In Situ Detection of Lithium‐Ion Battery Pack Capacity Inconsistency Using Magnetic Field Scanning Imaging

Abstract

generate more heat and pose potential safety issues like thermal runaway. [4b,5] Therefore, detection and minimization of cell inconsistency within the battery pack is the key for guaranteeing the operation safety of lithium-ion battery.At the individual cell level, the most reliable and accurate capacity detection methods is coulomb counting during a complete charge/discharge cycle, which is difficult to implement in practice facing large-scale cells because of time consuming and costly. [6] To improve detection efficiency, most existing studies estimate cell capacity based on its charge/discharge voltage curve. In recent years, incremental capacity-differential voltage (IC-DV) analysis has become a popular method for evaluating battery capacity degradation. [6] For the battery pack with series-connection configuration, the IC-DV method can be implemented, despite the measuring error, because the voltage of an individual cell is available. [7] On the other side, for parallelconnected cells with the same terminal voltage, this method is no longer applicable to monitor individual cells. In the absence of individual cell current detection in commercial battery packs, cell-to-cell capacity inconsistency is difficult to observe and lack controllability. [1a,8] Although current imbalance between cells can be used for indicating battery pack capacity inconsistency, [9] the use of current sensor for each cell is impractical and expensive, hindering this method in practical applications. In addition, other tools of detecting unbalanced current in the pack are still lacking.Recently, several advanced imaging technologies have been proposed and applied for monitoring lithium-ion cell performance. [10] X-ray imaging was employed to characterize structural changes of cell materials by virtue of its deeper transmission depth. [10a-c] Neutron imaging was used to observe battery internal phenomena including Li-ion distribution, dendrite growth, and gas generation via absorbing neutrons by Li and scattering neutrons by H. [10d,e] Ultrasonic imaging was proposed to visualize electrolyte wetting process and estimate battery state of charge (SOC) through parameters such as the time of flight and amplitude of acoustic waves. [10f,g] With aforementioned imaging techniques, internal structure behavior of individual cell can be monitored and analyzed, but due to the limitations of the imaging principle, the applications of these imaging techniques in detecting cell capacity or current are restricted.In situ inside-out magnetic resonance imaging was proposed in 2018 by Ilott et al. for application to detect tiny induced One of the main obstacles for the reliability and safety of a lithium-ion battery pack is the difficulty in guaranteeing its capacity consistency at harsh operating conditions, while the key solution is accurate detection of cell capacity inconsistency within the battery pack without taking it apart for destructive testing. Here, an in situ and nondestructive technology is proposed for this purpose, by imaging the...

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Application of Nondestructive Testing Technology in Device‐Scale for Lithium‐Ion Batteries

“…[ 97 ] Wu et al used computational transformation analysis to relate magnetic field strength to the current variation of the battery, and the area of the detected battery was divided and then analyzed by the principal component approach. [ 98 ] With this method, batteries with different current variation trends were located at different positions, while batteries with the same current variation trend but different magnitudes could also be distinguished from their locations.…”

Multiscale Imaging Techniques for Real‐Time, Noninvasive Diagnosis of Li‐Ion Battery Failures

“…Through magnetic field scanning using magnetic sensors, the uneven current and magnetic susceptibility of the materials were identified owing to the imbalance in capacity across the batteries connected in parallel in the pack. [ 108 ] As demonstrated, although MFI‐based analysis allows for the detection and quantification of the macroscopic current distribution and flow pattern, it accounts only for the current distribution dominantly at the conducting materials (i.e., the current collector) and perceives the target cell as a 2D object. This poses substantial limitations on data extraction concerning charge transfer in the direction of the battery depth.…”