LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering

Lithium iron phosphate (LiFePO4) batteries are widely used as power batteries for electric vehicle applications. For safety issues, it is important to estimate the State of Charge(SOC) of a battery accurately. The improved Thevenin equivalent circuit model is established according to the characteris...

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Main Authors: Xu, Zhu, Gao, Shibin, Yang, Shunfeng
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2016
Subjects:
Online Access:https://hdl.handle.net/10356/81519
http://hdl.handle.net/10220/40830
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-815192020-03-07T13:57:23Z LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering Xu, Zhu Gao, Shibin Yang, Shunfeng School of Electrical and Electronic Engineering Batteries Self organized systems Lithium iron phosphate (LiFePO4) batteries are widely used as power batteries for electric vehicle applications. For safety issues, it is important to estimate the State of Charge(SOC) of a battery accurately. The improved Thevenin equivalent circuit model is established according to the characteristics of the LiFePO4battery, and the model parameters are identified by experimental testing. Furthermore, a novel algorithm of SOC online estimation is proposed, which combines the open-circuit voltage method, ampere-hour integration, and Kalman filtering. The simulations and experimental results show that the improved Thevenin equivalent circuit model can enhance the accuracy of SOC estimation. This proposed algorithm could estimate the SOC precisely even with inaccurate initial values and current measurement errors and distinguish the performances between the batteries. The performance of the proposed SOC estimation method when the voltage sensor is unavailable has been investigated and presented as well. From the characteristics mentioned above, this novel approach is able to guarantee the reliability and safety of the batteries. Published version 2016-06-29T04:58:11Z 2019-12-06T14:32:49Z 2016-06-29T04:58:11Z 2019-12-06T14:32:49Z 2016 Journal Article Xu, Z., Gao, S., & Yang, S. (2016). LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering. Journal of Renewable and Sustainable Energy, 8(2), 024103-. 1941-7012 https://hdl.handle.net/10356/81519 http://hdl.handle.net/10220/40830 10.1063/1.4944335 en Journal of Renewable and Sustainable Energy © 2016 AIP Publishing LLC. This paper was published in Journal of Renewable and Sustainable Energy and is made available as an electronic reprint (preprint) with permission of AIP Publishing LLC. The published version is available at: [http://dx.doi.org/10.1063/1.4944335]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 14 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Batteries
Self organized systems
spellingShingle Batteries
Self organized systems
Xu, Zhu
Gao, Shibin
Yang, Shunfeng
LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering
description Lithium iron phosphate (LiFePO4) batteries are widely used as power batteries for electric vehicle applications. For safety issues, it is important to estimate the State of Charge(SOC) of a battery accurately. The improved Thevenin equivalent circuit model is established according to the characteristics of the LiFePO4battery, and the model parameters are identified by experimental testing. Furthermore, a novel algorithm of SOC online estimation is proposed, which combines the open-circuit voltage method, ampere-hour integration, and Kalman filtering. The simulations and experimental results show that the improved Thevenin equivalent circuit model can enhance the accuracy of SOC estimation. This proposed algorithm could estimate the SOC precisely even with inaccurate initial values and current measurement errors and distinguish the performances between the batteries. The performance of the proposed SOC estimation method when the voltage sensor is unavailable has been investigated and presented as well. From the characteristics mentioned above, this novel approach is able to guarantee the reliability and safety of the batteries.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Xu, Zhu
Gao, Shibin
Yang, Shunfeng
format Article
author Xu, Zhu
Gao, Shibin
Yang, Shunfeng
author_sort Xu, Zhu
title LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering
title_short LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering
title_full LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering
title_fullStr LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering
title_full_unstemmed LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering
title_sort lifepo4 battery state of charge estimation based on the improved thevenin equivalent circuit model and kalman filtering
publishDate 2016
url https://hdl.handle.net/10356/81519
http://hdl.handle.net/10220/40830
_version_ 1681040334617837568