Optimized Merging of the Virtual World and Reality on the Vehicle-in-the-Loop Test Bench

To overcome the upcoming complexity of testing future vehicles with versatile technologies and changing legal requirements, this research focuses on a development method and validation on full vehicle level based on combining simulation and test bench operation. The goal is to enhance realism and achieve a reproducible and controllable environment for full vehicle development and testing. While conventional test environments face challenges such as limited reproducibility or constraints of stationary test execution, integrating simulation with test bench operation presents significant advantages.
This research utilized a highly dynamic and steerable Vehicle-in-the-Loop test bench coupled with CarMaker from IPG Automotive to conduct holistic tests where the full vehicle operates within a simulated environment. Based on the drive shaft torques , the wheel-specific rotational speeds resulting from the defined scenarios are adjusted in a closed-loop approach. A driving robot, sensor stimulators or interconnections to control units can extend this testing environment. The vehicle can thus be the tested in a variety of situations with respect to safety, comfort and efficiency.
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Furthermore, this research extends the discussion to incorporate virtual reality on the Vehicle-in-the-Loop test bench. Leveraging virtual reality technology, a novel approach is proposed where a driver on the test bench experiences a virtual environment through wearable virtual reality headsets. This integration enhances test environment realism, providing a more immersive and accurate representation of real-world driving conditions.
On this basis, it is demonstrated how the Vehicle-in-the-Loop test bench, augmented with virtual reality capabilities, facilitates development and validation of different vehicle subsystems. By enabling engineers to assess various driving scenarios in a controlled yet immersive environment, this approach holds promise for advancing the accuracy and reliability of testing, particularly in the field of autonomous driving and electric vehicles.