Cell-to-cell Variation Evaluation for Lithium-ion Battery Packs in Electric Vehicles With Cloud Charging Data

被引：0
|
作者：
Zou D. [1 ]
Chen H. [1 ]
Li X. [1 ]
Lu Y. [2 ]
Huang P. [1 ]
机构：
[1] China Southern Power Grid Electric Vehicle Service Co., Ltd., Shenzhen
[2] Beijing Think Energy Technology Co., Ltd., Yanqing District, Beijing
来源：
Dianwang Jishu/Power System Technology | 2022年 / 46卷 / 03期
关键词：
Cell-to-cell variation; Cloud charging data; Electric vehicle; Fuzzy analytic hierarchy process; Lithium-ion battery;
D O I：
10.13335/j.1000-3673.pst.2021.0308
中图分类号：
学科分类号：
摘要：
When using an electric vehicle (EV), there is an increasing trend of cell-to-cell variation in the battery pack. After the battery cells are grouped, the cell-to-cell variation may cause the premature failure of the battery pack and even some safety problems. With the widespread application of cloud data, the EV data can be monitored to evaluate the safety and cell-to-cell variations of the battery packs in the EVs. Although the EV data are sampled with a high frequency, the recording frequency of the cloud data is relatively low, about 10s to 30s. Fortunately, the recording frequency of cloud charging data can reach within 10s. Therefore, the cloud charging data is more suitable for evaluating the cell-to-cell variations of the battery packs in the EVs. Taking the lithium-ion battery pack as the research object, this paper proposes a method of cell-to-cell variation evaluation for the battery packs in EVs with cloud charging data. Based on the cloud charging data, five indicators are analyzed and evaluated, which are the voltage variation, the temperature variation, the internal resistance variation, the capacity variation, and the electric quantity variation. To comprehensively score the cell-to-cell variation of the battery pack, a weighted scoring system is proposed. Further, the fuzzy analytic hierarchy process (FAHP) is used to determine the weight coefficient. Finally, with this scoring system, three battery packs are tested and scored. The experimental results show that the method of evaluation proposed in this paper can effectively distinguish and quantitatively describe the cell-to-cell variations of the battery packs. Besides, this paper also analyzes the data of the EVs. The results show that the method can be effectively applied to engineering and detect the cell-to-cell variation problems before accidents, thereby improving the safety of the EVs. © 2022, Power System Technology Press. All right reserved.
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页码：1049 / 1062
页数：13
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