Integration of IoT with Smart Battery Management Systems (BMS) in Electric Vehicles (EVs): A Cloud-Connected Framework for Ongoing Battery Health Monitoring and Optimization

New battery management systems are critical to meet the demand for electric vehicles, which is growing at a dizzying rate across the globe. These technologies are crucial for electric vehicles because of the reliability, safety, and longevity they provide. Intelligent optimisation, long-term monitoring, and predictive diagnostics are features that conventional BMSs lack because they operate autonomously within the car. To optimise, monitor, and detect anomalies in battery health in the cloud, this research presents a novel data-driven architecture that combines the characteristics of Smart Battery Management Systems (BMS) with Internet of Things (IoT) technology. By revealing battery performance in real time, this method enhances the design of conventional battery management systems. It accomplishes this by integrating Internet of Things (IoT) connectivity, cloud analytics, real-time data collection, and machine learning models. A high-frequency battery system would send onboard sensor data, including temperature, voltage, current, internal resistance, charge/discharge cycles, and State of Health (SoH), to cloud platforms over secure IoT channels. Advanced cloud analytics can predict RUL, detect damage early, and analyse patterns. Machine learning models excel at charging optimisation, cell performance balancing, and early failure detection. Integrating in-vehicle edge computing with cloud services allows fleet-level long-term evaluations and faster local decisions. Real-time alarms and feedback loops help electric car makers and drivers optimise battery health-related performance metrics.