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...

Full description

Saved in:
Bibliographic Details
Main Authors: Aung, Htet, Low, Kay Soon
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2016
Subjects:
Online Access:https://hdl.handle.net/10356/81592
http://hdl.handle.net/10220/39552
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-81592
record_format dspace
spelling 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
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Battery management sytems
spellingShingle Battery management sytems
Aung, Htet
Low, Kay Soon
Temperature dependent state-of-charge estimation of lithium ion battery using dual spherical unscented Kalman filter
description 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.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Aung, Htet
Low, Kay Soon
format 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
url https://hdl.handle.net/10356/81592
http://hdl.handle.net/10220/39552
_version_ 1681048055242031104