Non-Invasive Imaging Technique to Enhance Lithium Battery Cell

The search for optimal energy density and a lower cost continues as the popularity of electrochemical devices for energy storage grows. As a result, solutions for upgrading electric batteries, supercapacitors, and fuel cells are the focus of much research.

​​​​​​​Image Credit: Lightboxx/Shutterstock.com

Improving the efficiency of current technology requires optimizing design, creating monitoring tools, and failure-mitigation techniques, such as battery management systems. The advancement of electrochemical cells requires an improvement in sensing and imaging technologies.

Functional imaging provides insight into the important electrochemical processes, but structural information is required to understand and evaluate the integrity of the cell components.

Measurement qualities such as sensitivity and resolution are crucial throughout the research and development of new battery technologies. The emphasis will move to practical considerations, such as quick throughput and non-invasive, safe operation, throughout manufacturing, in-use monitoring, maintenance, and recycling. Thermal measurements and open-circuit voltages are commonly employed for this purpose.

Key reliable indicators of the state of charge (SoC), state of health (SoH), and capacity are required in particular. Individual sensing demands for battery research, manufacture, and operation have been addressed in various ways. A single measurement modality that combines excellent performance and convenience has yet to be discovered.

In this study, researchers present and demonstrate a non-invasive imaging technique for mapping intra-cell electrochemical activity, providing new insights into battery cell performance and safety. This technology employs very sensitive magnetometers to detect local current densities inside the cell in a non-invasive and contact-free manner using magnetic fields present outside the cell.

As an example, researchers get magnetic field maps of a lithium-ion cell under load, where the mapped current flow patterns develop due to an electrochemical cell’s overpotentials and impedance, as represented by the Newman model of porous electrodes.

Current density is crucial in creating SoC inhomogeneities, forecasting heat production, solid electrolyte interface thickness and creation, inhomogeneous lithium-ion extraction, and lithium plating, all of which are important to understanding battery behavior. Finally, a better knowledge of these impacts will aid in maximizing battery longevity.

Addressing lithium-ion transport mechanisms, especially long-term equilibration processes, requires an understanding of inhomogeneous current density distribution that is non-particular. While this research is focused on lithium-ion pouch cells, the technique may be easily adapted to other types of batteries and cell shapes by adjusting the computational current reconstruction procedures, which are the most straightforward for the current flat scenario.

The capacity to monitor defect development, such as dendritic growth, in real-time will be possible because of the ability to spatially resolve areas of high electrical conductivities. It will also make it much easier to investigate conduction processes and characterize new battery chemistries with more precision than open-circuit voltage measurements can offer.

Methodology

Figure 1 depicts a high-level overview of the system. A single cell is extracted from a 2^nd generation AESC pouch battery with a rated capacity of 66 Ah. Each cell consists of 35 electrode pairs as well as aluminum and copper current collectors measuring 22 cm x 26 cm in size.

Figure 1. The current flow within a Li-ion battery and magnetic field give rise to a magnetic field, which is measured by a magnetometer array. The image shows a combination of current collectors and electrodes while the separator is suppressed for clarity. Image Credit: Bason, et al., 2022

The battery is placed 6 mm under a 4 x 4 fluxgate array (FGA) of single-axis magnetometers (Texas Instruments DRV425); however, other low-cost magnetometers would also work. Each magnetometer is set up to record a component of the magnetic flux density in a plane above the cell, either B_x or B_y.

Researchers compare their magnetic field pictures to those predicted by a finite-element model (FEM) to see how accurate the magnetic field observations are. The stationary solutions of Poisson’s equation for the voltage of the cell are calculated using this model, which is based on a single pair of electrodes.

The effective conductivity, which is a mix of electrical and ionic conductivity, is adjusted at 1 x 10^-3 Sm^-1, the value required to provide a voltage drop in the open circuit. The incorporation of lithium ions inactive materials on both sides of the electrodes is therefore combined in the z component of the current density.

Results and Discussion

Figure 2 depicts an example of the two magnetic fields after background removal. Magnetic fields of over 100 µT have been measured, and the results are in good statistical agreement with the FEM calculations. The high current density at the outputs and inputs of the current tabs dominates the magnetic field intensity, which is a reflection of the pouch cell design under examination.

Figure 2. Magnetic fields generated by a 10 A (0.2 C_rate) charge: (a) and (b) correspond to the B_y and B_x magnetic field components produced by the FEM predictions, respectively. The results of the measurements after background subtraction are shown in (c) and (d). The standard error associated with each measured field component measurement is around 100 nT. Image Credit: Bason, et al., 2022

One method for enhancing measurement fidelity is to add more constraints to the model, such as Kirchhoff’s law—this method is employed in fuel cell analyses. Figure 3 shows a typical current density picture taken after cell discharge.

Figure 3. Reconstructed current density image corresponding to a single electrode pair, during a 10 A discharge. The top half of the image is shown here, with the battery tabs located at x = 0. Image Credit: Bason, et al., 2022

Researchers are presently measuring magnetic field variations that arise at different charge phases to study phenomena not described by this model, such as changes with SoC.

The magnetic field differences for the first column of measurements, i.e., those nearest to the current collectors, are shown in Figure 4.

The variations in total magnetic field components that correspond to the difference between an initially charged battery and successive charge states are shown in Figure 4(a). The difference between primarily empty batteries is depicted in Figure 4(b).

Figure 4. Change in total magnetic field around the battery terminals during a period of discharging (a) and charging (b) at 10 A. Image Credit: Bason, et al., 2022

Researchers envisage current density pictures with noise floors over six orders of magnitude lower than those reported here, given the ability to detect magnetic field changes with sub-femtotesla sensitivity and the advancement of sensor arrays. These will make it possible to measure current densities on a 1 nA cm² scale.

Conclusion

Researchers have demonstrated how extremely sensitive magnetometer arrays may be utilized to provide in-situ current density imaging of lithium-ion pouch cells under load without aggressive methods. On the percent level, researchers prove the general validity of FEM models while also identifying localized, SOC-dependent deviations.

Scientists expect the technology to be employed shortly to identify current density “hotspots” in real-time, such as those associated with dendrite development or mechanical integrity concerns like soft and hard short circuits. Furthermore, the technique will aid in the testing of new electrochemical cell designs in which current density uniformity is important.

Because of its speed, non-invasive nature, and highly-resolved functional mapping, integrating high-sensitivity and quantum magnetometers for functional battery image will significantly influence research and development, manufacturing, safe use, and recycling.

Journal Reference:

Bason, M.G., Coussens, T., Withers, M., Abel, C., Kendall, G., Krüger, P. (2022) Non-invasive current density imaging of lithium-ion batteries. Journal of Power Sources, 533, p. 231312. Available Online: https://www.sciencedirect.com/science/article/pii/S0378775322003251.

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