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Janina Costard

M. Sc. Janina Costard

Room: 330
Phone: +49 721 608-47583
Fax: +49 721 608-47492
janina costardOpw0∂kit edu

Institut für Angewandte Materialien - Werkstoffe der Elektrotechnik (IAM-WET)
Adenauerring 20b
Gebäude 50.40
D-76131 Karlsruhe

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Lithium-Ionen Batterien
Lithium-Ionen Batterien

M. Sc. Janina Costard

Marina Botros

Lithium-Ionen Batterien

Janina Costard

Marcel Heinzmann

Lithium-Ionen Batterien

Firat Yüce

Model-aided design of positive electrode blends




Fig.1: Modeling of two particles of different chemistry and size by  parallel connection


Lithium is the lightest solid element of the periodic table of elements and moreover provides the highest electrochemical potential, leading to high power and energy density. Consequently, lithium is ideally suited as material for battery electrodes for automobile applications. Therefore, an optimization of the particular components of the cell is indispensable. The cathode is thereby the limiting component with regard to performance, energy and power density. The overall goal of the optimization is an increase of energy density to achieve longer driving range and lower weight as well as an increase of power density for shorter charge time and good acceleration. For optimizing the cathode processes, all occurring loss mechanisms have to be understood and analyzed. Therefore, an electrochemical equivalent circuit model of the cathode is established, which can reproduce the cell impedance and performance in dependence of the cell chemistry under a variation of operating parameters.

For fulfilling the requirements on electric vehicle batteries, the advantages of different cell chemistries are combined in blend cathodes consisting of two or more distinct lithium intercalation compounds. One example therefore is the composition of LFP (lithium iron phosphate) and NMC (nickel-manganese-cobalt), exploiting the stability of LFP and the high energy density of NMC. The influence of the amount of iron phosphate on the performance of the cathode has to be analyzed be systematic variation. Consequently the model should be able to predict the cathode performance in dependence of the composition by evaluating the measurement results of the pure materials.



Fig.2: impedance spectra of a lithium ion battery with varying temperature

To fully exploit the capabilities of different electrode materials, the electrodes microstructure is of enormous importance. As is known, small particles lead to high power density, whereas big particles enable high energy densities. A bi-modal distribution of particle size with small particles on the interface of cathode and electrolyte can possibly combine these features. The presented model should consider the influence of the microstructure parameters such as porosity, active surface and particle size distribution, as well as the influence of the electrode composition.

As can be seen in figure 1, the model realizes these variations by a parallel connection of the particular models for different particle sizes and active material chemistries. The model is based on measurement results of established measurement tools, such as electrochemical impedance spectroscopy (EIS) and time domain measurements. These tools are highly supportive for analyzing loss processes taking place on different time-scales. An identification of the physical origin of the loss processes becomes possible by a variation of operating parameters, such as temperature (figure 2) and state of charge.

For a correct interpretation and evaluation of the measurement results, a supplementation by structure analyses like scanning electron microscopy (SEM) and focused ion beam milling (FIB) is necessary.

Finally, the established model should enable a definition of an optimization procedure for cathode materials with regard to composition and microstructure to achieve a given feature profile.




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