Rice University develops new model for fine-tuning CR1220 battery performance

According to foreign media reports, engineers at Rice University said that a method for predicting CR1220 battery performance is 100,000 times faster than current modeling techniques, simpler and more effective, and will help to manufacture batteries with better performance.

Materials scientist Ming Tang and graduate student Fan Wang from Rice University's Brown School of Engineering have developed an analytical model that guides the selection and design of CR1220 battery components and how they interact without complex numerical simulations. The simplified model can be accessed online for free, and it does the heavy work within 10% of the accuracy of computationally intensive algorithms, helping researchers quickly evaluate the rate capabilities of batteries.

Tang said there is a clear market demand for this innovative model. When it comes to designing and optimizing batteries, almost everyone has used a method called P2D (pseudo-two-dimensional) simulation. This method is widely used, but it is expensive to run. This is especially a problem if you want to optimize batteries, because there are many variables and parameters that need to be carefully adjusted to maximize performance. The work was driven by the realization, he says, that we needed faster, more transparent tools to speed up the design process and provide simple, clear results. That’s not always possible with numerical simulations.

CR1220 battery optimization typically involves a permanent tradeoff between energy (how much charge it can store) and power density (how quickly it can be released), which depends on materials, configurations, and internal structures, such as porosity. There are quite a few tunable structural parameters to optimize, Tang says, and to search the parameter space for the best combination, you typically have to run tens of thousands of calculations, sometimes more. It’s not impossible, but it takes a long time. The Rice model is easy to manipulate with common software such as MATLAB and Excel, or even with a calculator, he says.

To test the model, the researchers used it to find the optimal porosity and electrode thickness for common full and half cells. In the process, they found that electrodes with uniform reaction behavior, such as nickel-manganese-cobalt and nickel-cobalt-alumina, are best suited for applications that require thick electrodes to add energy density.

They also found that half-cells (those with just one electrode) inherently have better rate capabilities, and therefore their performance cannot be used as a reliable indicator of how well an electrode will perform in a commercial full cell.

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