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Deutsches Zentrum für Luft- und Raumfahrt (DLR)

Student Automotive Engineering, Mathematics, Computational Science or similar (f/m/x)

Stuttgart

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Deutsches Zentrum für Luft- und Raumfahrt (DLR)

Auf einen Blick

Aufgaben: Forschung und Entwicklung neuer Fahrzeugkonzepte und Technologien, insbesondere im Bereich der Crashstrukturoptimierung.
Arbeitgeber: Das Institut für Fahrzeugkonzepte, Teil des Next Generation Car Projekts.
Mitarbeitervorteile: Möglichkeit, an zukunftsweisenden Fahrzeugtechnologien mitzuarbeiten.
Warum dieser Job: Arbeite an innovativen Lösungen in einem dynamischen Team und trage zur Entwicklung nachhaltiger Fahrzeugtechnologien bei.
Gewünschte Qualifikationen: Studium im Bereich Automobiltechnik, Mathematik, Informatik oder ähnliches; Erfahrung mit Python und LS-Dyna bevorzugt.
Andere Informationen: Kenntnisse in nachhaltigem Design und Lebenszyklusanalyse sind von Vorteil.

The Institute of Vehicle Concepts researches, develops and evaluates new vehicle concepts and technologies in light of future demands on the transportation system.

The Urban Modular Vehicle is being developed at DLR as part of the Next Generation Car project. A key challenge in modern vehicle development is creating a fuel-efficient and safe vehicle that meets increasingly stringent requirements. Structural optimization plays a crucial role in this process. These optimization methods enable development engineers to design vehicle structures that are both optimal and lightweight. In the context of multi-material design, body structure concepts for alternatively powered vehicles are being developed using a wide range of materials. Ensuring crash safety is a primary goal in today’s vehicle development. However, the current design process for crash-loaded structures is highly time-consuming due to the complexity involved. Given this, new strategies have been developed at the Institute of Vehicle Concepts to derive crash safety under simplified boundary conditions early in the development phase. The objective of this thesis is to develop a process chain to support these new strategies, focusing on crash structures such as battery boxes and similar components. Finally, the crash structure has to be verified using a complete vehicle.

Content of your work:

Conduct research on existing crash optimization process chains
Investigate recycled materials and their mechanical properties used in automotive design, particularly for crash structures
Develop a new process chain for optimizing crash structures using the Python
Perform optimization on the crash structures
Verify the optimised result model with FEA global car model
Document the entire process and results

Students from the field related to automotive engineering, mathematics, computational science or a comparable engineering Ability to work effectively as part of a team An interest in automotive engineering, machine learning, and sustainability design Previous experience with of a scripting language (e.g., Python) and familiarity with the software such as LS-Dyna, Primer Ability to work thoroughly, reliably, and independently Capability to derive and verify design methods for estimating the crash safety of vehicle structures

Gewünschte Qualifikationen

Knowledge and experience in sustainable design and Life Cycle Assessment (LCA) are advantageous An aptitude for quickly developing and applying practical solutions is an asset

Payment

without remuneration