Regenerative and Assistive Ride Kit (RAR-K)
The project focuses on a sustainable “Smart E-Bike Conversion System” that transforms regular bicycles into intelligent hybrid vehicles. By combining advanced energy storage with ANFIS model, we aim to maximize efficiency and improve the rider experience.
The system uses real-time sensor data and a mobile app to manage energy smarter. Riders can choose between three specific modes:
This custom mobile application isn’t just a dashboard; it’s the brain of the ride.
- Advanced Power & Efficiency
- Supercapacitor Technology: Usage of supercapacitors to power the hub motor.
- Regenerative Braking: The system captures energy during braking to recharge the supercapacitors on the go.
- ANFIS Model: We use ANFIS-based predictive models to analyze the ride, making braking more efficient and stretching out the motor’s assistance time.
- Intelligent Ride Control
- OFF: Manual pedaling.
- Auto: Balanced, smart assistance.
- Hill Climb: Extra power for steep inclines based on altitude data.
- Mobile App & Data Tracking
- Route & Altitude Mapping: The app uses your route to predict exactly where you’ll need power or where you can brake to save energy.
- Performance Stats: Automatically stores ride data like average speed and total distance traveled
Project Details
- Student(s): Mohamad Jabr, George Abou Issa and Jennifer Farhat
- Advisor(s): Dr. Nagham El Ghossein
- Year: 2025-2026