A Compact Methodology Via a Recurrent Neural Network for Accurate Equivalent Circuit Type Modeling of Lithium-Ion Batteries

This work investigates the modeling of lithium-ion batteries (LIBs) with a recurrent neural network (RNN), rather than with an equivalent circuit or similar type model as is typically used. The RNN is trained with dynamic battery data, such as vehicle drive cycle test results. Specialized characterization tests and model parameterization are not necessary, simplifying the process of battery modeling. A compact unified methodology consisting of …