P2-041_Schlösser
As the parameterisation of an electrochemical model is time-consuming and requires a lot of equipment, this paper presents a new approach for determining the 18 main parameters of a Doyle-Fuller-Newman model. This is based on a machine learning model trained with simulations. By using PyBaMM 20000 EIS are simulated and used as a training dataset […]
P1-062_Abke
Lithium-ion batteries (LIBs) have been the primary choice for rechargeable energy storage in mobile applications since their inception in 1990. Despite continuous improvements, LIBs are approaching their theoretical limits, particularly in the context of the increasing energy demands of electric and hybrid electric vehicles. Lithium sulfur batteries (LSB) with lithium metal anodes address these challenges […]
P2-066
At the core of this research is the detailed analysis of battery electrode microstructures through computer vision techniques. By employing supervised learning methods such as classification and segmentation, the team has made significant strides in interpreting the complex internal structure of battery components. This deep dive into microstructural analysis is crucial for identifying key characteristics […]
P5-055
Sodium-ion batteries (SIBs) are gaining momentum, driven by highly fluctuating material costs, rising supply chain and ecological risks in the lithium-ion battery (LIB) industry. Postulated advantages of SIBs include a wide resource availability, lower cost and higher sustainability. However, sodium’s lower reduction potential, along with its larger and heavier ions, lead to decreased energy densities […]
P3-032
Battery technology is undergoing significant advancements due to the urgent need to combat climate change. To fully utilize batteries, monitoring and controlling their parameters, such as temperature, state-of-charge (SOC) and state-of-health (SOH), is crucial. A battery management system (BMS) with distributed sensors is used for this task but requires efficient data communication between the main […]
P5-081
In the production of lithium-ion batteries the secondary drying step is hardly investigated and little knowledge about the different secondary drying processes exist. Importantly, it is the last process step before cell assembly and hence can affect the quality of the battery components, e. g. electrodes. Furthermore, a comprehensive understanding regarding the influences on parameters […]
P1-087
This poster elucidated the governing factors for dendrite growth in lithium metal batteries (LMBs). Mechanistic insights are obtained by modeling dendrite growth on a coarse–grained (CG) and atomistic scale. Governing trends derived from the model have been compared to experimental observation. Driven by the increasing demand for portable high–capacity energy storage, there is a renewed […]
P2-066
At the core of this research is the detailed analysis of battery electrode microstructures through computer vision techniques. By employing supervised learning methods such as classification and segmentation, the team has made significant strides in interpreting the complex internal structure of battery components. This deep dive into microstructural analysis is crucial for identifying key characteristics […]
P5-029
So far, weld joints have mainly been characterised using elaborate cross-section preparation to obtain information about their quality, especially their size. However, this method is time-consuming, destructive, and not suited for inline qualification. In recent years, non-destructive characterisation of weld joints using Scanning Acoustic Microscopy (SAM) and X-ray absorption have emerged as promising alternatives. Via […]
P4-015
This study breaks down the supply chain for an NMC811/graphite prismatic battery cell, identifying 27 crucial processes from the mines to the final cell factory. We are investigating the logistical network formed by the top 3 producing countries in each process. For this, we developed a model to evaluate the determined locations in the network. […]