Full factorial design of experiments dataset for parallel-connected lithium-ion cells imbalanced performance investigation

被引:5
|
作者
Piombo, Gabriele [1 ,2 ]
Fasolato, Simone [1 ,3 ]
Heymer, Robert [2 ]
Hidalgo, Marc F. [2 ]
Niri, Mona Faraji [2 ]
Raimondo, Davide M. [3 ]
Marco, James [2 ]
Onori, Simona [1 ]
机构
[1] Stanford Univ, Dept Energy Sci & Engn, Stanford, CA 94305 USA
[2] Univ Warwick, WMG, Coventry, England
[3] Univ Pavia, Dept Elect Comp & Biomed Engn, Pavia, Italy
来源
DATA IN BRIEF | 2024年 / 53卷
关键词
Lithium -ion battery; Parallel -connected cells; Cell -to -cell parameters variation; Current and temperature imbalance; Design of experiments; Cell characterisation; MULTISINE SIGNALS;
D O I
10.1016/j.dib.2024.110227
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This paper shares an experimental dataset of lithium-ion battery parallel-connected modules. The campaign, conducted at the Stanford Energy Control Laboratory, employs a comprehensive full factorial Design of Experiment methodology on ladder-configured parallel strings. A total of 54 test conditions were investigated under various operating temperatures, cell-to-cell interconnection resistance, cell chemistry, and aging levels. The module-level testing procedure inand Constant Current (CC) discharge. Beyond monitoring total module current and voltage, Hall sensors and thermocouples were employed to measure the signals from each individual cell to quantify both current and temperature distribution within each tested module configuration. Additionally, the dataset contains cell characterization data for every cell (i.e. NCA Samsung INR21700-50E and NMC LG-Chem INR21700-M50T) used in the module-level experiments. This dataset provides valuable resources for developing battery physics-based, empirical, and data-driven models at single cell and module level. Ultimately, it contributes to advance our understanding of how cell-to-cell heterogeneity propagates within the module and how that affects the overall system performance. (c) 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
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页数:14
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