Online Capacity Estimation for Lithium-Ion Batteries Based on Semi-Supervised Convolutional Neural Network
Accurate capacity estimation can ensure the safe and reliable operation of lithium-ion batteries in practical applications. Recently, deep learning-based capacity estimation methods have demonstrated impressive advances. However, such methods suffer from limited labeled data for training, i.e., the...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
|
| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/12/4/256 |
| _version_ | 1797499796290797568 |
|---|---|
| author | Yi Wu Wei Li |
| author_facet | Yi Wu Wei Li |
| author_sort | Yi Wu |
| collection | DOAJ |
| description | Accurate capacity estimation can ensure the safe and reliable operation of lithium-ion batteries in practical applications. Recently, deep learning-based capacity estimation methods have demonstrated impressive advances. However, such methods suffer from limited labeled data for training, i.e., the capacity ground-truth of lithium-ion batteries. A capacity estimation method is proposed based on a semi-supervised convolutional neural network (SS-CNN). This method can automatically extract features from battery partial-charge information for capacity estimation. Furthermore, a semi-supervised training strategy is developed to take advantage of the extra unlabeled sample, which can improve the generalization of the model and the accuracy of capacity estimation even in the presence of limited labeled data. Compared with artificial neural networks and convolutional neural networks, the proposed method is demonstrated to improve capacity estimation accuracy. |
| first_indexed | 2024-03-10T03:52:34Z |
| format | Article |
| id | doaj.art-c88565346d294bb2bba8855d9c1dae0d |
| institution | Directory Open Access Journal |
| issn | 2032-6653 |
| language | English |
| last_indexed | 2024-03-10T03:52:34Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj.art-c88565346d294bb2bba8855d9c1dae0d2023-11-23T11:03:51ZengMDPI AGWorld Electric Vehicle Journal2032-66532021-12-0112425610.3390/wevj12040256Online Capacity Estimation for Lithium-Ion Batteries Based on Semi-Supervised Convolutional Neural NetworkYi Wu0Wei Li1College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, ChinaCenter on Frontiers of Computing Studies, Peking University, Beijing 100871, ChinaAccurate capacity estimation can ensure the safe and reliable operation of lithium-ion batteries in practical applications. Recently, deep learning-based capacity estimation methods have demonstrated impressive advances. However, such methods suffer from limited labeled data for training, i.e., the capacity ground-truth of lithium-ion batteries. A capacity estimation method is proposed based on a semi-supervised convolutional neural network (SS-CNN). This method can automatically extract features from battery partial-charge information for capacity estimation. Furthermore, a semi-supervised training strategy is developed to take advantage of the extra unlabeled sample, which can improve the generalization of the model and the accuracy of capacity estimation even in the presence of limited labeled data. Compared with artificial neural networks and convolutional neural networks, the proposed method is demonstrated to improve capacity estimation accuracy.https://www.mdpi.com/2032-6653/12/4/256lithium-ion batterycapacity estimationsemi-supervisedconvolutional neural network |
| spellingShingle | Yi Wu Wei Li Online Capacity Estimation for Lithium-Ion Batteries Based on Semi-Supervised Convolutional Neural Network World Electric Vehicle Journal lithium-ion battery capacity estimation semi-supervised convolutional neural network |
| title | Online Capacity Estimation for Lithium-Ion Batteries Based on Semi-Supervised Convolutional Neural Network |
| title_full | Online Capacity Estimation for Lithium-Ion Batteries Based on Semi-Supervised Convolutional Neural Network |
| title_fullStr | Online Capacity Estimation for Lithium-Ion Batteries Based on Semi-Supervised Convolutional Neural Network |
| title_full_unstemmed | Online Capacity Estimation for Lithium-Ion Batteries Based on Semi-Supervised Convolutional Neural Network |
| title_short | Online Capacity Estimation for Lithium-Ion Batteries Based on Semi-Supervised Convolutional Neural Network |
| title_sort | online capacity estimation for lithium ion batteries based on semi supervised convolutional neural network |
| topic | lithium-ion battery capacity estimation semi-supervised convolutional neural network |
| url | https://www.mdpi.com/2032-6653/12/4/256 |
| work_keys_str_mv | AT yiwu onlinecapacityestimationforlithiumionbatteriesbasedonsemisupervisedconvolutionalneuralnetwork AT weili onlinecapacityestimationforlithiumionbatteriesbasedonsemisupervisedconvolutionalneuralnetwork |