Power Battery Balancing Strategy of Electric Vehicle Based on Adaptive Algorithm

Ju Wang; Jinrui Nan; Xiaolin Xu; Zepeng Gao

doi:10.15918/j.jbit1004-0579.201726.S104

Power Battery Balancing Strategy of Electric Vehicle Based on Adaptive Algorithm

Ju Wang, Jinrui Nan^*, Xiaolin Xu, Zepeng Gao

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

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

1 Citation (Scopus)

Abstract

The method of equalization based state of charge (SOC) is introduced.The real time tracking of parameters is realized by the method of adaptive forgetting factor recursive least square (AFFRLS). The identification results show that the output error is within 10mVunder this dynamic stress test (DST). The joint estimation of AFFRLS and extended Kalman filter (EKF) shows that the maximum error of state of charge is 0.5%. This method as the basis of consistency by controlling SOC, realizes the management of inconformity in Lithium battery pack, whose results show that double layer equalization strategy based on the multi-channel can control the cells' consistency effectively by using DC/DC convertor.

Original language	English
Pages (from-to)	21-27
Number of pages	7
Journal	Journal of Beijing Institute of Technology (English Edition)
Volume	26
DOIs	https://doi.org/10.15918/j.jbit1004-0579.201726.S104
Publication status	Published - 1 Dec 2017

Keywords

Consistency
Equalization strategy
Joint estimation
Parameter identification
State of charge(SOC)

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10.15918/j.jbit1004-0579.201726.S104

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title = "Power Battery Balancing Strategy of Electric Vehicle Based on Adaptive Algorithm",

abstract = "The method of equalization based state of charge (SOC) is introduced.The real time tracking of parameters is realized by the method of adaptive forgetting factor recursive least square (AFFRLS). The identification results show that the output error is within 10mVunder this dynamic stress test (DST). The joint estimation of AFFRLS and extended Kalman filter (EKF) shows that the maximum error of state of charge is 0.5%. This method as the basis of consistency by controlling SOC, realizes the management of inconformity in Lithium battery pack, whose results show that double layer equalization strategy based on the multi-channel can control the cells' consistency effectively by using DC/DC convertor.",

keywords = "Consistency, Equalization strategy, Joint estimation, Parameter identification, State of charge(SOC)",

author = "Ju Wang and Jinrui Nan and Xiaolin Xu and Zepeng Gao",

note = "Publisher Copyright: {\textcopyright} 2017 Editorial Department of Journal of Beijing Institute of Technology.",

year = "2017",

month = dec,

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doi = "10.15918/j.jbit1004-0579.201726.S104",

language = "English",

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TY - JOUR

T1 - Power Battery Balancing Strategy of Electric Vehicle Based on Adaptive Algorithm

AU - Wang, Ju

AU - Nan, Jinrui

AU - Xu, Xiaolin

AU - Gao, Zepeng

PY - 2017/12/1

Y1 - 2017/12/1

N2 - The method of equalization based state of charge (SOC) is introduced.The real time tracking of parameters is realized by the method of adaptive forgetting factor recursive least square (AFFRLS). The identification results show that the output error is within 10mVunder this dynamic stress test (DST). The joint estimation of AFFRLS and extended Kalman filter (EKF) shows that the maximum error of state of charge is 0.5%. This method as the basis of consistency by controlling SOC, realizes the management of inconformity in Lithium battery pack, whose results show that double layer equalization strategy based on the multi-channel can control the cells' consistency effectively by using DC/DC convertor.

AB - The method of equalization based state of charge (SOC) is introduced.The real time tracking of parameters is realized by the method of adaptive forgetting factor recursive least square (AFFRLS). The identification results show that the output error is within 10mVunder this dynamic stress test (DST). The joint estimation of AFFRLS and extended Kalman filter (EKF) shows that the maximum error of state of charge is 0.5%. This method as the basis of consistency by controlling SOC, realizes the management of inconformity in Lithium battery pack, whose results show that double layer equalization strategy based on the multi-channel can control the cells' consistency effectively by using DC/DC convertor.

KW - Consistency

KW - Equalization strategy

KW - Joint estimation

KW - Parameter identification

KW - State of charge(SOC)

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SN - 1004-0579

VL - 26

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EP - 27

JO - Journal of Beijing Institute of Technology (English Edition)

JF - Journal of Beijing Institute of Technology (English Edition)

ER -

Power Battery Balancing Strategy of Electric Vehicle Based on Adaptive Algorithm

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