Fourier and laplace transform used in pretreatment for neural network battery modeling

Abstract

To solve the large storage capacity in neural network battery modeling, an input pretreatment, based on Fourier or Laplace transform, is proposed. As simulation shows, the improved battery model gets a better precision and consumes a smaller storage capacity. This method can also be used in SOC estimation if farther experiments are conducted.