Health diagnosis and recuperation of aged Li-ion batteries with data analytics and equivalent circuit modeling

التفاصيل البيبلوغرافية
العنوان: Health diagnosis and recuperation of aged Li-ion batteries with data analytics and equivalent circuit modeling
المؤلفون: Made, Riko I, Lin, Jing, Zhang, Jintao, Zhang, Yu, Moh, Lionel C. H., Liu, Zhaolin, Ding, Ning, Chiam, Sing Yang, Khoo, Edwin, Yin, Xuesong, Zheng, Guangyuan Wesley
المصدر: iScience (2024)
سنة النشر: 2023
المجموعة: Computer Science
Condensed Matter
Physics (Other)
مصطلحات موضوعية: Electrical Engineering and Systems Science - Signal Processing, Condensed Matter - Materials Science, Computer Science - Machine Learning, Physics - Applied Physics
الوصف: Battery health assessment and recuperation play a crucial role in the utilization of second-life Li-ion batteries. However, due to ambiguous aging mechanisms and lack of correlations between the recovery effects and operational states, it is challenging to accurately estimate battery health and devise a clear strategy for cell rejuvenation. This paper presents aging and reconditioning experiments of 62 commercial high-energy type lithium iron phosphate (LFP) cells, which supplement existing datasets of high-power LFP cells. The relatively large-scale data allow us to use machine learning models to predict cycle life and identify important indicators of recoverable capacity. Considering cell-to-cell inconsistencies, an average test error of $16.84\% \pm 1.87\%$ (mean absolute percentage error) for cycle life prediction is achieved by gradient boosting regressor given information from the first 80 cycles. In addition, it is found that some of the recoverable lost capacity is attributed to the lateral lithium non-uniformity within the electrodes. An equivalent circuit model is built and experimentally validated to demonstrate how such non-uniformity can be accumulated, and how it can give rise to recoverable capacity loss. SHapley Additive exPlanations (SHAP) analysis also reveals that battery operation history significantly affects the capacity recovery.
Comment: 20 pages, 5 figures, 1 table
نوع الوثيقة: Working Paper
DOI: 10.1016/j.isci.2024.109416
URL الوصول: http://arxiv.org/abs/2310.03750
رقم الأكسشن: edsarx.2310.03750
قاعدة البيانات: arXiv
الوصف
DOI:10.1016/j.isci.2024.109416