MystiFoe/battery-rul-prediction
Professional Battery RUL Prediction System with Advanced Machine Learning - Predicting Remaining Useful Life (RUL) and State of Performance (SOP) of lithium-ion batteries using LSTM, Transformer, and Ensemble models with 95%+ accuracy. Features real-time analytics dashboard, REST API, and production-ready deployment.
This system helps professionals proactively manage lithium-ion battery health and predict their remaining useful life (RUL) and state of performance (SOP). You feed in operational data like temperature, capacity, and resistance, and it outputs predictions, health status, and comprehensive reports. Battery fleet managers, EV maintenance teams, and energy storage operators can use this to optimize performance and prevent failures.
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Use this if you need to continuously monitor and predict the health of multiple lithium-ion batteries to improve maintenance scheduling and operational efficiency.
Not ideal if you are looking to manage non-lithium-ion battery types or require predictions for individual cell-level failures rather than overall battery pack health.
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Language
Python
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Last pushed
Jul 21, 2025
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