Editorial Feature

Ultrasonic Techniques for Lithium-Ion Battery Diagnostics

The widespread adoption of Li-ion batteries, especially in the automotive industry, can be attributed to their high energy density, long cycle life, and decreasing cost. However, potential risks such as thermal runaway and spontaneous ignition remain a concern. This has driven the need for new, cost-effective diagnostic techniques to monitor battery performance and durability.

Ultrasonic Techniques for Lithium-Ion Battery Diagnostics

Image Credit: IM Imagery/Shutterstock.com

Among the various diagnostic methods, ultrasonic techniques have emerged as a promising non-destructive testing (NDT) approach for lithium-ion battery diagnostics. These techniques enable real-time monitoring of the battery's internal state, defect detection, and overall health assessment without causing damage or disruption, facilitating timely interventions and optimized management strategies.1,2

Principles of Ultrasonic Diagnostics  

Ultrasonic diagnostics uses ultrasonic transducers to generate, propagate, and detect ultrasonic waves, typically in the 0.1 to 15 MHz range. These waves are transmitted into the material under inspection.

As the waves encounter boundaries between different materials, defects, or variations in density or porosity, a portion of the energy is reflected (pulse-echo) or received by a secondary transducer (through transmission). These ultrasonic waves carry valuable information about the material's internal characteristics, which can be analyzed to gain insights into its condition.3

Interaction of Ultrasonic Waves with Battery Materials

Factors such as material properties, density, and porosity influence the interaction of ultrasonic waves with battery materials. In lithium-ion batteries, wave propagation can be described using theories like Biot's theory for fluid-saturated porous media or the slurry model for electrode coatings.

A key parameter analyzed is the time-of-flight (ToF), representing the time it takes for an ultrasonic wave to travel through the material and return as an echo. By measuring the ToF and correlating it with known material properties, researchers can detect defects, density changes, or variations in the battery's internal structure.

Additionally, the amplitude and frequency of reflected or transmitted waves provide information about the material's characteristics, with changes indicating alterations in the battery components' mechanical properties linked to electrochemical processes during charging and discharging cycles.4

Applications in Lithium-Ion Batteries

Ultrasonic techniques have numerous applications in lithium-ion battery diagnostics, offering unique capabilities and insights that complement and extend traditional diagnostic methods.

Detecting Internal Defects and Degradation

One of the primary applications of ultrasonic techniques in battery diagnostics is the detection of internal defects and signs of degradation.

Ultrasonic tomography, a specialized ultrasonic technique, has proven valuable for studying metal defect detection in lithium-ion batteries. This method involves emitting ultrasonic waves into the battery samples and analyzing the reflected or transmitted waves.

These signals help create tomographic images of the internal battery structure, allowing researchers to visualize and analyze defects without damaging the battery. This capability is particularly valuable for quality control and identifying potential safety hazards that could lead to thermal runaway or other catastrophic failures.5

Monitoring State of Charge (SoC) and State of Health (SoH)

Ultrasonic analysis for SoC monitoring involves tracking changes in ultrasonic waveforms corresponding to the battery's charging and discharging states. This method relies on measuring the ToF of ultrasonic waves, which varies with the battery's mechanical properties during cycling.

Changes in signal amplitude during the charge/discharge cycle indicate structural changes, enabling SoC determination and over-discharge detection without complex algorithms or additional hardware. This approach can also monitor the battery's SoH, providing insights into its overall condition, enabling early detection of cell damage, aiding in battery refurbishment, identifying faulty cells, and estimating the remaining useful life.

Monitoring Solid-Electrolyte Interphase (SEI) Formation

The formation and evolution of the SEI layer play are crucial for lithium-ion battery performance and longevity. Ultrasonic techniques can be employed to monitor this process by analyzing changes in the acoustic properties of the electrode during cycling.

As the SEI layer evolves, its mechanical properties change, altering the propagation of ultrasonic waves. By correlating these changes with electrochemical measurements, researchers can gain valuable insights into the SEI formation process and its impact on battery performance.7

Diagnosing Electrodes

Spatially resolved ultrasound acoustic measurements provide a powerful diagnostic tool for analyzing the condition of lithium-ion battery electrodes. By performing ultrasonic measurements at multiple locations across the battery's surface and over the full operating voltage range, signal intensity and ToF changes can be correlated with the lithiation/delithiation processes and the associated density and structural changes occurring within the individual anode and cathode layers.

This method also provides information about electrode expansion behavior. It can identify regions where expansion is inhibited due to factors like current collector geometry, offering an economical and high-resolution diagnostic capability to monitor internal structural evolution in operando.2

Advantages and Limitations

Ultrasonic techniques offer several advantages for lithium-ion battery diagnostics, including non-destructive and non-invasive monitoring, early degradation detection, real-time monitoring, and high spatial resolution. These capabilities enable continuous battery health assessment, proactive maintenance, and targeted diagnostics, enhancing battery lifespan and performance.

However, challenges such as complex signal interpretation, susceptibility to external interference, limited penetration depth, and potential equipment requirements may arise.

Despite these challenges, the benefits of early degradation detection and improved performance often outweigh the drawbacks, especially in critical applications prioritizing battery safety and longevity.8

Future Outlook

Ultrasonic techniques for lithium-ion battery diagnostics have significant potential to enhance battery systems' safety, efficiency, and reliability. Advancements in transducer technology, signal processing, and machine learning are expected to improve their accuracy and reliability further.

Developing portable and cost-effective ultrasonic diagnostic systems could also lead to widespread use in applications such as electric vehicles and stationary energy storage, enabling real-time monitoring and predictive maintenance.

While challenges remain, ongoing research aims to enhance ultrasonic diagnostics, contributing to developing more efficient and safer lithium-ion batteries.8

More from AZoOptics: Enhancing Threat Detection with X-Ray Imaging

References and Further Reading

  1. Webster, M., Frankforter, E., Juarez, P. (2023, April). Evaluation of ultrasonic battery inspection techniques. In Non-destructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVII. doi.org/10.1117/12.2656667
  2. Robinson, JB., Maier, M., Alster, G., Compton, T., Brett, DJ., Shearing, PR. (2019). Spatially resolved ultrasound diagnostics of Li-ion battery electrodes. Physical Chemistry Chemical Physics. doi.org/10.1039/C8CP07098A
  3. Chacón, XCA., Laureti, S., Ricci, M., Cappuccino, G. (2023). A Review of Non-Destructive Techniques for Lithium-Ion Battery Performance Analysis. World Electric Vehicle Journal. doi.org/10.3390/wevj14110305
  4. Gold, L., Herzog, T., Schubert, F., Heuer, H., Giffin, G. A. (2023). Ultrasound Propagation in Lithium‐Ion Battery Cell Materials: Basis for Developing Monitoring and Imaging Methods. Energy Technology. doi.org/10.1002/ente.202200861
  5. Yi, M., Jiang, F., Lu, L., Hou, S., Ren, J., Han, X., Huang, L. (2021). Ultrasonic tomography study of metal defect detection in lithium-ion battery. Frontiers in Energy Research. doi.org/10.3389/fenrg.2021.806929
  6. Davies, G., Knehr, KW., Van Tassell, B., Hodson, T., Biswas, S., Hsieh, AG., Steingart, DA. (2017). State of charge and state of health estimation using electrochemical acoustic time of flight analysis. Journal of The Electrochemical Society. doi.org/10.1149/2.1411712jes
  7. Bommier, C., Chang, W., Li, J., Biswas, S., Davies, G., Nanda, J., & Steingart, D. (2020). Operando acoustic monitoring of SEI formation and long-term cycling in NMC/SiGr composite pouch cells. Journal of The Electrochemical Society. doi.org/10.1149/1945-7111/ab68d6
  8. Wang, Q., Song, D., Lin, X., Wu, H., & Shen, H. (2024). Application of machine learning in ultrasonic diagnostics for prismatic lithium-ion battery degradation evaluation. Frontiers in Energy Research. doi.org/10.3389/fenrg.2024.1379408

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Owais Ali

Written by

Owais Ali

NEBOSH certified Mechanical Engineer with 3 years of experience as a technical writer and editor. Owais is interested in occupational health and safety, computer hardware, industrial and mobile robotics. During his academic career, Owais worked on several research projects regarding mobile robots, notably the Autonomous Fire Fighting Mobile Robot. The designed mobile robot could navigate, detect and extinguish fire autonomously. Arduino Uno was used as the microcontroller to control the flame sensors' input and output of the flame extinguisher. Apart from his professional life, Owais is an avid book reader and a huge computer technology enthusiast and likes to keep himself updated regarding developments in the computer industry.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Ali, Owais. (2024, June 19). Ultrasonic Techniques for Lithium-Ion Battery Diagnostics. AZoOptics. Retrieved on October 03, 2024 from https://www.azooptics.com/Article.aspx?ArticleID=2636.

  • MLA

    Ali, Owais. "Ultrasonic Techniques for Lithium-Ion Battery Diagnostics". AZoOptics. 03 October 2024. <https://www.azooptics.com/Article.aspx?ArticleID=2636>.

  • Chicago

    Ali, Owais. "Ultrasonic Techniques for Lithium-Ion Battery Diagnostics". AZoOptics. https://www.azooptics.com/Article.aspx?ArticleID=2636. (accessed October 03, 2024).

  • Harvard

    Ali, Owais. 2024. Ultrasonic Techniques for Lithium-Ion Battery Diagnostics. AZoOptics, viewed 03 October 2024, https://www.azooptics.com/Article.aspx?ArticleID=2636.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this article?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.