NDLI: Estimation of State of Charge, Unknown Nonlinearities, and State of Health of a Lithium-Ion Battery Based on a Comprehensive Unobservable Model

Content Provider	IEEE Xplore Digital Library
Author	Gholizadeh, M. Salmasi, F.R.
Copyright Year	1982
Abstract	This paper considers the estimation of the state of charge and state of health for lithium-ion batteries, while an inclusive model is taken into account. The model includes two RC subnetworks, which represent the fast and slow transient responses of the terminal voltage. Nevertheless, the linear part of the model is unobservable. On the other hand, the nonlinear behavior of the open-circuit voltage versus state of charge is also included in the model. The proposed observer tackles the aforementioned problems to attain a reliable estimation of the state of charge. Moreover, as opposed to the methods in which the nonlinearities or uncertainties in the model are disregarded or those terms are discarded using a conventional sliding-mode observer, an analytical method is considered to estimate the additive nonlinear or uncertainty term in the model. This approach leads to a very accurate model of the battery to be used in a battery management system. Moreover, an online parameter estimation method is proposed to estimate the battery's state of health. The proposed scheme benefits from an adaptive rule for the online estimation of the series resistance in the lithium-ion battery based on the accurately identified model. Experimental tests certify the performance and feasibility of the proposed schemes.
Sponsorship	IEEE Industrial Electronics Society
Starting Page	1335
Ending Page	1344
Page Count	10
File Size	1962725
File Format	PDF
ISSN	02780046
Volume Number	61
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	state of health $(SoH)$ Adaptive observer estimation lithium-ion battery sliding motion state of charge
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Electrical and Electronic Engineering Computer Science Applications

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