Ternary lithium battery capacity detection method based on machine learning

The invention discloses a ternary lithium battery capacity detection method based on machine learning, and the method comprises the following steps: obtaining battery data, and constructing a data set based on the battery data; performing data dimension reduction and standardization processing on the data set; constructing a battery capacity detection model, training the battery capacity detection model through the data set, and evaluating the trained model; and inputting newly collected battery data into the evaluated battery capacity detection model to realize real-time online detection of the battery capacity. According to the invention, the technical problem of how to accurately and rapidly carry out accurate nondestructive detection on the battery capacity and output the result is solved. 本发明公开了一种基于机器学习的三元锂电池容量检测方法，其中，包括以下步骤：获取电池数据，并基于所述电池数据构建数据集；将所述数据集进行数据降维以及标准化处理；构建电池容量检测模型，通过所述数据集对电池容量检测模型进行训练，并对训练后的模型进行评估；将新采集的电池数据输入到完成评估后的电池容量检测模型中，即可实现对电池容量的实时在线检测。本发明解决了如何准确且快速的对电池容量进行精准无损检测并输出结果的技术问题。