A New Fault Diagnosis and Prognosis Technology for High-Power Lithium-Ion Battery

Chao Wu; Chunbo Zhu; Yunwang Ge

doi:10.1109/TPS.2017.2706088

A New Fault Diagnosis and Prognosis Technology for High-Power Lithium-Ion Battery

Chao Wu^*
, Chunbo Zhu
, Yunwang Ge

^*Corresponding author for this work

Luoyang Institute of Science and Technology
School of Electrical Engineering and Automation, Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

78 Scopus citations

Abstract

A fault diagnostic approach for lithium-ion battery is proposed in this paper, which is suitable for high-power applications such as hybrid electrical vehicle and electromagnetic launch. A serial of abusive experiments including overcharge, over-discharge, and low-temperature operation, which commonly occur during high-power applications, are arranged in order to extract corresponding features. Fault feature vector in the form of electrical parameter variation and incremental capacity analysis curve variation is obtained through reference test. The results from the tests are synthesized to establish the diagnosis system based on fuzzy logic, which provides a detailed description for the fault symptoms and connects them with internal fault mechanisms.

Original language	English
Article number	7936558
Pages (from-to)	1533-1538
Number of pages	6
Journal	IEEE Transactions on Plasma Science
Volume	45
Issue number	7
DOIs	https://doi.org/10.1109/TPS.2017.2706088
State	Published - Jul 2017
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Fault diagnosis and prognosis
fuzzy logic
incremental capacity analysis (ICA)
lithium-ion battery

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10.1109/TPS.2017.2706088

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title = "A New Fault Diagnosis and Prognosis Technology for High-Power Lithium-Ion Battery",

abstract = "A fault diagnostic approach for lithium-ion battery is proposed in this paper, which is suitable for high-power applications such as hybrid electrical vehicle and electromagnetic launch. A serial of abusive experiments including overcharge, over-discharge, and low-temperature operation, which commonly occur during high-power applications, are arranged in order to extract corresponding features. Fault feature vector in the form of electrical parameter variation and incremental capacity analysis curve variation is obtained through reference test. The results from the tests are synthesized to establish the diagnosis system based on fuzzy logic, which provides a detailed description for the fault symptoms and connects them with internal fault mechanisms.",

keywords = "Fault diagnosis and prognosis, fuzzy logic, incremental capacity analysis (ICA), lithium-ion battery",

author = "Chao Wu and Chunbo Zhu and Yunwang Ge",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.",

year = "2017",

month = jul,

doi = "10.1109/TPS.2017.2706088",

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volume = "45",

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AU - Wu, Chao

AU - Zhu, Chunbo

AU - Ge, Yunwang

PY - 2017/7

Y1 - 2017/7

N2 - A fault diagnostic approach for lithium-ion battery is proposed in this paper, which is suitable for high-power applications such as hybrid electrical vehicle and electromagnetic launch. A serial of abusive experiments including overcharge, over-discharge, and low-temperature operation, which commonly occur during high-power applications, are arranged in order to extract corresponding features. Fault feature vector in the form of electrical parameter variation and incremental capacity analysis curve variation is obtained through reference test. The results from the tests are synthesized to establish the diagnosis system based on fuzzy logic, which provides a detailed description for the fault symptoms and connects them with internal fault mechanisms.

AB - A fault diagnostic approach for lithium-ion battery is proposed in this paper, which is suitable for high-power applications such as hybrid electrical vehicle and electromagnetic launch. A serial of abusive experiments including overcharge, over-discharge, and low-temperature operation, which commonly occur during high-power applications, are arranged in order to extract corresponding features. Fault feature vector in the form of electrical parameter variation and incremental capacity analysis curve variation is obtained through reference test. The results from the tests are synthesized to establish the diagnosis system based on fuzzy logic, which provides a detailed description for the fault symptoms and connects them with internal fault mechanisms.

KW - Fault diagnosis and prognosis

KW - fuzzy logic

KW - incremental capacity analysis (ICA)

KW - lithium-ion battery

UR - https://www.scopus.com/pages/publications/85029047992

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DO - 10.1109/TPS.2017.2706088

M3 - 文章

AN - SCOPUS:85029047992

SN - 0093-3813

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JO - IEEE Transactions on Plasma Science

JF - IEEE Transactions on Plasma Science

IS - 7

M1 - 7936558

ER -

A New Fault Diagnosis and Prognosis Technology for High-Power Lithium-Ion Battery

Abstract

UN SDGs

Keywords

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