What are the applications of electrochemical simulation technology in 2025 button cell battery research?

With the introduction of the timetable for the ban on the sale of fuel vehicles in various countries, the status of new energy vehicles has become increasingly stable. As the core power source of electric vehicles, lithium-ion batteries are also increasingly sought after by the market. The production process of lithium-ion batteries involves the selection and matching of materials such as positive electrodes, electrolytes, negative electrodes, and diaphragms, and the selection of pole piece design parameters; the battery working process involves chemical reactions, mass transfer, conductivity, heat generation and other processes. It can be seen that lithium-ion batteries are a very complex system.

It is an effective means to explore lithium-ion batteries with experimental means, especially with the continuous advancement of characterization methods, we can get more and more information about the impact of design parameters, working conditions, etc. on battery performance. It is undeniable that in the development of lithium-ion batteries, there are too many design parameters and heavy experimental tasks; the impact of various parameters on battery performance is unclear, and the experimental design is somewhat blind, and sometimes even time-consuming, labor-intensive, and costly, but thankless. The opportunity to improve this situation is to apply battery simulation technology to batteries.

Lithium-ion battery simulation technology can use equivalent circuit models, semi-empirical models, electrochemical models, etc. Simulation technology based on electrochemical models can solve the problems mentioned above very well. As a supplement to experiments, electrochemical simulation can simulate various schemes before experiments to remove the dross and retain the essence; it can also simulate the charging and discharging process of batteries under different working conditions, which helps researchers to understand the internal process of batteries; at the same time, the experimental results can also point out the shortcomings of simulation and promote the continuous development of simulation models. It can be said that simulation makes experiments more powerful, and experiments make simulation icing on the cake.

Let's talk about electrochemical models briefly. Electrochemical models are mainly composed of three processes: mass transfer, conductivity, and electrochemical reactions. In terms of complexity, electrochemical models include single-particle models, quasi-two-dimensional models, two-dimensional models, and three-dimensional models. Quasi-two-dimensional models are commonly used. Based on this model, multiple purposes including battery design, charging and discharging performance, and battery internal resistance (polarization) analysis can be achieved. When predicting battery life, single-particle models are often used to reduce the amount of calculation.

01 Application of simulation technology in battery design

In the process of battery design, in addition to the inherent property parameters of positive and negative electrode materials, electrolytes and diaphragms, many design parameters need to be considered, such as positive and negative electrode particle size (r), electrode thickness (L), electrode porosity (ε), etc. Marc Doyle et al. used simulation technology to simulate Sony's graphite battery at a multiple, and the obtained battery rate performance was very similar to the test results. The following figure is a comparison of the test results and simulation results of the charge and discharge curves at different rates.

Venkat Srinivasan et al. used simulation technology to study the effect of particle size on the power density of LiFePO4 half-cells, and found that the use of small-particle positive electrode materials is conducive to improving the power density of the battery, providing a direction for the development of high-power batteries. The author also used the discharge platform of LiFePO4 to mark the ohmic overpotential, reaction overpotential and diffusion overpotential of the battery during constant current discharge, and found the reason why the platform becomes a slope during high-rate discharge, and at the same time provided ideas for reducing the internal resistance of the battery.

In the process of battery development, the model can be used to first explore the relationship between each design parameter and battery performance, determine the main influencing factors, and then conduct experiments on this factor, which can greatly reduce the amount of experiments.

02 Simulation of side reactions and lithium plating in batteries

In LiMn2O4 batteries, when studying the self-discharge caused by the co-embedding side reaction (irreversible) of the electrolyte solvent (PC) and lithium ions, the low-speed CV curve is used as the model correction standard, and the transfer coefficient of the side reaction is used as a variable parameter. For batteries with different active material loadings, the side reaction transfer coefficients obtained are different. Side reactions in batteries are difficult to control and monitor. Using models and parameter identification to obtain physical and chemical parameters related to side reactions is sometimes an effective means.

Lithium plating is one of the culprits for battery safety and capacity attenuation. In theory, lithium plating will occur when the lithium potential is lower than 0V. In fact, because the reaction requires a driving force, there will be a certain overpotential, which will cause the negative electrode lithium plating potential to deviate from 0V. In the lithium precipitation model, in addition to adding a BV formula to describe the lithium precipitation reaction, the influence of lithium deposition on capacity and the influence of the deposition layer on the particle surface film layer must also be considered. The study of LiMn2O4/graphite full battery found that N/P is an effective method to inhibit lithium precipitation. The larger the particle size, the easier it is to precipitate lithium. The thicker the pole piece, the easier it is to precipitate lithium. Lithium precipitation mainly occurs at the end of constant current charging. The lithium precipitation phenomenon rapidly weakens and disappears in the constant voltage stage. The figure below shows the effect of pole piece thickness, particle size, and charging cut-off voltage on the amount of lithium precipitation.

In addition, for other side reactions, such as the decomposition of electrolyte, the formation of SEI film on the negative electrode, and the generation of irreversible products in the electrode, simulation technology can be used to explore.

03 Battery internal resistance

DCR and EIS are commonly used to describe the internal resistance of the battery. Both internal resistances can be described by models. During the EIS test, a small disturbance signal is required to ensure that the system remains in a steady state, and the input signal is linearly related to the output signal. Therefore, in the modeling process, it is believed that the battery is in a steady state process and it is a linear response. Based on these assumptions and the fact that impedance has real and imaginary parts, the control equations of the electrochemical model are modified to obtain the EIS model. With the help of EIS simulation, the effects of diffusion, electrochemistry and other processes on EIS can be studied; the effects of the electrochemical activity and conductivity of electrode materials on EIS can also be studied; and the conditions of the two electrodes of the full battery can be examined separately. To simulate DCR, simply put, it is to change the charge and discharge mode in the electrochemical model, changing constant current charging or discharging to pulse charging or discharging. Andreas Nyman gave the calculation formula for polarization when analyzing various polarizations of batteries in his article, and based on this, calculated the proportion of different polarizations in each system.

04 Battery life prediction

There are many reasons for the capacity decay of lithium-ion batteries, such as material structure collapse, side reaction consumption of lithium, SEI consumption of lithium and the resulting increase in internal resistance, lithium precipitation, etc. For the convenience of calculation, only one or two decay reasons are considered in the general model.

The single particle model is a simplification of the quasi-two-dimensional model: it is assumed that all active particles in the pole piece are the same, that is, the internal lithium ion concentration distribution and the external environment are the same.

When the life decay is attributed to the reduction of electrolyte solvent, which consumes lithium and causes the negative electrode film resistance to increase, Gang Ning et al. quantitatively studied the effect of discharge depth (DOD) on discharge cut-off voltage, the effect of charge cut-off voltage on Li loss and internal resistance, and the effect of cycle number on capacity and internal resistance. The simulation results are consistent with our basic understanding of batteries, and its advantage is to quantify these effects.

Some researchers believe that lithium plating exists in most charging and discharging processes, and the inflection point of battery capacity decay rate (transition from linear decay zone to nonlinear decay zone) is caused by lithium plating. The basic idea is: in the first few cycles of the cycle, the formation of SEI film causes the local porosity of the negative electrode near the diaphragm to decrease, which increases the local electrolyte potential gradient and creates conditions for lithium plating; and lithium plating further causes the porosity to decrease, forming a positive feedback, which ultimately leads to exponential capacity decay. Based on this consideration, a life model of capacity decay caused by SEI growth and lithium plating is established. When predicting the life of the graphite system, this model has some small errors in predicting the charge and discharge curves during the cycle, but the flaws do not outweigh the merits; the accuracy of the capacity prediction during the cycle is relatively high. The model results show that the potential of the negative electrode electrolyte gradually increases from the diaphragm/negative end to the negative electrode/copper foil end; the electrode potential distribution also conforms to this trend. There is no lithium precipitation in the fresh battery, and lithium precipitation has occurred when the cycle reaches 1000 cycles; lithium precipitation first occurs in the negative electrode area close to the diaphragm, and the negative electrode potential is the lowest at the end of constant current charging, which is most likely to cause lithium precipitation.

The battery life is predicted by the electrochemical model. Although the model is relatively complex, it is based on the actual process inside the battery, so it is more accurate. Using the model to explore the main reasons for capacity loss is faster and more convenient than disassembling and testing the battery after the cycle.

The above is a brief introduction to the main functions of the electrochemical model in lithium-ion battery simulation, but the electrochemical model can do much more than that. Other things such as power, temperature rise, and safety can also be explored using the model. Although there are many difficulties in building electrochemical models ourselves, such as understanding the internal processes of the battery, solving partial differential equations and nonlinear equations, and coupling physical fields, there is now a commercial software Comsol that can help us quickly build electrochemical models and reduce the time and effort required for the modeling process.

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