期刊
ENERGY
卷 239, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.122181
关键词
Parallel-connected battery module; Physics-based battery model; Heterogeneous characteristic analysis; Battery sorting method
资金
- Natural Science Foundation of Guangdong Province [2021A1515010525]
- National Natural Science Foundation of China [51807121, 61803268]
- Natural Science Foundation of SZU
- Shenzhen Municipal Peacock Program [827-000420]
This paper investigates the impact of cell inconsistencies in a battery module and proposes a battery sorting method that has been validated to effectively reduce inconsistencies, aiding in fault analysis of electric vehicle battery modules, module level grading, or secondary applications of batteries.
Cell inconsistencies inevitably occur inside a battery module. Particularly, the inconsistencies in current distribution and heat generation in a parallel-connected battery module may lead to battery degradation and potential safety issues. Consequently, it is imperative to evaluate and reduce cell inconsistencies in a battery module. In this paper, an extended single particle model of a battery cell is constructed using the Pade approximation and the first-order Taylor expansion to simplify the conventional electrochemical mechanism model. On this basis, a multidomain electrochemical mechanism simulation model of a parallel-connected battery module is attained. Then, the influence of cell inconsistencies on the battery module voltage, internal current distribution and heat generation under different aging situation is assessed by a parameter sensitivity analysis method. Moreover, based on the contribution of each battery model parameter to the inconsistency of the parallel-connected battery module, a battery cell sorting method is proposed. Finally, this proposed sorting method for secondary applications of batteries is validated based on 15 aged batteries. Results indicate that the average standard deviation of the cell current in the NCM parallel-connected module can be reduced from 0.209 A to 0.060 A. The proposed approach is helpful to the fault analysis of electric vehicle battery modules, module level grading or the secondary applications of retired batteries. (c) 2021 Elsevier Ltd. All rights reserved.
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