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For the achievement of progress in sustainable transport solutions, it is extremely crucial to upgrade the efficiency and increase the lifespan of the electric vehicle battery. The work focuses on the role of Artificial Intelligence (AI) methodologies within Battery Management Systems (BMS) to handle or reduce problems like state estimation, cell balancing, and faults. On the contrary, surveillance and adaptive management methods in conventional BMS methodologies are not efficient with superior accuracy compared to AI frameworks. It discusses current challenges being faced by BMS, motivation for choosing AI-driven approach, reviews related literature, and then new solutions are presented by applications of AI techniques such as neural networks, genetic algorithms, and reinforcement learning to enhance the lifespan of batteries in order to appropriately optimize energy usage, thereby improving general performance of Electric Vehicles (EVs) in its entirety.

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Survey Paper on Enhancing Electric Vehicle Battery Management Systems Using Artificial Intelligence

  • 会议论文

  • 发表日期：

    2026年

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  • Shailesh Galande,
  • Gargi Barve,
  • Sneha Bhavsar,
  • Eliza Alvi

摘要

For the achievement of progress in sustainable transport solutions, it is extremely crucial to upgrade the efficiency and increase the lifespan of the electric vehicle battery. The work focuses on the role of Artificial Intelligence (AI) methodologies within Battery Management Systems (BMS) to handle or reduce problems like state estimation, cell balancing, and faults. On the contrary, surveillance and adaptive management methods in conventional BMS methodologies are not efficient with superior accuracy compared to AI frameworks. It discusses current challenges being faced by BMS, motivation for choosing AI-driven approach, reviews related literature, and then new solutions are presented by applications of AI techniques such as neural networks, genetic algorithms, and reinforcement learning to enhance the lifespan of batteries in order to appropriately optimize energy usage, thereby improving general performance of Electric Vehicles (EVs) in its entirety.