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Real-time knowledge- and data-driven reliability analysis for lithium-ion battery energy storage system by Bayesian fault propagation network
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DOI：10.1016/j.apenergy.2025.127013.png)
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Abstract
En 中文
• Establish a Bayesian network-based framework for fault propagation in BESS. • Develop a hybrid knowledge-data driven method for failure probability estimation. • Implement real-time failure probability updating. • Integrate fault blocking conditions for realistic failure propagation in BESS.
Journal
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11
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2.6W
Citations:
17.8W