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Open AccessArticle

Using Self Organizing Maps to Achieve Lithium-Ion Battery Cells Multi-Parameter Sorting Based on Principle Components Analysis

1
Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
2
Sunwoda Electronic Co. Ltd., Shenzhen 518108, China
*
Author to whom correspondence should be addressed.
Energies 2019, 12(15), 2980; https://doi.org/10.3390/en12152980
Received: 28 June 2019 / Revised: 26 July 2019 / Accepted: 29 July 2019 / Published: 1 August 2019
(This article belongs to the Special Issue Energy Storage and Management for Electric Vehicles)
Battery sorting is an important process in the production of lithium battery module and battery pack for electric vehicles (EVs). Accurate battery sorting can ensure good consistency of batteries for grouping. This study investigates the mechanism of inconsistency of battery packs and process of battery sorting on the lithium-ion battery module production line. Combined with the static and dynamic characteristics of lithium-ion batteries, the battery parameters on the production line that can be used as a sorting basis are analyzed, and the parameters of battery mass, volume, resistance, voltage, charge/discharge capacity and impedance characteristics are measured. The data of batteries are processed by the principal component analysis (PCA) method in statistics, and after analysis, the parameters of batteries are obtained. Principal components are used as sorting variables, and the self-organizing map (SOM) neural network is carried out to cluster the batteries. Group experiments are carried out on the separated batteries, and state of charge (SOC) consistency of the batteries is achieved to verify that the sorting algorithm and sorting result is accurate. View Full-Text
Keywords: lithium-ion battery; cell sorting; multi-parameters sorting; principal component analysis; self-organizing maps clustering lithium-ion battery; cell sorting; multi-parameters sorting; principal component analysis; self-organizing maps clustering
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MDPI and ACS Style

Xia, B.; Yang, Y.; Zhou, J.; Chen, G.; Liu, Y.; Wang, H.; Wang, M.; Lai, Y. Using Self Organizing Maps to Achieve Lithium-Ion Battery Cells Multi-Parameter Sorting Based on Principle Components Analysis. Energies 2019, 12, 2980. https://doi.org/10.3390/en12152980

AMA Style

Xia B, Yang Y, Zhou J, Chen G, Liu Y, Wang H, Wang M, Lai Y. Using Self Organizing Maps to Achieve Lithium-Ion Battery Cells Multi-Parameter Sorting Based on Principle Components Analysis. Energies. 2019; 12(15):2980. https://doi.org/10.3390/en12152980

Chicago/Turabian Style

Xia, Bizhong; Yang, Yadi; Zhou, Jie; Chen, Guanghao; Liu, Yifan; Wang, Huawen; Wang, Mingwang; Lai, Yongzhi. 2019. "Using Self Organizing Maps to Achieve Lithium-Ion Battery Cells Multi-Parameter Sorting Based on Principle Components Analysis" Energies 12, no. 15: 2980. https://doi.org/10.3390/en12152980

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