锂(药物)
表征(材料科学)
电池(电)
离子
锂离子电池
材料科学
计算机科学
化学
纳米技术
物理
医学
有机化学
内科学
热力学
功率(物理)
作者
Simone Fasolato,Nicola Blasuttigh,Giacomo Galuppini,Davide Martino Raimondo
出处
期刊:Data in Brief
[Elsevier BV]
日期:2025-01-18
卷期号:58: 111301-111301
被引量:4
标识
DOI:10.1016/j.dib.2025.111301
摘要
This paper presents an experimental dataset for a batch of eleven prismatic CALB L148N58A lithium-ion B-grade battery cells with a nominal capacity of 58 Ah. The experimental campaign, conducted at the Energy Laboratory for Interdisciplinary Storage Applications (ELISA) at the University of Trieste, Italy, employs non-destructive tests to assess the performance of each cell within the batch. The cell-level testing procedures include fixed Constant Current Constant Voltage (CCCV) charging and Constant Current (CC) discharging at low current rates, Hybrid Pulse Power Characterization (HPPC) tests at various C-rates (i.e., 1C and C/3), Electrochemical Impedance Spectroscopy (EIS) at different State of Charge (SOC) levels, and three distinct driving cycles (WLTP, UDDS and US06). All the experiments were conducted at three different ambient temperatures (10°C, 25°C, and 40°C), resulting in a comprehensive dataset for assessing the performance metrics of the battery cells. This dataset provides valuable insights into post-manufacturing cell-to-cell variations in performance metrics such as capacity and impedance within a batch of fresh cells. Additionally, it serves as a crucial resource for developing battery models, including physics-based, empirical, and data-driven approaches. Moreover, it may contribute to validate model-based and data-driven estimation and control strategies within battery management systems, enhancing the reliability and efficiency of energy storage solutions.
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