Please login first
Design and Implementation of a Battery Management System for Electric Bicycles Using Hybrid SoC Estimation Techniques
* 1 , * 1, 2 , 1
1  School of Electrical and Electronics Engineering, CETVET, Fiji National University, Fiji
2  University of Engineering and Management Jaipur
Academic Editor: Francisco Falcone

https://doi.org/10.3390/ECSA-12-26513 (registering DOI)
Abstract:

Electric bicycles (E-Bikes) are gaining popularity as a sustainable mode of transportation
due to their energy efficiency and zero-emission operation. However, challenges such as
battery overcharging, overheating, and degradation from improper use can reduce battery
lifespan and increase maintenance costs. To address these issues, this paper presents the
design and implementation of a Battery Management System (BMS) tailored for E-Bike
applications, with a focus on enhancing safety, reliability, and performance. The proposed
BMS includes core functionalities such as State of Charge (SoC) estimation, temperature
monitoring, under-voltage, and overcharge protection. Different approaches including
Open-Circuit Voltage (OCV), Coulomb Counting (CC), and Kalman Filter techniques is
employed to improve SoC estimation accuracy. The circuit for CC based BMS was first simulated using Proteus, and system behavior was modeled in MATLAB Simulink to validate
design assumptions before hardware implementation. An Arduino Uno microcontroller
was used to control the system, interfacing with an LM35 temperature sensor, a voltage
divider, and an ACS712 current sensor. The BMS controls battery charging based on SoC
levels and activates a cooling fan when the battery temperature exceeds 45 °C. It disconnects
the charger at 100% SoC and triggers a beep alarm when SoC falls below 40%. An
external charger and regenerative charging from four electrodynamometers on the bicycle
chain recharge the battery when SoC drops below 20%, provided the load is disconnected.
Measurement results closely matched simulation data, with the MATLAB model showing
44% SoC after 3 h, compared to the actual real-time 45.85%. The system accurately tracked
charging/discharging patterns, validating its effectiveness. This compact and cost-effective
BMS design ensures safe operation, improves battery longevity, and supports broader
adoption of E-Bikes as an eco-friendly transportation solution.

Keywords: electric vehicle; temperature and current sensors; Battery management system; real data; State of Charge; Sustainable transport
Top