Abstract: The present disclosure relates to a method for determining battery design parameters that satisfy all of current rate (C-rate)-specific target capacities using a neural network model. A method for determining battery design parameters according to an embodiment of the present disclosure includes: training a neural network model with correlations between design parameters of a battery and current rate-specific capacities; creating profiles of current rate-specific capacities corresponding to design parameters, respectively, by inputting design parameters sampled within preset ranges into the neural network model; and determining at least one group of design parameters satisfying all of current rate-specific target capacity conditions on the basis of the profiles.

Abstract: A method for preparing a negative electrode active material for a lithium secondary battery according to one aspect of the present invention comprises the steps of: uniformly mixing silicon and metal oxide; and heating or ball-milling the mixture.