DESIGN AND DEVELOPMENT OF AN INTELLIGENT BATTERY MANAGEMENT SYSTEM FOR ELECTRIC BIKE
Abstract
This project focuses on the design and development of an intelligent 48V Battery Management System (BMS) for a lithium-ion battery pack used in an electric bike (E-bike), which aim to create a system that ensures operational safety, optimizes battery performance through real-time monitoring and cell balancing, and extends the overall lifespan of the battery, thereby promoting sustainable electric mobility. The methodology adopted combined theoretical design analysis and practical experimentation. The process began with system analysis and requirement definition, followed by the design of both hardware and software components. Hardware development included the integration of multiple ATmega328P microcontrollers for sensing and protection, and an ESP32 microcontroller as the central processing and communication unit. Sensors such as voltage dividers, Hall-effect current sensors, and LM35 temperature sensors were employed for accurate monitoring of electrical and thermal parameters. The software, developed using Arduino IDE and Arduino IoT Cloud, implemented Coulomb counting for State of Charge (SOC) estimation, algorithm-based protection, and MQTT communication for real-time data visualization. A conventional gasoline-powered motorcycle was converted into an electric bike to serve as a test platform for validating the system. Experimental results demonstrated that the BMS protected the battery from overcharging, deep discharging, and overheating, while maintaining balanced cell voltages. The IoT interface enabled seamless remote monitoring of voltage, current, temperature, SOC, and State of Health (SOH) on a web dashboard. In conclusion, the system achieved stable operation, protection, and reliable communication, demonstrating that an intelligent, IoT-enabled BMS can enhance the safety and efficiency of electric bike applications. These results provide a foundation for future improvements such as AI-based predictive maintenance and battery life estimation.
Full-Text Access Notice
In accordance with the NERD Policy on promoting peer-reviewed publication, public access to the full text of a project, thesis or dissertation is restricted for three years, allowing the author and supervisors sufficient time to pursue peer-reviewed publication.
During this period, researchers with legitimate academic or research purposes may request authorisation directly from the author to enable NERD to release the indexed full texts of the work using the form below.