Abstract: A load prediction method for a component of a vehicle includes a model creation process. A load model is created using an identification method based on a training-drive data group, a training vehicle data group and a training load group. The training-drive data group contains training-drive data sets, each containing route data and/or accompanying drive data for a training drive of a training vehicle on a training route. The training vehicle data group comprises vehicle data from the training vehicle used on the training drive. The training load group includes training load data including a load of the component that corresponds to a training-drive data set. The load model approximates the occurring load on a predetermined training route or with predetermined accompanying drive data or according to predetermined vehicle data. In a model evaluation process, the load prediction is determined using the load model.

Abstract: A method for determining a sensor configuration in a vehicle which includes a plurality of sensors. The method comprises: (i) establishing a preliminary sensor configuration for the vehicle, which sensor configuration includes a first number of real sensors, each of which outputting a real sensor signal, (ii) determining whether at least one of the real sensors can be replaced by a virtual sensor, and (iii) changing the preliminary sensor configuration into a final sensor configuration which includes a second number of real sensors and at least one virtual sensor which has been determined to replace at least one of the real sensors, wherein the second number is smaller than the first number.

Abstract: The invention relates to a method (1) for determining supporting points of a test plan (9) for measuring pre-defined test variables of a test machine on the basis of previously measured operating values (3) of operating variables of at least one field machine during the normal use thereof. In an aggregation step (2), the detected operating values (3) are allocated to categories (4) with regard to at least one selected operating variable, according to a predefined classification rule. Default variables are selected in a default step (5) before or after the aggregation step (2). The default variables form at least one subset of the operating variables. The operating category frequency (7) for each category (4) is determined in a determination step (6) following the aggregation step (2). In a subsequent determination step (8), the supporting points of the test plan (9) are determined on the basis of the operating category frequency (7).

Abstract: The invention relates to a method (1) for determining supporting points of a test plan (9) for measuring pre-defined test variables of a test machine on the basis of previously measured operating values (3) of operating variables of at least one field machine during the normal use thereof. In an aggregation step (2), the detected operating values (3) are allocated to categories (4) with regard to at least one selected operating variable, according to a predefined classification rule. Default variables are selected in a default step (5) before or after the aggregation step (2). The default variables form at least one subset of the operating variables. The operating category frequency (7) for each category (4) is determined in a determination step (6) following the aggregation step (2). In a subsequent determination step (8), the supporting points of the test plan (9) are determined on the basis of the operating category frequency (7).

Abstract: The invention relates to a method (1) for designing and dimensioning a new part (2) of a motor vehicle (3). All of the motor vehicles (5) of a motor vehicle fleet (6) have a reference part (4) with an identical structure, and the reference parts (4) and the new part (2) are of the same component type. Load spectra and damage levels of the reference parts of all the motor vehicles (5) of the motor vehicle fleet (6) are continuously ascertained on the basis of sensor and vehicle state information available in each motor vehicle (5) using specified algorithms. The load spectra and damage levels are stored in a central database (9). A reference stress on a component of the component type is ascertained regularly on the basis of the load spectra and damage levels provided in the central database (9) at a specific point in time for the reference parts (4) of all of the motor vehicles (5) of the vehicle fleet (6). The new part (2) is designed and dimensioned while taking into consideration the reference stress.