Electric Vehicles Battery And Check-Up Using Machine Learning

Author(s)	Mr. Ashok Y, Kaushik N, Kavitha Selvamani, Sanjai R
Country	India
Abstract	Electric vehicles (EVs) rely on high-performance batteries, making their health and efficiency critical for optimal operation. This paper presents an intelligent EV battery scanner and check-up system using machine learning to assess battery condition, detect faults, and predict potential failures. The system utilizes sensor data from the battery, including voltage, temperature, current, and charge cycles, which are analyzed through machine learning models. By leveraging classification and predictive algorithms, the system can identify battery degradation patterns, optimize charging strategies, and enhance overall battery lifespan. This approach ensures improved reliability, cost savings, and safety for EV users. The proposed model aims to revolutionize battery diagnostics, reducing maintenance efforts and promoting sustainable EV adoption.
Keywords	Electric Vehicles (EVs) , Battery Health Monitoring , Machine Learning , Battery Diagnostics , Predictive Maintenance, Battery Degradation Analysis, State of Health (SOH) Prediction
Field	Engineering
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-03-27
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.39625
Short DOI	https://doi.org/g8935t

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