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Correction published on 30 November 2011, see Energies 2011, 4(12), 2132.

Open AccessArticle
Energies 2010, 3(9), 1586-1603; doi:10.3390/en3091586

Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer

School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
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Author to whom correspondence should be addressed.
Received: 29 July 2010 / Accepted: 23 August 2010 / Published: 9 September 2010
(This article belongs to the Special Issue Hybrid Vehicles)

Abstract

In order to safely and efficiently use the power as well as to extend the lifetime of the traction battery pack, accurate estimation of State of Charge (SoC) is very important and necessary. This paper presents an adaptive observer-based technique for estimating SoC of a lithium-ion battery pack used in an electric vehicle (EV). The RC equivalent circuit model in ADVISOR is applied to simulate the lithium-ion battery pack. The parameters of the battery model as a function of SoC, are identified and optimized using the numerically nonlinear least squares algorithm, based on an experimental data set. By means of the optimized model, an adaptive Luenberger observer is built to estimate online the SoC of the lithium-ion battery pack. The observer gain is adaptively adjusted using a stochastic gradient approach so as to reduce the error between the estimated battery output voltage and the filtered battery terminal voltage measurement. Validation results show that the proposed technique can accurately estimate SoC of the lithium-ion battery pack without a heavy computational load.
Keywords: State of Charge; lithium-ion battery; electric vehicle; adaptive observer State of Charge; lithium-ion battery; electric vehicle; adaptive observer
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Hu, X.; Sun, F.; Zou, Y. Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer. Energies 2010, 3, 1586-1603.

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