alexdatadesign/lfp_soc_ml
LiFePo4(LFP) Battery State of Charge (SOC) estimation from BMS raw data
This project helps optimize the performance and longevity of your home's Lithium Iron Phosphate (LFP) battery by accurately predicting its State of Charge (SOC). It takes raw data from your Battery Management System (BMS), like cell voltages and current, and provides a more reliable SOC estimate, especially when the battery isn't regularly fully charged or discharged. Homeowners with LFP battery systems, particularly those integrated with solar power, would find this valuable.
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Use this if you need a highly accurate and stable State of Charge (SOC) reading for your LFP home battery system to ensure optimal performance, safety, and lifespan, especially if current monitoring methods are prone to cumulative errors.
Not ideal if you don't have an LFP battery system, or if you're comfortable with the accuracy of your existing Coulomb counting method without needing advanced error correction.
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32
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6
Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Dec 20, 2023
Commits (30d)
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