terencetaothucb/TBSI-Sunwoda-Battery-Dataset

Sunwoda Electronic Co., Ltd, and Tsinghua Berkeley Shenzhen Institute (TBSI) generate the TBSI Sunwoda Battery Dataset. We open-source this dataset to inspire more data-driven novel material verification, battery management research and applications.

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Experimental

This dataset helps battery researchers and engineers predict the degradation trajectory of lithium-ion batteries without costly, time-consuming experiments. It provides multi-step fast charging data for NCM811 batteries, along with derived thermodynamic and kinetic parameters. The output is features that characterize battery performance and degradation, enabling earlier, data-driven battery material verification and management.

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Use this if you need to develop predictive models for battery lifetime, especially for ternary lithium-ion batteries under fast-charging conditions, and want to leverage physics-informed data without extensive new testing.

Not ideal if your focus is on battery chemistries other than NCM811 or if you require data from different charging protocols (e.g., purely constant current charging) for your research.

battery-management-systems materials-science electric-vehicle-batteries sustainable-manufacturing battery-lifetime-prediction
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Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 5 / 25

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59

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2

Language

MATLAB

License

MIT

Last pushed

Jan 14, 2025

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