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Lithium-Ion Battery Screening by K-Means with DBSCAN for Denoising

Yudong Wang1, 2, Jie Tan1, *, Zhenjie Liu1, Allah Ditta3

1 Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
2 School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China.
3 University of Education, Township, College Rd Lahore Punjab, Lahore, 54770, Pakistan.

* Corresponding Author: Jie Tan. Email: email.

Computers, Materials & Continua 2020, 65(3), 2111-2122. https://doi.org/10.32604/cmc.2020.011098

Abstract

Batteries are often packed together to meet voltage and capability needs. However, due to variations in raw materials, different ages of equipment, and manual operation, there is inconsistency between batteries, which leads to reduced available capacity, variability of resistance, and premature failure. Therefore, it is crucial to pack similar batteries together. The conventional approach to screening batteries is based on their capacity, voltage and internal resistance, which disregards how batteries perform during manufacturing. In the battery discharge process, real time discharge voltage curves (DVCs) are collected as a set of unlabeled time series, which reflect how the battery voltage changes. However, few studies have focused on DVC based battery screening. In this paper, we provide an effective approach for battery screening. First, we apply interpolation on DVCs and give a method to transform them into slope sequences. Then, we use density-based spatial clustering of applications with noise (DBSCAN) for denoising and treat the remaining data as input to the K-means algorithm for screening. Finally, we provide the experimental results and give our evaluation. It is proved that our method is effective.

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APA Style
Wang, Y., Tan, J., Liu, Z., Ditta, A. (2020). Lithium-ion battery screening by k-means with DBSCAN for denoising. Computers, Materials & Continua, 65(3), 2111-2122. https://doi.org/10.32604/cmc.2020.011098
Vancouver Style
Wang Y, Tan J, Liu Z, Ditta A. Lithium-ion battery screening by k-means with DBSCAN for denoising. Comput Mater Contin. 2020;65(3):2111-2122 https://doi.org/10.32604/cmc.2020.011098
IEEE Style
Y. Wang, J. Tan, Z. Liu, and A. Ditta "Lithium-Ion Battery Screening by K-Means with DBSCAN for Denoising," Comput. Mater. Contin., vol. 65, no. 3, pp. 2111-2122. 2020. https://doi.org/10.32604/cmc.2020.011098



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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