Non‐Invasive Smart Pressure Sensor for Early‐Stage Thermal Runaway Warning for Cylindrical Batteries

ABSTRACT Batteries have been widely applied in various fields due to the advantages such as high energy density, long service life and so on, whereas they are accompanied by frequent thermal runaway incidents and this is a worldwide challenge. However, non‐invasive warning methods capable of providing early‐stage alerts are missing, especially for non‐planar sidewall pressure monitoring of cylindrical batteries. Here, a smart pressure sensor based on shape memory sensing composite is introduced, which enables conformal contact with cylindrical batteries and can continuously monitor the lateral pressure caused by volume expansion during charging‐discharging. Moreover, the assembly process, designed based on COMSOL simulations, ensures conformal contact between the sensor and the test interface, effectively preventing uneven stress distribution during the assembly of the multi‐layer structure. This smart sensor features impressive stability and recoverability, a broad pressure detection range (50–2340 kPa), excellent hysteresis error (1.17%), high linearity ( R 2 = 0.99) and a maximum deviation of 1.56% over 20000 cycles. It can monitor radial pressure changes, achieving a warning time ratio of 80%, 84%, 86%, and 79% in thermal runaway tests on 18650, 21700 ternary lithium‐ion batteries, 32700 LiFePO 4 battery and 18650 sodium‐ion battery, respectively. Timely measures after warning can prevent thermal runaway.

Authors

Institutions

Publication Details

Journal
Small
Published
2026-10-29
DOI
https://doi.org/10.1002/smll.76428
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Non‐Invasive Smart Pressure Sensor for Early‐Stage Thermal Runaway Warning for Cylindrical Batteries

邹佑云, Yuqi Huang, Zongrong Wang, Shaoxing Qu et al.
8 links
Small
Advanced Battery Technologies Research
article

Non‐Invasive Smart Pressure Sensor for Early‐Stage Thermal Runaway Warning for Cylindrical Batteries

邹佑云, Yuqi Huang, Zongrong Wang, Shaoxing Qu, Xinyu Wang, Yaobo Wu, Yang Shaohua, Ang Wang, Yi Liu, Yingying Xu
article en

Abstract

ABSTRACT Batteries have been widely applied in various fields due to the advantages such as high energy density, long service life and so on, whereas they are accompanied by frequent thermal runaway incidents and this is a worldwide challenge. However, non‐invasive warning methods capable of providing early‐stage alerts are missing, especially for non‐planar sidewall pressure monitoring of cylindrical batteries. Here, a smart pressure sensor based on shape memory sensing composite is introduced, which enables conformal contact with cylindrical batteries and can continuously monitor the lateral pressure caused by volume expansion during charging‐discharging. Moreover, the assembly process, designed based on COMSOL simulations, ensures conformal contact between the sensor and the test interface, effectively preventing uneven stress distribution during the assembly of the multi‐layer structure. This smart sensor features impressive stability and recoverability, a broad pressure detection range (50–2340 kPa), excellent hysteresis error (1.17%), high linearity ( R 2 = 0.99) and a maximum deviation of 1.56% over 20000 cycles. It can monitor radial pressure changes, achieving a warning time ratio of 80%, 84%, 86%, and 79% in thermal runaway tests on 18650, 21700 ternary lithium‐ion batteries, 32700 LiFePO 4 battery and 18650 sodium‐ion battery, respectively. Timely measures after warning can prevent thermal runaway.

Small
Shandong University (CN), Zhejiang Energy Research Institute (CN), Zhejiang University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities, Natural Science Foundation of Zhejiang Province
Affordable and clean energy, Industry, innovation and infrastructure
Openalex Percentile: Top 23%
Advanced Battery Technologies Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon