Abstract: A method for monitoring a device battery for the presence of an anomaly in the battery operation. In some examples, the method includes providing temporal operational variable profiles of operational variables for the device battery; determining an input dataset of operational characteristics for a historical evaluation period as a function of the temporal operational variable profiles; and using an anomaly detection model with an encoder/decoder model to determine a reconstruction error for the input dataset. The encoder/decoder model is trained with input datasets of device batteries of normal function to map an input dataset onto an input dataset that is reconstructed as identically as possible. When a reconstruction error is found, a rule-based criticality value is determined as a function of one or more characteristic-based criticality values. An error type is also signaled.

Abstract: The disclosure relates to a method for providing an aging state of a device battery of a battery-operated device including detecting curves of operating variables of the device battery and providing at least one load factor at a determination time, providing a correction model that maps a correction variable depending on the at least one load factor, and ascertaining an aging state by evaluating the curves of the operating variables with the aid of an aging state model or an aging state observer or an aging state measurement and depending on the correction variable resulting from the at least one load factor of the device battery of the battery-operated device at the determination time.