State-of-Power Estimation of Li-Ion Batteries Considering the Battery Surface Temperature

Liu, X; He, Y; Zeng, G; Zhang, J; Zheng, X

State-of-Power Estimation of Li-Ion Batteries Considering the Battery Surface Temperature

Liu, X He, Y Zeng, G Zhang, J

Zheng, X

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Publication Type:: Journal Article
Citation:: Energy Technology, 2018, 6 (7), pp. 1352 - 1360
Issue Date:: 2018-07-01

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Field	Value	Language
dc.contributor.author	Liu, X	en_US
dc.contributor.author	He, Y	en_US
dc.contributor.author	Zeng, G	en_US
dc.contributor.author	Zhang, J https://orcid.org/0000-0003-2616-6722	en_US
dc.contributor.author	Zheng, X	en_US
dc.date.available	2020-05-25T19:21:38Z
dc.date.issued	2018-07-01	en_US
dc.identifier.citation	Energy Technology, 2018, 6 (7), pp. 1352 - 1360	en_US
dc.identifier.issn	2194-4288	en_US
dc.identifier.uri	http://hdl.handle.net/10453/129663
dc.description.abstract	© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim The state-of-power (SOP) of a Li-ion battery (LIB) is an important evaluation index for safety control and energy recovery in electric vehicles. Major state estimation methods are only applicable to fixed room temperature at 20 °C, although the battery capacity and resistance vary dramatically with a change in battery surface temperature in the working process of the battery. This causes significant errors in state estimation if only room temperature is assumed. The inaccurate state may cause further excessive current at high or low temperatures to affect safety and life cycle of the battery. Therefore, a novel state estimation method applicable to various battery surface temperatures is developed here. This method uses capacity–temperature and resistance–temperature relationships from experimental data to more accurately predict battery capacity and resistance over the full temperature range. It then applies the extended Kalman filter (EKF) technique to estimate the state-of-charge, and a method of constrained multi-parameter algorithm (CMPA) to estimate the SOP of LIBs. Simulation and experimental results show that the proposed method can obtain accurate SOP results at different temperatures.	en_US
dc.relation.ispartof	Energy Technology	en_US
dc.relation.isbasedon	10.1002/ente.201700680	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	State-of-Power Estimation of Li-Ion Batteries Considering the Battery Surface Temperature	en_US
dc.type	Journal Article
utslib.citation.volume	7	en_US
utslib.citation.volume	6	en_US
utslib.for	0902 Automotive Engineering	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0904 Chemical Engineering	en_US
utslib.for	0912 Materials Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
pubs.issue	7	en_US
pubs.publication-status	Published	en_US
pubs.volume	6	en_US

Abstract:

© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim The state-of-power (SOP) of a Li-ion battery (LIB) is an important evaluation index for safety control and energy recovery in electric vehicles. Major state estimation methods are only applicable to fixed room temperature at 20 °C, although the battery capacity and resistance vary dramatically with a change in battery surface temperature in the working process of the battery. This causes significant errors in state estimation if only room temperature is assumed. The inaccurate state may cause further excessive current at high or low temperatures to affect safety and life cycle of the battery. Therefore, a novel state estimation method applicable to various battery surface temperatures is developed here. This method uses capacity–temperature and resistance–temperature relationships from experimental data to more accurately predict battery capacity and resistance over the full temperature range. It then applies the extended Kalman filter (EKF) technique to estimate the state-of-charge, and a method of constrained multi-parameter algorithm (CMPA) to estimate the SOP of LIBs. Simulation and experimental results show that the proposed method can obtain accurate SOP results at different temperatures.

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http://hdl.handle.net/10453/129663