The Internet of Things has become an evolving area of wireless technologies. Energy storage plays a crucial role in developing, implementing, and deploying the Internet of Things (IoT) to help solve some of the problems facing our daily activities. It is known that in batteries, energy-stored systems are able to get spoiled due to undercharging or over-charging and might profoundly affect the operation of the whole system. Electric and hybrid vehicles need an exact state-of-charge approximation technique to improve battery safety and lifetime and prevent damage. An efficient battery managing system is vital to accurately indicate the battery operating temperature and state of charge and protect the Battery against cell disproportion. This paper presents a simulation-based Battery Management System (BMS) for e-bikes, it was implemented on Arduino Nano. The battery parameters such as Temperature, Voltage, Current, State-of-Charge (SoC), and Depth-of-Discharging (DoD) will be sent to a cloud server via the BOLT IoT module, and a data analysis tool will be used to approximate bad battery pack cells. To effectively estimate the state-of charge of the system battery, three different mathematical models for a single and packed battery management system techniques, namely, Coulomb Counting (CC), the Unscented Kalman filter (UKF), and the Extended Kalman Filter (EKF), were proposed and explained in this study. The battery Management System is expected to improve the overall performance of the IoT-enabled systems and will also contribute to mass acceptance of renewable energy systems since Battery Management systems would be one of its key components.