Shun-Li Wang
A novel power state evaluation method for the lithium battery packs based on the improved external measurable parameter coupling model.
Wang, Shun-Li; Stroe, Daniel-Ioan; Fernandez, Carlos; Xiong, Li-Ying; Fan, Yong-Cun; Cao, Wen
Authors
Daniel-Ioan Stroe
Dr Carlos Fernandez c.fernandez@rgu.ac.uk
Senior Lecturer
Li-Ying Xiong
Yong-Cun Fan
Wen Cao
Abstract
The power state evaluation plays a decisive influence on the safety implication of the lithium battery packs, and there is no effective online evaluation method so far due to the imbalance phenomenon among the internal connected battery cells, which cannot be abstained by the advancement of the materials and techniques. A novel power state mathematical evaluation method is proposed in this paper by investigating the improved external parameter coupling treatment, in which the mutual relationship description is conducted by the parameter information feature decomposition together with the Bayesian sequential decision algorithm. The complicated power state evaluation model with the coupling relationship decomposition is constructed by investigating the non-convex optimization treatment under complex working conditions for the lithium battery packs. The evidence combination is realized by introducing the information fusion strategy, according to which the multi criteria decision is realized by using the evidence theory. As can be seen from the experimental results, the voltage difference is within 10 mV in both of the first and the second phases, which increases rapidly in the third phase and reaches a maximum of 120 mV. Meanwhile, its power state evaluation accuracy is 95.00% and has a good output voltage tracking effect in the complex working conditions. The power state evaluation can be realized effectively by the proposed model constructing method, which is suitable for the complex battery cell combination structures and environmental influences, protecting the reliable and hierarchical working state monitoring and management of the lithium battery packs. It provides safety protection and energy management basis for the reliable power supply in the cleaner production of the power lithium battery packs.
Citation
WANG, S.-L., STROE, D.-I., FERNANDEZ, C., XIONG, L.-Y., FAN, Y.-C. and CAO, W. 2020. A novel power state evaluation method for the lithium battery packs based on the improved external measurable parameter coupling model. Journal of cleaner production [online], 242, article ID 118506. Available from: https://doi.org/10.1016/j.jclepro.2019.118506
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 18, 2019 |
Online Publication Date | Sep 19, 2019 |
Publication Date | Jan 1, 2020 |
Deposit Date | Oct 4, 2019 |
Publicly Available Date | Sep 20, 2020 |
Journal | Journal of cleaner production |
Print ISSN | 0959-6526 |
Electronic ISSN | 1879-1786 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 242 |
Article Number | 118506 |
DOI | https://doi.org/10.1016/j.jclepro.2019.118506 |
Keywords | Data modeling; Coupling relationship model; Lithium battery pack; Multi-parameter optimization; Power state evaluation |
Public URL | https://rgu-repository.worktribe.com/output/618131 |
Files
WANG 2020 A novel power
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Publisher Licence URL
https://creativecommons.org/licenses/by-nc-nd/4.0/
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