Statistical learning for accurate and interpretable battery lifetime prediction

@article{Attia2021StatisticalLF,
  title={Statistical learning for accurate and interpretable battery lifetime prediction},
  author={Peter M. Attia and Kristen A. Severson and Jeremy D. Witmer},
  journal={ArXiv},
  year={2021},
  volume={abs/2101.01885}
}
Data-driven methods for battery lifetime prediction are attracting increasing attention for applications in which the degradation mechanisms are poorly understood and suitable training sets are available. However, while advanced machine learning and deep learning methods promise high performance with minimal data preprocessing, simpler linear models with engineered features often achieve comparable performance, especially for small training sets, while also providing physical and statistical… 

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