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Use of ML Techniques for Li-Ion Battery Remaining Useful Life Prediction-A Survey

Publication Type : Conference Paper

Publisher : IEEE

Source : 2023 5th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2023, 2023.

Url : https://ieeexplore.ieee.org/document/10179668

Campus : Bengaluru

School : School of Engineering

Department : Electrical and Electronics

Year : 2023

Abstract : Batteries made of lithium-ion material are crucially important for charge storage in Electric Vehicles. Most of the appliances use these batteries for the storage of energy which can be drawn as per the appliance requirement. It is important to know the reliability of the battery, as these batteries have a vital role in energy storage. As the number of cycles of usage of the battery increases there is always a change in the capacity of the battery even at 100 percentage State of Charge, once this capacity crosses the threshold of failure then it results in a dry cell and the cell does not hold the capacity to retain the charge. Therefore, Remaining Useful Life (RUL) becomes an important concept in Battery Management System [BMS] for industrial as well as academic research. The suitable method for RUL prediction along with the implementation of ML techniques are covered in this paper.

Cite this Research Publication : A. Tiwari, C. R. A. Varshini, A. Jha, K. R. Annamalai, K. Deepa and V. Sailaja, "Use of ML Techniques for Li-Ion Battery Remaining Useful Life Prediction-A Survey," 2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT), Erode, India, 2023, pp. 1-6, doi: 10.1109/ICECCT56650.2023.10179668.

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