AI-Enabled Wireless Predictive Battery Health Monitoring System for Electric Vehicles

The exponential growth of electric vehicles (EVs) necessitates reliable, smart, and cost-effective battery monitoring systems. This paper proposes an innovative AI-enabled, wireless Lithium-ion battery packs used in electric vehicles are managed by a battery management system (BMS). Our design integrates edge computing with machine learning to enable real-time, predictive health monitoring and early fault detection. Wireless sensors gather critical parameters such as temperature, voltage, and gas emissions, transmitting data to a central edge device running lightweight AI models. In the event of possible failure situations such as gas leaking or thermal runaway, proactive actions such as motor shut-off and alert notifications are initiated. The system not only ensures enhanced safety but also provides a scalable and affordable alternative for next-generation EVs.