A TD3-trained current excitation policy yields higher Fisher information and lower parameter estimation errors for anode and cathode rate constants than NMPC and conventional test profiles, in simulation only.
Optimal ex- perimental design for parameterization of an electrochemical lithium- ion battery model,
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Optimal Design of Experiment for Electrochemical Parameter Identification of Li-ion Battery via Deep Reinforcement Learning
A TD3-trained current excitation policy yields higher Fisher information and lower parameter estimation errors for anode and cathode rate constants than NMPC and conventional test profiles, in simulation only.