next for Maglev Smart Sonar System
We would very much love to test out our system on an actual maglev train, but unfortunately those are not close to Calgary, yet! But our team has produced a very good final product that we will be further working on as it has potential if the right work is put in!