A novel weight coefficient calculation method for the real‐time state monitoring of the lithium‐ion battery packs under the complex current variation working conditions
Abstract A novel real‐time state monitoring method is proposed to realize the real‐time energy management of the lithium‐ion battery packs, which is conducted in the iterative computational calculation process by introducing an improved weighting factor‐unscented Kalman filtering algorithm. The accu...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-12-01
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| Series: | Energy Science & Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ese3.478 |
| _version_ | 1828775314276220928 |
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| author | Shun‐Li Wang Carlos Fernandez Zheng‐Wei Xie Xiao‐Xia Li Chuan‐Yun Zou Qiang Li |
| author_facet | Shun‐Li Wang Carlos Fernandez Zheng‐Wei Xie Xiao‐Xia Li Chuan‐Yun Zou Qiang Li |
| author_sort | Shun‐Li Wang |
| collection | DOAJ |
| description | Abstract A novel real‐time state monitoring method is proposed to realize the real‐time energy management of the lithium‐ion battery packs, which is conducted in the iterative computational calculation process by introducing an improved weighting factor‐unscented Kalman filtering algorithm. The accurate state monitoring treatment is investigated by applying a new iterate calculation thought, in which the improved weight coefficient parameter is constructed and its numerical stability is improved. Meanwhile, the recursive calculation is derived by using the real‐time measured factors, according to which the state‐of‐charge estimation is realized accurately. Aiming to adapt the complex current variation working conditions, the nonlinear treatment is introduced to construct the mathematical unscented transforming function. As can be known from the experimental results, the state‐of‐charge estimation accuracy is 98.34% under the complex current charge‐discharge working conditions. Meanwhile, the effective closed‐circuit voltage trackage is also investigated accurately and its tracking error is within 3.51% in the complex working conditions, which provides a good security guarantee for the reliable energy supply of the lithium‐ion battery packs. |
| first_indexed | 2024-12-11T15:38:08Z |
| format | Article |
| id | doaj.art-a8f41276d25d492db74314fb5b9c7762 |
| institution | Directory Open Access Journal |
| issn | 2050-0505 |
| language | English |
| last_indexed | 2024-12-11T15:38:08Z |
| publishDate | 2019-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Energy Science & Engineering |
| spelling | doaj.art-a8f41276d25d492db74314fb5b9c77622022-12-22T00:59:53ZengWileyEnergy Science & Engineering2050-05052019-12-01763038305710.1002/ese3.478A novel weight coefficient calculation method for the real‐time state monitoring of the lithium‐ion battery packs under the complex current variation working conditionsShun‐Li Wang0Carlos Fernandez1Zheng‐Wei Xie2Xiao‐Xia Li3Chuan‐Yun Zou4Qiang Li5School of Information Engineering & Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Southwest University of Science and Technology Mianyang ChinaSchool of Pharmacy and Life Sciences Robert Gordon University Aberdeen UKChengdu Institute of Organic Chemistry Chinese Academy of Sciences Chengdu ChinaSchool of Information Engineering & Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Southwest University of Science and Technology Mianyang ChinaSchool of Information Engineering & Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Southwest University of Science and Technology Mianyang ChinaSchool of Information Engineering & Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Southwest University of Science and Technology Mianyang ChinaAbstract A novel real‐time state monitoring method is proposed to realize the real‐time energy management of the lithium‐ion battery packs, which is conducted in the iterative computational calculation process by introducing an improved weighting factor‐unscented Kalman filtering algorithm. The accurate state monitoring treatment is investigated by applying a new iterate calculation thought, in which the improved weight coefficient parameter is constructed and its numerical stability is improved. Meanwhile, the recursive calculation is derived by using the real‐time measured factors, according to which the state‐of‐charge estimation is realized accurately. Aiming to adapt the complex current variation working conditions, the nonlinear treatment is introduced to construct the mathematical unscented transforming function. As can be known from the experimental results, the state‐of‐charge estimation accuracy is 98.34% under the complex current charge‐discharge working conditions. Meanwhile, the effective closed‐circuit voltage trackage is also investigated accurately and its tracking error is within 3.51% in the complex working conditions, which provides a good security guarantee for the reliable energy supply of the lithium‐ion battery packs.https://doi.org/10.1002/ese3.478complex current variationKalman filterlithium‐ion batterystate monitoringunscented transformweight coefficient |
| spellingShingle | Shun‐Li Wang Carlos Fernandez Zheng‐Wei Xie Xiao‐Xia Li Chuan‐Yun Zou Qiang Li A novel weight coefficient calculation method for the real‐time state monitoring of the lithium‐ion battery packs under the complex current variation working conditions Energy Science & Engineering complex current variation Kalman filter lithium‐ion battery state monitoring unscented transform weight coefficient |
| title | A novel weight coefficient calculation method for the real‐time state monitoring of the lithium‐ion battery packs under the complex current variation working conditions |
| title_full | A novel weight coefficient calculation method for the real‐time state monitoring of the lithium‐ion battery packs under the complex current variation working conditions |
| title_fullStr | A novel weight coefficient calculation method for the real‐time state monitoring of the lithium‐ion battery packs under the complex current variation working conditions |
| title_full_unstemmed | A novel weight coefficient calculation method for the real‐time state monitoring of the lithium‐ion battery packs under the complex current variation working conditions |
| title_short | A novel weight coefficient calculation method for the real‐time state monitoring of the lithium‐ion battery packs under the complex current variation working conditions |
| title_sort | novel weight coefficient calculation method for the real time state monitoring of the lithium ion battery packs under the complex current variation working conditions |
| topic | complex current variation Kalman filter lithium‐ion battery state monitoring unscented transform weight coefficient |
| url | https://doi.org/10.1002/ese3.478 |
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