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.
Optimization of current excitation for identification of battery electrochemical parameters based on analytic sensitivity expression,
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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.