galpynostatic
galpynostatic is a Python/C++ package with physics-based and data-driven models to predict optimal conditions for fast-charging lithium-ion batteries.
Contact
If you have any questions, you can contact me at ffernandev@gmail.com
Requirements
You need Python 3.12+ to run galpynostatic. All other dependencies, which are the usual ones of the scientific computing stack (matplotlib, NumPy, pandas, scikit-learn and SciPy), are installed automatically.
Code Repository
Contents
API Reference
- galpynostatic package
galpynostatic.make_predictionmodulegalpynostatic.metricmodulegalpynostatic.modelmodulegalpynostatic.plotmodulegalpynostatic.preprocessingmodulegalpynostatic.simulationmodulegalpynostatic.utilsmodulegalpynostatic.datasetssubmodulegalpynostatic.datasets.paramssubmodulegalpynostatic.base(dev module)
Citations
If you use galpynostatic in a scientific publication, we would appreciate it if you could cite the main article of the package:
F. Fernandez, E. M. Gavilán-Arriazu, D. E. Barraco, A. Visintin, Y. Ein-Eli and E. P. M. Leiva. “Towards a fast-charging of LIBs electrode materials: a heuristic model based on galvanostatic simulations.” Electrochimica Acta 464 (2023): 142951.
For certain modules of the code, please refer to other works:
galpynostatic.metric: TODO DOI
galpynostatic.datasets: https://doi.org/10.1002/cphc.202200665
BibTeX entries can be found in the CITATIONS.bib file.