The performance and the driving distance of electric vehicles (EVs) mainly depend on the efficient charging and discharging capabilities of the battery packs. The rise in battery temperature influences the battery performance degradation which affects the performance of the battery-driven vehicles. The battery’s internal temperature causes a decline in resistance, which generates a considerable amount of heat in the battery which results in a fire accident. Hence a reliable, safe, and efficient management system is required to monitor and control the battery pack parameters. This research presents the design and development of an advanced battery management system (ABMS) leveraging artificial intelligence (AI) which mainly concentrates on enhanced charging monitoring and fire protection to the battery pack in EV. The developed ABMS integrates with efficient sensing technologies and AI-based computational algorithms to provide a real-time battery pack module with cell balancing mechanisms to monitor the charging process which ensures the optimal charging conditions and in turn, maximizes the battery lifespan in EVs. In the current research work, within the hardware model, a fire protection system is implemented by utilizing AI to detect early signs of thermal runaway which ensures fire safety in BMS. The experimental validation is done on the proposed ABMS through comprehensive testing in the simulation model and real-time operating conditions. The results demonstrate that enhancing charging efficiency, prolonging battery life, and ensuring robust fire protection capabilities.