According to foreign media reports, Japan’s National Institute of Materials Science (NIMS) and SoftBank Corp.
Co-developed a model that can predict the (charge and discharge) cycle life of high-energy-density lithium metal batteries by applying machine learning methods to battery performance data analysis.
Research has proved that this model can accurately predict the service life of the battery by analyzing data on the battery’s charging, discharging and voltage relaxation processes without relying on any assumptions about specific battery degradation mechanisms.
This technology is expected to improve the safety and reliability of devices powered by lithium metal batteries.
, Battery life prediction model (Photo source: National Institute of Materials Science of Japan), lithium metal batteries have the potential to achieve higher energy densities per unit mass than currently used lithium-ion batteries.
Therefore, such batteries are expected to be used in various technologies such as drones, electric vehicles and household power storage systems.
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