Temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented Kalman filter
Accurate and reliable state-of-charge (SOC) estimation is an important task for battery management system in a satellite. Ambient temperature is one of the significant factors that affect SOC estimation. Since satellite operates at different temperatures throughout the orbit, it must be taken care...
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sg-ntu-dr.10356-815922020-03-07T13:57:25Z Temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented Kalman filter Aung, Htet Low, Kay Soon School of Electrical and Electronic Engineering Battery management sytems Accurate and reliable state-of-charge (SOC) estimation is an important task for battery management system in a satellite. Ambient temperature is one of the significant factors that affect SOC estimation. Since satellite operates at different temperatures throughout the orbit, it must be taken care of accordingly to safeguard the battery performance and reliability. Moreover, SOC estimation depends on battery model accuracy as well. The battery parameters are affected by temperature, SOC, charging and discharging rates. Hence, the parameters need to be updated accordingly to improve the battery model and the SOC estimation accuracy. In this study, a SOC estimation method and online parameter updating using a dual square root unscented Kalman filter based on unit spherical unscented transform is proposed. The proposed method has been validated experimentally and the results are compared with extended Kalman filter and unscented Kalman filter based on unit spherical unscented transform. Experimental results have shown that the proposed method has better performance in terms of lower root mean square error and absolute maximum error. Accepted version 2016-01-05T02:45:14Z 2019-12-06T14:34:30Z 2016-01-05T02:45:14Z 2019-12-06T14:34:30Z 2015 Journal Article Aung, H., & Low, K. S. (2015). Temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented Kalman filter. IET Power Electronics, 8(10), 2026-2033. 1755-4535 https://hdl.handle.net/10356/81592 http://hdl.handle.net/10220/39552 10.1049/iet-pel.2014.0863 en IET Power Electronics © 2015 Institution of Engineering and Technology (IET). This is the author created version of a work that has been peer reviewed and accepted for publication by IET Power Electronics, Institution of Engineering and Technology (IET). It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1049/iet-pel.2014.0863]. 9 p. application/pdf |
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Battery management sytems Aung, Htet Low, Kay Soon Temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented Kalman filter |
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Accurate and reliable state-of-charge (SOC) estimation is an important task for battery management system in a
satellite. Ambient temperature is one of the significant factors that affect SOC estimation. Since satellite operates at
different temperatures throughout the orbit, it must be taken care of accordingly to safeguard the battery performance
and reliability. Moreover, SOC estimation depends on battery model accuracy as well. The battery parameters are
affected by temperature, SOC, charging and discharging rates. Hence, the parameters need to be updated accordingly
to improve the battery model and the SOC estimation accuracy. In this study, a SOC estimation method and online
parameter updating using a dual square root unscented Kalman filter based on unit spherical unscented transform is
proposed. The proposed method has been validated experimentally and the results are compared with extended
Kalman filter and unscented Kalman filter based on unit spherical unscented transform. Experimental results have
shown that the proposed method has better performance in terms of lower root mean square error and absolute
maximum error. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Aung, Htet Low, Kay Soon |
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Article |
author |
Aung, Htet Low, Kay Soon |
author_sort |
Aung, Htet |
title |
Temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented Kalman filter |
title_short |
Temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented Kalman filter |
title_full |
Temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented Kalman filter |
title_fullStr |
Temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented Kalman filter |
title_full_unstemmed |
Temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented Kalman filter |
title_sort |
temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented kalman filter |
publishDate |
2016 |
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https://hdl.handle.net/10356/81592 http://hdl.handle.net/10220/39552 |
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1681048055242031104 |