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.
Modeling and estimation for advanced battery management,
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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.