Smart Battery Management Systems for Optimizing Electric Vehicle Performance

1Dr. Narendra Kumar Yegireddy

1Lendi Institute of Engineering and technology


The proliferation of electric vehicles (EVs) has sparked a growing interest in optimizing their performance and extending their driving range while ensuring battery longevity. This research paper delves into the critical role of Smart Battery Management Systems (BMS) in achieving these objectives. Traditional BMS systems are limited in their ability to adapt to real-time conditions, leaving room for performance improvements. Smart BMS, which integrates advanced technologies such as artificial intelligence, machine learning, and the Internet of Things (IoT), has the potential to revolutionize the way we manage EV batteries. By continuously monitoring and controlling critical parameters like voltage, current, temperature, and state of charge (SoC), smart BMS enables precise battery management, thermal control, and state estimation. This, in turn, leads to optimized EV performance, extended battery life, and improved safety. Through a comprehensive review of existing literature, detailed analysis, and empirical evidence, this paper explores the advantages of smart BMS in enhancing EV performance and addresses the challenges and considerations associated with its implementation. It provides insights into practical implications, showcases real-world examples of EVs equipped with smart BMS, and underscores the significance of smart BMS technology in shaping the future of electric mobility. In a rapidly evolving automotive landscape, the findings of this study offer valuable guidance to industry stakeholders, researchers, and policymakers. The paper concludes with a call for further research and the widespread adoption of smart BMS to promote the sustainable development of electric vehicles, ultimately reducing our carbon footprint and advancing the adoption of clean and efficient transportation.


Electric Vehicles (EVs), Battery Management Systems (BMS), Smart BMS, Optimization

Paper Details
IssueIssue 3