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New battery model and state-of-health determination through subspace parameter estimation and state-observer techniques

Gould, C.R., Bingham, C.M., Stone, D.A. and Bentley, P. (2009) New battery model and state-of-health determination through subspace parameter estimation and state-observer techniques. IEEE Transactions on Vehicular Technology, 58 (8). pp. 3905-3916. ISSN 0018-9545


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This paper describes a novel adaptive battery model based on a remapped variant of the well-known Randles' lead-acid model. Remapping of the model is shown to allow improved modeling capabilities and accurate estimates of dynamic circuit parameters when used with subspace parameter-estimation techniques. The performance of the proposed methodology is demonstrated by application to batteries for an all-electric personal rapid transit vehicle from the Urban Light TRAnsport (ULTRA) program, which is designated for use at Heathrow Airport, U. K. The advantages of the proposed model over the Randles' circuit are demonstrated by comparisons with alternative observer/estimator techniques, such as the basic Utkin observer and the Kalman estimator. These techniques correctly identify and converge on voltages associated with the battery state-of-charge (SoC), despite erroneous initial conditions, thereby overcoming problems attributed to SoC drift (incurred by Coulomb-counting methods due to overcharging or ambient temperature fluctuations). Observation of these voltages, as well as online monitoring of the degradation of the estimated dynamic model parameters, allows battery aging (state-of-health) to also be assessed and, thereby, cell failure to be predicted. Due to the adaptive nature of the proposed algorithms, the techniques are suitable for applications over a wide range of operating environments, including large ambient temperature variations. Moreover, alternative battery topologies may also be accommodated by the automatic adjustment of the underlying state-space models used in both the parameter-estimation and observer/estimator stages.

Item Type: Article
Copyright, Publisher and Additional Information: © Copyright 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: Battery-management systems; energy storage; parameter estimation; system identification
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield)
Depositing User: Miss Anthea Tucker
Date Deposited: 30 Oct 2009 10:46
Last Modified: 04 Jun 2014 12:14
Published Version: http://dx.doi.org/10.1109/TVT.2009.2028348
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Refereed: Yes
Identification Number: 10.1109/TVT.2009.2028348
URI: http://eprints.whiterose.ac.uk/id/eprint/10047

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