journal article·2026-07-20

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

Jiayong Pan, Zhongbao Wei, Rui Wang, Hongwen He, Lingshi Zhang, Yifei Yu

Publisher page

Abstract

ABSTRACT 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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Battery Technologies Research · Advanced Sensor and Energy Harvesting Materials · Advancements in Battery Materials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Mechanical Engineering Beijing Institute of Technology Beijing China

College of Information Science and Engineering Northeastern University Shenyang China

School of Materials Science and Engineering Huazhong University of Science and Technology Wuhan China

Funding

National Natural Science Foundation of China

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