A Novel Grouping Method for Lithium Iron Phosphate Batteries Based on a Fractional Joint Kalman Filter and a New Modified K-Means Clustering Algorithm

Xiaoyu Li, Kai Song, Guo Wei, Rengui Lu and Chunbo Zhu
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Xiaoyu Li: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Kai Song: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Guo Wei: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Rengui Lu: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Chunbo Zhu: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China

Energies, 2015, vol. 8, issue 8, 1-26

Abstract: This paper presents a novel grouping method for lithium iron phosphate batteries. In this method, a simplified electrochemical impedance spectroscopy (EIS) model is utilized to describe the battery characteristics. Dynamic stress test (DST) and fractional joint Kalman filter (FJKF) are used to extract battery model parameters. In order to realize equal-number grouping of batteries, a new modified K-means clustering algorithm is proposed. Two rules are designed to equalize the numbers of elements in each group and exchange samples among groups. In this paper, the principles of battery model selection, physical meaning and identification method of model parameters, data preprocessing and equal-number clustering method for battery grouping are comprehensively described. Additionally, experiments for battery grouping and method validation are designed. This method is meaningful to application involving the grouping of fresh batteries for electric vehicles (EVs) and screening of aged batteries for recycling.

Keywords: battery grouping; fractional joint Kalman filter; equal-number; modified K-means 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: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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