INR18650-LG-3500-MJ1 Lithium-Ion Battery Cell Complete Continuum Simulation Parameters

Scope This record contains a complete and PyBaMM-compatible parameter set for the INR18650-LG-3500-MJ1 cell and incomplete versions of it that were used in an exempular GITT characterization workflow. Most parameters are repackaged laboratory measurement results and SOC alignment checks with a GITT (without intermittent EIS) measurement on the harvested electrodes. Files Metadata Filename Description Format Usage lg_mj1.py A PyBaMM-compatible parameter set obtained from laboratory characterization of MJ1 battery cells and a characterization of GITT measurements with the DFN model. Python script (.py) Adequate dataset for a digital twin simulation of the MJ1 cell. lg_mj1_parameterize_negative_diffusivity_lithiation.py A PyBaMM-compatible parameter set obtained from laboratory characterization of MJ1 battery cells in lithiation direction with inherent parameter uncertainties and a prior parameter distribution for the negative electrode diffusivity. Python script (.py) Used for lithiation GITT characterization with the SPM, SPMe, and DFN models. lg_mj1_parameterize_positive_diffusivity_lithiation.py A PyBaMM-compatible parameter set obtained from laboratory characterization of MJ1 battery cells in lithiation direction with inherent parameter uncertainties and a prior parameter distribution for the positive electrode diffusivity. Python script (.py) Used for lithiation GITT characterization with the SPM, SPMe, and DFN models. lg_mj1_parameterize_negative_diffusivity_delithiation.py A PyBaMM-compatible parameter set obtained from laboratory characterization of MJ1 battery cells in delithiation direction with inherent parameter uncertainties and a prior parameter distribution for the negative electrode diffusivity. Python script (.py) Used for delithiation GITT characterization with the SPM, SPMe, and DFN models. lg_mj1_parameterize_positive_diffusivity_delithiation.py A PyBaMM-compatible parameter set obtained from laboratory characterization of MJ1 battery cells in delithiation direction with inherent parameter uncertainties and a prior parameter distribution for the positive electrode diffusivity. Python script (.py) Used for delithiation GITT characterization with the SPM, SPMe, and DFN models. Related Resources Relationship Record Description isPartOf INR18650-LG-3500-MJ1 Lithium-Ion Battery Cell Characterization Data This collection contains records related to laboratory characterization of INR18650-MJ1 cells manufactured by LG Chem. The records contain (i) the raw data provided by laboratory personnel and (ii) model parameters obtained from processing this raw data. The data contained in these records is intended to support model parameterization for INR18650-MJ1 cells and could also be relevant for other Li-ion batteries using NMC, Graphite, and Silicon Oxide as active materials. Continues INR18650-LG-3500-MJ1 Anode GITT Parameters This record contains parameters fitted from a GITT (without intermittent EIS) measurement on the harvested ngative electrode (anode) of the INR18650-MJ1 Li-ion battery cell from LG CHEM. Continues INR18650-LG-3500-MJ1 Anode GITT OCV Model Fit This record contains an open-circuit voltage (OCV) model fitted to OCV curves from GITT measurements during discharging and charging. The GITT measurements were obtained from negative electrode (anode) harvested from an INR18650-MJ1 Li-ion battery cell manufactured by LG CHEM. The active material in the electrode is composite graphite/silicon oxide. The measurment is obtained in three-electrode configuration with the working electrode composite graphite/silicon oxide, counter electrode NMC, and reference electrode lithium metal in a coin cell casing. Continues INR18650-LG-3500-MJ1 Lithium-Ion Battery Cell Direct Characterization Data This record contains characterization data of components harvested from INR18650-LG-3500-MJ1 #001 cell used in the DLReps project. The characterization was performed using a combination of destructive techniques including half-cell electrochemical testing, SEM, and EDX analysis. The source data is contained in the files MJ1_parameters.xlsx and MJ1-Parameters.pptx, which is then processed to obtain the extracted and encapsulated data (images and parquet files). IsContinuedBy 18650-LG-3500-MJ1 Anode GITT Featurization This record contains workflows to extract feactures from the GITT (without intermittent EIS) measurement on the harvested negative electrode (anode) of the INR18650-MJ1 Li-ion battery cell from LG CHEM. It simulteaneously sets up the simulator and EP-BOLFI optimizer inputs for later parameterization. IsContinuedBy 18650-LG-3500-MJ1 Anode GITT Parameterization This record contains workflows to parameterize with EP-BOLFI a GITT (without intermittent EIS) measurement. Licensing This dataset is licensed under CC-BY 4.0, allowing for sharing and adaptation with proper attribution. Contact Information For questions or further assistance, please contact Dennis Kopljar at [e-mail]. References This dataset is linked to the following publication: [DOI/Link to publication].### 数据集范围 本记录包含一套完整且适配PyBaMM的INR18650-LG-3500-MJ1型锂离子电池电芯参数集，以及用于示例性恒电流间歇滴定技术（Galvanostatic Intermittent Titration Technique，GITT）表征工作流的该参数集不完全版本。多数参数经重新封装整理，源自实验室测量结果，以及对取出电极进行GITT（无间歇电化学阻抗谱（Electrochemical Impedance Spectroscopy，EIS））测量得到的荷电状态（State of Charge，SOC）对齐校验结果。 ### 文件 #### 元数据 | 文件名 | 描述 | 格式 | 用途 | | --- | --- | --- | --- | | lg_mj1.py | 适配PyBaMM的参数集，源自MJ1电池电芯的实验室表征以及采用多伊尔-富勒-纽曼模型（Doyle-Fuller-Newman model，DFN）的GITT测量表征 | Python脚本（.py） | 可用于MJ1电芯的数字孪生仿真的合格数据集 | | lg_mj1_parameterize_negative_diffusivity_lithiation.py | 适配PyBaMM的参数集，源自MJ1电池电芯在嵌锂方向的实验室表征，带有固有参数不确定性以及负极扩散系数的先验参数分布 | Python脚本（.py） | 可与单粒子模型（Single Particle Model，SPM）、带电解液的单粒子模型（Single Particle Model with Electrolyte，SPMe）及DFN模型配合，用于嵌锂方向GITT表征 | | lg_mj1_parameterize_positive_diffusivity_lithiation.py | 适配PyBaMM的参数集，源自MJ1电池电芯在嵌锂方向的实验室表征，带有固有参数不确定性以及正极扩散系数的先验参数分布 | Python脚本（.py） | 可与SPM、SPMe及DFN模型配合，用于嵌锂方向GITT表征 | | lg_mj1_parameterize_negative_diffusivity_delithiation.py | 适配PyBaMM的参数集，源自MJ1电池电芯在脱锂方向的实验室表征，带有固有参数不确定性以及负极扩散系数的先验参数分布 | Python脚本（.py） | 可与SPM、SPMe及DFN模型配合，用于脱锂方向GITT表征 | | lg_mj1_parameterize_positive_diffusivity_delithiation.py | 适配PyBaMM的参数集，源自MJ1电池电芯在脱锂方向的实验室表征，带有固有参数不确定性以及正极扩散系数的先验参数分布 | Python脚本（.py） | 可与SPM、SPMe及DFN模型配合，用于脱锂方向GITT表征 | ### 相关资源 #### 关联关系 | 关联类型 | 关联记录 | 描述 | | --- | --- | --- | | 隶属于 | INR18650-LG-3500-MJ1锂离子电池电芯表征数据集 | 该数据集集合包含与LG Chem制造的INR18650-MJ1电芯实验室表征相关的多条记录。这些记录包含（i）实验室人员提供的原始数据，以及（ii）经该原始数据处理得到的模型参数。本数据集旨在为INR18650-MJ1电芯的模型参数化提供支持，同时也可用于其他以镍锰钴（Nickel Manganese Cobalt，NMC）、石墨及氧化硅作为活性材料的锂离子电池相关研究。 | | 延续自 | INR18650-LG-3500-MJ1负极GITT参数 | 本记录包含从LG CHEM生产的INR18650-MJ1锂离子电池电芯取出的负极（阳极）上获取的、经GITT（无间歇EIS）测量拟合得到的参数。 | | 延续自 | INR18650-LG-3500-MJ1负极GITT开路电压（Open-Circuit Voltage，OCV）模型拟合 | 本记录包含针对充放电过程中GITT测量所得开路电压曲线拟合得到的OCV模型。该GITT测量数据源自从LG CHEM生产的INR18650-MJ1锂离子电池电芯取出的负极（阳极），该电极的活性材料为石墨/氧化硅复合体系。测量采用三电极体系：工作电极为石墨/氧化硅复合电极、对电极为NMC电极、参比电极为锂金属，封装于扣式电池壳中。 | | 延续自 | INR18650-LG-3500-MJ1锂离子电池电芯直接表征数据集 | 本记录包含从DLReps项目所用的INR18650-LG-3500-MJ1 #001电芯上取出的组件的表征数据。表征采用包括半电池电化学测试、扫描电子显微镜（Scanning Electron Microscopy，SEM）及能量色散X射线光谱（Energy Dispersive X-ray Spectroscopy，EDX）分析在内的破坏性表征技术组合完成。源数据存储于MJ1_parameters.xlsx和MJ1-Parameters.pptx文件中，经处理后得到提取并封装的各类数据（图像文件及Parquet格式文件）。 | | 被以下记录延续 | 18650-LG-3500-MJ1负极GITT特征提取 | 本记录包含从LG CHEM生产的INR18650-MJ1锂离子电池电芯取出的负极（阳极）的GITT（无间歇EIS）测量数据中提取特征的工作流，可同时为后续参数化配置仿真器与EP-BOLFI优化器输入。 | | 被以下记录延续 | 18650-LG-3500-MJ1负极GITT参数化 | 本记录包含采用EP-BOLFI对GITT（无间歇EIS）测量进行参数化的工作流。 | ### 授权说明 本数据集采用知识共享署名4.0（CC-BY 4.0）许可协议进行授权，允许在注明原作者的前提下进行共享与改编。 ### 联系方式 如有疑问或进一步协助需求，请联系Dennis Kopljar，邮箱：[e-mail]。 ### 参考文献 本数据集关联以下出版物：[出版物DOI/链接]。