Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias

State of Charge (SOC) is essential for a smart Battery Management System (BMS). Traditional SOC estimation methods of lithium-ion batteries are usually conducted using battery equivalent circuit models (ECMs) and the impact of current sensor bias on SOC estimation is rarely considered. For this reas...

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Main Authors: Longxing Wu, Kai Liu, Hui Pang, Jiamin Jin
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/17/5265
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spelling doaj-359fa2df1aaa461bbcaa31e2fd8af3972021-09-09T13:42:43ZengMDPI AGEnergies1996-10732021-08-01145265526510.3390/en14175265Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current BiasLongxing Wu0Kai Liu1Hui Pang2Jiamin Jin3School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, ChinaState of Charge (SOC) is essential for a smart Battery Management System (BMS). Traditional SOC estimation methods of lithium-ion batteries are usually conducted using battery equivalent circuit models (ECMs) and the impact of current sensor bias on SOC estimation is rarely considered. For this reason, this paper proposes an online SOC estimation based on a simplified electrochemical model (EM) for lithium-ion batteries considering sensor bias. In EM-based SOC estimation structure, the errors from the current sensor bias are addressed by proportional–integral observer. Then, the accuracy of the proposed EM-based SOC estimation is validated under different operating conditions. The results indicate that the proposed method has good performance and high accuracy in SOC estimation for lithium-ion batteries, which facilitates the on-board application in advanced BMS.https://www.mdpi.com/1996-1073/14/17/5265lithium-ion batteriessimplified electrochemical modelstate of chargeproportional–integral observersensor bias
collection DOAJ
language English
format Article
sources DOAJ
author Longxing Wu
Kai Liu
Hui Pang
Jiamin Jin
spellingShingle Longxing Wu
Kai Liu
Hui Pang
Jiamin Jin
Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias
Energies
lithium-ion batteries
simplified electrochemical model
state of charge
proportional–integral observer
sensor bias
author_facet Longxing Wu
Kai Liu
Hui Pang
Jiamin Jin
author_sort Longxing Wu
title Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias
title_short Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias
title_full Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias
title_fullStr Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias
title_full_unstemmed Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias
title_sort online soc estimation based on simplified electrochemical model for lithium-ion batteries considering current bias
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2021-08-01
description State of Charge (SOC) is essential for a smart Battery Management System (BMS). Traditional SOC estimation methods of lithium-ion batteries are usually conducted using battery equivalent circuit models (ECMs) and the impact of current sensor bias on SOC estimation is rarely considered. For this reason, this paper proposes an online SOC estimation based on a simplified electrochemical model (EM) for lithium-ion batteries considering sensor bias. In EM-based SOC estimation structure, the errors from the current sensor bias are addressed by proportional–integral observer. Then, the accuracy of the proposed EM-based SOC estimation is validated under different operating conditions. The results indicate that the proposed method has good performance and high accuracy in SOC estimation for lithium-ion batteries, which facilitates the on-board application in advanced BMS.
topic lithium-ion batteries
simplified electrochemical model
state of charge
proportional–integral observer
sensor bias
url https://www.mdpi.com/1996-1073/14/17/5265
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AT huipang onlinesocestimationbasedonsimplifiedelectrochemicalmodelforlithiumionbatteriesconsideringcurrentbias
AT jiaminjin onlinesocestimationbasedonsimplifiedelectrochemicalmodelforlithiumionbatteriesconsideringcurrentbias
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