Zhang, C, Li, K orcid.org/0000-0001-6657-0522, Deng, J et al. (1 more author) (2017) Improved Realtime State-of-Charge Estimation of LiFePO₄ Battery Based on a Novel Thermoelectric Model. IEEE Transactions on Industrial Electronics, 64 (1). pp. 654-663. ISSN 0278-0046
Abstract
Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-of-charge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is first built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviors are captured, thus offering a comprehensive description of the battery thermal and electrical behavior. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a metaheuristic algorithm and the least-square approach. Further, time-varying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IEEE. This is an author produced version of a paper published in IEEE Transactions on Industrial Electronics. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Internal temperature estimation; joint extended Kalman filter (EKF); state-of-charge (SOC) estimation; thermoelectric model |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 26 Nov 2018 10:47 |
Last Modified: | 18 Mar 2019 11:00 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/TIE.2016.2610398 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:139091 |