Nejad, S., Gladwin, D.T. orcid.org/0000-0001-7195-5435 and Stone, D.A. orcid.org/0000-0002-5770-3917 (2016) A hybrid battery parameter identification concept for lithium-ion energy storage applications. In: IECON Proceedings (Industrial Electronics Conference). IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society, October 24-27, 2016, Florence. , pp. 1980-1985. ISBN 9781509034741
Abstract
© 2016 IEEE.Persistent of excitation of the input/output signals is a necessity for any online parameter identification technique. In most real battery systems, the drive signals may not fully satisfy this condition at all times, which can lead to divergence and failure of the incorporated battery management system. Therefore, in this paper, a hybrid battery parameter identification concept is proposed whereby the parameters are initially identified using a special random signal called the pseudo random binary sequences. Thereafter, the Kalman filter algorithm is implemented online to estimate and track any 'disturbances' caused by varying operating conditions. A dynamic European drive cycle is used to experimentally verify the excellent performance of the proposed technique against a more precise electrochemical impedance spectroscopy method.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Lithium-ion; Battery Energy Storage; Online; Extended Kalman Filter; Hybrid; Parameter Identification; |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 Mar 2017 15:23 |
Last Modified: | 14 Apr 2017 03:02 |
Published Version: | https://doi.org/10.1109/IECON.2016.7793233 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1109/IECON.2016.7793233 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:113906 |