LAPSE:2023.15804v1
Published Article
LAPSE:2023.15804v1
Extended Rauch−Tung−Striebel Smoother for the State of Charge Estimation of Lithium-Ion Batteries Based on an Enhanced Circuit Model
Yinfeng Jiang, Wenxiang Song, Hao Zhu, Yun Zhu, Yongzhi Du, Huichun Yin
March 2, 2023
Abstract
The state of charge (SOC) of a lithium battery system is critical since it indicates the remaining operating hours, full charge time, and peak power of the battery. This paper recommends an extended Rauch−Tung−Striebel smoother (ERTSS) for estimating SOC. It is implemented based on an improved equivalent circuit model with hysteresis voltage. The smoothing step of ERTSS will reduce the estimation error further. Additionally, the genetic algorithm (GA) is employed for searching the optimal ERTSS’s smoothing time interval. Various dynamic cell tests are conducted to verify the model’s accuracy and error estimation deviation. The test results demonstrate that ERTSS’s SOC estimation error is limited to 4% with an initial error between −25 ∘C and 45 ∘C and that the root mean square error (RMSE) of ERTSS’s SOC estimation is approximately 5% lower than that of extended Kalman filter (EKF). The ERTSS improves the SOC estimation accuracy at all operating temperatures of batteries.
Keywords
equivalent circuit model, extended Kalman filter, extended Rauch–Tung–Striebel smoother, lithium-ion battery, parameter identification, state of charge
Suggested Citation
Jiang Y, Song W, Zhu H, Zhu Y, Du Y, Yin H. Extended Rauch−Tung−Striebel Smoother for the State of Charge Estimation of Lithium-Ion Batteries Based on an Enhanced Circuit Model. (2023). LAPSE:2023.15804v1
Author Affiliations
Jiang Y: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
Song W: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
Zhu H: HNU College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China
Zhu Y: Hunan Hong Xun Yi’An New Energy and Technology, Co., Ltd., Zhuzhou 412007, China
Du Y: Hunan Hong Xun Yi’An New Energy and Technology, Co., Ltd., Zhuzhou 412007, China
Yin H: Hunan Hong Xun Yi’An New Energy and Technology, Co., Ltd., Zhuzhou 412007, China
Journal Name
Energies
Volume
15
Issue
3
First Page
963
Year
2022
Publication Date
2022-01-28
ISSN
1996-1073
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Original Submission
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PII: en15030963, Publication Type: Journal Article
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LAPSE:2023.15804v1
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https://doi.org/10.3390/en15030963
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