State of Charge Estimation of Lithium-Ion Battery for Electric Vehicles under Extreme Operating Temperatures Based on an Adaptive Temporal Convolutional Network
- DOI
- 10.3390/batteries8100145
- Published
- 09
- Container
- Batteries
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/batteries8100145,
title = {State of Charge Estimation of Lithium-Ion Battery for Electric Vehicles under Extreme Operating Temperatures Based on an Adaptive Temporal Convolutional Network},
author = {Jiazhi Miao and Zheming Tong and Shuiguang Tong and Jun Zhang and Jiale Mao},
year = {2022},
journal = {Batteries},
doi = {10.3390/batteries8100145},
url = {https://doi.org/10.3390/batteries8100145}
}RIS
TY - JOUR TI - State of Charge Estimation of Lithium-Ion Battery for Electric Vehicles under Extreme Operating Temperatures Based on an Adaptive Temporal Convolutional Network AU - Jiazhi Miao AU - Zheming Tong AU - Shuiguang Tong AU - Jun Zhang AU - Jiale Mao PY - 2022 JO - Batteries DO - 10.3390/batteries8100145 UR - https://doi.org/10.3390/batteries8100145 ER -
APA
Miao, J., Tong, Z., Tong, S., Zhang, J., & Mao, J. (2022). State of Charge Estimation of Lithium-Ion Battery for Electric Vehicles under Extreme Operating Temperatures Based on an Adaptive Temporal Convolutional Network. Batteries. https://doi.org/10.3390/batteries8100145
Source records
- doaj · retrieved 2026-09-25T18:59:47.738Z