Integrated model construction for state of charge estimation in electric vehicle lithium batteries
Abstract This research addresses the issue of State of Charge (SOC) prediction for electric vehicle batteries by employing a dynamic Kalman neural network model. The model is optimized using a Genetic algorithm to adjust the neural network weights. Additionally, a strategy involving support vector m...
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| Главные авторы: | , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
SpringerOpen
2024-03-01
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| Серии: | Energy Informatics |
| Предметы: | |
| Online-ссылка: | https://doi.org/10.1186/s42162-024-00322-6 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
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