Contributed by Niloofar Kamyab, Product Management Lead, COMSOL, Inc.
The demand for producing long-lasting, safe batteries spans various industries and is particularly prominent as novel technologies continue to emerge. The automotive and aerospace & defense industries are seeing a rapid rise in the production of electric vehicles, drones, and electric vertical takeoff and landing (eVTOL) aircraft. Battery-powered technology in the healthcare and electronics industries is continuously becoming more advanced. More governments and agencies in the energy industry are adopting battery energy storage systems (BESS) to store excess clean energy. The competitive markets for these applications require faster and more efficient battery design processes.
To add to the complexity of current battery demands, an optimal battery design cannot be easily applied across different applications. Similar to the applications mentioned above, which differ in style, size, and use, the batteries required to power such applications also vary in their design requirements. For instance, the weight of batteries in an eVTOL, which requires lightweight components to ensure a smooth takeoff and steady cruise period, is more critical than in the design of batteries for stationary devices such as BESS, where low cost and long cycle life are more important considerations.
Adapting battery designs to specific applications requires a strong understanding of battery operation, including how different chemistries, component properties, cell architecture, pack configurations, and operating conditions influence overall performance, longevity, and safety. Modeling and simulation provides a means to analyze these factors and optimize battery designs. Beyond design, battery users also benefit from a deeper understanding of battery behavior, enabling improved and more efficient use.
In this article, we will discuss the motivation for modeling batteries across different scales, from the microscale to the cell scale and pack scale, and what engineers and researchers can gain by incorporating these models into their workflow.
Modeling at Different Scales
Battery modeling serves a range of purposes depending on the modeling objectives. By recognizing the specific modeling needs and selecting the appropriate scale, researchers and engineers can fully leverage the benefits of simulation software. Some use microscale modeling to conduct fundamental studies of battery chemistry, porous structures, and aging mechanisms, enabling the development of high-performance battery cells.
Others focus on cell-level optimization, analyzing how geometric and material properties influence battery operation and life. At the pack level, engineers may concentrate not only on battery cells but also on other components connected to them, such as electric connections and cooling systems, to ensure uniform operation while mitigating abuse scenarios such as thermal runaway. Across all these scales, time-dependent studies can be used to investigate different load profiles and real-world operating conditions, while electrochemical impedance spectroscopy (EIS) simulations enable analysis and characterization of batteries based on their frequency response.
Microscale Modeling
Modeling at the microscale enables visualization of the detailed structure of a battery cell and provides an in-depth understanding of its components. By constructing a microscale model, also known as a heterogeneous model, one can study the arrangement of materials within porous electrodes, examine factors such as particle size, porosity, and distribution, and simulate particle-level physics to analyze how structural details influence battery performance.
Model geometries at this scale, whether obtained through imaging-based techniques such as X-ray or TEM tomography, or generated synthetically when full imaging isn’t feasible, serve as the simulation domain for resolving underlying physics, including electrochemical reactions as well as mass and charge transport, as shown in the example of a heterogeneous model of an NMC electrode structure in Figure 2.
Multiphysics aspects can also be explored in microscale models. For instance, coupling electrochemistry with structural analysis in a heterogeneous model of a solid-state battery cell, as shown in Figure 3, enables the study of particle expansion and contraction caused by lithium intercalation and the resulting stress in the solid electrolyte. A microscale approach also provides a higher-resolution view of degradation mechanisms at the particle level, offering insight into how a battery ages over time and how designs can be modified to minimize this process.
Cell-Level Modeling
At the cell level, the detailed electrode microstructure is homogenized and represented by averaged properties such as porosity and tortuosity (Figure 4).
This high-fidelity framework, based on porous electrode homogenization and known as the Doyle–Fuller–Newman (DFN) model, can be used, for instance, to study nonuniform current distribution (Figure 5) and electrode utilization, which may lead to inefficient electrode use and accelerated aging. For a different objective, it can also be applied to investigate geometrical effects introduced during the manufacturing of a lithium-ion battery by spirally winding the active materials to create a cylindrical jelly roll design.
Results from the example model indicate locally higher discharge rates at the ends of the spiral, which could lead to shorter lifetimes in these regions compared to the more uniformly discharged inner parts of the spiral (Figure 6). Additional modeling objectives and analysis needs can similarly be addressed using this framework.
In addition to high-fidelity frameworks, simplified approaches with lower complexity can also be used for cell analysis, such as the single-particle model (SPM) and its extension, SPMe, as well as lumped or equivalent circuit models, which are easier to set up and run faster. All of these approaches, regardless of complexity, can be applied to any cell format, such as cylindrical, pouch, and prismatic cells, and can be extended to a variety of battery chemistries. The flexibility to model different chemistries, including lithium-ion and beyond, is increasingly important as next-generation technologies such as solid-state, sodium-ion, and lithium–sulfur batteries continue to emerge, along with various types of flow batteries (Figure 7) that are also gaining interest for stationary applications.
Electrochemical cell models can be coupled with other physics as well. For instance, by integrating electrochemical and thermal analyses, one can capture the effects of temperature on cell performance and degradation. As shown in Figure 8, the temperature distribution in a jelly roll and current collectors reveals higher temperatures near the terminals, indicating potential hotspot areas.
Pack-Scale Modeling
Pack-scale models with simplified embedded electrochemical models enable the simulation of hundreds of cells arranged in various configurations, allowing for full electrothermal analysis of 3D battery packs in a time-efficient manner. Battery pack designers can also incorporate electrical components such as current collectors, feeders, and busbars, along with cooling systems, to gain a comprehensive understanding of overall performance and to evaluate thermal management strategies, as shown in Figures 9, 10, and 11.
By analyzing electrothermal models of packs or modules, engineers can evaluate temperature gradients during operation and their impact on the performance of both individual cells and the pack as a whole. Phenomena such as capacity loss, short circuits, and thermal runaway propagation can also be studied in the context of abuse conditions. Such simulations enable engineers to assess the likelihood of thermal events in a design or to virtually trigger such events in order to study how quickly thermal runaway would propagate, the maximum temperature reached in the pack, and the total amount of heat released as a result.
The Multiscale Approach Benefits All Battery Applications
Multiscale modeling enables virtual iterations of battery designs, providing more accurate predictions of performance and aging before physical prototypes are built and offering a better understanding of their behavior to support improved use. Across the many industries where batteries are used today, whether engineers are focused on manufacturing, optimization, or integrating with other components, design teams can benefit from simulation by selecting the modeling scale that best matches their needs and desired level of analysis
