Charge State Estimation of Power Battery Based on CARMA Model

In order to perfect main functions of electric vehicle battery management system, this paper aims to realize accurate battery modeling and state of charge(SOC) estimation. In this paper, based on the second-order RC equivalent circuit model, a controlled auto regressive moving average (CARMA) of the...

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Main Authors: HUANG Yusha, CHEN Yushan, QIN Linlin, SHI Chun, WU Gang
Format: Article
Language:zho
Published: Editorial Office of Control and Information Technology 2020-01-01
Series:Kongzhi Yu Xinxi Jishu
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Online Access:http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2020.01.400
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author HUANG Yusha
CHEN Yushan
QIN Linlin
SHI Chun
WU Gang
author_facet HUANG Yusha
CHEN Yushan
QIN Linlin
SHI Chun
WU Gang
author_sort HUANG Yusha
collection DOAJ
description In order to perfect main functions of electric vehicle battery management system, this paper aims to realize accurate battery modeling and state of charge(SOC) estimation. In this paper, based on the second-order RC equivalent circuit model, a controlled auto regressive moving average (CARMA) of the battery was established. The optimal estimation of open circuit voltage (OCV) is derived from the CARMA model, and battery SOC estimation is realised by OCV-SOC segmentation model. The method realizes online real-time identification of battery model parameters and real-time SOC estimation, which solves the problem of unreasonable initial value setting that affects the accuracy of SOC estimation. Simulation results show that under the operating conditions of the federal city in the United States, the absolute value of the SOC estimation error does not exceed 2.39%, and a more accurate SOC estimation is achieved.
format Article
id doaj-art-2b23dbc7babc4858913da9e52b91e356
institution Kabale University
issn 2096-5427
language zho
publishDate 2020-01-01
publisher Editorial Office of Control and Information Technology
record_format Article
series Kongzhi Yu Xinxi Jishu
spelling doaj-art-2b23dbc7babc4858913da9e52b91e3562025-08-25T06:50:50ZzhoEditorial Office of Control and Information TechnologyKongzhi Yu Xinxi Jishu2096-54272020-01-01373682320553Charge State Estimation of Power Battery Based on CARMA ModelHUANG YushaCHEN YushanQIN LinlinSHI ChunWU GangIn order to perfect main functions of electric vehicle battery management system, this paper aims to realize accurate battery modeling and state of charge(SOC) estimation. In this paper, based on the second-order RC equivalent circuit model, a controlled auto regressive moving average (CARMA) of the battery was established. The optimal estimation of open circuit voltage (OCV) is derived from the CARMA model, and battery SOC estimation is realised by OCV-SOC segmentation model. The method realizes online real-time identification of battery model parameters and real-time SOC estimation, which solves the problem of unreasonable initial value setting that affects the accuracy of SOC estimation. Simulation results show that under the operating conditions of the federal city in the United States, the absolute value of the SOC estimation error does not exceed 2.39%, and a more accurate SOC estimation is achieved.http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2020.01.400SOC(state of charge)CARMA(controlled auto-regressive moving average)power batterySOC estimation
spellingShingle HUANG Yusha
CHEN Yushan
QIN Linlin
SHI Chun
WU Gang
Charge State Estimation of Power Battery Based on CARMA Model
Kongzhi Yu Xinxi Jishu
SOC(state of charge)
CARMA(controlled auto-regressive moving average)
power battery
SOC estimation
title Charge State Estimation of Power Battery Based on CARMA Model
title_full Charge State Estimation of Power Battery Based on CARMA Model
title_fullStr Charge State Estimation of Power Battery Based on CARMA Model
title_full_unstemmed Charge State Estimation of Power Battery Based on CARMA Model
title_short Charge State Estimation of Power Battery Based on CARMA Model
title_sort charge state estimation of power battery based on carma model
topic SOC(state of charge)
CARMA(controlled auto-regressive moving average)
power battery
SOC estimation
url http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2020.01.400
work_keys_str_mv AT huangyusha chargestateestimationofpowerbatterybasedoncarmamodel
AT chenyushan chargestateestimationofpowerbatterybasedoncarmamodel
AT qinlinlin chargestateestimationofpowerbatterybasedoncarmamodel
AT shichun chargestateestimationofpowerbatterybasedoncarmamodel
AT wugang chargestateestimationofpowerbatterybasedoncarmamodel