Abstract: To subject a test object during a test run on a test bench to real environmental and/or surrounding conditions, particularly thermal conditions, it is provided that at least one temperature is measured at a measurement point as a measured variable during the test run on the test bench. At least one test object component of the test object is subdivided in a number of segments. The thermal interaction of at least one segment with the environment of the vehicle is simulated during the test run by a thermal simulation model of the simulation model. The thermal simulation model calculates the segment heat flow that is supplied to or dissipated from the at least one segment. This segment heat flow is adjusted as a function of the measured temperature at the test bench on at least one segment by means of a number of heat flow actuators.

Abstract: In a process for testing the powertrain of vehicles that are at least in part electrically driven, the voltage supplied to the powertrain is controlled by a controller coupled with a simulation system for the energy storage system in a way that the voltage acts dynamically as for a real energy storage system. The controller is designed with a model based controller design method, with a load model of the powertrain being used in the model of the controlled system.

Abstract: A method for generating a model ensemble that estimates at least one output variable of a physical process as a function of at least one input variable, the model ensemble being formed from a sum of model outputs from a plurality of models that have been weighted with a weighting factor.

Abstract: In a test run, in order to easily provide a high-quality propulsion torque of a torque generator based on the partially low-quality measured variables available on the test bench, it is foreseen that an inner torque (Mi) of the torque generator (D) is measured and based on the measured inner torque (Mi), from an equation of motion, including the measured inner torque (Mi), a dynamic torque (Mdyn) and a shaft torque (Mw) measured on the output shaft of the torque generator (D), a correction torque ({circumflex over (M)}cor) is estimated, and from the estimated correction torque ({circumflex over (M)}cor) and the measured inner torque (Mi), the propulsion torque (Mv) according to the relation Mv={circumflex over (M)}cor+Mi is computed.

Abstract: For an easily implementable method for model predictive control of a DC/DC converter, and a corresponding controller, with which the optimization problem of the model predictive control can also be solved sufficiently quickly with large prediction horizons, the optimization problem is divided into two optimization problems by a model predictive output variable control and a model predictive choke current control being implemented in the control unit (10), wherein: the strands of the multiphase DC/DC converter (12) for the output variable control are combined into a single strand; a time-discrete state space model is produced therefrom; and the output variable control predicts the input voltage (uv,k+1) of the next sampling step (k+1) for this single strand on the basis of a first cost function (Jv) of the optimization problem of the output variable control, said input voltage being given to the choke current control as a setpoint and the choke current control determining therefrom the necessary switch positio

Abstract: A method for obtaining data from a nonlinear dynamic real system during a test run, for instance an internal combustion engine, a drivetrain, or parts thereof, a sequence of dynamic excitation signals is generated according to an initial design and a system output is measured. To enable the quick and precise generation of experimental designs for global measurement, modeling, and optimization of a nonlinear dynamic real system, a sequence of dynamic excitation signals was generated by generating a design with a sequence of excitation signals, obtaining output data by feeding said sequence into a model for the real system, determining a criterion for the information content of the complete design of experiment sequence, varying the sequence, obtaining new output data by feeding said modified sequence into the model, determining again said criterion, iterating until said criterion improves, and using the improved sequence of excitation signals for the real system.

Abstract: In order to reduce the excitation of vibrations and resonances in a test bed (1) for a real component (4) and a virtual component (5), one of the following method steps is provided: a) determining a first correction value (K1) from the measured variable (M), wherein the first correction value (K1) is added to the measured variable (M) and the sum is communicated as a corrected measured variable (M*) to the virtual component (5) for calculating the control variable (S), b) determining a second correction value (K2) from the calculated control variable (S), wherein the second correction value (K2) is added to the calculated control variable (S) and the sum is transferred as a corrected control variable (S*) to the actuator (3), c) determining a third correction value (K3) from the measured variable (M), wherein the third correction value (K3) is used to modify a parameter (P) of the equation of movement.

Abstract: To determine a model for an output quantity (y) of a technical system that is dependent in a nonlinear manner on a number of input quantities in the form of an input quantity vector (u), a target output quantity range (COR) is defined and a model-based experimental design is determined with which the model is parameterized in the target output quantity range (COR) through the selection of associated input quantity vectors (Ucand,COR).

Abstract: For the determination of a non-linear controller for a non-linear system it is proposed that a parameter set (KPID(k)) of the controller (1) is determined by means of an optimization using a multi-criteria evolutionary algorithm, in which algorithm a plurality of parameter sets (KPIS(k)), which each represent a possible solution of the optimization, are determined in each evolution step and at least two quality values (fi) are determined for each parameter set (KPID(k)) and the quality values (fi) are optimized by the multi-criteria evolutionary algorithm.

Abstract: In order to create a control observer for any battery type in a structured and at least partially automated manner, first, a nonlinear model of the battery, in form of a local model network including a number of local, linear, time-invariant, and dynamic models, which each have validity in specific ranges of the input variables, is determined from the measuring data of a previously ascertained, optimized experimental design via a data-based modeling method. For each local model (LMi) of the model network determined in this manner, a local observer is then determined. The control observer (13) for estimating the SoC then results from a linear combination of the local observers.

Abstract: In a process for testing the powertrain of vehicles that are at least in part electrically driven, the voltage supplied to the powertrain is controlled by a controller coupled with a simulation system for the energy storage system in a way that the voltage acts dynamically as for a real energy storage system. The controller is designed with a model based controller design method, with a load model of the powertrain being used in the model of the controlled system.

Abstract: A method for testing electrical energy storage systems for driving vehicles provides that the load current of the energy storage system traces by means of a control loop, if possible without delay, a reference current that varies over time according to predetermined test cycles. The control loop is created by means of a model-based controller design method in which a model of the impedance of the energy storage system is integrated in the model of the controlled system.

Abstract: In a machine-implemented method for obtaining data from a nonlinear dynamic real system during a test run, for instance an internal combustion engine, a drive-train or parts thereof, of a sequence of dynamic excitation signals for at least one measurement channel is generated according to a previously generated design of experiment for said test run and the system output of at least one output channel is measured.

Abstract: A method for creating a non-linear, stationary or dynamic overall model of a control variable of a combustion engine or partial systems thereof is based on simplified partial model functions that are used to determine in a weighted fashion at each desired operating point the total output quantities from the partial model function with an associated weighting function. The difference between the total output quantity and the real value is determined for all real operating points; and in areas of operating points with an absolute value of this difference that is above the preset value, a further model function with a further associated weighting function is used for which the absolute value of the difference stays below the preset value.

Abstract: A method for creating a non-linear, stationary or dynamic overall model of a control variable of a combustion engine or partial systems thereof, is based on simplified partial model functions that are used to determine in a weighted fashion at each desired operating point the total output quantities from the partial model function with an associated weighting function. The difference between the total output quantity and the real value is determined for all real operating points; and in areas of operating points with an absolute value of this difference that is above the preset value, a further model function with a further associated weighting function is used for which the absolute value of the difference stays below the preset value. To use such a method in order to arrive faster, i.e.