基于DRT的锂离子电池建模框架
DRT-based modelling framework for Li-ion cells
摘要：
正确评估电池状态对于最大限度地提高电池组性能同时确保可靠和安全运行至关重要。本文介绍了一种基于弛豫时间分布（DRT）的新型锂离子电池建模框架EIS 2 MOD。从电化学阻抗谱（EIS）和开路电压（OCV）测量出发，开发了基于物理的电路模型（ECM）。应用DRT对EIS中的电化学现象进行反卷积。所提出的方法是基于：i）从EIS的DRT计算，ii）DRT分析ECM配置和iii）模型参数提取和拟合。所提出的框架适用于大型锂离子软包电池，在整个充电状态（SoC）范围和宽温度范围（-10 ° C至35°C）内进行测试。已经测试了不同的电流曲线以验证模型，显示出其在再现电池单元行为方面的高精度（例如，对于可变温度和SoC下的驾驶循环模拟，电池端子电压的RMSE低于1.50%）。EIS 2 MOD的另一个优点是其计算负载轻，从而为电池管理系统的实现提供了一个有吸引力的框架。
英文摘要：
The correct assessment of battery states is essential to maximize battery pack performances while ensuring reliable and safe operation. This work introduces EIS2MOD, a novel modelling framework for Li-ion cells based on Distribution of Relaxation Time (DRT). A physically based Electric Circuit Model (ECM) is developed starting from Electrochemical Impedance Spectroscopy (EIS) and Open Circuit Voltage (OCV) measurements. DRT is applied to deconvolve the electrochemical phenomena from the EIS. The presented methodology is based on: i) DRT calculation from EIS, ii) DRT analysis for ECM configuration and iii) Model parameters extraction and fitting. The proposed framework is applied to large format Li-ion pouch cells, which are tested over the whole State of Charge (SoC) range and a wide temperature range (-10°C to 35°C). Different current profiles have been tested to validate the model, showing its high accuracy in reproducing the battery cell behavior (e.g. RMSE on the battery terminals voltage lower than 1.50% for driving cycle simulations at variable temperature and SoC). An additional advantage of EIS2MOD is its light computational load thus offering an attractive framework for battery management system implementation.
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