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ISLPED 2023: Battery SOH Dataset Generation by 20dec002 is a document available to read on EtoBox.

This paper proposes generating datasets for training battery state of health models by simulating a traditional battery model. Using simulated data achieves reasonable accuracy compared to the simulated model, with reduced memory usage and faster calculations. The approach allows exploring more workload profiles than experimental measurements alone to improve data-driven models.

Author
20dec002
Language
EN