Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method

Xiaopeng TANG; Ke YAO; Boyang LIU; Furong GAO

doi:10.12783/dteees/iceee2019/31808

Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method

Xiaopeng TANG
, Ke YAO
, Boyang LIU
, Furong GAO

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

Abstract

This paper presents a connection failure detection for a Lithium-ion battery pack when no external vibrations exist. First, the gradient correction method is employed to identify the overall ohmic resistance, which is the summation of the internal and external (contact) resistance. Second, the battery state of health (SOH) is estimated with incremental capacity analysis (ICA) - based method. Third, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is applied to diagnose the connection failure by matching the calculated resistance with the estimated SOH. Finally, a linear projection is applied to reduce the method sensitivity to the testing conditions such as different state of charge (SOC). Experiments show that the proposed method can identify the location of the connection failure well in real time.

Original language	English
Title of host publication	Proceeding of the 3rd Joint International Conference on Energy, Ecology and Environment (ICEEE 2019) and Electrical Intelligent Vehicles (ICEIV 2019)
Publisher	Destech Publications, Inc
Pages	203-206
Number of pages	4
ISBN (Print)	9781605956411
DOIs	https://doi.org/10.12783/dteees/iceee2019/31808
Publication status	Published - 2019
Externally published	Yes
Event	The 3rd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles - Stavanger, Norway Duration: 23 Jul 2019 → 27 Jul 2019

Publication series

Name	DEStech Transactions on Environment, Energy and Earth Sciences
ISSN (Electronic)	2475-8833

Conference

Conference	The 3rd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles
Abbreviated title	ICEEE 2019/ICEIV 2019
Country/Territory	Norway
City	Stavanger
Period	23/07/19 → 27/07/19

Bibliographical note

We would like to thank Kaori Ikegaya for correcting the language problems. This work is supported partly by the National Natural Science Foundation of China (61433005), partly by Guangdong Scientific and Technological Project (2017B010120002), partly by Guangzhou Scientific and Technological Project (201807010089) and partly by Hong Kong Research Grant Council (16207717).

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Lithium-ion batteries
connection failure
DBSCAN
state of health estimation
gradient correction

Access to Document

10.12783/dteees/iceee2019/31808

Cite this

TANG, X., YAO, K., LIU, B., & GAO, F. (2019). Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method. In Proceeding of the 3rd Joint International Conference on Energy, Ecology and Environment (ICEEE 2019) and Electrical Intelligent Vehicles (ICEIV 2019) (pp. 203-206). (DEStech Transactions on Environment, Energy and Earth Sciences). Destech Publications, Inc. https://doi.org/10.12783/dteees/iceee2019/31808

TANG, Xiaopeng ; YAO, Ke ; LIU, Boyang et al. / Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method. Proceeding of the 3rd Joint International Conference on Energy, Ecology and Environment (ICEEE 2019) and Electrical Intelligent Vehicles (ICEIV 2019). Destech Publications, Inc, 2019. pp. 203-206 (DEStech Transactions on Environment, Energy and Earth Sciences).

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title = "Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method",

abstract = "This paper presents a connection failure detection for a Lithium-ion battery pack when no external vibrations exist. First, the gradient correction method is employed to identify the overall ohmic resistance, which is the summation of the internal and external (contact) resistance. Second, the battery state of health (SOH) is estimated with incremental capacity analysis (ICA) - based method. Third, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is applied to diagnose the connection failure by matching the calculated resistance with the estimated SOH. Finally, a linear projection is applied to reduce the method sensitivity to the testing conditions such as different state of charge (SOC). Experiments show that the proposed method can identify the location of the connection failure well in real time.",

keywords = "Lithium-ion batteries, connection failure, DBSCAN, state of health estimation, gradient correction",

author = "Xiaopeng TANG and Ke YAO and Boyang LIU and Furong GAO",

note = "We would like to thank Kaori Ikegaya for correcting the language problems. This work is supported partly by the National Natural Science Foundation of China (61433005), partly by Guangdong Scientific and Technological Project (2017B010120002), partly by Guangzhou Scientific and Technological Project (201807010089) and partly by Hong Kong Research Grant Council (16207717). ; The 3rd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles , ICEEE 2019/ICEIV 2019 ; Conference date: 23-07-2019 Through 27-07-2019",

year = "2019",

doi = "10.12783/dteees/iceee2019/31808",

language = "English",

isbn = "9781605956411",

series = "DEStech Transactions on Environment, Energy and Earth Sciences",

publisher = "Destech Publications, Inc",

pages = "203--206",

booktitle = "Proceeding of the 3rd Joint International Conference on Energy, Ecology and Environment (ICEEE 2019) and Electrical Intelligent Vehicles (ICEIV 2019)",

}

TANG, X, YAO, K, LIU, B & GAO, F 2019, Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method. in Proceeding of the 3rd Joint International Conference on Energy, Ecology and Environment (ICEEE 2019) and Electrical Intelligent Vehicles (ICEIV 2019). DEStech Transactions on Environment, Energy and Earth Sciences, Destech Publications, Inc, pp. 203-206, The 3rd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles , Stavanger, Norway, 23/07/19. https://doi.org/10.12783/dteees/iceee2019/31808

Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method. / TANG, Xiaopeng; YAO, Ke; LIU, Boyang et al.
Proceeding of the 3rd Joint International Conference on Energy, Ecology and Environment (ICEEE 2019) and Electrical Intelligent Vehicles (ICEIV 2019). Destech Publications, Inc, 2019. p. 203-206 (DEStech Transactions on Environment, Energy and Earth Sciences).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

TY - GEN

T1 - Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method

AU - TANG, Xiaopeng

AU - YAO, Ke

AU - LIU, Boyang

AU - GAO, Furong

N1 - We would like to thank Kaori Ikegaya for correcting the language problems. This work is supported partly by the National Natural Science Foundation of China (61433005), partly by Guangdong Scientific and Technological Project (2017B010120002), partly by Guangzhou Scientific and Technological Project (201807010089) and partly by Hong Kong Research Grant Council (16207717).

PY - 2019

Y1 - 2019

N2 - This paper presents a connection failure detection for a Lithium-ion battery pack when no external vibrations exist. First, the gradient correction method is employed to identify the overall ohmic resistance, which is the summation of the internal and external (contact) resistance. Second, the battery state of health (SOH) is estimated with incremental capacity analysis (ICA) - based method. Third, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is applied to diagnose the connection failure by matching the calculated resistance with the estimated SOH. Finally, a linear projection is applied to reduce the method sensitivity to the testing conditions such as different state of charge (SOC). Experiments show that the proposed method can identify the location of the connection failure well in real time.

AB - This paper presents a connection failure detection for a Lithium-ion battery pack when no external vibrations exist. First, the gradient correction method is employed to identify the overall ohmic resistance, which is the summation of the internal and external (contact) resistance. Second, the battery state of health (SOH) is estimated with incremental capacity analysis (ICA) - based method. Third, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is applied to diagnose the connection failure by matching the calculated resistance with the estimated SOH. Finally, a linear projection is applied to reduce the method sensitivity to the testing conditions such as different state of charge (SOC). Experiments show that the proposed method can identify the location of the connection failure well in real time.

KW - Lithium-ion batteries

KW - connection failure

KW - DBSCAN

KW - state of health estimation

KW - gradient correction

U2 - 10.12783/dteees/iceee2019/31808

DO - 10.12783/dteees/iceee2019/31808

M3 - Conference paper (refereed)

SN - 9781605956411

T3 - DEStech Transactions on Environment, Energy and Earth Sciences

SP - 203

EP - 206

BT - Proceeding of the 3rd Joint International Conference on Energy, Ecology and Environment (ICEEE 2019) and Electrical Intelligent Vehicles (ICEIV 2019)

PB - Destech Publications, Inc

T2 - The 3rd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles

Y2 - 23 July 2019 through 27 July 2019

ER -

TANG X, YAO K, LIU B, GAO F. Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method. In Proceeding of the 3rd Joint International Conference on Energy, Ecology and Environment (ICEEE 2019) and Electrical Intelligent Vehicles (ICEIV 2019). Destech Publications, Inc. 2019. p. 203-206. (DEStech Transactions on Environment, Energy and Earth Sciences). doi: 10.12783/dteees/iceee2019/31808

Connection Failure Detection for Lithium-ion Batteries Based on DBSCAN-Projection Method

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

Access to Document

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Cite this