Fast charging can increase the risk of lithium plating, a condition where metallic lithium deposits on the battery anode. This can contribute to capacity loss, battery aging and safety concerns, while conventional voltage, current and temperature measurements cannot directly detect the condition.
To address this, Gamma Technologies combines its physics-based battery model, GT-AutoLion, with machine learning to estimate anode behavior and generate a real-time lithium-plating risk indicator without additional hardware. The indicator can support feedback-based charging control, allowing charging current to be adjusted according to the estimated plating risk. With this approach, Gamma Technologies aims to make lithium plating a measurable and manageable factor in battery charging, rather than a hidden risk.
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