Searching for a Pulse: Evaluating the Use of Rapid DC Pulses for Diagnosing Battery Health, State-of-Charge, and Safety

This is the data and code associated with the manuscript 'Searching for a pulse: Evaluating the Use of Rapid DC Pulses for Diagnosing Battery Health, State-of-Charge, and Safety', link: https://iopscience.iop.org/article/10.1149/1945-7111/addd50/meta.

A collection of about 50,000 independent DC pulse sequences, collected from ~80 cells of 4 different types of commercially produced Li-ion batteries, with varying state-of-health (lab-aged, field-aged, and both), pulse state-of-charge, pulse design, pulse current, battery temperature, and battery hysteresis, while also measuring battery performance metrics relevant to a variety of battery applications (rate capability, mobility application, and stationary energy storage application). To diagnose safety, we have attempted to quantify potential safety and reliability issues using both electrochemical (post-charge voltage relaxation) and physical methods (rapid X-ray CT screening). We then use machine-learning methods to predict different target metrics using rapid pulse data and analyze results.

Code with potential future updates to analysis is also at https://github.com/NREL/battery_pulse_diagnostics

本数据集配套有研究论文《探寻脉冲信号：评估快速直流脉冲在电池健康状态、荷电状态与安全诊断中的应用》（原标题：Searching for a pulse: Evaluating the Use of Rapid DC Pulses for Diagnosing Battery Health, State-of-Charge, and Safety）的相关数据与代码，论文链接：https://iopscience.iop.org/article/10.1149/1945-7111/addd50/meta。
该数据集包含约50000组独立直流脉冲序列，采集自4种商用锂离子电池（Li-ion batteries）的约80颗电芯，涵盖实验室老化、现场老化及二者兼具的不同健康状态（State-of-Health, SOH），并覆盖了脉冲荷电状态（State-of-Charge, SOC）、脉冲设计参数、脉冲电流、电池温度与电池滞后效应；同时测量了适配多类电池应用场景的核心性能指标，包括倍率性能、移动储能应用性能及固定式储能应用性能。
为开展电池安全诊断，本研究通过电化学方法（充电后电压弛豫过程）与物理检测方法（快速X射线计算机断层扫描（X-ray Computed Tomography, CT）筛查）对潜在安全与可靠性隐患进行量化表征；随后借助机器学习方法，基于快速脉冲数据预测各类目标指标，并对分析结果展开系统性研究。
此外，包含后续可能更新的分析代码已托管于：https://github.com/NREL/battery_pulse_diagnostics