Fraunhofer Institute for Industrial Mathematics ITWM
Fraunhofer Institute for Industrial Mathematics ITWM
Original REM-Aufnahme »structur.e«
© Fraunhofer ITWM / Institut für Materialforschung Hochschule Aalen
Original REM-Aufnahme »structur.e«

Project »structur.e«

Our BEST simulation software is being used in the project »structur.e«. The aim is to enable a shorter charging time and a greater range for electromobility. This is realized by analysing cell ageing and cell performance based on simulations.

© Fraunhofer ITWM / Institut für Materialforschung Hochschule Aalen

Analysing Aging and Microstructure Designs of Li-Ion Batteries by Simulation

BMWK Project »structur.e«: The Next Generation of Lithium-Ion Batteries

Two key criteria for battery electric vehicles (BEVs) are the range of the vehicle and its fast-charging capability. On the battery level, the former translates to demands for high energy densities for the battery cells, while the latter imposes demands for high power densities. However, these two criteria are typically conflicting, such that an improvement in one of them comes at the cost of a trade-off in the other. 

The BMWK-funded project »structur.e« is therefore focusing on the development of processing techniques that modify the anode microstructure in such a way that the power density of electrodes is as high as possible despite the high energy density. This will improve the fast-charging capability of long-range electric vehicles. The focus is specifically on anodes, as they are the limiting factor for fast-charging scenarios. During fast charging, the life of the battery is significantly impaired due to cell degradation caused by lithium plating and growth of the solid electrolyte interphase (SEI) layer.

Our team at Fraunhofer ITWM is involved in the project with mathematical expertise and our electrochemical simulation software BEST. We are further developing BEST to capture cell degradation and electrode structuring methods in our simulations. This enables us to answer design questions within the project and provides insights into the internal transport processes of Li-ion batteries.

Challenges for the automotive industry and their impact on the requirements for Li-ion batteries for electric vehicles
© Fraunhofer ITWM
Challenges for the automotive industry and their impact on the requirements for Li-ion batteries for electric vehicles.

Cell Aging and Degradation – Simulations in BEST

Cell aging is strongly influenced by the stability and growth behaviour of the solid electrolyte interphase (SEI), a thin, porous layer which forms on top of the anode active material. Thus, it is essential to capture this effect in simulations in order to make accurate predictions for the aging behaviour of Li-ion batteries.

Within this project we implemented a long-term SEI growth model from our project partner DLR into our BESTmicro model. The resulting model is able to describe both calendar and cyclic aging behaviour resulting from the inhomogeneous growth dynamics of the SEI along the anode active surface area.

The aging rate can be quantified by evaluating the capacity fade and power fade resulting from the SEI. Regarding the implementation, we modified our numerical solution approach to account for the newly introduced characteristics of the model based on the introduction of the SEI. Consequently, we were able to significantly improve the performance and stability of the cell aging simulations.

Furthermore, the SEI model has been adapted and integrated into our cell scale model BESTmeso, which allows to get estimates on the effective cell aging behaviour and SEI distribution on electrode scale, while requiring less computational effort. 

The Solid Electrolyte Interphase (SEI)
© Fraunhofer ITWM
Qualitative representation of cell ageing simulations by SEI growth in BESTmicro and BESTmeso. Starting from an initial, thin SEI layer, both models depict the long-term SEI growth during storage and dynamic operation. The detailed simulation in BESTmicro resolves the inhomogeneous SEI layer thickness along the complex surface of the anode microstructure, while the more efficient BESTmeso simulation describes the effective layer thickness on the homogenized electrode.

Investigate 3D Electrode Perforation by Simulations in BEST

The project is concerned with different 3D microstructure design techniques to improve fast charging capabilities for high energy density Li-ion batteries. By introducing electrolyte channels into the anode, the goal is to improve accessibility of active material deep inside the electrode. As a result, intercalation takes place more homogeneously and the risk for lithium plating is reduced. Assuming a fixed energy density, the crucial question becomes, if there is a benefit by distributing the electrode porosity locally in form of the electrolyte channels in comparison to electrodes with the same effective, but homogenous, porosity.


While this design question can also be investigated with BESTmicro, we focus in this project on using BESTmeso to allow for more efficient simulations. Thus, we developed a model adaptation which allows to capture the three-dimensional perforation patterns within the pseudo-4D BESTmeso model. In order to evaluate the electrolyte transport through the different anode designs, we determine the ionic resistance of the electrodes by performing electrochemical impedance simulations on symmetric cells. The tested anode designs and the obtained impedance results are shown in the picture down below.

Our simulations show that the perforation can improve the ionic resistance of the electrode compared to an unperforated electrode of the same effective, but homogenous, porosity. However, this depends on the parameters of the perforation pattern. Performing a parameter study for the perforation pattern under the assumption of constant volume removal, we identify a trend for an optimal design to feature deep, narrow, and densely distributed electrolyte channels. 

Results of symmetric cell impedance simulations in BESTmeso using different anode designs. The small plot shows a zoomed in part of the plot on the left. The obtained impedance allows to determine the ionic resistance of the electrode designs, which exhibits a monotonic dependency on the length of the 45°-line segment. The overall smallest resistance is obtained with Anode 8, while Anode 1 yields the largest resistance.
© Fraunhofer ITWM
Results of symmetric cell impedance simulations in BESTmeso using different anode designs. The small plot shows a zoomed in part of the plot on the left. The obtained impedance allows to determine the ionic resistance of the electrode designs, which exhibits a monotonic dependency on the length of the 45°-line segment. The overall smallest resistance is obtained with Anode 8, while Anode 1 yields the largest resistance.

Project Funding and Duration

The project is scheduled to run for four years (01.05.2019 - 30.04.2023) and is funded by the Federal Ministry of Economics and Climate Policy (BMWK) (funding reference: 03ETE018G).

Logo structur.e
© structur.e
Structur.e

Related Links: