Recent Advances and Future Prospects in Digital Twin Technology for Battery Management Systems of Electric Vehicles

Year : 2025 | Volume : 12 | Issue : 02 | Page : –
    By

    Amol Shinde,

  • Bhushan Chavan,

  • Manish Pokharna,

  • Sameer Nanivadekar,

  1. Assistant Professor, Department of Mechanical Engineering, A.P. Shah Institute of Technology, Thane, Maharashtra, India
  2. Research Scholar, Department of Mechanical Engineering, Pacific Academy of Higher Education and Research University, Udaipur, Rajasthan, India
  3. Professor, Department of Mechanical Engineering, Pacific Academy of Higher Education and Research University, Udaipur, Rajasthan, India
  4. Associate Professor, Department of Information Technology, A.P. Shah Institute of Technology, Thane, Maharashtra, India

Abstract

Digital twin technology in battery management systems (BMS) for electric cars (EVs) represents a major development in the automotive industry. Digital twins provide predictive maintenance, modelling, and real-time monitoring by creating virtual copies of real-time monitoring, actual battery systems. This paper describes the functional components, architecture, and design of Digital Twin technology along with how it may be included into BMS. Emphasizing how consistent data flow from sensors improves battery safety and performance, it looks at the benefits of merging and gathering data in real time. The paper emphasizes the use of modern machine learning techniques for predictive maintenance, which may identify any issues early on and resolve them to extend battery life and save money. The report also addresses the prerequisites
for high computational needs, robust data integration systems, and data security concerns. By means of case studies and practical results, the paper demonstrates how well Digital Twin technology addresses heat control, battery management, and guarantees of effective energy consumption. The results show that digital twin technology has great power to revolutionize EV BMS and inspire innovation in the electric car sector by means of efficiency. This study reviews existing research status as well as future perspectives for the integration of Digital Twin in BMS for EVs.

Keywords: Digital twin, battery management system, electric vehicles, predictive maintenance, data acquisition

[This article belongs to Journal of Automobile Engineering and Applications ]

How to cite this article:
Amol Shinde, Bhushan Chavan, Manish Pokharna, Sameer Nanivadekar. Recent Advances and Future Prospects in Digital Twin Technology for Battery Management Systems of Electric Vehicles. Journal of Automobile Engineering and Applications. 2025; 12(02):-.
How to cite this URL:
Amol Shinde, Bhushan Chavan, Manish Pokharna, Sameer Nanivadekar. Recent Advances and Future Prospects in Digital Twin Technology for Battery Management Systems of Electric Vehicles. Journal of Automobile Engineering and Applications. 2025; 12(02):-. Available from: https://journals.stmjournals.com/joaea/article=2025/view=215717


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Regular Issue Subscription Review Article
Volume 12
Issue 02
Received 28/05/2025
Accepted 18/06/2025
Published 30/06/2025
Publication Time 33 Days
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