ユーザー事例集

By Sarah Fields
July 2019

Lithium-ion batteries can come in the form of laminated lithium-ion batteries for mobile electronic devices, cylindrical batteries for industrial power tools, and other cylindrical batteries for energy storage systems. The R&D division of Murata Manufacturing Co., Ltd., is using multiphysics simulation to examine batteries using lithium metal as a negative electrode material.

Dendrites, needle-like growths, are a fierce antagonist to efficient lithium-ion battery functioning. Dendrites form when a current is applied to a lithium metal electrode and can cause unwanted side reactions that result in short circuiting, drastically limiting the life of the battery.

Mitigating dendrite formation is an active area of research for the entire battery industry. Most researchers approach the problem of safety hazards and life span due to dendrite formation by changing the chemistry in some way. However, gains in this area have been painstakingly slow, prompting some researchers to take an alternative path.

When examining batteries that use lithium metal as a negative electrode material, Jusuke Shimura, a R&D engineer at Murata, looked to investigate the effect of changing the charging current pattern on dendrite formation.

This approach is gaining traction in the battery and energy storage world as the industry ramps up to meet the needs of an era of electrification and renewable energy.

Using Multiphysics to Minimize Dendrites

Lithium dendrite occurs when current is applied to the lithium metal electrode, resulting in a short circuit. “In order to commercialize lithium-ion batteries with lithium metal electrodes, this problem must be solved,” says Shimura.

The key to his approach was identifying a current pattern for charging that would minimize the growth of lithium dendrites. This approach works because at the off time between pulses, the concentration gradient at the electrode interface decreases, minimizing dendrite buildup. Also, introducing reverse pulses in the current pattern plays an important role by repeatedly dissolving formed dendrites.

To capture the electrochemical effects over his geometry, Shimura enlisted the battery modeling capabilities of COMSOL Multiphysics®. He used a combination of experimental evidence and simulation to determine the best charging pattern. Many researchers have been exploring this challenge from a chemical and material perspective. To make strides in this area, Shimura wanted to establish a baseline understanding of his physical system experimentally. It was important for him to understand the shape of dendrite formation over time. To accomplish this, he created an X-ray CT-compatible laminated cell that contains a contrast agent in its electrolyte membrane, and visually measured the formation of dendrites over time (Figure 1).

“I created a laminated cell that could be imaged with X-ray computed tomography, so that I would know where the dendrites are forming. Then, I used COMSOL® to find the best pulse pattern of charging to limit dendrite growth based on the shape and the size of the formed dendrites,” explains Shimura.

With the data from the X-ray computed tomography, Shimura created a model of a lithium metal cell and analyzed the effect of changing the current pattern. The results showed how much lithium metal precipitated onto the dendrite (Figure 2).

Using multiphysics modeling, Shimura evaluated various current patterns to determine the current pattern with the slowest rate of dendrite formation (Figure 3). This method allowed him to examine which has more lithium deposition — the electrode surface with planar diffusion (bottom part of Figure 3) or the dendrite with spherical-like diffusion (left part of Figure 3) through one cycle of the pulse pattern.

He ultimately found that a repetition of reverse pulse for 20 seconds, off-time for 10 seconds, forward pulse for 20 seconds, and off-time for 10 seconds resulted in the least dendrite growth (Figure 4).

「このパターンでは, デンドライとの成長率が3分の1未満になることがわかりました. 予想通り, これは充電パターンを変更することによってのみ達成されました. 化学は一定でした」とShimura氏は説明します.

Shimura氏のシミュレーションは, 実験的に決定されたデンドライトのサイズに基づいていました. これは, 電極の反応をモデル化するための濃度依存のバトラー・ボルマー方程式と, リチウムイオン輸送をモデル化するための結合拡散泳動方程式を利用する COMSOL Multiphysics のバッテリモデリング機能を利用しました.“

未来のバッテリーの開発

シミュレーションを使用して, Shimura氏はリチウム金属電極でリチウムイオン電池を充電するための最良のパルスパターンを見つけました. 直流を印加する場合と比較して, このアプローチは電池の寿命を3倍以上改善しました. 「COMSOLのおかげで, 最適化された充電パターンが電池の寿命を改善したことを第一原理に基づくシミュレーションで示すことができました」とShimura氏は言います.

Shimura氏は将来, マルチフィジックスシミュレーションが研究の速いペースを維持する上で継続的な役割を果たすと考えており,「COMSOLを引き続き使用して, 最適化された充電パターンの利点を市場の電池に利用できることを楽しみにしています」と言っています.