Intelligent modeling for thermal management of cylindrical lithium ion batteries

Zhen Liu; Han-Xiong Li

doi:10.1109/iFuzzy.2013.6825440

Intelligent modeling for thermal management of cylindrical lithium ion batteries

Zhen Liu
, Han-Xiong Li

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

2 Citations (Scopus)

Abstract

Effective thermal management is crucial to the optimal operation of lithium ion batteries and its health management. Since only the surface temperature of battery can be measured, an accurate mathematical model describing the thermal process is needed to estimate the temperature distribution of batteries. Furthermore, the thermal behaviors of batteries are governed by complex chemical process whose parameters will degrade over time and different environment. Advanced identification algorithms should be developed for the model to be able to be updated in real time application. In this paper, a neural network based model is developed for thermal management of cylindrical lithium ion batteries. The relative identification algorithms are introduced. The developed model is simple enough for online thermal management, and numerical simulations demonstrate the effectiveness of the proposed model. © 2013 IEEE.

Original language	English
Title of host publication	iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications
Publisher	IEEE Computer Society
Pages	224-229
ISBN (Print)	9781479903863
DOIs	https://doi.org/10.1109/iFuzzy.2013.6825440
Publication status	Published - 2013
Event	iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications - Taipei, Taiwan, China Duration: 6 Dec 2013 → 8 Dec 2013

Conference

Conference	iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications
Place	Taiwan, China
City	Taipei
Period	6/12/13 → 8/12/13

UN SDGs

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

SDG 7 Affordable and Clean Energy

Research Keywords

distributed parameter system
intelligent modeling
lithium ion battery
thermal management

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10.1109/iFuzzy.2013.6825440

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title = "Intelligent modeling for thermal management of cylindrical lithium ion batteries",

abstract = "Effective thermal management is crucial to the optimal operation of lithium ion batteries and its health management. Since only the surface temperature of battery can be measured, an accurate mathematical model describing the thermal process is needed to estimate the temperature distribution of batteries. Furthermore, the thermal behaviors of batteries are governed by complex chemical process whose parameters will degrade over time and different environment. Advanced identification algorithms should be developed for the model to be able to be updated in real time application. In this paper, a neural network based model is developed for thermal management of cylindrical lithium ion batteries. The relative identification algorithms are introduced. The developed model is simple enough for online thermal management, and numerical simulations demonstrate the effectiveness of the proposed model. {\textcopyright} 2013 IEEE.",

keywords = "distributed parameter system, intelligent modeling, lithium ion battery, thermal management",

author = "Zhen Liu and Han-Xiong Li",

year = "2013",

doi = "10.1109/iFuzzy.2013.6825440",

language = "English",

isbn = "9781479903863",

pages = "224--229",

booktitle = "iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications",

publisher = "IEEE Computer Society",

address = "United States",

note = "iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications ; Conference date: 06-12-2013 Through 08-12-2013",

}

Liu, Z & Li, H-X 2013, Intelligent modeling for thermal management of cylindrical lithium ion batteries. in iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications., 6825440, IEEE Computer Society, pp. 224-229, iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications, Taipei, Taiwan, China, 6/12/13. https://doi.org/10.1109/iFuzzy.2013.6825440

Intelligent modeling for thermal management of cylindrical lithium ion batteries. / Liu, Zhen; Li, Han-Xiong.
iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications. IEEE Computer Society, 2013. p. 224-229 6825440.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Intelligent modeling for thermal management of cylindrical lithium ion batteries

AU - Liu, Zhen

AU - Li, Han-Xiong

PY - 2013

Y1 - 2013

N2 - Effective thermal management is crucial to the optimal operation of lithium ion batteries and its health management. Since only the surface temperature of battery can be measured, an accurate mathematical model describing the thermal process is needed to estimate the temperature distribution of batteries. Furthermore, the thermal behaviors of batteries are governed by complex chemical process whose parameters will degrade over time and different environment. Advanced identification algorithms should be developed for the model to be able to be updated in real time application. In this paper, a neural network based model is developed for thermal management of cylindrical lithium ion batteries. The relative identification algorithms are introduced. The developed model is simple enough for online thermal management, and numerical simulations demonstrate the effectiveness of the proposed model. © 2013 IEEE.

AB - Effective thermal management is crucial to the optimal operation of lithium ion batteries and its health management. Since only the surface temperature of battery can be measured, an accurate mathematical model describing the thermal process is needed to estimate the temperature distribution of batteries. Furthermore, the thermal behaviors of batteries are governed by complex chemical process whose parameters will degrade over time and different environment. Advanced identification algorithms should be developed for the model to be able to be updated in real time application. In this paper, a neural network based model is developed for thermal management of cylindrical lithium ion batteries. The relative identification algorithms are introduced. The developed model is simple enough for online thermal management, and numerical simulations demonstrate the effectiveness of the proposed model. © 2013 IEEE.

KW - distributed parameter system

KW - intelligent modeling

KW - lithium ion battery

KW - thermal management

UR - https://www.scopus.com/pages/publications/84903587273

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84903587273&origin=recordpage

U2 - 10.1109/iFuzzy.2013.6825440

DO - 10.1109/iFuzzy.2013.6825440

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781479903863

SP - 224

EP - 229

BT - iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications

PB - IEEE Computer Society

T2 - iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications

Y2 - 6 December 2013 through 8 December 2013

ER -

Intelligent modeling for thermal management of cylindrical lithium ion batteries

Abstract

Conference

UN SDGs

Research Keywords

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