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An interpretable safety assessment method for battery thermal runaway based on belief rule base

https://doi.org/10.2139/ssrn.6923099
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Model-based thermal runaway prediction of lithium-ion batteries from kinetics analysis of cell components
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Study on thermal runaway characteristics of lithium batteries under high-rate charge/discharge and development of a deep learning-based early warning model
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Thermal runaway mechanism of lithium ion battery for electric vehicles: A review
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Thermal behaviour and thermal runaway propagation in lithium-ion battery systems – A critical review
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Combined experimental and modeling approaches of the thermal runaway of fresh and aged lithium-ion batteries
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A study of the thermal runaway of lithium-ion batteries: A Gaussian Process based global sensitivity analysis
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Advancing battery safety: Integrating multiphysics and machine learning for thermal runaway prediction in lithium-ion battery module
inferredcites →https://doi.org/10.1016/j.pecs.2019.03.002openalex-snapshot
A review of lithium ion battery failure mechanisms and fire prevention strategies
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An integrated methodology for dynamic risk prediction of thermal runaway in lithium-ion batteries
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A novel optimization method for belief rule base expert system with activation rate
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A review of explainable artificial intelligence in smart manufacturing
inferredcites →https://doi.org/10.1109/jas.2020.1003399openalex-snapshot
A New Safety Assessment Method Based on Belief Rule Base With Attribute Reliability
inferredcites →https://doi.org/10.1109/tcyb.2021.3063285openalex-snapshot
Transparent Digital Twin for Output Control Using Belief Rule Base
inferredcites →https://doi.org/10.1109/tfuzz.2020.3024024openalex-snapshot
On the Interpretability of Belief Rule-Based Expert Systems
inferredcites →https://doi.org/10.1109/tsmc.2017.2759026openalex-snapshot
A Belief Rule-Based Expert System for Fault Diagnosis of Marine Diesel Engines
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A Survey of Belief Rule-Base Expert System
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Belief rule-base inference methodology using the evidential reasoning Approach-RIMER
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Ante-Hoc Methods for Interpretable Deep Models: A Survey
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A Coupled Electrochemical-Thermal Failure Model for Predicting the Thermal Runaway Behavior of Lithium-Ion Batteries
inferredcites →https://doi.org/10.3390/app14199107openalex-snapshot
Thermal Runaway Diagnosis of Lithium-Ion Cells Using Data-Driven Method
inferredcites →https://doi.org/10.3390/en15239088openalex-snapshot
Thermal Modeling and Prediction of The Lithium-ion Battery Based on Driving Behavior
inferredcites →https://doi.org/10.3390/en16176360openalex-snapshot
A Review of the Applications of Explainable Machine Learning for Lithium–Ion Batteries: From Production to State and Performance Estimation
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