Abstract: A method for processing status data of a battery comprises applying an autoencoder artificial neural network to initial status data. Reconstructed status data are obtained therefrom. The method comprises carrying out an aging estimation based on the reconstructed status data in order to obtain a status indicator which is indicative of an aging status of the battery.

Abstract: A method for monitoring a battery system is proposed. The method includes providing a sequence of pairs of measured current and voltage values that follow one another in time. The pairs of current and voltage values indicate the current flowing through the battery system and the voltage present at the battery system. The method also provides for an electrical equivalent model of the battery system to be provided. The equivalent electrical model has several impedances connected in series. Initial impedance parameter values are provided for the impedances of the equivalent electrical model. The method provides for adjusting a first impedance parameter of an impedance of the equivalent electrical model based on the difference between a first voltage value simulated based on the initial impedance parameter values and the first current value of the finite sequence and the first measured voltage value of the finite sequence. An optimized first impedance parameter value is thereby obtained.