pydpeet.extract_ocv_dva_ica#

pydpeet.extract_ocv_dva_ica(df_primitives=None, df=None, min_pause_lenght=120.0, min_loops=70, soc_max_voltage=4.21, soc_min_voltage=2.49, soc_c_ref=4.8, savgol=False, savgol_window_lenght_percentage=0.07, visualize=False)[source]#

Compute DVA and ICA curves from given data.

Parameters:

  • df_primitives (DataFrame or None) – DataFrame containing the primitives of the data.

  • df (DataFrame or None) – DataFrame containing the original data.

  • min_pause_lenght (float) – Minimum length of a pause in seconds.

  • min_loops (float) – Minimum number of unique IDs.

  • soc_max_voltage (float) – Maximum voltage of the battery.

  • soc_min_voltage (float) – Minimum voltage of the battery.

  • soc_c_ref (float) – Reference capacity of the battery.

  • savgol (bool) – Whether to apply Savitzky-Golay filter to smooth the data.

  • savgol_window_lenght_percentage (float) – Percentage of the window length for the Savitzky-Golay filter.

  • visualize (bool) – Whether to visualize the DVA and ICA curves over SOC.

Returns:

DataFrame containing all DVA and ICA curves.

Return type:

pd.DataFrame