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March 3, 2026Measurement3 citationsOpen Access

Experimental investigation of surface strain behavior in commercial pouch and prismatic Lithium-Ion batteries

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SCSaihan ChenPLPeng LiuHYHaixu Yang

Key Points

  • Surface strain is a crucial signal for monitoring internal states and safety in lithium-ion batteries.
  • The investigation revealed that the side-surface strain in prismatic cells exhibits a negative correlation with state of charge, a novel finding.
  • Measurements employed fiber Bragg grating sensors to capture both surface strain and temperature in commercial lithium-ion battery formats.
  • Key mechanisms driving dynamic strain were identified during different charge-discharge stages, aiding in enhanced fault diagnosis.

Abstract

• Decoupled temperature and strain measurements of lithium-ion batteries using FBG • Revealed SOC- and temperature-induced surface strain mechanisms. • Quantified the contributions of strain-inducing factors to total dynamic strain. • Identified dominant factors of strain evolution across charge–discharge stages. The surface strain of lithium-ion batteries (LIBs) is a critical signal for accurate internal state estimation and safety monitoring. However, a unified understanding of strain evolution for different cell formats is still lacking. In this investigation, fiber Bragg grating sensors were employed to acquire decoupled measurements of surface strain and temperature in commercial pouch and prismatic LIBs. Static experiments under controlled state of charge (SOC) and temperature conditions enabled a systematic analysis of surface strain characteristics, revealing the underlying response mechanisms for each cell type. Notably, under SOC-induced variations, the side-surface strain of prismatic cells evolves opposite to the cell’s volumetric change and exhibits a strong negative correlation with SOC, a phenomenon reported here for the first time. Cycling experiments further provided dynamic strain data, and a strain composition model was developed to quantitatively assess the contributions of SOC, temperature, and inconsistency-induced strain to total dynamic strain. Finally, the stage-wise evolution of dynamic strain was analyzed, elucidating the dominant mechanisms at each stage. This work provides both theoretical and experimental guidance for optimizing surface strain measurement in commercial LIBs and lays the foundation for high-precision, mechanically informed state estimation and intelligent fault diagnosis in engineering applications.

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Cite This Study

Chen et al. (2026) studied this question.

synapsesocial.com/papers/69a75feec6e9836116a2c4eahttps://doi.org/10.1016/j.measurement.2026.120686
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