LAPSE:2019.0063
Published Article
LAPSE:2019.0063
Battery Grouping with Time Series Clustering Based on Affinity Propagation
January 7, 2019
Battery grouping is a technology widely used to improve the performance of battery packs. In this paper, we propose a time series clustering based battery grouping method. The proposed method utilizes the whole battery charge/discharge sequence for battery grouping. The time sequences are first denoised with a wavelet denoising technique. The similarity matrix is then computed with the dynamic time warping distance, and finally the time series are clustered with the affinity propagation algorithm according to the calculated similarity matrices. The silhouette index is utilized for assessing the performance of the proposed battery grouping method. Test results show that the proposed battery grouping method is effective.
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Keywords
affinity propagation, battery grouping, time series clustering, wavelet denoising
Subject
Suggested Citation
He Z, Gao M, Ma G, Liu Y, Tang L. Battery Grouping with Time Series Clustering Based on Affinity Propagation. (2019). LAPSE:2019.0063
Author Affiliations
He Z: Department of Electronic & Information, Hangzhou Dianzi University, 2nd Street, Xiasha Higher Education Zone, Hangzhou 310018, China [ORCID]
Gao M: Department of Electronic & Information, Hangzhou Dianzi University, 2nd Street, Xiasha Higher Education Zone, Hangzhou 310018, China
Ma G: Department of Electronic & Information, Hangzhou Dianzi University, 2nd Street, Xiasha Higher Education Zone, Hangzhou 310018, China
Liu Y: Department of Electronic & Information, Hangzhou Dianzi University, 2nd Street, Xiasha Higher Education Zone, Hangzhou 310018, China
Tang L: Department of Electronic & Information, Hangzhou Dianzi University, 2nd Street, Xiasha Higher Education Zone, Hangzhou 310018, China
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Gao M: Department of Electronic & Information, Hangzhou Dianzi University, 2nd Street, Xiasha Higher Education Zone, Hangzhou 310018, China
Ma G: Department of Electronic & Information, Hangzhou Dianzi University, 2nd Street, Xiasha Higher Education Zone, Hangzhou 310018, China
Liu Y: Department of Electronic & Information, Hangzhou Dianzi University, 2nd Street, Xiasha Higher Education Zone, Hangzhou 310018, China
Tang L: Department of Electronic & Information, Hangzhou Dianzi University, 2nd Street, Xiasha Higher Education Zone, Hangzhou 310018, China
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Journal Name
Energies
Volume
9
Issue
7
Article Number
E561
Year
2016
Publication Date
2016-07-19
Published Version
ISSN
1996-1073
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Original Submission
Other Meta
PII: en9070561, Publication Type: Journal Article
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Published Article
LAPSE:2019.0063
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External Link
doi:10.3390/en9070561
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Version History
[v1] (Original Submission)
Jan 7, 2019
Verified by curator on
Jan 7, 2019
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v1
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URL Here
https://psecommunity.org/LAPSE:2019.0063
Original Submitter
Calvin Tsay
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