Joint State of Charge and State of Health Estimation Using Bidirectional LSTM and Bayesian Hyperparameter Optimization
In this study, a novel Machine learning-based method for the joint State of Charge and State of Health estimation of Lithium Batteries that tackle real-world applications and with Bayesian Hyperparameter optimization is proposed. The estimated State of Health is used as an input for State of Charge...
Shranjeno v:
| Principais autores: | , , , , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
IEEE
2024-01-01
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| Serija: | IEEE Access |
| Teme: | |
| Online dostop: | https://ieeexplore.ieee.org/document/10550193/ |
| Oznake: |
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