A physics-informed neural network for pouch cell temperature estimation achieves 49.1% lower mean squared error and faster convergence than a purely data-driven model on varying cooling geometries.
Measurement of two-dimensional heat generation rate of pouch type lithium-ion battery using a multifunc- tional calorimeter,
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Physics-Informed Machine Learning for Pouch Cell Temperature Estimation
A physics-informed neural network for pouch cell temperature estimation achieves 49.1% lower mean squared error and faster convergence than a purely data-driven model on varying cooling geometries.