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Das Ziel dieser Arbeit ist die subjektive Bewertung des Einflusses von Schäden an Achsbauteilen auf die Fahrzeugbeherrschbarkeit. Ein besonderer Fokus liegt dabei zum einen auf der Entwicklung von Methoden, um Gesamtfahrzeugmodelle mit Achsbauteilschäden in Echtzeit berechnen zu können. Zum anderen wird ein dynamischer Fahrsimulator verwendet, um die Gesamtfahrzeugmodelle subjektiv zu erleben und deren Funktionalität zu validieren. Für die echtzeitfähige Berechnung von Gesamtfahrzeugmodellen können kennfeldbasierte Zweispurmodelle sowie adaptierte Mehrkörpermodelle verwendet werden. Beide Ansätze werden zunächst an einem dynamischen Fahrsimulator appliziert und das grundlegende fahrdynamische Verhalten mit dem eines Realfahrzeuges verglichen. Anschließend werden als erste Schadenskonfiguration Bauteildeformationen untersucht. Dabei werden verschiedene Ansätze entwickelt, um Bauteildeformationen im Echtzeitmodell zu integrieren. Darauf aufbauend wird mit einer umfangreichen Validierungsstudie untersucht, inwiefern sich die subjektive Wahrnehmung der Schadenskritikalität von deformierten Bauteilen im Realfahrzeug mit der Wahrnehmung im dynamischen Fahrsimulator deckt. Dabei kann für ein breites Spektrum an Bauteildeformationen absolute Verhaltensvalidität nachgewiesen werden. Danach wird untersucht, wie Risse in Bauteilen auf echtzeitfähige Gesamtfahrzeugmodelle übertragen werden können. Ein physikalisches Ersatzmodell, welches die Nichtlinearitäten aus dem Material, der Geometrie und dem Kontakt der Rissufer erfasst, ermöglicht die echtzeitfähige Berechnung angerissener Bauteile. Ebenfalls untersucht wird der vollständige Bauteilabriss. Da infolge eines Lenkerabrisses die Radebene im Allgemeinen nicht mehr statisch definiert ist, sind kennfeldbasierte Modelle für derartige Anwendungsfälle ungeeignet. Durch eine Optimierung des Mehrkörpermodells sowie des zugehörigen numerischen Integrationsverfahrens kann jedoch eine echtzeitfähige Berechnung von spontanen Lenkerabrissen realisiert werden. Bisher ist die Bewertung des Einflusses von Achsbauteilschäden auf die Fahrzeugbeherrschbarkeit auf subjektive Fahreindrücke und somit (virtuelle) Fahrversuche angewiesen. Daher wird abschließend untersucht, ob Korrelationen zwischen objektiven fahrphysikalischen Größen und den Subjektivbewertungen gefunden werden können. Diese können teilweise identifiziert werden und ermöglichen somit eine Prädiktion des Subjektiveindrucks basierend auf Gesamtfahrzeugsimulationen in Kombination mit den Korrelationsmodellen.
For the assessment of axle damages, real vehicle tests have mostly been used so far, but they are dangerous and difficult to reproduce. Therefore, driving simulators are becoming increasingly important for the virtual rating of vehicles. Regardless of whether a real vehicle or a driving simulator is used, the prediction of the subjective perception of axle damages requires time-consuming driving tests. A powerful dynamic driving simulator is used to obtain subjective evaluations of various axle damages. Objective vehicle quantities are logged simultaneously. Subsequently, multilinear regression (MLR) models and artificial neural networks (ANN) are used to identify correlations and predict subjective evaluations based on objective data. Furthermore, real-time capable vehicle models in CarMaker and multibody dynamic (MBD) models in ADAMS/Car are used to virtually carry out driving manoeuvres and generate synthetic data. By combining the simulated vehicle data with an ANN, subjective driver evaluations can be predicted entirely virtual.
Up to now, cracked axle components are subjectively examined in real vehicle tests. In order to save development costs and time, these tests should be carried out in a dynamic driving simulator. A necessary prerequisite for this is a real-time capable full vehicle model that correctly represents all crack-related non-linear effects. This publication develops and validates a purely virtual process chain to describe cracked axle components in real time. Rear axle tie rods with different crack lengths at the same position are considered as an example. First, the stiffness behaviour is simulated at the component level and compared with real tests. The determined stiffness curves serve as a basis for the parameterisation of a physical substitute model. The tie rods are modelled as a non-linear FE component, as a linear flexible body and via the physical substitute model. These modelling approaches are integrated and validated in a FE semi-axle model as well as in the MBS full vehicle model. It is shown that the physical substitute model provides very good results. Finally, the full vehicle model with a cracked tie rod is converted into a real-time model based on elastokinematic maps and validated based on the MBS model.
In the development process of passenger cars, various scopes are defined by subjective criteria, which have to be determined in road tests. Therefore driving simulators are increasingly used in order to improve the efficiency of the development process. In the context of vehicle dynamics, map-based models are used predominantly, as they are unconditionally real-time capable. Multi-body simulation (MBS) models have a higher complexity and are therefore more accurate. However, adherence to the real-time condition depends on the available computing power and model complexity. A main advantage of this approach is that no conversion into map-based models is required. As a result, spontaneous changes can be made to the full vehicle model, which significantly enhances the tuning process at the driving simulator. First, a theoretical comparison of the two simulation approaches is made. This shows that real-time MBS models deliver significantly better results than map models, especially at higher frequencies. Subsequently, expert drivers assess both, the full vehicle models (map-based model and real-time MBS model) on a dynamic driving simulator in direct comparison with the real vehicle on the proving ground. The vehicle's controllability and steering behaviour through lane change manoeuvres and sinusoidal steering are assessed. It turns out that the subjective assessments between the driving simulator and the real vehicle agree very well. There are hardly any differences between the two simulation approaches for the driving manoeuvres examined. As a result, the process for integrating vehicle dynamics models on a driving simulator can be significantly downsized by the use of realtime multi-body models without experiencing any loss of evaluation quality. At the same time, this opens up potential for assessing comfort issues on the driving simulator.
Steering feedback provides an essential contribution to the validity of driving simulators. Previous works have shown significant effects on steering feedback in dynamic driving simulators through steering and vehicle body excitations up to 100 Hz. Based on these findings, this work extends the discussion by addressing its implications for lateral driving performance. It presents the results from a meta-analysis of the data from three subject studies comparing participants’ lateral driving performance between a reference vehicle and different variants of its virtual representation in a dynamic driving simulator. The effects of different modifications of steering feedback through steering wheel and vehicle body excitations covering the frequency ranges of noise, vibration, and harshness are investigated. The results show a clear beneficial effect of rotational steering wheel vibrations up to 30 Hz whereas non-rotational excitations in higher frequency ranges yield less conclusive results. The influence of the participant selection and interactions between modifications is discussed. Recommendations for the use of high-fidelity driving simulators and the development of modern steering systems are developed.
Steering feedback plays a substantial role in the validity of driving simulators for the virtual development of modern vehicles. Established objective steering characteristics typically assess the feedback behavior in the frequency range of up to 30 Hz while factors such as steering wheel and vehicle body vibrations at higher frequencies are mainly approached as comfort issues. This work investigates the influence of steering wheel and vehicle body excitations in the frequency range between 30 and 100 Hz on the subjective evaluation of steering feedback in a dynamic driving simulator. A controlled subject study with 42 participants was performed to compare a reference vehicle with an electrical power steering system to four variants of its virtual representation on a dynamic driving simulator. The effects of road-induced excitations were investigated by comparing a semi-empirical and a physics-based tire model, while the influence of non-road-induced excitations was investigated by implementing engine and wheel orders. The simulator variants were evaluated in comparison to the reference vehicle during closed-loop driving on a country road in a single-blind within-subjects design. The subjective evaluation focused on the perception of road feedback compared to the reference vehicle. The statistical analysis of subjective results shows that there is a strong effect of non-road-induced steering and vehicle body excitations, while the effect of road-induced excitations is considerably less pronounced.
The validity of the subjective evaluation of steering feedback in driving simulators is crucial for modern vehicle development. Although there are established objective steering characteristics for the assessment of both stationary and dynamic feedback behaviour, factors such as steering wheel vibrations and vehicle body motion, particularly in high-frequency ranges, present challenges in simulator fidelity. This work investigates the influence of steering wheel vibration and vehicle body motion frequency content on the subjective evaluation of steering feedback during closed-loop driving in a dynamic driving simulator. A controlled subject study with 30 participants consisting of a back-to-back comparison of a reference vehicle with an electrical power steering system on a country road and three variants of its virtual representation on a dynamic driving simulator was performed. Subjective evaluation focused on the representation of road feedback in comparison to the reference vehicle. The statistical analysis of subjective results show that there is a significant influence of the frequency content of both steering wheel torque and vehicle motion on the subjective evaluation of steering feedback in a dynamic driving simulator. The results suggest an influence of frequency content on the subjective evaluation quality of steering feedback characteristics that are not associated with the dynamic feedback behaviour in the context of established performance indicators.
A common goal of unpaired image-to-image translation is to preserve content consistency between source images and translated images while mimicking the style of the target domain. Due to biases between the datasets of both domains, many methods suffer from inconsistencies caused by the translation process. Most approaches introduced to mitigate these inconsistencies do not constrain the discriminator, leading to an even more ill-posed training setup. Moreover, none of these approaches is designed for larger crop sizes. In this work, we show that masking the inputs of a global discriminator for both domains with a content-based mask is sufficient to reduce content inconsistencies significantly. However, this strategy leads to artifacts that can be traced back to the masking process. To reduce these artifacts, we introduce a local discriminator that operates on pairs of small crops selected with a similarity sampling strategy. Furthermore, we apply this sampling strategy to sample global input crops from the source and target dataset. In addition, we propose feature-attentive denormalization to selectively incorporate content-based statistics into the generator stream. In our experiments, we show that our method achieves state-of-the-art performance in photorealistic sim-to-real translation and weather translation and also performs well in day-to-night translation. Additionally, we propose the cKVD metric, which builds on the sKVD metric and enables the examination of translation quality at the class or category level.
This paper focuses on developing a high-fidelity model of a frequency-modulated continuous wave (FMCW) radio detection and ranging (RADAR) sensor for automated train systems. The model uses ray tracing for virtual environmental perception in railway scenarios. It includes a multiple input multiple output (MIMO) antenna array and a complete signal processing toolchain of real RADAR sensors. The model outputs raw data, including range maps (RMs), range-Doppler maps (RDMs), and detection lists, including distance, relative radial velocity, and signal-to-noise ratio (SNR), radar-cross section (RCS), azimuth, and elevation angles. Results show a strong correlation with real measurements with a mean absolute percentage error (MAPE) below 4.8% for all the parameters defined at the detection level. To the author's knowledge, these error levels are among the lowest reported for RADAR sensor model validation. This finding allows for a cost-effective perception of virtual environments, facilitating simulation-based testing of automated railway systems.
Virtual radar for the railway of tomorrow – testing automated trains in a virtual environment
(2025)
This article presents a method for developing and validating a virtual radar sensor model designed to simulate automated train operations as part of the Digitale Schiene Deutschland (DSD) sector initiative. The model generates realistic sensor data in a digital environment and supports the evaluation and future validation of radar-based object detection systems used in automated trains. An initial validation has been carried out under controlled laboratory conditions so as to ensure the accuracy and reliability of the virtual sensor. A static test setup was used in which a radar corner reflector served as a reference target for comparing the real and simulated sensor data. The use of simulation instead of physical testing on tracks means that complex railway scenarios can be evaluated more flexibly, cost-effectively and without any safety risks. This accelerates the development process and reduces the reliance on time consuming field trials.