This repository contains the codes for all the experiments performed in the paper R. Ibraheem, C. Strange, G. dos Reis, Capacity and internal resistance of lithium-ion batteries: Full degradation curve prediction from voltage response at constant current at discharge, Journal of Power Sources 556 (2023)232477.

• config: configuration files
• experiments: jupyter notebook files for all experiments
• utils: custom modules used in the project

1. Clone the repository by running

   git clone https://github.com/Rasheed19/cc-voltage-project.git
   

2. Navigate to the root folder, i.e., cc-voltage-project and create a python virtual environment by running

   python3 -m venv .venv
   

3. Activate the virtual environment by running

   source .venv/bin/activate
   

4. Prepare all modules by running

   pip install -e .
   

5. Create a folder named data in the root directory cc-voltage-project. Download the following data and put them in this folder:

   • all the batches of data in this link https://data.matr.io/1/ which are the data for the papers Data driven prediciton of battery cycle life before capacity degradation by K.A. Severson, P.M. Attia, et al and Attia, P.M., Grover, A., Jin, N. et al. Closed-loop optimization of fast-charging protocols for batteries with machine learning. Nature 578, 397–402 (2020).
   • the internal resistance data used to complement batch 8 can be downloaded from https://doi.org/10.7488/ds/2957 which is published in the paper Strange, C.; Li, S.; Gilchrist, R.; dos Reis, G. Elbows of Internal Resistance Rise Curves in Li-Ion Cells. Energies 2021, 14, 1206.

6. Create folders named plots and models in the root directory cc-voltage-project to store the generated figures and models respectively.

7. Start running jupyter notebooks in the experiments folder.

8. When you are done experimenting, deactivate the virtual environment by running

   deactivate
   

If you use this work in your project, please cite:

@article{IBRAHEEM2023232477,
    title = {Capacity and Internal Resistance of lithium-ion batteries: Full degradation curve prediction from Voltage response at constant Current at discharge},
    author = {Rasheed Ibraheem and Calum Strange and Gonçalo {dos Reis}},
    journal = {Journal of Power Sources},
    volume = {556},
    pages = {232477},
    year = {2023},
    issn = {0378-7753},
    doi = {https://doi.org/10.1016/j.jpowsour.2022.232477},
    url = {https://www.sciencedirect.com/science/article/pii/S0378775322014549},
}

Licence: CC BY 4.0.