Acoustic Characterization of Lithium-Ion Batteries State of Charge Based on Flexible Piezoelectric Fiber Array

doi:10.3969/j.issn.1008-0198.2025.01.005

Abstract

Abstract: Lithium-ion batteries under complex service conditions are prone to local abnormal state of charge(SOC) problems, which seriously affects their safety and stability.Traditional electrical measurement methods are difficult to fully evaluate the distribution of health status of lithium-ion batteries in multiple regions, which can easily lead to missed detection of local weak performance areas or potential abnormal state areas of individual cells.To address the above issues, a ultrasonic guided wave detection method based onpiezoelectric fiber array is proposed. The acoustic characteristic parameters of lithium-ion batteries in different regions are experimentally extracted to explore the distribution differences of lithium-ion batteries SOC in different regions. Subsequently, a complete database is formed by combining acoustic and electrical characteristic parameters, and a neural network intelligent inversion model is used to quantitatively evaluate SOC with an error of less than 0.25%. The proposed detection method can provide a new technical solution for nondestructive quantitative evaluation of lithium-ion batteries SOC.

Key words: lithium-ion batteries, state of charge(SOC), ultrasonic guided wave, piezoelectric fiber array, inversion

CLC Number:

TM911

LIU Xuan, LYU Yan, GAO Jie. Acoustic Characterization of Lithium-Ion Batteries State of Charge Based on Flexible Piezoelectric Fiber Array[J]. Hunan Electric Power, 2025, 45(1): 29-36.

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