MIT/Stanford Data-driven Prediction of Battery Cycle Life Dataset

The raw dataset was found to be contaminated with different anomalies. Due to the large number of cells used for the experiments in their works, we have only used the experimental dataset from 46 cells in this study. Each cell has an average of 845 cycles, which is more than sufficient for benchmarking anomaly detection algorithms in the present study. In addition, we have also enriched the raw dataset by manually labelling normal (denoted as 0) vs anomalous cycle (denoted as 1) for each cycle across all 46 cells.

cell cycling dataset with anomalies from severson dataset

Battery Chemistry Description

Property

MIT/Stanford

Positive electrode

LFP (LiFePO₄)

Electrolyte

Liquid electrolyte

Negative electrode

Graphite

Number of cells

46 cells

Nominal capacity

1.1 Ah

Discharging C-rates

4 C (1C ≈ 1.1 A)

ΔSOC in %

100%

Theoretical voltage limits

2.0 V - 3.6 V

Operating temperature

30 °C

Anomalous data type

Discharge-capacity profile

Data source

Severson et al.

Train and Test Dataset

The dataset from 46 cells is split into training dataset (train_dataset_severson.db) and test dataset (test_dataset_severson.db). The features used for anomaly detection were further extracted and saved in another database, so that the pipeline can be automated for all cells in a leaner manner. The same protocols used for creating the training features are applied to create the test features.

Dataset Information

  • Total number of cells: 46

  • Number of cells for Training (train_dataset_severson.db): 23

  • Number of cells for Testing (test_dataset_severson.db): 23

  • Average number of cycles for each cell: 845 (Maximum: 1226, Minimum: 648)

  • File format: SQLite database file (.db)

  • File Size: Training set - 195 Mb, Test set-169 Mb

  • Missing values: None (100% complete dataset)

  • Target variable: outlier (1 for outlier, 0 for normal cycle)

Features Description

Using cell: 2017-05-12_5_4C-70per_3C_CH17 as an example.

Feature Details

Feature

Type

Description

Range/Values

Anomaly Relevance

test_time

Float

Experimental test time in [seconds]

0 - 390923.69

Low

cycle_index

Integer

Discharge cycle index of the experiment

0 - 691

Low

cell_index

String

Identifier for the tested cell

voltage

Float

Measured voltage during the experiment in [V]

1.99 - 4.62

High

discharge_capacity

Float

Cell discharge capacity measured in [Ah]

0 - 2.88

High

current

Float

Current applied at the given test step measured in [A]

-4.40 – -0.02

Medium

internal_resistance

Float

Measured internal resistance of the system [Ohm]

0.01 - 0.02

Medium

temperature

Float

Recorded temperature during the experiment in [°C]

25.14 - 39.73

Medium

outlier

Bool

Boolean flag (0/1) marking whether the data point is an outlier

0, 1

TARGET VARIABLE

Data Quality Assessment

  • 100% data completeness ensures robust model training and validation.

  • 0.47% positive cases on average for each cell (outlier cycles). This makes it a highly imbalanced anolmaly detection problem.

  • 0 duplicate or corrupted records.

  • 0 bad outlier label values.

  • 103 observations where voltage is outside chemistry limits [0.1, 4.5]

  • 0 observations where temperature is outside safe range (-40°C to 90°C).

  • 40 observations where internal resistance ≤ 0.

  • 0 observations with ≤ 0 discharge capacity.

  • Wide range of cycle numbers (1226-648) in training cells for better generalization and validation for different test datasets.

  • Wide range of experimental test time for train cells from 108 - 252 hrs.

  • Major and Minor anomalous cycles included in the dataset.

Sample Dataset for Cell 2017-05-12_5_4C-70per_3C_CH17

Note

Only the first 50 rows are shown here to give a feel for the data. See the repository for the full dataset.

test_time cycle_index cell_index voltage discharge_capacity current internal_resistance temperature outlier
1801.8192 0.0 2017-05-12_5_4C-70per_3C_CH17 3.291887 0.000013 -0.429022 0.021567 30.086733 1
1810.4760 0.0 2017-05-12_5_4C-70per_3C_CH17 3.281853 0.001368 -0.562722 0.021567 30.087885 1
1820.4780 0.0 2017-05-12_5_4C-70per_3C_CH17 3.277881 0.002930 -0.562731 0.021567 30.103170 1
1830.4810 0.0 2017-05-12_5_4C-70per_3C_CH17 3.275130 0.004494 -0.562708 0.021567 30.103170 1
1830.4811 0.0 2017-05-12_5_4C-70per_3C_CH17 3.275130 0.004494 -0.562708 0.021567 30.115175 1
1840.4906 0.0 2017-05-12_5_4C-70per_3C_CH17 3.272992 0.006059 -0.562737 0.021567 30.067207 1
1850.4939 0.0 2017-05-12_5_4C-70per_3C_CH17 3.271236 0.007622 -0.562697 0.021567 30.100651 1
1860.4959 0.0 2017-05-12_5_4C-70per_3C_CH17 3.270297 0.009186 -0.562731 0.021567 30.084396 1
1870.4972 0.0 2017-05-12_5_4C-70per_3C_CH17 3.268752 0.010747 -0.562722 0.021567 30.067207 1
1880.5067 0.0 2017-05-12_5_4C-70per_3C_CH17 3.267866 0.012313 -0.562724 0.021567 30.127209 1
1890.5086 0.0 2017-05-12_5_4C-70per_3C_CH17 3.267042 0.013875 -0.562703 0.021567 30.037971 1
1900.5112 0.0 2017-05-12_5_4C-70per_3C_CH17 3.266493 0.015439 -0.562721 0.021567 30.107929 1
1910.5139 0.0 2017-05-12_5_4C-70per_3C_CH17 3.265641 0.016998 -0.562713 0.021567 30.094955 1
1920.5166 0.0 2017-05-12_5_4C-70per_3C_CH17 3.265156 0.018568 -0.562683 0.021567 30.151680 1
1930.5194 0.0 2017-05-12_5_4C-70per_3C_CH17 3.264662 0.020127 -0.562742 0.021567 30.152626 1
1940.5209 0.0 2017-05-12_5_4C-70per_3C_CH17 3.264221 0.021692 -0.562741 0.021567 30.152626 1
1940.5210 0.0 2017-05-12_5_4C-70per_3C_CH17 3.264221 0.021692 -0.562741 0.021567 30.125301 1
1950.5222 0.0 2017-05-12_5_4C-70per_3C_CH17 3.263810 0.023256 -0.562713 0.021567 30.098951 1
1960.5369 0.0 2017-05-12_5_4C-70per_3C_CH17 3.263316 0.024822 -0.562723 0.021567 30.098951 1
1960.5370 0.0 2017-05-12_5_4C-70per_3C_CH17 3.263316 0.024822 -0.562723 0.021567 30.074696 1
1970.5388 0.0 2017-05-12_5_4C-70per_3C_CH17 3.262977 0.026380 -0.562716 0.021567 30.116869 1
1980.5432 0.0 2017-05-12_5_4C-70per_3C_CH17 3.262585 0.027949 -0.562696 0.021567 30.116869 1
1980.5433 0.0 2017-05-12_5_4C-70per_3C_CH17 3.262585 0.027949 -0.562696 0.021567 30.103893 1
1990.5473 0.0 2017-05-12_5_4C-70per_3C_CH17 3.262277 0.029511 -0.562686 0.021567 30.112867 1
2000.5515 0.0 2017-05-12_5_4C-70per_3C_CH17 3.261970 0.031059 -0.562692 0.021567 30.112867 1
2000.5516 0.0 2017-05-12_5_4C-70per_3C_CH17 3.261970 0.031059 -0.562692 0.021567 30.117811 1
2010.5662 0.0 2017-05-12_5_4C-70per_3C_CH17 3.261719 0.032642 -0.562717 0.021567 30.118996 1
2020.5802 0.0 2017-05-12_5_4C-70per_3C_CH17 3.261459 0.034193 -0.562729 0.021567 30.143436 1
2030.5909 0.0 2017-05-12_5_4C-70per_3C_CH17 3.261168 0.035767 -0.562705 0.021567 30.143436 1
2030.5910 0.0 2017-05-12_5_4C-70per_3C_CH17 3.261168 0.035767 -0.562705 0.021567 30.117083 1
2040.6062 0.0 2017-05-12_5_4C-70per_3C_CH17 3.260855 0.037339 -0.562703 0.021567 30.117083 1
2040.6063 0.0 2017-05-12_5_4C-70per_3C_CH17 3.260855 0.037339 -0.562703 0.021567 30.107929 1
2050.6105 0.0 2017-05-12_5_4C-70per_3C_CH17 3.260563 0.038896 -0.562715 0.021567 30.052101 1
2060.6195 0.0 2017-05-12_5_4C-70per_3C_CH17 3.260436 0.040467 -0.562729 0.021567 30.138063 1
2070.6205 0.0 2017-05-12_5_4C-70per_3C_CH17 3.260166 0.042016 -0.562724 0.021567 30.138063 1
2070.6206 0.0 2017-05-12_5_4C-70per_3C_CH17 3.260166 0.042016 -0.562724 0.021567 30.089340 1
2080.6272 0.0 2017-05-12_5_4C-70per_3C_CH17 3.259867 0.043594 -0.562752 0.021567 30.071968 1
2090.6290 0.0 2017-05-12_5_4C-70per_3C_CH17 3.259577 0.045151 -0.562738 0.021567 30.071968 1
2090.6291 0.0 2017-05-12_5_4C-70per_3C_CH17 3.259577 0.045151 -0.562738 0.021567 30.069845 1
2100.6317 0.0 2017-05-12_5_4C-70per_3C_CH17 3.259337 0.046707 -0.562717 0.021567 30.065424 1
2110.6447 0.0 2017-05-12_5_4C-70per_3C_CH17 3.259079 0.048280 -0.562729 0.021567 30.065424 1
2110.6448 0.0 2017-05-12_5_4C-70per_3C_CH17 3.259079 0.048280 -0.562729 0.021567 30.063540 1
2120.6553 0.0 2017-05-12_5_4C-70per_3C_CH17 3.258783 0.049847 -0.562735 0.021567 30.063540 1
2120.6554 0.0 2017-05-12_5_4C-70per_3C_CH17 3.258783 0.049847 -0.562735 0.021567 30.079763 1
2130.6589 0.0 2017-05-12_5_4C-70per_3C_CH17 3.258705 0.051403 -0.562735 0.021567 29.983484 1
2140.6674 0.0 2017-05-12_5_4C-70per_3C_CH17 3.258512 0.052973 -0.562725 0.021567 30.091805 1
2150.6714 0.0 2017-05-12_5_4C-70per_3C_CH17 3.258246 0.054541 -0.562708 0.021567 30.046875 1
2160.6805 0.0 2017-05-12_5_4C-70per_3C_CH17 3.258018 0.056097 -0.562725 0.021567 30.046875 1
2160.6806 0.0 2017-05-12_5_4C-70per_3C_CH17 3.258018 0.056097 -0.562725 0.021567 30.023558 1
2170.6856 0.0 2017-05-12_5_4C-70per_3C_CH17 3.257801 0.057662 -0.562716 0.021567 30.003332 1

Citation

Severson, K.A., Attia, P.M., Jin, N. et al. Data-driven prediction of battery cycle life before capacity degradation. Nat Energy 4, 383–391 (2019). https://doi.org/10.1038/s41560-019-0356-8