Unlocking Wide‐Temperature Battery States via Noninvasive Nonlinear Ultrasound

ABSTRACT Lithium‐ion batteries (LIBs) are central to modern energy storage, yet evaluating their internal states under extreme thermal fluctuations remains a critical challenge. Here we present a non‐destructive evaluation framework that leverages the quasi‐static component (QSC) of nonlinear ultrasonic guided waves. By integrating an operando electro‐acoustic‐thermal platform, we isolate temperature‐induced artefacts from intrinsic acoustic signals. This statistical compensation enables the precise, simultaneous prediction of state of charge (SOC) and state of charge relative to nominal capacity (SOC N ) across a wide temperature span (−10°C to 40°C). Furthermore, in situ multidimensional characterization maps these ultrasonic signatures to temperature‐dependent mechanics and irreversible capacity fade mechanisms. Ultimately, this unified framework provides a scalable, quantitative diagnostic tool for reliable energy systems operating under extreme environments.

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Publication Details

Journal
Advanced Energy Materials
Published
2026-11-05
DOI
https://doi.org/10.1002/aenm.71798
Primary Topic
Battery Modeling and Management
Type
article
Field-Weighted Citation Impact
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article

Unlocking Wide‐Temperature Battery States via Noninvasive Nonlinear Ultrasound

Yancheng You, Xinyi Yuan, Mingxi Deng, Jinshan Wen et al.
Advanced Energy Materials
Battery Modeling and Management
article

Unlocking Wide‐Temperature Battery States via Noninvasive Nonlinear Ultrasound

Yancheng You, Xinyi Yuan, Mingxi Deng, Jinshan Wen, Xiaofeng Li, Xiaolei Lin, Jiyu Liu, Xianlin Cao, Weibin Li
article en

Abstract

ABSTRACT Lithium‐ion batteries (LIBs) are central to modern energy storage, yet evaluating their internal states under extreme thermal fluctuations remains a critical challenge. Here we present a non‐destructive evaluation framework that leverages the quasi‐static component (QSC) of nonlinear ultrasonic guided waves. By integrating an operando electro‐acoustic‐thermal platform, we isolate temperature‐induced artefacts from intrinsic acoustic signals. This statistical compensation enables the precise, simultaneous prediction of state of charge (SOC) and state of charge relative to nominal capacity (SOC N ) across a wide temperature span (−10°C to 40°C). Furthermore, in situ multidimensional characterization maps these ultrasonic signatures to temperature‐dependent mechanics and irreversible capacity fade mechanisms. Ultimately, this unified framework provides a scalable, quantitative diagnostic tool for reliable energy systems operating under extreme environments.

Advanced Energy Materials
Chongqing University (CN), Xiamen University (CN)
Openalex Percentile: Top 23%
Battery Modeling and Management
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