Battery Aging Dataset for 15 Minute Fast Charging of Samsung 30T Cells

This aging dataset was designed to be used for training/parameterization and testing of machine learning and conventional filter based state of charge and state of health estimation models. A number of characterization tests (HPPC, C/20 charge discharge, etc) are applied to each cell and are followed by repeating series of drive cycle discharges and a fifteen minute fast charge. The characterization and drive cycle tests are repeated until the battery cells reach 70% SOH (around 1500 to 2000 cycles). The rate of aging for each cell is different because each cell is fast charged using a different method (standard CC/CV, boost charge - higher current at low SOC, and two pulsed charge methods). The four cells tested are brand new 3Ah Samsung INR21700-30T lithium ion battery cells. The testing was performed in a thermal chamber at 25 degrees Celsius using an Arbin battery cycler.

本老化数据集专为机器学习与传统基于滤波器的荷电状态（State of Charge, SOC）及健康状态（State of Health, SOH）估算模型的训练、参数配置与测试而设计。针对每一颗电池单体，均开展了一系列特性表征测试（含HPPC、C/20充放电等），随后依次执行多组驱动循环放电工况与单次15分钟快充流程。上述特性表征测试与驱动循环测试将持续重复，直至电池单体的健康状态降至70%（对应约1500至2000次循环）。由于本次测试的四颗电池单体采用了不同的快充方案——包括标准恒流恒压充电、低SOC下大电流升压快充，以及两种脉冲充电方案，因此每颗电池的老化速率存在差异。本次测试所用的四颗单体均为全新三星INR21700-30T型3Ah锂离子电池，测试全程在25摄氏度的恒温试验箱中通过Arbin电池循环测试仪完成。