Speed up the development of EV battery cells with parametric design optimization

by Apurva Gokhale and Michael Bambula Edited for #SimulationSaturday by Thomas G.

This #SimulationSaturdaySpecial article is based on the webinar “ESTECO & AVL Webinar: Robust design of a lithium ion battery considering manufacturing tolerance” https://www.youtube.com/watch?v=1OLmp4DeoAA originally broadcasted on Nov 13, 2023 and the full length blog post “Speed up the development of EV battery cells with parametric design optimization” https://engineering.esteco.com/blog/optimize-ev-battery-parametric-design/ originally posted on Sept 24, 2024

Optimizing Lithium-Ion Battery Manufacturing with Simulation-Driven Design

The global trend towards electrification, particularly with the rise of electric vehicles (EVs) in the automotive industry, has created a growing demand for lithium-ion batteries. This relatively new domain presents significant challenges for original equipment manufacturers (OEMs) and pack suppliers who often lack expertise in the chemical manufacturing process involved in making these batteries.

At the heart of lithium-ion batteries is the cell, the fundamental building block. Designing an optimal cell requires a thorough understanding of its requirements, which includes delivering high energy density, maintaining stable voltage output, ensuring a long cycle life, and demonstrating excellent thermal stability. It’s important to design a battery cell that can maintain required performance even when subjected to manufacturing tolerances.

To address this knowledge gap and improve the cell manufacturing process, a simulation-driven approach which combines the AVL multi-physics system simulation solver with the ESTECO modeFRONTIER’s process automation and design optimization software can be used.

Overview of Lithium-Ion Battery Manufacturing Process

The simulation-driven design approach helps to identify optimal cell designs and predicts their performance in view of manufacturing tolerances. But, before we get into the specifics of the approach, let's take a look at the stages of the manufacturing process for lithium-ion batteries relevant to the simulation analysis:

1. Dosing and Mixing of Electrode Slurry: The electrode slurry for anode and cathode, consisting of active material, binder, additives, and solvents, must be carefully blended to ensure the uniform distribution of these components. Proper dosing of the raw materials is essential to achieve the desired electrochemical performance of the battery.
2. Coating and Drying of Electrode Foil: The electrode foil is then coated with slurry using a slot die to ensure distribution. Monitoring the coating of the foil is critical to achieving the desired porosity and layer thickness. The coated sections are then sent through a drying channel to remove any excess moisture and solidify the coating.
3. Calendering of Electrode: To ensure the uniform thickness of the electrode, which is essential to performance, the lithium-ion battery undergoes calendering. The foil is compressed with rollers and shaped into the final form. The roller pressure influences porosity and the energy density of the cell. An excessive roller pressure will cause stress cracks in the electrode.

Manage Battery Development with AVL Advanced Simulation Technologies

Electrochemical experimentation for lithium-ion battery development is a time-consuming process. It requires multiple hands-on steps to create a prototype cell and thorough testing which takes even more time. AVLs CRUISE? M simulation software is capable of virtualizing much of this process. It defines chemistries, assesses the resulting cell performance, and analyzes the electrical, thermal, and safety characteristics of the battery system in a virtual environment — all at a fraction of the time and cost of the real experimental process.

In this study to showcase simulation-driven design, six parameters with characteristics that are sensitive to the early- stage manufacturing of the battery cell were selected. The slurry preparation, coating and drying, and calendering processes impact the layer thickness, porosity, and particle radius of the anode and cathode. These parameters were selected to understand how deviations in the manufacturing process could ultimately affect cell performance. To understand the impact of these variables on cell performance, statistical methods like those found in ESTECO modeFRONTIER need to be applies. AVL CRUISE? M can be executed repeatedly during the variation study, a process seamlessly integrated with modeFRONTIER. Given the computational complexities involved, the modeFRONTIER ability to generate accurate meta-models (Response Surface Models) is invaluable. Together, these capabilities in a cohesive workflow between CRUISE? M and modeFRONTIER create a powerful tool for battery chemistry assessment.

Optimize a Battery Cell Simulation Model with modeFRONTIER

After creating a model of the lithium-ion battery cell, modeFRONTIER is used to automate the simulation of the AVL CRUSIE? M model. This automated simulation process enables to run design exploration and optimization studies, where various algorithms modified design parameters and analyzed their impact on key objectives.

The procedure can be summarized via the following steps (An in-depth explanation can be found in the original blog post):

1. Integrate CRUISE M’s electrochemical battery model into an automated simulation workflow
2. Perform Design of Experiments (DOE) and sensitivity analysis
3. Apply design optimization to maximize charge and minimize power loss
4. Understanding variations in performance due to manufacturing tolerances

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As a result powerful visualizations like the example result shown below, help the engineer understand the sensitivity and correlations among design variables, optimize performance criteria while respecting constraints.

Conclusion

In summary, a comprehensive simulation driven approach to the parametric design of lithium-ion battery cells can contribute to accelerated development of tailored battery cells. With AVL CRUISE? M, the battery can be modeled and simulated, and with ESTECO modeFRONTIER the simulations can be automated in a way to conduct multiple design exploration and optimization studies. Understanding the sensitivity and correlations among design variables, optimize performance criteria while respecting constraints are key for educated design and manufacturing decisions. Performing robustness analysis around the selected designs to ensure that charge and power loss performance remain within acceptable limits despite uncertainties in design variables should be standard method for advancing cell design.?

?As much as we love to nerd out about simulation and read lengthy articles about it, we have to cut it short at this point.

We want to thank Apurva Gokhale and Michael Bambula for the insights and the impressive work that is performed day to day behind the scenes.

Real-world activities and their real-time limitations bring this Simulation Saturday to an end, but stay tuned for another one soon!

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