Featured Project
# Remotely Controlled Self-balancing Mini Bike
Team Members:
- Will Chen hongyuc5
- Jiaming Xu jx30
- Eric Tang leweit2
# Problem
Bike Share and scooter share have become more popular all over the world these years. This mode of travel is gradually gaining recognition and support. Champaign also has a company that provides this service called Veo. Short-distance traveling with shared bikes between school buildings and bus stops is convenient. However, since they will be randomly parked around the entire city when we need to use them, we often need to look for where the bike is parked and walk to the bike's location. Some of the potential solutions are not ideal, for example: collecting and redistributing all of the bikes once in a while is going to be costly and inefficient; using enough bikes to saturate the region is also very cost inefficient.
# Solution
We think the best way to solve the above problem is to create a self-balancing and moving bike, which users can call bikes to self-drive to their location. To make this solution possible we first need to design a bike that can self-balance. After that, we will add a remote control feature to control the bike movement. Considering the possibilities for demonstration are complicated for a real bike, we will design a scaled-down mini bicycle to apply our self-balancing and remote control functions.
# Solution Components
## Subsystem 1: Self-balancing part
The self-balancing subsystem is the most important component of this project: it will use one reaction wheel with a Brushless DC motor to balance the bike based on reading from the accelerometer.
MPU-6050 Accelerometer gyroscope sensor: it will measure the velocity, acceleration, orientation, and displacement of the object it attaches to, and, with this information, we could implement the corresponding control algorithm on the reaction wheel to balance the bike.
Brushless DC motor: it will be used to rotate the reaction wheel. BLDC motors tend to have better efficiency and speed control than other motors.
Reaction wheel: we will design the reaction wheel by ourselves in Solidworks, and ask the ECE machine shop to help us machine the metal part.
Battery: it will be used to power the BLDC motor for the reaction wheel, the stepper motor for steering, and another BLDC motor for movement. We are considering using an 11.1 Volt LiPo battery.
Processor: we will use STM32F103C8T6 as the brain for this project to complete the application of control algorithms and the coordination between various subsystems.
## Subsystem 2: Bike movement, steering, and remote control
This subsystem will accomplish bike movement and steering with remote control.
Servo motor for movement: it will be used to rotate one of the wheels to achieve bike movement. Servo motors tend to have better efficiency and speed control than other motors.
Stepper motor for steering: in general, stepper motors have better precision and provide higher torque at low speeds than other motors, which makes them perfect for steering the handlebar.
ESP32 2.4GHz Dual-Core WiFi Bluetooth Processor: it has both WiFi and Bluetooth connectivity so it could be used for receiving messages from remote controllers such as Xbox controllers or mobile phones.
## Subsystem 3: Bike structure design
We plan to design the bike frame structure with Solidworks and have it printed out with a 3D printer. At least one of our team members has previous experience in Solidworks and 3D printing, and we have access to a 3D printer.
3D Printed parts: we plan to use PETG material to print all the bike structure parts. PETG is known to be stronger, more durable, and more heat resistant than PLA.
PCB: The PCB will contain several parts mentioned above such as ESP32, MPU6050, STM32, motor driver chips, and other electronic components
## Bonus Subsystem4: Collision check and obstacle avoidance
To detect the obstacles, we are considering using ultrasonic sensors HC-SR04
or cameras such as the OV7725 Camera function with stm32 with an obstacle detection algorithm. Based on the messages received from these sensors, the bicycle could turn left or right to avoid.
# Criterion For Success
The bike could be self-balanced.
The bike could recover from small external disturbances and maintain self-balancing.
The bike movement and steering could be remotely controlled by the user.
Project Videos