Jialu Qiao
A novel intelligent weight decreasing firefly–particle filtering method for accurate state‐of‐charge estimation of lithium‐ion batteries.
Qiao, Jialu; Wang, Shunli; Yu, Chunmei; Yang, Xiao; Fernandez, Carlos
Abstract
Accurate state-of-charge estimation plays an extremely crucial role in battery management systems. To realize the real-time and precise state-of-charge estimation, an intelligent weight decreasing firefly–particle filtering algorithm is proposed. In this research, the second-order RC equivalent circuit model is established, and the parameters are identified online, and state-of-charge particles simulate the attraction behavior of fireflies in nature and approach the global optimal value to complete the particle optimization process. The linear weight decreasing strategy is introduced to avoid the algorithm falling into local optimization. The data of different complex conditions are used to verify the feasibility of the proposed algorithm; the results show that the root-mean-square error of intelligent weight decreasing firefly–particle filtering method when the initial SOC value is set to 1 under Hybrid Pulse Power Characterization and Beijing Bus Dynamic Stress Test condition can be controlled within 0.60% and 1.12%, respectively, which verifies that the proposed algorithm has high accuracy in state-of-charge estimation of lithium-ion batteries. The algorithm proposed in this article provides a theoretical basis for real-time state monitoring and security of battery management systems.
Citation
QIAO, J., WANG, S., YU, C., YANG, X. and FERNANDEZ, C. 2022. A novel intelligent weight decreasing firefly-particle filtering method for accurate state-of-charge estimation of lithium-ion batteries. International journal of energy research [online], 46(5), pages 6613-6622Early View. Available from: https://doi.org/10.1002/er.7596
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 14, 2021 |
Online Publication Date | Dec 27, 2021 |
Publication Date | Apr 30, 2022 |
Deposit Date | Jan 13, 2022 |
Publicly Available Date | Dec 28, 2022 |
Journal | International Journal of Energy Research |
Print ISSN | 0363-907X |
Electronic ISSN | 1099-114X |
Publisher | Wiley |
Peer Reviewed | Peer Reviewed |
Volume | 46 |
Issue | 5 |
Pages | 6613-6622 |
DOI | https://doi.org/10.1002/er.7596 |
Keywords | Intelligent weight decreasing firefly; Lithium-ion battery; Particle filtering; Second-order RC equivalent circuit model; State-of-charge |
Public URL | https://rgu-repository.worktribe.com/output/1569429 |
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Copyright Statement
This is the peer reviewed version of the following article: QIAO, J., WANG, S., YU, C., YANG, X. and FERNANDEZ, C. 2022. A novel intelligent weight decreasing firefly-particle filtering method for accurate state-of-charge estimation of lithium-ion batteries. International journal of energy research, 46(5), pages 6613-6622, which has been published in final form at https://doi.org/10.1002/er.7596. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
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