MichaelBosello/battery-rul-estimation
Remaining Useful Life (RUL) estimation of Lithium-ion batteries using deep LSTMs
This project helps engineers and researchers predict how much useful life remains in Lithium-ion batteries. By analyzing historical battery usage data, it provides an estimate of the Remaining Useful Life (RUL), helping with proactive maintenance and replacement decisions. It's designed for professionals managing battery health in electric vehicles or power tools.
198 stars. No commits in the last 6 months.
Use this if you need to accurately forecast the lifespan of Lithium-ion batteries based on their operational data to optimize their usage or plan replacements.
Not ideal if you are working with battery chemistries other than Lithium-ion or if you do not have access to detailed historical usage data for training.
Stars
198
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44
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Sep 19, 2023
Commits (30d)
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