Nejad, S., Gladwin, D.T. orcid.org/0000-0001-7195-5435, Foster, M.P. orcid.org/0000-0002-8565-0541 et al. (1 more author) (2017) Parameterisation and Online States Estimation of High-Energy Lithium-Titanate Cells. In: IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. 43rd Annual Conference of the IEEE Industrial Electronics Society, 29 Oct - 01 Nov 2017, Beijing, China. IEEE , pp. 7660-7665.
Abstract
In 2013, the University of Sheffield commissioned a 1 MWh lithium-titanate (LTO) battery energy storage system (BESS), directly connected to the grid through an 11 kV feed. With a view to later on develop a comprehensive model structure for the whole battery pack - key to many online battery management system (BMS) operations - in this paper, an in-depth frequency-domain analysis is performed on one of the constituent 2.3 V 20 Ah LTO cells, using a potentiostatic sine-swept method. A first-order resistor-capacitor (RC) equivalent-circuit model is put forward, capable of representing the LTO cell's impedance magnitude with an error of less than 0.1 mΩ. Thereafter, the performance of the proposed one-RC model structure for online SOC estimation is experimentally verified using the Extended Kalman Filter (EKF). The verification test is performed on a dynamic pulsed-power profile, derived from a real grid frequency-support service that is offered by several BESSs in the UK.
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-Titanate; Battery; Equivalent-Circuit Modelling; Online; Kalman Filter; State-of-Charge; Estimation |
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) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC) EP/N032888/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 29 Aug 2018 11:16 |
Last Modified: | 19 Dec 2022 13:50 |
Published Version: | https://doi.org/10.1109/IECON.2017.8217342 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/IECON.2017.8217342 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:135065 |