State of health prediction for proton exchange membrane fuel cells combining semi-empirical model and machine learning
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Elsevier BV
Reference39 articles.
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1. A data-driven method with sample entropy and CEEMDAN for short-term performance degradation prediction of dynamic hydrogen fuel cells;International Journal of Hydrogen Energy;2024-09
2. An adaptive and interpretable SOH estimation method for lithium-ion batteries based-on relaxation voltage cross-scale features and multi-LSTM-RFR2;Energy;2024-09
3. Deep Learning-Based State-of-Health Estimation of Proton-Exchange Membrane Fuel Cells under Dynamic Operation Conditions;Sensors;2024-07-10
4. State-of-Health observer for PEM fuel cells—A novel approach for real-time online analysis;International Journal of Hydrogen Energy;2024-03
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