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Energies 2017, 10(7), 1035; https://doi.org/10.3390/en10071035

A Robust Battery Grouping Method Based on a Characteristic Distribution Model

1
Department of Electronics and Information, Hangzhou Dianzi University, 2nd Street, Xiasha Higher Education Zone, Hangzhou 310018, China
2
Departmant of Electric and Computer Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA
*
Author to whom correspondence should be addressed.
Received: 17 May 2017 / Revised: 10 July 2017 / Accepted: 12 July 2017 / Published: 19 July 2017
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Abstract

The inconsistent characteristics of individual power batteries in a battery pack can seriously affect the performance and service life of the whole pack. Battery grouping is an effective approach for dealing with the inconsistency problem by grouping batteries with similar characteristics in the same battery pack. In actual production, the battery grouping process still relies on the traditional manual method, which results in high labor and time costs. In this paper, a robust and effective battery grouping method based on the characteristic distribution model is developed. Specifically, a novel characteristic distribution model is proposed to determine the grouping priority of different batteries. Then, an improved k-nearest-neighbor algorithm is used to decide which batteries should be group into the same battery pack. Experimental results demonstrate the effectiveness of the proposed method. View Full-Text
Keywords: battery grouping; battery pack; discharging characteristic curve; characteristic distribution model battery grouping; battery pack; discharging characteristic curve; characteristic distribution model
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Yang, Y.; Gao, M.; He, Z.; Wang, C. A Robust Battery Grouping Method Based on a Characteristic Distribution Model. Energies 2017, 10, 1035.

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