摘要
Two internal side reactions that have the greatest impact on the battery aging mode are introduced. The negative region equation of the traditional pseudo two-dimensional model is improved，and the electrochemical degradation model of lithium-ion batteries is proposed. The response surface analysis method is applied to establish the aging characteristic parameters that can comprehensively describe the degradation of battery performance. A long short-term memory neural network is established to predict the future capacity. The aging characteristic parameters obtained based on the mechanism model and historical capacity retention rate are as the input of the network. Verification results of capacity forecast show that the prediction error is within 2%.
| 投稿的翻译标题 | Multi-dimensional aging diagnosis of lithium-ion battery with a long short-term memory neural network |
|---|---|
| 源语言 | 繁体中文 |
| 页（从-至） | 3135-3147 |
| 页数 | 13 |
| 期刊 | Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) |
| 卷 | 54 |
| 期 | 11 |
| DOI | |
| 出版状态 | 已出版 - 11月 2024 |
| 已对外发布 | 是 |
关键词
- aging diagnosis
- aging mechanism modeling
- lithium-ion battery
- long short-term memory neural network
- response surface methodology
