Lithium-ion battery manufacturing is a multiprocess serial system and the consistency of each single cell will affect the performance and safety of battery system after grouping. Therefore, optimizing the battery preparation process and improving the battery consistency have become the key technical issues in battery preparation process. In this study, the inconsistency of finished batteries caused by manufacturing process is analyzed from three processes: electrode preparation, battery assembly, and liquid injection and formation and the structure–activity relationship between manufacturing process data and battery consistency is studied. Taking the actual capacity, self-discharge rate, and internal resistance of single cell as target variables, the correlation coefficient matrix between original process variables and target variables is constructed by using correlation analysis method and the correlation index between process variables and target variables is obtained. The multiple linear regression model is established by stepwise regression method and the weight of original process variables affecting battery consistency is deduced. The results show that the data of multiple process links have a high influence weight on the actual capacity and self-discharge rate of batteries, which provide a theoretical model for the key strategies of improving quality consistency in lithium-ion battery industry.

中文翻译：

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基于相关系数和多元线性回归模型的车用锂离子电池制造过程一致性影响因素研究

锂离子电池制造是一个多工序串联系统，每个单体电池的一致性会影响分组后电池系统的性能和安全性。因此，优化电池制备工艺，提高电池一致性成为电池制备工艺中的关键技术问题。本研究从电极制备、电池组装、注液成型三个过程分析制造工艺导致的成品电池不一致性，研究制造工艺数据与电池一致性之间的构效关系。以单体电池的实际容量、自放电率、内阻为目标变量，采用相关分析方法构建原始过程变量与目标变量的相关系数矩阵，得到过程变量与目标变量的相关指数。采用逐步回归方法建立多元线性回归模型，推导出影响电池一致性的原始工艺变量的权重。结果表明，多个工艺环节的数据对电池的实际容量和自放电率具有较高的影响权重，为锂离子电池行业提高质量一致性的关键策略提供了理论模型。采用逐步回归方法建立多元线性回归模型，推导出影响电池一致性的原始工艺变量的权重。结果表明，多个工艺环节的数据对电池的实际容量和自放电率具有较高的影响权重，为锂离子电池行业提高质量一致性的关键策略提供了理论模型。采用逐步回归方法建立多元线性回归模型，推导出影响电池一致性的原始工艺变量的权重。结果表明，多个工艺环节的数据对电池的实际容量和自放电率具有较高的影响权重，为锂离子电池行业提高质量一致性的关键策略提供了理论模型。