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Energies 2015, 8(8), 7703-7728; doi:10.3390/en8087703

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

School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
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Academic Editor: Paul Stewart
Received: 27 May 2015 / Revised: 1 July 2015 / Accepted: 22 July 2015 / Published: 28 July 2015
(This article belongs to the Special Issue Electrical Power and Energy Systems for Transportation Applications)
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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. View Full-Text
Keywords: battery grouping; fractional joint Kalman filter; equal-number; modified K-means clustering battery grouping; fractional joint Kalman filter; equal-number; modified K-means clustering
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Li, X.; Song, K.; Wei, G.; Lu, R.; Zhu, C. A Novel Grouping Method for Lithium Iron Phosphate Batteries Based on a Fractional Joint Kalman Filter and a New Modified K-Means Clustering Algorithm. Energies 2015, 8, 7703-7728.

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