Abstract: A computer-implemented method for determining an anomaly of a behavior of an electrical energy store in a technical device includes sensing an operating variable profile of at least one operating variable of the electrical energy store, and determining at least one feature from the sensed operating variable profile of the at least one operating variable of the electrical energy store. The method further includes evaluating an anomaly detection model using an autoencoder with a supplied input vector that includes or depends on the determined at least one feature, in order to determine a reconstructed input vector, and signaling an error based on a reconstruction error between the reconstructed input vector and the supplied input vector.

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: A method for determining an internal-resistance based state-of-health of a battery in a device includes determining the internal-resistance based state-of-health of the battery using a hybrid state-of-health model including a physical ageing model and a correction model by (i) determining, based on an electrochemical battery model, a physical state-of-health according to one or more operating parameters of the battery using the physical ageing model, (ii) mapping operating features derived from the one or more operating parameters onto a correction parameter using the correction model that includes a data-based configuration, and (iii) applying the correction parameter to the physical state of health to determine the internal-resistance based state-of-health. The method further includes determining a modeled battery voltage, and determining a characteristic of the modeled battery voltage using an adaptation model.

Abstract: A method for parameterizing an electrochemical battery model of a specific battery of a device, includes providing a current operating feature point of the specific battery and operating feature points of further batteries of a plurality of further devices for various evaluation periods. The operating feature points of the further batteries characterize an operation of a respective further battery within one or more of the evaluation periods based on several operating features. The several operating features are produced depending on characteristics of operating variables of the respective further battery. The method further includes selecting operating feature points of the further batteries that are similar to the current operating feature point of the specific battery, and providing model parameters of the electrochemical battery model that are associated with the current operating feature point and the selected operating feature points.

Abstract: A method for determining an internal-resistance based state-of-health of a battery in a device includes determining the internal-resistance based state-of-health of the battery using a hybrid state-of-health model including a physical ageing model and a correction model by (i) determining, based on an electrochemical battery model, a physical state-of-health according to one or more operating parameters of the battery using the physical ageing model, (ii) mapping operating features derived from the one or more operating parameters onto a correction parameter using the correction model that includes a data-based configuration, and (iii) applying the correction parameter to the physical state of health to determine the internal-resistance based state-of-health. The method further includes determining a modeled battery voltage, and determining a characteristic of the modeled battery voltage using an adaptation model.

Abstract: A method for parameterizing an electrochemical battery model of a specific battery of a device, includes providing a current operating feature point of the specific battery and operating feature points of further batteries of a plurality of further devices for various evaluation periods. The operating feature points of the further batteries characterize an operation of a respective further battery within one or more of the evaluation periods based on several operating features. The several operating features are produced depending on characteristics of operating variables of the respective further battery. The method further includes selecting operating feature points of the further batteries that are similar to the current operating feature point of the specific battery, and providing model parameters of the electrochemical battery model that are associated with the current operating feature point and the selected operating feature points.