Citation¶
If you use BatteryML in your research, please cite:
BatteryML Citation¶
@misc{batteryml2024,
title={BatteryML: A Modular Platform for Battery Degradation Modeling},
author={Research Module},
year={2024},
publisher={GitHub},
howpublished={\url{https://github.com/yourusername/battery-ml}}
}
Dataset Citation¶
LG M50T Dataset¶
@article{enmg_data,
title={Lithium-ion battery degradation: Measuring rapid loss of active silicon in silicon-graphite composite electrodes},
author={ENMG Oxford},
journal={Oxford Battery Intelligence Lab},
year={2023},
note={LG M50T Dataset}
}
Related Citations¶
Neural ODEs¶
@article{chen2018neural,
title={Neural Ordinary Differential Equations},
author={Chen, Ricky T. Q. and Rubanova, Yulia and Bettencourt, Jesse and Duvenaud, David K.},
journal={Advances in Neural Information Processing Systems},
year={2018}
}
SHAP¶
@article{lundberg2017unified,
title={A Unified Approach to Interpreting Model Predictions},
author={Lundberg, Scott M. and Lee, Su-In},
journal={Advances in Neural Information Processing Systems},
year={2017}
}
LightGBM¶
@article{ke2017lightgbm,
title={LightGBM: A Highly Efficient Gradient Boosting Decision Tree},
author={Ke, Guolin and Meng, Qi and Finley, Thomas and Wang, Taifeng and Chen, Wei and Ma, Weidong and Ye, Qiwei and Liu, Tie-Yan},
journal={Advances in Neural Information Processing Systems},
year={2017}
}
Acknowledgments¶
- Oxford Battery Intelligence Lab for the LG M50T dataset
- PyTorch team for torchdiffeq (Neural ODEs)
- Hydra team for configuration management
- All contributors to BatteryML
Next Steps¶
- Getting Started - Installation guide
- User Guide - Usage documentation