Data and code for target dependent cleaner production screening of end of life electric vehicle lithium ion battery recycling pathways

Description

This dataset contains the cleaned data and reproducible code associated with the study “Target dependent cleaner production screening of recycling pathways for end of life electric vehicle lithium ion batteries using an interpretable machine learning framework”. The package provides harmonized scenario tables, deterministic target outputs, machine learning baseline inputs and results, uncertainty and robustness diagnostics, interpretability outputs, and figure source data for evaluating recycling pathways of end of life electric vehicle lithium ion batteries. The dataset supports target dependent cleaner production screening across recycling route, cathode chemistry, region, year, electricity scenario, cell basis and pack basis functional units. It is intended to allow readers to reproduce the main computational results, inspect route ranking logic, and verify the data products used for manuscript figures and supplementary analyses.

Steps to reproduce

1. Download and unzip the data and code package. 2. Create a Python environment and install the dependencies listed in requirements.txt. 3. Open the README file and follow the scripts in the documented order. 4. Run the deterministic target scripts to regenerate scenario level target tables. 5. Run the machine learning baseline scripts to reproduce model validation outputs. 6. Run the uncertainty and interpretability scripts to reproduce robustness and driver diagnostics. 7. Compare the generated outputs with the processed data and figure source tables included in the package.

Institutions

• Wuhan University of Science and Technology

  Hubei, Wuhan

Categories

Licence