REAL-TIME MULTI-SENSOR FUSION FRAMEWORK FOR EARLY FAULT DETECTION IN ELECTRIC VEHICLE LITHIUM-ION BATTERIES

Abstract: The power storage component that mainly powers electric vehicles (EVs) is lithium batteries due to their high performance, comparative durability, and excellent operational efficiency. However, there are chances of battery failures such as over temperature, over voltage, internal short circuit, gas leakage, and swelling, which can cause serious battery failures. Generally, Battery Management Systems (BMS) methods often use fewer sensing parameters, thus limiting the detection capabilities of battery faults. In this article, a real-time multi sensor fusion system will be proposed as an early warning system of lithium battery faults in electric vehicles. The multi sensor fault detection will be implemented using a rule-based algorithm, integrating voltage sensors, current sensors, temperature sensors, gas sensors, pressure sensors, and strain sensors. The developed system will be verified using Proteus IS software.

Keywords: Lithium-Ion Battery, Multi-Sensor Fusion, Thermal Runaway, Real-Time Monitoring.