DEFACTO enables us to thoroughly examine by simulations nearly every aspect of battery manufacturing on multiple scales – Interview with the Technical University of Braunschweig

DEFACTO enables us to thoroughly examine by simulations nearly every aspect of battery manufacturing on multiple scales – Interview with the Technical University of Braunschweig

Silas Wolf, from the Technical University of Braunschweig (TUBS) speaks on this interview about the main role of TUBS in the DEFACTO project, their expectations, and the work they will carry out on modelling and simulation of electrode processing.

Q: What is the main role of TUBS in DEFACTO?

A: At the Institute for Particle Technology of the Technical University of Braunschweig we have a broad knowledge of electrode manufacturing as well as particle simulation. Therefore, our role in the project consists of two parts. On the one hand, the main task is the simulation of the electrode production from the processing of the electrode slurry over the coating and drying step to the final calendering fixing the electrode structure. On the other hand, apart from performing simulations, we are also responsible for the manufacturing of battery electrodes in our pilot plant with extensive characterization of the suspensions and electrodes. This will enable us to properly calibrate and validate our models.

Q: What are your expectations from the project?

A: The project consortium combines competences in multiple fields of modelling and characterization of lithium-ion battery materials, electrodes, cells and their behavior during cycling. Therefore, DEFACTO enables us to thoroughly examine by simulations nearly every aspect of battery manufacturing on multiple scales. Having project partners that are able to characterize the electrode microstructure in detail allows for determining influencing factors in modelling and manufacturing on a level of detail that is not possible for us yet.  Being able to understand the influences in every process step on the performance of the resulting batteries will push the development of new processes for the manufacturing of next generation batteries. Also, the optimization tool could lead to rethinking of already established processes to increase the quality and lowering the costs of the resulting electrodes and cells even further.

Q:   Can you talk a bit about the work you are planning to do on modelling and simulation of electrode processing?

A: For the simulation of the electrode process chain and the resulting microstructure we use a combination of the discrete element method (DEM), a particle simulation technique, and computational fluid dynamics (CFD), a method for simulating fluid flow. In a first step, we will develop models that can capture the influence of material and machine parameters of electrode slurry production on the resulting particle sizes. For this, fluid forces acting on particle agglomerates leading to the breakage of such can be captured by coupling CFD and DEM. After the coating of the slurry on the current collector, the slurry is being dried. Therefore, forces acting on the particles due to surface tension of the solvent and the displacement of the fluid as well as particle collisions need to be considered. Additionally, agglomeration and diffusive effects can have an influence on the resulting porous electrode structure and might therefore have to be included. Here, the fluid forces acting on the coarser active material particles will be calculated based on a resolved fluid field around the particles whereas the forces acting on the smaller conductive additive particles will be taken account for in an unresolved, volume averaged manner. The electrode microstructure resulting from drying is compressed in the calendering step which can be simulated by using DEM only in which interparticle bonds mimic the binder and an elastic-plastic contact force model is able to represent the compaction of the microstructure. The computational generated electrode structure can then serve as an input for the modelling of the following cell manufacturing steps.

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