Over the last decade, acoustic methods, including acoustic emission (AE) and ultrasonic testing (UT), have been increasingly deployed for process diagnostics and health monitoring of electrochemical power devices, including batteries, fuel cells, and water electrolysers. Their application in electrochemical devices is based on identifying changes in acoustic signals emitted from or propagated through materials as a result of physical, structural, and electrochemical changes within the material.
As batteries charge and discharge lithium ions move within the cell and intercalate within the host materials in the positive and negative electrodes. This process changes the density and Young’s modulus, thus affecting the acoustic impedance of the electrodes. Batteries are layered materials and so interfacial reflections of transmitted waves can propagate back to the emitting transducer and reveal information about different regions of the cell. These changes in acoustic signals are then correlated to critical processes and the health status as well as the state of charge and temperature of the battery.
Acoustics may provide an important window into battery operation, but the signals are often very complex due to the interaction of reflected waves from up to 30 or 40 layers in the larger pouch cell batteries. Signal analysis both from physical modelling and machine learning is therefore critical to understanding and using the data for predictions. An overview of the current work performed in this field to date will be presented including advances in both experimental and numerical characterisation.
Bio:
Tom Tranter is a post-doctoral researcher in the Electrochemical Innovation Lab (EIL) at UCL and a co-investigator of the multiscale modelling project which is funded by the Faraday Institution. He received his masters in Physics from Warwick university in 2007 before spending time working in industry as a software developer. Tom then returned to academia to study and model electrochemical devices and received a PhD from Leeds university in 2017. Tom is a developer of many open source modelling projects and since joining the EIL in 2019 and has been working on thermal problems related to battery cells and packs and acoustic modelling.
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