Ultrasonic nondestructive diagnosis of lithium-ion batteries with multiple frequencies

Hongbin Sun; Nitin Muralidharan; Ruhul Amin; Vivek Rathod; Pradeep Ramuhalli; Ilias Belharouak

doi:10.1016/j.jpowsour.2022.232091

Ultrasonic nondestructive diagnosis of lithium-ion batteries with multiple frequencies

Hongbin Sun, Nitin Muralidharan, Ruhul Amin, Vivek Rathod, Pradeep Ramuhalli, Ilias Belharouak

Research output: Contribution to journal › Article › peer-review

32 Scopus citations

Abstract

Accurately estimating the state of charge (SoC) in battery management systems (BMSs) requires the measurement of numerous parameters and advanced algorithms. This work studies multifrequency ultrasonic waves to estimate the SoC of Li-ion batteries by sensing the material changes during charge/discharge. A pouch-type LiNi_0.6Mn_0.2Co_0.2O₂ (NMC622)||graphite battery cell is designed and fabricated with a capacity of 2.4 Ah. Different ultrasonic testing setups are explored to determine the optimal testing parameters for the battery. An ultrasonic monitoring system is developed to monitor the battery during charge/discharge at 750 kHz, 1 MHz, and 1.5 MHz. Signal processing algorithms are proposed for extracting three ultrasonic features—amplitude, wave velocity, and attenuation. In a three-cycle test, the amplitude histories do not show clear correlations with the SoC. The wave velocities of all three frequencies have an approximately linear relationship with the SoC, which can be used for SoC estimation. Hysteresis behavior is observed for the wave velocity in terms of a larger slope in the discharge process and velocity drop after a close charge/discharge cycle. The wave attenuation is able to capture the material phase transitions during charge/discharge.

Original language	English
Article number	232091
Journal	Journal of Power Sources
Volume	549
DOIs	https://doi.org/10.1016/j.jpowsour.2022.232091
State	Published - Nov 30 2022

Funding

This work was funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE). The research was in support of the US DOE Battery Recycling Prize voucher program awarded to Titan Advanced Energy Solutions and administered by the National Renewable Energy Laboratory (NREL). Titan's input in support of this work and NREL's support are gratefully acknowledged. This research conducted at Oak Ridge National Laboratory, managed by UT Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725, was also sponsored by the Office of Energy Efficiency and Renewable Energy Vehicle Technologies Office (Director: David Howell, Program Manager: Samuel Gillard). This work was done in collaboration with the ReCell Center at Argonne National Laboratory. We would also like to acknowledge Kelsey Livingston of the Battery Manufacturing Facility, ORNL, for the support in cell fabrication. Jianlin Li and Dan Sweeney are also acknowledged for their helpful comments on an earlier draft of the manuscript. This work was funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE) . The research was in support of the US DOE Battery Recycling Prize voucher program awarded to Titan Advanced Energy Solutions and administered by the National Renewable Energy Laboratory (NREL). Titan’s input in support of this work and NREL’s support are gratefully acknowledged. This research conducted at Oak Ridge National Laboratory, managed by UT Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725, was also sponsored by the Office of Energy Efficiency and Renewable Energy Vehicle Technologies Office (Director: David Howell, Program Manager: Samuel Gillard). This work was done in collaboration with the ReCell Center at Argonne National Laboratory. We would also like to acknowledge Kelsey Livingston of the Battery Manufacturing Facility, ORNL, for the support in cell fabrication. Jianlin Li and Dan Sweeney are also acknowledged for their helpful comments on an earlier draft of the manuscript. Notice: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).

Keywords

Attenuation
Lithium-ion battery
Multiple frequencies
State of charge
Ultrasonic wave
Wave velocity

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.jpowsour.2022.232091

Cite this

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abstract = "Accurately estimating the state of charge (SoC) in battery management systems (BMSs) requires the measurement of numerous parameters and advanced algorithms. This work studies multifrequency ultrasonic waves to estimate the SoC of Li-ion batteries by sensing the material changes during charge/discharge. A pouch-type LiNi0.6Mn0.2Co0.2O2 (NMC622)||graphite battery cell is designed and fabricated with a capacity of 2.4 Ah. Different ultrasonic testing setups are explored to determine the optimal testing parameters for the battery. An ultrasonic monitoring system is developed to monitor the battery during charge/discharge at 750 kHz, 1 MHz, and 1.5 MHz. Signal processing algorithms are proposed for extracting three ultrasonic features—amplitude, wave velocity, and attenuation. In a three-cycle test, the amplitude histories do not show clear correlations with the SoC. The wave velocities of all three frequencies have an approximately linear relationship with the SoC, which can be used for SoC estimation. Hysteresis behavior is observed for the wave velocity in terms of a larger slope in the discharge process and velocity drop after a close charge/discharge cycle. The wave attenuation is able to capture the material phase transitions during charge/discharge.",

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Ultrasonic nondestructive diagnosis of lithium-ion batteries with multiple frequencies

Abstract

Funding

Keywords

UN SDGs

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