Datasets of three downstream tasks in LLiM

The data for the three downstream tasks are as follows: anomaly detection is a classification task, while SoH estimation and remain range prediction are both regression tasks. The objectives of the three tasks are to identify whether lithium batteries are abnormal, estimate the actual capacity of the lithium battery, and predict the remain riding range of the lithium battery based on the time-series data, respectively

三项下游任务所用数据集如下：异常检测属于分类任务，而SoH（State of Health）估计与剩余骑行续航预测均为回归任务。三项任务的目标分别为基于时序数据识别锂离子电池是否异常、估算锂离子电池的实际容量，以及预测锂离子电池的剩余骑行续航里程。