The Technische Universität Dresden (TUD) is one of the largest “Technische Universitäten” in Germany and one of the leading and most dynamic universities in Germany. As a full-curriculum university with 17 faculties in five schools it offers a broad variety of 124 disciplines and covers a wide research spectrum. Its focuses Health Sciences, Biomedicine & Bioengineering, Information Technology & Microelectronics, Smart Materials & Structures, Energy, Mobility & Environment as well as Culture & Societal Change are considered exemplary in Germany and throughout Europe.
Since 2012, TUD has been one of the “Universities of Excellence”. In the second phase of the Excellence Initiative, TUD was successful with four applications: The Institutional Strategy, the Clusters of Excellence Center for Advancing Electronics Dresden (cfaed), Center for Regenerative Therapies Dresden (CRTD) and the Graduate School Dresden International Graduate School for Biomedicine and Bioengineering (DIGS-BB. In January 2019, three new Clusters of Excellence have started their work: PoL – Physics of Life, ct.qmat – Complexity and Topology in Quantum Materials, and CeTI – Centre for Tactile Internet.
As of 1 November 2019, TU Dresden will receive permanent funding within the framework of the Excellence Strategy of the Federal and State Governments .
About 32.000 students are enrolled at TUD – more than three times as many as in 1990 (11.220 students). Internationally, the TUD has earned a good reputation, about one eighths of its students come from abroad. Today, about 8.300 employees from 70 countries are working at the Technische Universität Dresden.
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Dipl.-Ing. Clemens Deubel, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY; Mr. Peter Hoffmann, Technische Universität Dresden, GERMANY; Mr. Chao Liu, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY; Dipl.-Ing. Jan Kubenz, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY; Prof. Dr.-Ing. Günther Prokop, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY
The knowledge of the suspension kinematic points are of main interest for many engineers in order to create complex multi body system (MBS) models of road vehicles for benchmarking or in-depth investigation on the suspension. In many cases, those either are known from OEM construction data or are commonly determined with the help of contact giving multi-axis coordinate measurement machines. Another literature-discussed approach is the indirect determination under usage of Kinematics and Compliance (KnC) measurements.
The method presented hereinafter has the advantage of an easy integration in the standard KnC measurement process, reducing both time and costs. As a result, the hard point information obtained will transfer the real suspension to the simulation in the same conditions as on the test rig. This will be advantageous for pursuing investigations in case of special consideration of the position of the vehicle relative to the (virtual) test environment.
At the Institute of Automobile Engineering of the TU Dresden, a systematic method for the identification of kinematic point positions (x-, y- and z-values) using a hybrid photogrammetric and optimization approach has been developed. In a first step, the kinematic point positions are approximately determined using a high resulting optical measurement system. The suspension is positioned at the respective wheel deflection, typically because of the vehicles empty weight with or without an additional drivers weight. In a second step, the approximately identified hard points are used as initial values of the subsequent iteration process as to find possible spatial positions of kinematic points in a small range. Therefore, the KnC simulation results from an MBS model in ADAMS/Car are compared to the KnC measurements from the Suspension Motion Simulator (SMS) test rig iteratively. The objective is to minimize the errors between the KnC characteristic curves and the simulation.
The iteration is realized with a simulation exchange between ADAMS/Car and MATLAB. For the purpose of validating the developed identification method, the kinematic points have been measured by a coordinate measurement machine directly as well. The differences between identified positions of kinematic points and those gathered from the measurement machine show to be sufficient for the desired modelling of the suspension.
FISITA Web Congress 2020
Vehicle Dynamics and Controls (VDC)
Paper + Video
Mr. Fan Chang, AUDI AG / Technische Universität Dresden, GERMANY
Dipl.-Ing. Matthias Bayer, Chair of Automotive Engineering / Technische Universität Dresden, GERMANY
Dr.-Ing. Sebastiaan van Putten, Virtual Chassis, Concept Attributes and Functions / AUDI AG, GERMANY
Prof. Dr.-Ing. Günther Prokop, Dean of Faculty of Transport and Traffic Sciences / Technische Universität Dresden, GERMANY
FISITA World Congress 2021
VDC - Vehicle Dynamics and Controls
Dipl.-Ing. Steven Ernst, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY; Dipl.-Ing. Felix Schmid, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY; Dr.-Ing. Kay Büttner, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY; Prof. Dr.-Ing. Günther Prokop, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY
With the continuous digitalization of the vehicle development process, virtual design methods play an increasingly important role. Representative load profiles, which can be determined for example with the aid of multi-body system simulation, are required for the reliable design and validation of complex elastomeric bearings such as engine mounts for conventional and electrified drive trains. Due to the complex material properties and complex designs of today's elastomer and hydro mounts, the virtual representation of these components is a challenging task.
In already published researches (46th Conference of the "DVM Arbeitsgruppe Betriebsfestigkeit") it could be shown that the current standard characterization of elastomeric bearings using static and dynamic stiffness as well as loss angle is only partly appropriate to build up and parameterize exact models for the virtual load data determination. On the basis of multi-axial load tests of selected engine mounts, which are done at the highly dynamic component test rig of the Chair of Automotive Engineering of the TU Dresden, physical effects with relevance for the durability could be determined. These are multi-axial static, dynamic and transient changes in stiffness and damping properties. With the knowledge of these effects, a complex model was developed which is designed for the representation of high dynamic loads, hydraulic damping and superposition effects of multi-axial excitations. The model is to be used primarily to calculate operating load signals using multi-body system simulation.
Within the context of the research described here, a complex multistep parameter identification procedure based on particle swarm optimization is presented. With this method it is possible to use complex stochastic signals to identify the model parameters. The first step is to determine the static stiffness of the bearing model in the considered main direction. The uniaxial dynamic parameters are identified afterwards. In the following, the dependence of the uniaxial dynamic parameters on the deformation amplitude is evaluated. Finally, the parameters of the model elements are identified which are dependent on the deformation of the secondary directions (multi-axial model components). The described procedure allows a modularization of the complex bearing model, whereby the model complexity can be adapted according to the application.
Multi-axial test rig measurements showed a significant improvement in the image quality of measured load signals compared to standard models for the newly developed model and the parameter identification process. The simulation error is used as evaluation criterion and the signal damage is considered by means of a standard fatigue strength evaluation. Different types of elastomeric and hydromounts are investigated for validation. Furthermore, the simulation quality of the modelling process outside the fitting range is evaluated. With the help of these investigations it can be deduced that the methods work robustly and will be suitable for practical use after a few adjustments. The investigations contribute to an improved and validated digital representation of elastomeric bearings with a focus on load data determination.
FISITA Web Congress 2020
Digital Transformation (DGT)
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