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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Online Access: | https://www.mdpi.com/1996-1073/14/17/5265 |
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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 |
work_keys_str_mv |
AT longxingwu onlinesocestimationbasedonsimplifiedelectrochemicalmodelforlithiumionbatteriesconsideringcurrentbias AT kailiu onlinesocestimationbasedonsimplifiedelectrochemicalmodelforlithiumionbatteriesconsideringcurrentbias AT huipang onlinesocestimationbasedonsimplifiedelectrochemicalmodelforlithiumionbatteriesconsideringcurrentbias AT jiaminjin onlinesocestimationbasedonsimplifiedelectrochemicalmodelforlithiumionbatteriesconsideringcurrentbias |
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1717760502036168704 |