Physical interpretation of early battery life prediction models

Using Fused Lasso and PLSR machine learning methods to develop physically interpretable models for predicting battery lifetime from the first few weeks of testing. The data set can be downloaded from https://iastate.figshare.com/articles/dataset/b_ISU-ILCC_Battery_Aging_Dataset_b/22582234.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-05
DOI
https://doi.org/10.5281/zenodo.14285817
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
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article

Physical interpretation of early battery life prediction models

Zenodo (CERN European Organization for Nuclear Research)
Advanced Battery Technologies Research
article

Physical interpretation of early battery life prediction models

article en

Abstract

Using Fused Lasso and PLSR machine learning methods to develop physically interpretable models for predicting battery lifetime from the first few weeks of testing. The data set can be downloaded from https://iastate.figshare.com/articles/dataset/b_ISU-ILCC_Battery_Aging_Dataset_b/22582234.

Zenodo (CERN European Organization for Nuclear Research)
National Laboratory of the Rockies (US), Technische Universität Darmstadt (DE)
Responsible consumption and production
Openalex Percentile: Top 65%
Advanced Battery Technologies Research
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Physical interpretation of early battery life prediction models · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS