• Mohanish Gaygaye
• Pravin Kale
• Rohit Bodade
• Dnyaraj Patil
• Prof. (Dr.). Sachin Borse

Digital twin technology is a powerful tool for predictive and preventive analysis of battery systems. It involves creating a virtual model to simulate the behavior and performance of the actual system in real-time, enabling proactive maintenance and preventing costly downtime. It has the potential to revolutionize the way we design, operate, and maintain battery systems, leading to improvements in efficiency, sustainability, and reliability

Digital Twin, Battery Health, Machine Learning, SoH, Deep Learning, RUL Estimation.

"Digital Twin Technology for Predictive and Preventive Analysis of Battery Systems.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.j205-j209, May-2023, Available :http://www.jetir.org/papers/JETIR2305978.pdf

"Digital Twin Technology for Predictive and Preventive Analysis of Battery Systems.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppj205-j209, May-2023, Available at : http://www.jetir.org/papers/JETIR2305978.pdf