A computer-implemented method for testing an real and/or virtual automotive system through a test by a test environment interacting with the real and/or virtual part, which includes a test series with different test cases of the test for different execution conditions that are specified in test configurations. Each combination of test case and test configuration is assigned a test status value from a group of predefined test status values in accordance with an evaluation of the function of the system in the corresponding test. For further planning, execution, and/or evaluation of the test series at least once a relative test coverage of at least one of the status values is determined in the resulting test case configuration matrix and/or a relative potential for improvement of the test coverage of at least one of the status values with regard to a test case and/or with regard to a configuration is determined.

A method is provided for connecting an input/output interface of a tester equipped for control unit development to a model of a technical system present in the tester using an already-existing basic test model of a control unit. The input/output interface is designed for connecting a hardware implementation of the control unit or for connecting a technical system to be controlled, and the model to be connected to the input/output interface is a test model of the technical system to be controlled or a test model of the control unit. The already-existing basic test model of the control unit is accessed, and at least one communication requirement is extracted from the basic test model of the control unit.

A simulator and a method for testing a control device function of a control device of a vehicle. The vehicle includes various environmental sensors, such as radar, a camera, and a radio receiver, which serve as inputs to the control device function of the control device. A corresponding simulation utilizing a vehicle model, sensor models, and an environmental model is executed in a distributed fashion via a plurality of computing units and a memory of a simulator. The simulation utilizing the vehicle model, the sensor models, and the environmental model provides inputs to the control device function. Moreover, the simulation utilizing these models is started synchronously on the computing units, wherein data exchange occurs amongst the memory and the multiple computing units.

A method to evaluate a quality of road feedback to a driver in a steer-by-wire system includes setting a test bench by grounding a steering system steering wheel using a physical 6.sup.th order impedance constraint; preloading the steering system with data defining a steering wheel angle and a vehicle speed; applying tie rod load signals to the steering system and recording signals representing each of a tie rod load, a steering wheel torque and a steering wheel acceleration. In parallel: applying first a fast Fourier transform algorithm to the recorded signals to calculate each of a gain, a phase and a coherence response from the tie rod load to the steering wheel torque; applying second a fast Fourier transform algorithm to the recorded signals to calculate a power spectral density of the steering wheel torque versus frequency; and applying frequency weighting functions to the gain and power spectral density functions.

A simulation device for simulating a peripheral circuit arrangement that can be connected to a control device, wherein the simulation device can be electrically connected to the control device, and the simulation device has a first control element for influencing a first simulation current that can be passed from a first load terminal of the control device to a first control element output of the first control element. The first control element contains a first multistage converter that includes a first converter output, which is electrically connected to a terminal on the converter side of a first inductive component at whose terminal on the control device side the first control element output is implemented. A direction of flow of the first simulation current is reversible, and the simulation device also includes a computing unit for execution of model code.

A decentralized peripheral having process input and process output modules which, in a process control mode of operation, interact with field devices connected to these modules, and having an interface module in which a process image is stored, wherein in the process control mode of operation the process input modules write process input values for processing via an automation device connected to the decentralized peripheral into the process image, and the automation device writes process output values for processing via the process output modules into the process image such that as real a behavior as possible of this decentralized peripheral can be simulated.

A device for testing an electronic control unit with a hardware-in-the-loop simulator to simulate at least one sensor signal and equipped with a two-wire cable via which the sensor signal is outputted, and with a switchover device which is connected to the hardware-in-the-loop simulator via the two-wire cable, so that the sensor signal is receivable from the switchover device. The two-wire cable in the switchover device is routed to a two-pole interface of the switchover device to which the electronic control unit can be connected in order to receive the sensor signal, and the switchover device has two voltage sources, each of which is assigned to a wire of the two-wire cable and can be connected to the respective wire via a controllable switch. In this way, it is possible to continue to supply the sensor with electrical energy via two switchable voltage sources during diagnostics, thus avoiding diagnostic errors.

A method for training a control system model includes introducing a simulated fault into a software simulation of a physical system and generating emulated sensor data based on the simulated fault, where the emulated sensor data emulates output from one or more sensors of the physical system. The method further includes obtaining output data from a test control system provided with the emulated sensor data, where the test control system emulates a control system of the physical system and tagging the output data with the simulated fault to create training data. The method further includes utilizing the training data to train the control system model, where the control system model is a machine learning model for use with the control system of the physical system during operation of the physical system.

A method for determining a physical connection topology of a test device with real-time capability and set up for control device development includes: determining logical communication links between a plurality of simulation models; and automatically determining the physical connection topology by specifying direct physical communication links between the plurality of data processing units based on the respective specified quantities of physical interfaces of the plurality of data processing units. Specifying the direct physical communication links includes determining, for each of the logical communication links, whether a direct physical communication link corresponding to the logical communication link forms part of the physical connection topology.

Systems, methods, and software to facilitate simulating machines used in industrial automation are disclosed herein. In at least one implementation, an API is utilized to establish at least a communication link between a simulation model created in a simulation application and an industrial controller system outside of the simulation model, wherein the simulation model comprises definitions for a virtual representation of at least a portion of a machine used in an industrial automation environment. Data is then exchanged between the industrial controller system and the simulation model over the communication link.