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A Data-Driven Identification Method for Reaction Rate Constant and Diffusion Coefficient in the P2D Model
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DOI：10.1016/j.cjche.2025.05.045.png)
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Abstract
En 中文
• A DNN-driven method is proposed for determining internal state parameters of lithium-ion and sodium-ion batteries. • Four different systems of Li-ion and Na-ion batteries were identified. • The battery parameters before and after aging is identified and compared. • DNN has demonstrated the ability to learn and recognize the material state inside the battery
Keywords:
deep neural network
lithium-ion batteries
sodium-ion batteries
battery state estimation
aging analysis
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