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Volume 11
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10.3390/batteries11010022
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Article

A State-of-Health Estimation Method of a Lithium-Ion Power Battery for Swapping Stations Based on a Transformer Framework

by
Yu Shi
1,
Haicheng Xie
2,
Xinhong Wang
1,
Xiaoming Lu
1,
Jing Wang
1,
Xin Xu
1,
Dingheng Wang
1 and
Siyan Chen
2,3,*
1
Jilin State Power Economic and Technical Research Institute, Changchun 130022, China
2
College of Automotive Engineering, Jilin University, Changchun 130022, China
3
State Key Laboratory of Automotive Chassis Integration and Bionic, Jilin University, Changchun 130022, China
*
Author to whom correspondence should be addressed.
Batteries 2025, 11(1), 22; https://doi.org/10.3390/batteries11010022
Submission received: 3 December 2024 / Revised: 27 December 2024 / Accepted: 9 January 2025 / Published: 11 January 2025
(This article belongs to the Collection Advances in Battery Energy Storage and Applications)
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Abstract

Against the backdrop of automobile electrification, an increasing number of battery-swapping stations for electric vehicles have been launched to address the issue of slow battery charging under cold temperature conditions. However, due to the separation of the discharging and charging processes for lithium-ion batteries (LIBs) at swapping stations, and the circulation of batteries across different vehicles and stations, the operating data become fragmented, making it difficult to accurately identify the battery state-of-health (SOH). This study proposes a BiLSTM-Transformer framework that extracts the Constant Voltage Time (CVT) feature using only charging data, enabling the precise estimation of battery capacity degradation. Validation experiments conducted on battery samples under different operating temperatures showed that the model achieved a normalized RMSE of less than 1.6%. In ideal conditions, the normalized RMSE of the estimation reached as low as 0.11%. This model enables SOH estimation without relying on discharge data, contributing to the efficient and safe operation of battery swapping stations.
Keywords: lithium-ion battery; capacity estimation; transformer framework; swapping stations; multi-feature analysis lithium-ion battery; capacity estimation; transformer framework; swapping stations; multi-feature analysis

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MDPI and ACS Style

Shi, Y.; Xie, H.; Wang, X.; Lu, X.; Wang, J.; Xu, X.; Wang, D.; Chen, S. A State-of-Health Estimation Method of a Lithium-Ion Power Battery for Swapping Stations Based on a Transformer Framework. Batteries 2025, 11, 22. https://doi.org/10.3390/batteries11010022

AMA Style

Shi Y, Xie H, Wang X, Lu X, Wang J, Xu X, Wang D, Chen S. A State-of-Health Estimation Method of a Lithium-Ion Power Battery for Swapping Stations Based on a Transformer Framework. Batteries. 2025; 11(1):22. https://doi.org/10.3390/batteries11010022

Chicago/Turabian Style

Shi, Yu, Haicheng Xie, Xinhong Wang, Xiaoming Lu, Jing Wang, Xin Xu, Dingheng Wang, and Siyan Chen. 2025. "A State-of-Health Estimation Method of a Lithium-Ion Power Battery for Swapping Stations Based on a Transformer Framework" Batteries 11, no. 1: 22. https://doi.org/10.3390/batteries11010022

APA Style

Shi, Y., Xie, H., Wang, X., Lu, X., Wang, J., Xu, X., Wang, D., & Chen, S. (2025). A State-of-Health Estimation Method of a Lithium-Ion Power Battery for Swapping Stations Based on a Transformer Framework. Batteries, 11(1), 22. https://doi.org/10.3390/batteries11010022

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