Battery state-of-charge estimation using machine learning analysis of ultrasonic signatures

The potential of acoustic signatures to be used for State-of-Charge (SoC) estimation is demonstrated using artificial neural network regression models. This approach represents a streamlined method of processing the entire acoustic waveform instead of performing manual, and often arbitrary, waveform peak selection. For applications where computational economy is prioritised, simple metrics of statistical significance are used to formally identify the most informative waveform features. These alone can be exploited for SoC inference. It is further shown that signal portions representing both early and late interfacial reflections can correlate highly with the SoC and be of predictive value, challenging the more common peak selection methods which focus on the latter. Although later echoes represent greater through-thickness coverage, and are intuitively more information-rich, their presence is not guaranteed. Holistic waveform treatment offers a more robust approach to correlating acoustic signatures to electrochemical states. It is further demonstrated that transformation into the frequency domain can reduce the dimensionality of the problem significantly, while also improving the estimation accuracy. Most importantly, it is shown that acoustic signatures can be used as sole model inputs to produce highly accurate SoC estimates, without any complementary voltage information. This makes the method suitable for applications where redundancy and diversification of SoC estimation approaches is needed. Data is obtained experimentally from a 210 mAh LiCoO2/graphite pouch cell. Mean estimation errors as low as 0.75% are achieved on a SoC scale of 0–100%

In-Situ Li-Ion Pouch Cell Diagnostics Utilising Plasmonic Based Optical Fibre Sensors

As the drive to improve the cost, performance characteristics and safety of lithium-ion batteries increases with adoption, one area where significant value could be added is that of battery diagnostics. This paper documents an investigation into the use of plasmonic-based optical fibre sensors, inserted internally into 1.4 Ah lithium-ion pouch cells, as a real time and in-situ diagnostic technique. The successful implementation of the fibres inside pouch cells is detailed and promising correlation with battery state is reported, while having negligible impact on cell performance in terms of capacity and columbic efficiency. The testing carried out includes standard cycling and galvanostatic intermittent titration technique (GITT) tests, and the use of a reference electrode to correlate with the anode and cathode readings separately. Further observations are made around the sensor and analyte interaction mechanisms, robustness of sensors and suggested further developments. These finding show that a plasmonic-based optical fibre sensor may have potential as an opto-electrochemical diagnostic technique for lithium-ion batteries, offering an unprecedented view into internal cell phenomena

Determining the electrochemical transport parameters of sodium-ions in hard carbon composite electrodes

Sodium-ion batteries offer advantages over conventional Li-ion batteries, including cost and safety. However, much less is known about their operation and performance properties, particularly at the anode. The electron and ion transport in the active materials and composite electrode significantly impact battery performance. Understanding the changes in transport properties as a function of state-of-charge and state-of-health is essential for effective electrode design and performance assessment. In this work, the resistivity and diffusivity of sodium transport in hard carbon composite electrodes are studied at different states-of-health, using Galvanostatic Intermittent Titration Technique (GITT), Electrochemical Impedance Spectroscopy (EIS), and Electrochemical Potential Spectroscopy (EPS) in a stable 3-electrode test cell configuration. The reference electrode eliminated some voltage errors arising from the overpotentials on the counter electrode. The resistance contributions from the surface electrolyte interface, electrolyte transport in the electrode pores, and the charge transfer resistance are extrapolated from the impedance measurements and the diffusion coefficient from the GITT and EPS. The different techniques indicate similar trends in the diffusion coefficient during sodiation, desodiation, and ageing, although different orders of magnitude were observed between the EPS and GITT data. The accuracy of the parameters calculated using the different electrochemical techniques is discussed in detail

Electro-thermal impedance spectroscopy applied to an open-cathode polymer electrolyte fuel cell

The development of in-situ diagnostic techniques is critical to ensure safe and effective operation of polymer electrolyte fuel cell systems. Infrared thermal imaging is an established technique which has been extensively applied to fuel cells; however, the technique is limited to measuring surface temperatures and is prone to errors arising from emissivity variations and reflections. Here we demonstrate that electro-thermal impedance spectroscopy can be applied to enhance infrared thermal imaging and mitigate its limitations. An open-cathode polymer electrolyte fuel cell is used as a case study. The technique operates by imposing a periodic electrical stimulus to the fuel cell and measuring the consequent surface temperature response (phase and amplitude). In this way, the location of heat generation from within the component can be determined and the thermal conduction properties of the materials and structure between the point of heat generation and the point of measurement can be determined. By selectively ‘locking-in’ to a suitable modulation frequency, spatially resolved images of the relative amplitude between the current stimulus and temperature can be generated that provide complementary information to conventional temporal domain thermograms

4D analysis of the microstructural evolution of Si-based electrodes during lithiation: Time-lapse X-ray imaging and digital volume correlation

Silicon is a promising candidate to substitute or complement graphite as anode material in Li-ion batteries due, mainly, to its high energy density. However, the lithiation/delithiation processes of silicon particles are inherently related to drastic volume changes which, within a battery's physically constrained case, can induce significant deformation of the fundamental components of the battery that can eventually cause it to fail. In this work, we use non-destructive time-lapse X-ray imaging techniques to study the coupled electrochemo-mechanical phenomena in Li-ion batteries. We present X-ray computed tomography data acquired at different times during the first lithiation of custom-built silicon-lithium battery cells. Microstructural volume changes have been quantified using full 3D strain field measurements from digital volume correlation analysis. Furthermore, the extent of lithiation of silicon particles has been quantified in 3D from the grey-scale of the tomography images. Correlation of the volume expansion and grey-scale changes over the silicon-based electrode volume indicates that the process of lithiation is kinetically affected by the reaction at the Si/LixSi interface

In Situ Ultrasound Acoustic Measurement of the Lithium-Ion Battery Electrode Drying Process

The electrode drying process is a crucial step in the manufacturing of lithium-ion batteries and can significantly affect the performance of an electrode once stacked in a cell. High drying rates may induce binder migration, which is largely governed by the temperature. Additionally, elevated drying rates will result in a heterogeneous distribution of the soluble and dispersed binder throughout the electrode, potentially accumulating at the surface. The optimized drying rate during the electrode manufacturing process will promote balanced homogeneous binder distribution throughout the electrode film; however, there is a need to develop more informative in situ metrologies to better understand the dynamics of the drying process. Here, ultrasound acoustic-based techniques were developed as an in situ tool to study the electrode drying process using NMC622-based cathodes and graphite-based anodes. The drying dynamic evolution for cathodes dried at 40 and 60 °C and anodes dried at 60 °C were investigated, with the attenuation of the reflective acoustic signals used to indicate the evolution of the physical properties of the electrode-coating film. The drying-induced acoustic signal shifts were discussed critically and correlated to the reported three-stage drying mechanism, offering a new mode for investigating the dynamic drying process. Ultrasound acoustic-based measurements have been successfully shown to be a novel in situ metrology to acquire dynamic drying profiles of lithium-ion battery electrodes. The findings would potentially fulfil the research gaps between acquiring dynamic data continuously for a drying mechanism study and the existing research metrology, as most of the published drying mechanism research studies are based on simulated drying processes. It shows great potential for further development and understanding of the drying process to achieve a more controllable electrode manufacturing process

MicroCT optimisation for imaging fascicular anatomy in peripheral nerves

Due to the lack of understanding of the fascicular organisation, vagus nerve stimulation (VNS) leads to unwanted off-target effects. Micro-computed tomography (microCT) can be used to trace fascicles from periphery and image fascicular anatomy. In this study, we present a simple and reproducible method for imaging fascicles in peripheral nerves with iodine staining and microCT for the determination of fascicular anatomy and organisation

Observation of Zn Dendrite Growth via Operando Digital Microscopy and Time-Lapse Tomography

The zinc-ion battery is one of the promising candidates for next-generation energy storage devices beyond lithium technology due to the earth’s abundance of Zn materials and their high volumetric energy density (5855 mA h cm–3). To date, the formation of Zn dendrites during charge–discharge cycling still hinders the practical application of zinc-ion batteries. It is, therefore, crucial to understand the formation mechanism of the zinc dendritic structure before effectively suppressing its growth. Here, the application of operando digital optical microscopy and in situ lab-based X-ray computed tomography (X-ray CT) is demonstrated to probe and quantify the morphologies of zinc electrodeposition/dissolution under multiple galvanostatic plating/stripping conditions in symmetric Zn||Zn cells. With the combined microscopy approaches, we directly observed the dynamic nucleation and subsequent growth of Zn deposits, the heterogeneous transportation of charged clusters/particles, and the evolution of ‘dead’ Zn particles via partial dissolution. Zn electrodeposition at the early stage is mainly attributed to activation, while the subsequent dendrite growth is driven by diffusion. The high current not only facilitates the formation of sharp dendrites with a larger mean curvature at their tips but also leads to dendritic tip splitting and the creation of a hyper-branching morphology. This approach offers a direct opportunity to characterize dendrite formation in batteries with a metal anode in the laboratory

A spinal organ of proprioception for integrated motor action feedback

Proprioception is essential for behavior and provides a sense of our body movements in physical space. Proprioceptor organs are thought to be only in the periphery. Whether the central nervous system can intrinsically sense its own movement remains unclear. Here we identify a segmental organ of proprioception in the adult zebrafish spinal cord, which is embedded by intraspinal mechanosensory neurons expressing Piezo2 channels. These cells are late-born, inhibitory, commissural neurons with unique molecular and physiological profiles reflecting a dual sensory and motor function. The central proprioceptive organ locally detects lateral body movements during locomotion and provides direct inhibitory feedback onto rhythm-generating interneurons responsible for the central motor program. This dynamically aligns central pattern generation with movement outcome for efficient locomotion. Our results demonstrate that a central proprioceptive organ monitors self-movement using hybrid neurons that merge sensory and motor entities into a unified network

A Review of Lithium-Ion Battery Electrode Drying: Mechanisms and Metrology

Lithium-ion battery manufacturing chain is extremely complex with many controllable parameters especially for the drying process. These processes affect the porous structure and properties of these electrode films and influence the final cell performance properties. However, there is limited available drying information and the dynamics are poorly understood due to the limitation of the existing metrology. There is an emerging need to develop new methodologies to understand the drying dynamics to achieve improved quality control of the electrode coatings. A comprehensive summary of the parameters and variables relevant to the wet electrode film drying process is presented, and its consequences/effects on the finished electrode/final cell properties are mapped. The development of the drying mechanism is critically discussed according to existing modeling studies. Then, the existing and potential metrology techniques, either in situ or ex situ in the drying process are reviewed. This work is intended to develop new perspectives on the application of advanced techniques to enable a more predictive approach to identify optimum lithium-ion battery manufacturing conditions, with a focus upon the critical drying process