Towards a hybrid approach to SoC estimation for a smart Battery Management System (BMS) and battery supported Cyber-Physical Systems (CPS)

K. L. Man; T. O. Ting; T. Krilavičius; Kaiyu Wan; C. Chen; J. Chang; S. H. Poon

doi:10.1109/BCFIC.2012.6217989

Towards a hybrid approach to SoC estimation for a smart Battery Management System (BMS) and battery supported Cyber-Physical Systems (CPS)

K. L. Man, T. O. Ting, T. Krilavičius, Kaiyu Wan, C. Chen, J. Chang, S. H. Poon

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

19 Citations (Scopus)

Abstract

One of the most important and indispensable parameters of a Battery Management System (BMS) is to accurately estimate the State of Charge (SoC) of battery. Precise estimation of SoC can prevent battery from damage or premature aging by avoiding over charge or discharge. Due to the limited capacity of a battery, advanced methods must be used to estimate precisely the SoC in order to keep battery safely being charged and discharged at a suitable level and to prolong its life cycle. We review several existing effective approaches such as Coulomb counting, Open Circuit Voltage (OCV) and Kalman Filter method for performing the SoC estimation. Then we investigate both Artificial Intelligence (AI) approach and Formal Methods (FM) approach that can be efficiently used to precisely determine the SoC estimation for the smart battery management system as presented in [1]. By using presented approach, a more accurate SoC measurement can be obtained for the smart battery management system and battery supported Cyber-Physical Systems (CPS).

Original language	English
Title of host publication	2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012
Pages	113-116
Number of pages	4
DOIs	https://doi.org/10.1109/BCFIC.2012.6217989
Publication status	Published - 2012
Externally published	Yes
Event	2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012 - Vilnius, Lithuania Duration: 25 Apr 2012 → 27 Apr 2012

Publication series

Name	2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012

Conference

Conference	2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012
Country/Territory	Lithuania
City	Vilnius
Period	25/04/12 → 27/04/12

Keywords

Artificial Intelligence (AI)
Battery Management Systems (BMS)
Cyber-Physical Systems (CPS)
Formal Methods (FM)
State of Charge (SoC)

ASJC Scopus subject areas

Computer Science Applications

Access to Document

10.1109/BCFIC.2012.6217989

Cite this

Man, K. L., Ting, T. O., Krilavičius, T., Wan, K., Chen, C., Chang, J., & Poon, S. H. (2012). Towards a hybrid approach to SoC estimation for a smart Battery Management System (BMS) and battery supported Cyber-Physical Systems (CPS). In 2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012 (pp. 113-116). Article 6217989 (2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012). https://doi.org/10.1109/BCFIC.2012.6217989

@inproceedings{fe1fdacaf90546bcb4a81ff6cdee1a14,

title = "Towards a hybrid approach to SoC estimation for a smart Battery Management System (BMS) and battery supported Cyber-Physical Systems (CPS)",

abstract = "One of the most important and indispensable parameters of a Battery Management System (BMS) is to accurately estimate the State of Charge (SoC) of battery. Precise estimation of SoC can prevent battery from damage or premature aging by avoiding over charge or discharge. Due to the limited capacity of a battery, advanced methods must be used to estimate precisely the SoC in order to keep battery safely being charged and discharged at a suitable level and to prolong its life cycle. We review several existing effective approaches such as Coulomb counting, Open Circuit Voltage (OCV) and Kalman Filter method for performing the SoC estimation. Then we investigate both Artificial Intelligence (AI) approach and Formal Methods (FM) approach that can be efficiently used to precisely determine the SoC estimation for the smart battery management system as presented in [1]. By using presented approach, a more accurate SoC measurement can be obtained for the smart battery management system and battery supported Cyber-Physical Systems (CPS).",

keywords = "Artificial Intelligence (AI), Battery Management Systems (BMS), Cyber-Physical Systems (CPS), Formal Methods (FM), State of Charge (SoC)",

author = "Man, {K. L.} and Ting, {T. O.} and T. Krilavi{\v c}ius and Kaiyu Wan and C. Chen and J. Chang and Poon, {S. H.}",

year = "2012",

doi = "10.1109/BCFIC.2012.6217989",

language = "English",

isbn = "9781467316712",

series = "2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012",

pages = "113--116",

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}

Man, KL, Ting, TO, Krilavičius, T, Wan, K, Chen, C, Chang, J & Poon, SH 2012, Towards a hybrid approach to SoC estimation for a smart Battery Management System (BMS) and battery supported Cyber-Physical Systems (CPS). in 2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012., 6217989, 2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012, pp. 113-116, 2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012, Vilnius, Lithuania, 25/04/12. https://doi.org/10.1109/BCFIC.2012.6217989

Towards a hybrid approach to SoC estimation for a smart Battery Management System (BMS) and battery supported Cyber-Physical Systems (CPS). / Man, K. L.; Ting, T. O.; Krilavičius, T. et al.
2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012. 2012. p. 113-116 6217989 (2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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AU - Man, K. L.

AU - Ting, T. O.

AU - Krilavičius, T.

AU - Wan, Kaiyu

AU - Chen, C.

AU - Chang, J.

AU - Poon, S. H.

PY - 2012

Y1 - 2012

N2 - One of the most important and indispensable parameters of a Battery Management System (BMS) is to accurately estimate the State of Charge (SoC) of battery. Precise estimation of SoC can prevent battery from damage or premature aging by avoiding over charge or discharge. Due to the limited capacity of a battery, advanced methods must be used to estimate precisely the SoC in order to keep battery safely being charged and discharged at a suitable level and to prolong its life cycle. We review several existing effective approaches such as Coulomb counting, Open Circuit Voltage (OCV) and Kalman Filter method for performing the SoC estimation. Then we investigate both Artificial Intelligence (AI) approach and Formal Methods (FM) approach that can be efficiently used to precisely determine the SoC estimation for the smart battery management system as presented in [1]. By using presented approach, a more accurate SoC measurement can be obtained for the smart battery management system and battery supported Cyber-Physical Systems (CPS).

AB - One of the most important and indispensable parameters of a Battery Management System (BMS) is to accurately estimate the State of Charge (SoC) of battery. Precise estimation of SoC can prevent battery from damage or premature aging by avoiding over charge or discharge. Due to the limited capacity of a battery, advanced methods must be used to estimate precisely the SoC in order to keep battery safely being charged and discharged at a suitable level and to prolong its life cycle. We review several existing effective approaches such as Coulomb counting, Open Circuit Voltage (OCV) and Kalman Filter method for performing the SoC estimation. Then we investigate both Artificial Intelligence (AI) approach and Formal Methods (FM) approach that can be efficiently used to precisely determine the SoC estimation for the smart battery management system as presented in [1]. By using presented approach, a more accurate SoC measurement can be obtained for the smart battery management system and battery supported Cyber-Physical Systems (CPS).

KW - Artificial Intelligence (AI)

KW - Battery Management Systems (BMS)

KW - Cyber-Physical Systems (CPS)

KW - Formal Methods (FM)

KW - State of Charge (SoC)

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T3 - 2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012

SP - 113

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BT - 2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012

T2 - 2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012

Y2 - 25 April 2012 through 27 April 2012

ER -

Man KL, Ting TO, Krilavičius T, Wan K, Chen C, Chang J et al. Towards a hybrid approach to SoC estimation for a smart Battery Management System (BMS) and battery supported Cyber-Physical Systems (CPS). In 2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012. 2012. p. 113-116. 6217989. (2012 2nd Baltic Congress on Future Internet Communications, BCFIC 2012). doi: 10.1109/BCFIC.2012.6217989

Towards a hybrid approach to SoC estimation for a smart Battery Management System (BMS) and battery supported Cyber-Physical Systems (CPS)

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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