Electric Bi-Cycle Monitoring and Controlling System Based on Internet of Things

Abstract

The purpose of this paper was to design and build an electric bicycle that incorporates the Pedal Assist System (PAS). The PAS system detects when the rider starts pedaling and immediately provides electric assistance, making riding easier and more efficient. The team utilized a lithium-ion battery and a brushless DC (BLDC) motor to power the PAS system. The bicycle was designed to be easy to ride, energy-efficient, and a sustainable mode of transportation. The PAS system was successfully integrated into the bicycle and proved to be highly effective in assisting the rider. Overall, the paper demonstrated that PAS-based electric bicycles are a viable alternative to traditional bicycles and gasoline-powered vehicles, with the potential to revolutionize personal transportation.

Introduction

Due to environmental concerns, fuel costs, and the push for sustainable transportation, electric bicycles (e-bikes) have gained popularity as energy-efficient and eco-friendly alternatives. Integrating Pedal Assist Systems (PAS) with Internet of Things (IoT) technologies enhances not only user convenience but also real-time monitoring, remote control, and system intelligence.

2. System Overview

The proposed system combines:

• Pedal Assist System (PAS): Provides motor assistance based on pedaling effort using cadence and torque sensors.

• IoT Integration: Enables live data monitoring, predictive maintenance, GPS tracking, and remote control using cloud platforms (e.g., Blynk, ThingSpeak, MQTT).

Core Features:

• Smooth pedal-assisted ride with adjustable assist modes (Eco, Normal, Sport).

• Real-time monitoring of speed, battery, temperature, and location.

• Enhanced safety via fault detection and auto motor cutoff.

• User interaction through a mobile/web dashboard.

3. Hardware Components

• Motor: 36V, 250W BLDC motor with PWM-controlled driver.

• Battery: 36V, 12Ah lithium-ion pack (range: 40–50 km).

• Microcontroller: ESP32 or Arduino for control and connectivity.

• Sensors: Cadence, voltage, current, temperature, speed, and GPS.

• Protection Features: Overcurrent, overheat, and voltage cutoff.

4. Software & Architecture

• IoT Communication: MQTT/HTTP protocols for real-time data exchange.

• Firmware: Developed in C/C++ (Arduino IDE/ESP-IDF).

• System Flow:

  • Input from sensors → Processed by microcontroller → Output to motor and cloud.

  • Data displayed on mobile dashboard with analytics and alerts.

• Control Logic:

  • Motor power adjusted based on pedal speed and assist mode.

  • Smart safety cutoffs for abnormal conditions.

5. Key Functionalities

• Real-time Monitoring: Speed, battery status, temperature, GPS location.

• Predictive Maintenance: Alerts for abnormal behavior or component wear.

• Remote Features: Motor ON/OFF, security mode, GPS-based theft alerts.

• Data Analytics: Usage trends, energy consumption, and route logs.

• Adaptability: Potential for machine-learning-based adaptive ride optimization.

6. Performance Evaluation

Conclusion

The implementation and testing of the IoT-based Electric Bicycle Pedal Assist System successfully demonstrated the integration of intelligent control and real-time monitoring to enhance riding efficiency. The system effectively detected pedal motion and provided proportional motor assistance, ensuring smoother acceleration and reduced rider fatigue. Testing results confirmed that the pedal-assist mechanism responded within 100 ms, offering quick and reliable support. The IoT module efficiently transmitted performance data such as speed, voltage, and current to the cloud dashboard with minimal latency (~1.2 s), enabling accurate remote monitoring. Power consumption and battery discharge rates remained within the designed safety limits, validating the system’s energy efficiency and stability across various terrains. Overall, the project proved that combining IoT technology with pedal-assist systems can significantly improve electric bicycle performance, rider comfort, and system monitoring. This approach provides a foundation for future developments such as predictive maintenance, GPS-based tracking, and AI-driven adaptive assist levels for enhanced user experience and sustainability. The developed IoT-based Electric Bicycle Pedal Assist System performed efficiently during testing. The pedal-assist feature provided smooth motor support with a fast response time of 100 ms, maintaining a speed of 22 km/h on flat roads and 17 km/h on inclines. The IoT module successfully transmitted real-time data with an average latency of 1.2 seconds, and the battery showed a normal discharge from 36.8 V to 34.9 V after 10 km. Overall, the system proved to be stable, responsive, and energy-efficient, confirming the effectiveness of IoT integration in enhancing e-bike performance.

References

[1] P. K. Gujarathi, \"Emission Reduction by Conversion of Bicycle to Plug-In Hybrid Electric Bicycle for Low Distance Commuter as Replacement of Motorized Two Wheelers,\" 2019 11th International Symposium on Advanced Topics in Electrical Engineering (ATEE), Bucharest, Romania, 2019, pp. 1-5, doi: 10.1109/ATEE.2019.8724905. [2] Satyanarayana, Addala, and I. E. S. Naidu. \"Modeling and analysis of fuel cell power generation system using proportional integral speed controller.\" Advances in Science and Technology. Research Journal 18.2 (2024). [3] Addala, Satyanarayana, and I. E. S. Naidu. \"A Bat Algorithm and Hybrid Algorithm based PQ Enhancement in Grid Tied PV System.\" (2023). [4] V. P. Keseev, \"Electric Bicycle Design Experiences and Riding Costs,\" 2020 7th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE), Ruse, Bulgaria, 2020, pp. 1-4, doi: 10.1109/EEAE49144.2020.9279070. [5] Satyanarayana, Addala, and I. E. S. Naidu. \"Modeling and analysis of fuel cell power generation system using proportional integral speed controller.\" Advances in Science and Technology. Research Journal 18.2 (2024). [6] V. Dimitrov, \"Overview of the Ways to Design an Electric Bicycle,\" 2018 IX National Conference with International Participation (ELECTRONICA), Sofia, Bulgaria, 2018, pp. 1-4, doi: 10.1109/ELECTRONICA.2018.8439456. [7] A. Z. Aliyadin, A. Purwadi and S. Hidayat, \"Performance Analysis and Design of 250 Watt Outer Rotor BLDC Motor for Urban Electric Bicycles,\" 2022 7th International Conference on Electric Vehicular Technology (ICEVT), Bali, Indonesia, 2022, pp. 195-199, doi: 10.1109/ICEVT55516.2022.9925011. [8] H. Oman, W. C. Morchin and F. E. Jamerson, \"Electric-bicycle propulsion power,\" Proceedings of WESCON\'95, San Francisco, CA, USA, 1995, pp. 555-, doi: 10.1109/WESCON.1995.485440. [9] J. Sivaguru and P. Anush, \"Electrical bicycle: Selection of Components and Retrofitting,\" 2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), Coimbatore, India, 2021, pp. 1-5, doi: 10.1109/ICAECA52838.2021.9675745.

Copyright

Copyright © 2025 A.B L S Suharsha, A. Ushasri Varshini, D V V S Naganjaneyulu, D. Venkat. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.