Summary: This dataset consists of tests performed on a Panasonic 18650PF Li-ion battery to support the development of Neural Network and Kalman Filter State of Charge algorithms, and to aid in creating accurate battery models.
| Parameter | Value |
|---|---|
| Name | Panasonic 18650PF Li-ion Battery Data |
| Labeled | Yes |
| Time Series | Yes |
| Simulation | No |
| Missing Values | No |
| Dataset Characteristics | Multivariate, Time-Series |
| Feature Type | Real |
| Associated Tasks | Regression, State of Charge Estimation |
| Number of Instances | INA |
| Number of Features | INA |
| Date Donated | 21 June 2018 |
| Source | Mendeley Data |
The included tests were performed at the University of Wisconsin-Madison by Dr. Phillip Kollmeyer (phillip.kollmeyer@gmail.com). If this data is utilized for any purpose, it should be appropriately referenced.
The tests can be used to test Neural Network and Kalman Filter State of Charge algorithms, or to develop battery models, and are intended to be a reference so researchers can compare their algorithm and model performance for a standard data set.
Li-ion battery, State of charge, Battery testing, Energy storage, Neural networks