Battery optimization generally involves a tradeoff between energy (the amount it can store) and power density (the rate of its release), all of which depends on the materials, their configurations, and such internal structures as porosity. There are adjustable parameters associated with the structure that need to be optimized. Typically, tens of thousands of calculations need to be made to search the parameter space and find the best combination. This is a time-consuming process.
Researchers have developed a faster and simpler method that does not require complex numerical simulation to guide the selection and design of battery components and how they interact. The simplified model has an accuracy within 10% of more computationally intensive algorithms and will allow researchers to quickly evaluate the rate capability of batteries.
Almost all battery cell designers and optimizers use pseudo-two dimensional (P2D) simulations, which are expensive to run. This especially becomes a problem when optimizing battery cells because they have many variables and parameters that need to be carefully tuned to maximize the performance.
The new tool provides a faster, more transparent way to accelerate the design process and offers simple, clear insights that are not always easy to obtain from numerical simulations. The model could be easily implemented in such common software as MATLAB and Excel, and even on calculators.
To test the model, the researchers let it search for the optimal porosity and thickness of an electrode in common full- and half-cell batteries. In the process, they discovered that electrodes with “uniform reaction” behavior such as nickel-manganese-cobalt and nickel-cobalt-aluminum oxide are best for applications that require thick electrodes to increase the energy density. They also found that battery half-cells (with only one electrode) have inherently better rate capability, meaning their performance is not a reliable indicator of how electrodes will perform in the full cells used in commercial batteries.