terencetaothucb/CVAE-Rapid-SOH-Estimation-for-Retired-Batteries-Using-Generated-Data

Code for PulseBat dataset. We use conditional variational autoencoder to generate sufficient pulse voltage response data across random battery SOC retirement conditions, facilitating rapid, accurate and sustainable downstream SOH estimation tasks.

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This project helps battery recycling facilities rapidly and accurately assess the health of retired lithium-ion batteries. It takes limited pulse voltage response data from various battery types and historical usages to generate a much larger dataset. This synthetic data then fuels a simple prediction model that outputs the battery's State-of-Health (SOH), even for conditions not seen in the original data. Battery recycling operations managers or quality control engineers would use this.

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Use this if you need to quickly and precisely estimate the SOH of diverse retired lithium-ion batteries for recycling, especially when collecting extensive real-world test data is impractical or too slow.

Not ideal if you have abundant, comprehensive SOH data across all retirement conditions for your specific battery types, or if you require direct physical measurement rather than data-driven estimation.

battery-recycling lithium-ion-batteries state-of-health-estimation quality-control materials-science
No License Stale 6m No Package No Dependents
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Last pushed

Oct 12, 2024

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