Online Diagnosis for the Capacity Fade Fault of a Parallel-Connected Lithium Ion Battery Group

Hua Zhang, Lei Pei, Jinlei Sun, Kai Song, Rengui Lu, Yongping Zhao, Chunbo Zhu and Tiansi Wang
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Hua Zhang: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Lei Pei: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Jinlei Sun: 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
Rengui Lu: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Yongping Zhao: 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
Tiansi Wang: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China

Energies, 2016, vol. 9, issue 5, 1-18

Abstract: In a parallel-connected battery group (PCBG), capacity degradation is usually caused by the inconsistency between a faulty cell and other normal cells, and the inconsistency occurs due to two potential causes: an aging inconsistency fault or a loose contacting fault. In this paper, a novel method is proposed to perform online and real-time capacity fault diagnosis for PCBGs. Firstly, based on the analysis of parameter variation characteristics of a PCBG with different fault causes, it is found that PCBG resistance can be taken as an indicator for both seeking the faulty PCBG and distinguishing the fault causes. On one hand, the faulty PCBG can be identified by comparing the PCBG resistance among PCBGs; on the other hand, two fault causes can be distinguished by comparing the variance of the PCBG resistances. Furthermore, for online applications, a novel recursive-least-squares algorithm with restricted memory and constraint (RLSRMC), in which the constraint is added to eliminate the “imaginary number” phenomena of parameters, is developed and used in PCBG resistance identification. Lastly, fault simulation and validation results demonstrate that the proposed methods have good accuracy and reliability.

Keywords: parallel-connected battery group; capacity fade; online fault diagnosis; recursive least squares algorithm with restricted memory and constraint; fault simulation (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: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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