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

Bizhong Xia, Yadi Yang, Jie Zhou, Guanghao Chen, Yifan Liu, Huawen Wang, Mingwang Wang and Yongzhi Lai
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Bizhong Xia: Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
Yadi Yang: Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
Jie Zhou: Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
Guanghao Chen: Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
Yifan Liu: Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
Huawen Wang: Sunwoda Electronic Co. Ltd., Shenzhen 518108, China
Mingwang Wang: Sunwoda Electronic Co. Ltd., Shenzhen 518108, China
Yongzhi Lai: Sunwoda Electronic Co. Ltd., Shenzhen 518108, China

Energies, 2019, vol. 12, issue 15, 1-17

Abstract: 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.

Keywords: lithium-ion battery; cell sorting; multi-parameters sorting; principal component analysis; self-organizing maps clustering (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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