Abstract: A computer-implemented method for generating a hybrid artificial intelligence algorithm. The method includes: providing a system state vector that includes at least two system states of the physical system, wherein at least one of the at least two states can be calculated by at least one analytical and/or statistical equation, and wherein at least one other of the at least two states can be calculated by at least one artificial intelligence algorithm to be ascertained; carrying out at least one automatic learning method for ascertaining a plurality of artificial intelligence algorithms using which at least the other of the at least two states can be calculated in each case; and selecting at least one artificial intelligence algorithm from the plurality of artificial intelligence algorithms as a function of at least one selection criterion to generate the hybrid artificial intelligence algorithm coupled with the at least one equation.

Abstract: A method for operating a vehicle using a vehicle dynamics model. The method includes: providing input values of one or at least one of a plurality of input variables of the vehicle dynamics model; determining output values of one or at least one of a plurality of state variables of the vehicle dynamics model based on the input values, wherein the vehicle dynamics model includes a physical model component and a data-based model component, and providing the output values for use in the operation of the vehicle.

Abstract: A method for simulating a technical system. Time series are obtained with the aid of a simulation model of the system, variable values being assigned to at least one epistemic parameter of the simulation model, at least one measurement series is obtained by corresponding measurements on the system, for each value of the epistemic parameter, a real-value error measure of the time series obtained for this value with respect to the measurement series and a distribution function of the error measure are calculated, and for the simulation, that value is used, for which the distribution function has the smallest distance to a Heaviside function.

Abstract: A method for assessing validation points for a simulation model. The method includes: obtaining a reference measured value for at least two measuring points; determining a model form error for each of the at least two measuring points, based on a deviation between the reference measured value of the particular measuring point and a probability distribution for a simulation value at the measuring point, the probability distribution being obtained from the simulation model; forming a metamodel of the model form errors, based on the determined model form errors for the measuring points; determining an uncertainty of the metamodel for at least one further data point that is not contained in the measuring points; and defining the at least one data point as sufficient for a virtual validation if the uncertainty of the metamodel at the at least one further data point is less than a predefined limiting value.

Abstract: A method for checking a vehicle dynamics model of a vehicle, with which a value of an output variable is ascertainable from a value of a variable input variable, for multiple values of the input variable respectively associated model-based values of the output variable being ascertained with the aid of vehicle dynamics model, for the multiple values of the input variable at the vehicle respectively associated vehicle-based values of the output variable being ascertained, difference values being ascertained from mutually corresponding model-based values and vehicle-based values, respectively, an updated dataset of the ascertained difference values being compared with a comparison dataset with the aid of a comparison method and a concordance measure being ascertained in the process, and the vehicle dynamics model being determined to be valid if the concordance measure meets a predefined concordance criterion.

Abstract: A method for the automated assessment, especially validation, of a simulation model which is used to simulate measured values of a quantity that is defined by one fixed parameter and one varying parameter. Multiple simulation values are determined for the quantity with the aid of the simulation model. Multiple associated reference values are determined for the quantity. For each of multiple values of the varying parameter, in each case a model-form error is determined as deviation between the simulation value with respect to this value of the varying parameter and the reference value with respect to this value of the varying parameter. On the basis of the model-form errors for the multiple values of the varying parameter, a function of the model-form error is determined depending on the varying parameter and used for the assessment, especially validation, of the simulation model.

Abstract: A method for assessing validation points for a simulation model. The method includes: obtaining a reference measured value for at least two measuring points; determining a model form error for each of the at least two measuring points, based on a deviation between the reference measured value of the particular measuring point and a probability distribution for a simulation value at the measuring point, the probability distribution being obtained from the simulation model; forming a metamodel of the model form errors, based on the determined model form errors for the measuring points; determining an uncertainty of the metamodel for at least one further data point that is not contained in the measuring points; and defining the at least one data point as sufficient for a virtual validation if the uncertainty of the metamodel at the at least one further data point is less than a predefined limiting value.

Abstract: A method for simulating a technical system. Time series are obtained with the aid of a simulation model of the system, variable values being assigned to at least one epistemic parameter of the simulation model, at least one measurement series is obtained by corresponding measurements on the system, for each value of the epistemic parameter, a real-value error measure of the time series obtained for this value with respect to the measurement series and a distribution function of the error measure are calculated, and for the simulation, that value is used, for which the distribution function has the smallest distance to a Heaviside function.

Abstract: A method for checking a vehicle dynamics model of a vehicle, with which a value of an output variable is ascertainable from a value of a variable input variable, for multiple values of the input variable respectively associated model-based values of the output variable being ascertained with the aid of vehicle dynamics model, for the multiple values of the input variable at the vehicle respectively associated vehicle-based values of the output variable being ascertained, difference values being ascertained from mutually corresponding model-based values and vehicle-based values, respectively, an updated dataset of the ascertained difference values being compared with a comparison dataset with the aid of a comparison method and a concordance measure being ascertained in the process, and the vehicle dynamics model being determined to be valid if the concordance measure meets a predefined concordance criterion.

Abstract: A method for validating a simulation of a technical system. The method including the following features: for combinations of measurement series obtained on the system and results of the simulation corresponding to the measurement series, a specified validation metric is computed in each case; and the simulation is validated on the basis of the computed validation metrics.

Abstract: An electric motor, includes a stator, which is composed at least of stamp-packed tooth segments, the tooth segments being able to be slid together radially in the manufacture and being able to be held together by retaining elements slid on axially.

Abstract: An electric motor, includes a stator, which is composed at least of stamp-packed tooth segments, the tooth segments being able to be slid together radially in the manufacture and being able to be held together by retaining elements slid on axially.