Embedded sensing: The neural frontier and early-warning revolution in battery safety monitoring

• The review identifies critical challenges of embedded sensors in batteries: material compatibility, miniaturization, and multidimensional sensing. • Highlights recent advances in thermocouple, fiber-optic, and thin-film sensors for in-situ battery safety monitoring. • System-level integration of intelligent, multifunctional sensors for safety monitoring and early warning is proposed. The rapid proliferation of battery systems has positioned thermal runaway prevention as a crucial technological imperative. In-situ sensor-based monitoring frameworks enable real-time tracking of internal parameters, thereby providing early warnings and interventions for thermal management. However, conventional sensors, limited by their unidimensional architectures, struggle to accurately capture the intricate interplay among thermal, mechanical, and chemical fields. This limitation results in significant blind spots when predicting battery degradation under multiphysics conditions over the entire lifecycle. Consequently, advancing multi-parameter sensing technologies and developing multidimensional sensing architectures become essential for achieving comprehensive battery safety monitoring. From an embedded sensing perspective, this review systematically examines critical challenges related to chemical compatibility, measurement accuracy, and multi-parameter monitoring encountered during sensor integration. It provides a detailed elaboration on the operating principles and practical applications of thermocouples, optical fiber sensors, and thin-film sensors in batteries. To address technological bottlenecks, such as risks to structural integrity, electrolyte-induced performance degradation, and limitations in single-parameter monitoring, we propose strategies that include sensor miniaturization, the selection of chemically robust materials, integrated multidimensional in-situ platforms, and the incorporation of artificial intelligence (AI) technologies. This review advances comprehensive understanding of battery multidimensional sensing systems, significantly enhancing active safety engineering and multiphysics diagnostic frameworks. This review presents a comprehensive summary of the research advancements in embedded sensor technologies, including thermocouples, light sensors, and thin-film sensors. It further elaborates on the key challenges currently facing the development of embedded sensing systems, as well as their interdisciplinary nature and diverse applications in battery safety technology.

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Publication Details

Journal
Energy storage materials
Published
2025-09-01
DOI
https://doi.org/10.1016/j.ensm.2025.104582
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Embedded sensing: The neural frontier and early-warning revolution in battery safety monitoring

Hao Luo, Yonghua Ding, Yajie Song, Lichang Wang et al.
Energy storage materials
Advanced Battery Technologies Research
article

Embedded sensing: The neural frontier and early-warning revolution in battery safety monitoring

Hao Luo, Yonghua Ding, Yajie Song, Lichang Wang, Na Ren, Shiwen Wang, Mi Lu, Feihong Wang, Zhe Gao, Junyu Cao, Sheng Guo
article en

Abstract

• The review identifies critical challenges of embedded sensors in batteries: material compatibility, miniaturization, and multidimensional sensing. • Highlights recent advances in thermocouple, fiber-optic, and thin-film sensors for in-situ battery safety monitoring. • System-level integration of intelligent, multifunctional sensors for safety monitoring and early warning is proposed. The rapid proliferation of battery systems has positioned thermal runaway prevention as a crucial technological imperative. In-situ sensor-based monitoring frameworks enable real-time tracking of internal parameters, thereby providing early warnings and interventions for thermal management. However, conventional sensors, limited by their unidimensional architectures, struggle to accurately capture the intricate interplay among thermal, mechanical, and chemical fields. This limitation results in significant blind spots when predicting battery degradation under multiphysics conditions over the entire lifecycle. Consequently, advancing multi-parameter sensing technologies and developing multidimensional sensing architectures become essential for achieving comprehensive battery safety monitoring. From an embedded sensing perspective, this review systematically examines critical challenges related to chemical compatibility, measurement accuracy, and multi-parameter monitoring encountered during sensor integration. It provides a detailed elaboration on the operating principles and practical applications of thermocouples, optical fiber sensors, and thin-film sensors in batteries. To address technological bottlenecks, such as risks to structural integrity, electrolyte-induced performance degradation, and limitations in single-parameter monitoring, we propose strategies that include sensor miniaturization, the selection of chemically robust materials, integrated multidimensional in-situ platforms, and the incorporation of artificial intelligence (AI) technologies. This review advances comprehensive understanding of battery multidimensional sensing systems, significantly enhancing active safety engineering and multiphysics diagnostic frameworks. This review presents a comprehensive summary of the research advancements in embedded sensor technologies, including thermocouples, light sensors, and thin-film sensors. It further elaborates on the key challenges currently facing the development of embedded sensing systems, as well as their interdisciplinary nature and diverse applications in battery safety technology.

Energy storage materialsVol. 82
General Administration of Quality Supervision, Inspection and Quarantine (CN), Zhejiang Research Institute of Chemical Industry (CN), Zhejiang Medicine (China) (CN), Xiamen Tobacco Industry (China) (CN), Xiamen University of Technology (CN)
Openalex Percentile: Top 75%
Advanced Battery Technologies Research
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