Assessment of State-of-Charge Estimation Method for Lithium-Ion Batteries
In this paper, a numerical model of lithium-ion batteries is developed and deployed to a Speedgoat Baseline target machine. The estimation method for the state-of-charge (SOC), based on a nonlinear autoregressive with exogenous input (NARX) and artificial neural networks (ANNs) that are correctly trained with multiple datasets, is designed, and experimentally validated by hardware-in-the-loop simulation.
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