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 - same profile on two cells, boost charge - higher current at low SOC, and three pulsed charge methods). The six 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。针对每节电池单体，首先开展一系列特性表征测试（混合脉冲功率特性测试（Hybrid Pulse Power Characterization, HPPC）、C/20倍率充放电测试等），随后依次开展多组重复的驱动循环放电与15分钟快速充电流程。
上述特性表征与驱动循环测试将持续重复，直至电池单体的健康状态衰减至70%（对应约1500至2000次循环）。每节电池的老化速率存在差异，原因在于其快速充电采用了不同策略：标准恒流恒压（Constant Current Constant Voltage, CC/CV）策略（其中两节电池采用完全一致的充电曲线）、提升型快充（低荷电状态下采用更大电流）以及三种脉冲充电策略。本次测试共使用6节全新3Ah规格的三星INR21700-30T锂离子电池单体，测试全程在25摄氏度的恒温箱内开展，测试设备为Arbin电池循环测试仪。

搜集汇总

背景与挑战

背景概述

该数据集包含三星INR21700-30T锂离子电池在15分钟快速充电条件下的老化测试数据，涵盖六种不同充电方法的对比测试（1500-2000次循环至70%健康状态），旨在为机器学习和传统滤波器的电荷/健康状态估计算法提供训练和测试数据。所有测试均在25°C恒温环境下使用Arbin设备完成，包含特性测试、驱动循环放电和快速充电的重复序列。