Quantitative Characterisation of the Layered Structure within Lithium-Ion Batteries Using Ultrasonic Resonance

Wednesday, 12 October 2022: 11:40
Room 304 (The Hilton Atlanta)
M. Huang, N. Kirkaldy (Department of Mechanical Engineering, Imperial College London), Y. Zhao (Breathe Battery Technologies Limited), Y. Patel, F. Cegla, and B. Lan (Department of Mechanical Engineering, Imperial College London)
Characterising the internal states of lithium-ion batteries (LIBs) is vital for ensuring the performance, durability, and safety of the batteries, and it represents one of the most demanding and challenging aspects of rapidly-growing battery research. This work reports an exciting ultrasonic methodology for quantitatively characterising the internal layered structure of LIBs using ultrasonic resonance. This work first employs simple, conventional ultrasound equipment to experimentally acquire resonant signals from batteries. Then it establishes a new theoretical model from the ground up, to explain the physical principles of how resonance forms from layer reflections, and how to retrieve various crucial information about battery inner structures from the resonant signals. Finally, to showcase the capabilities of the new methodology, this work demonstrates that the technique is very successful in recovering the number of repetitive layers, the average thicknesses of anode and cathode active material coating layers, a spatially resolved image of internal layers in the depth direction, and the state of charge (SOC) with layer-to-layer resolutions. This new methodology's quantitative layer characterisation capability considerably improves the existing ultrasonic characterisation techniques. For example, the layer-resolved characterisation capacities, especially on the in-operando SOC monitoring, have not been achieved by other techniques yet. Also notable is that it maintains the same low-cost, in-operando operation as conventional ultrasonic or electrical signal-based methods. These qualities could make the reported technique a powerful tool for battery inner structure characterisation and management, enabling better quality control during production and quantitative monitoring of the states of health and charge during operation.