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Smart Battery Perceiving Future Lifetime at Ultra-Early Life Stage by Decoding SEI Evolution

delete2026-07-27
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PRE
AI
J
Jiayong Pan
魏中宝 (Zhongbao Wei) *
王锐 cover
王锐 (Rui Wang)
H
Hongwen He
L
Lingshi Zhang
于逸飞 (Yifei Yu)
DOI:10.1002/aenm.71338delete
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Abstract

Abstract

En 中文
Accurate lifetime prediction is critical for the reliable use of lithium-ion batteries. However, batteries at early stage commonly show consistent electrical behaviors impeding distinguishing their future life trends. In this work, the internal strain is monitored in-situ by implanting fiber Bragg grating (FBG) sensors into 18 cells belonging to 3 different electrochemical systems. We find the internal strain at the formation stage exhibits a biphasic feature attributed to the dynamic competition between solid-phase growth and gas-phase accumulation. The SEI formation strain (SFS) is further found to be linked closely to the thickness and compactness of SEI which influence the degradation path of battery. The high correlation between SFS and capacity loss is further explored to build an elastic net model for battery lifetime prediction, achieving a mean absolute percentage error (MAPE) of 5.40%. This work presents a new avenue for understanding the mechanism of SEI formation and predicting the battery lifetime at the ultra-early formation stage.
Keywords:
fiber Bragg grating sensors
lifetime prediction
lithium-ion batteries
solid electrolyte interphases

Journal

Advanced Energy Materials cover
Advanced Energy Materials
IF:
26
Papers:
1.0W
Citations:
15.7W

Organization

B
beijing institute of technology
Scholars:
5.4W
Papers: 4.0W
Citations: 63
N
Northeastern University
Scholars:
2.4W
Papers: 1.5W
Citations: 3.0W
H
huazhong university of science and technology
Scholars:
2.5W
Papers: 7.6K
Citations: 5
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