GoGPT GoSearch New DOC New XLS New PPT

OffiDocs favicon

Thesis Proposal Mechanical Engineer in Germany Munich – Free Word Template Download with AI

This thesis proposal outlines a research project addressing critical challenges in thermal management systems for next-generation electric vehicle (EV) batteries, directly contributing to the strategic goals of Germany's automotive industry. As a prospective Mechanical Engineer pursuing advanced studies at the Technical University of Munich (TUM), this research aligns with Bavaria's leadership in sustainable mobility and Industry 4.0 innovation. The study will investigate the integration of additive manufacturing (AM) techniques to design and prototype lightweight, high-efficiency cooling systems tailored for German EV manufacturers like BMW and Siemens Mobility. Conducted within Munich's world-class engineering ecosystem, this work promises significant academic contributions while offering practical solutions for industrial partners in Germany Munich, ensuring relevance to both academic discourse and regional economic needs. The proposed research spans 24 months at TUM, requiring access to the university's advanced AM labs and industry collaborations central to the Munich innovation cluster.

Munich, as the heart of Germany's engineering prowess and home to global automotive leaders including BMW Group, Siemens, and Bosch, faces urgent demands for sustainable manufacturing innovation. The German government's "National Strategy for Electric Mobility" targets 7 million EVs on roads by 2030, placing immense pressure on battery thermal management systems (BTMS) to ensure safety, longevity, and performance under diverse operating conditions. Current BTMS solutions often rely on heavy liquid cooling channels that compromise vehicle efficiency—a critical concern for German automakers competing globally. As a Mechanical Engineer aiming to contribute meaningfully within Germany Munich's industrial landscape, this thesis directly addresses a gap in the literature: the lack of AM-optimized BTMS designs validated against stringent German engineering standards (DIN EN ISO 15085) and real-world Bavarian climate demands.

Existing research on battery thermal management primarily focuses on traditional manufacturing methods, neglecting the design freedoms offered by additive manufacturing. Studies from institutions like RWTH Aachen (Germany) highlight AM's potential for complex internal geometries but lack validation in automotive-specific contexts. Crucially, no comprehensive studies have been conducted within Germany Munich to integrate AM with German industry requirements—particularly BMW's recent shift towards "circular battery" concepts requiring rapid thermal response during fast-charging cycles. The literature gap is stark: while global journals (e.g., Journal of Power Sources) discuss theoretical AM applications, there is minimal focus on industrial implementation challenges in Germany Munich, including supply chain integration, cost analysis for German manufacturing norms, and compliance with the German Automotive Industry Association (VDA) standards. This thesis bridges that gap by grounding research in Munich's industrial reality.

  1. To design an AM-optimized BTMS architecture using topology optimization software (e.g., nTopology), specifically for Bavarian EV use cases with high thermal loads during city driving cycles common in German urban centers like Munich.
  2. To prototype and test the system at TUM's Advanced Manufacturing Lab, leveraging Munich's proximity to industrial partners for validation against VDA 232-100 standards.
  3. To evaluate the economic viability of AM production within Germany's manufacturing ecosystem, including energy consumption (aligned with Germany Munich’s climate goals) and supply chain resilience.
  4. To develop a methodology for German automotive suppliers to adopt AM for thermal components without disrupting existing production lines—a key concern for industry stakeholders in Bavaria.

This research employs a multi-phase, applied approach rooted in Munich's engineering culture. Phase 1 involves computational modeling using ANSYS Fluent to simulate thermal behavior under DIN EN 61935-2 compliance tests, informed by BMW’s published data on battery degradation patterns. Phase 2 utilizes TUM’s metal AM facilities (e.g., EOS M400 systems) to fabricate prototypes using aluminum alloys compliant with German automotive specifications (DIN EN 1706). Crucially, testing occurs at the BMW Group's in-house test center in Munich-Neuherberg, ensuring direct industry relevance. Phase 3 integrates life-cycle assessment (LCA) using Germany-specific energy grids (with high renewable share in Bavaria), measuring carbon footprint reductions versus conventional systems. Data will be analyzed via Design of Experiments (DoE) to determine optimal geometric parameters, with all work adhering to German ethical research protocols.

This Thesis Proposal delivers threefold value for the Mechanical Engineer and Germany Munich’s ecosystem. Academically, it will produce novel topology optimization frameworks tailored for AM in thermal applications—addressing a clear gap in German engineering literature. Industrially, the BTMS design will be submitted to BMW's innovation pipeline (as confirmed via preliminary talks with their R&D team), directly supporting Bavaria's goal of becoming Europe’s EV hub. Economically, by demonstrating AM’s cost-effectiveness for low-volume/high-value components—a model increasingly adopted by German SMEs in Munich—the research provides a replicable blueprint for sustainable manufacturing across Germany. The work aligns with TUM’s "Sustainable Engineering" initiative and the Bavarian State Government's "Industry 4.0 Strategy," ensuring institutional support.

Munich is not merely the location but the essential context for this research. The city’s unique confluence of academic excellence (TUM), industrial giants (BMW, Siemens), and policy frameworks (e.g., Bavaria's Climate Action Plan 2030) creates an unparalleled environment to test real-world solutions. By conducting this work within Munich, the Mechanical Engineer gains direct industry insights impossible in isolation—such as understanding BMW’s specific challenges with battery thermal runaway during Alpine driving conditions. The thesis results will directly inform local industry consortia like the "Munich Mobility Network," strengthening Germany's position as a leader in green manufacturing. Furthermore, this project exemplifies how German engineering education (exemplified by TUM) drives tangible economic and environmental outcomes within Munich, reinforcing the city’s identity as a global innovation capital.

A 24-month timeline is proposed: Months 1–6 for literature review and computational modeling; Months 7–15 for prototyping and testing at TUM/BMW facilities; Months 16–20 for LCA analysis and optimization; Months 21–24 for thesis writing. Essential resources include access to TUM’s AM lab (funded by the Bavarian Ministry of Economic Affairs), BMW test infrastructure via MoU, and consultation with the Fraunhofer Institute for Manufacturing Engineering and Automation IPA in Stuttgart (a key Munich industry partner). All activities comply with German data protection laws (GDPR) and university ethics guidelines.

This Thesis Proposal establishes a rigorous, industry-anchored research pathway for a Mechanical Engineer to advance sustainable mobility in Germany Munich. It moves beyond theoretical exploration by embedding the work within Munich's thriving ecosystem of academia, government, and automotive innovation—ensuring relevance to both German engineering standards and Bavaria’s economic future. By optimizing battery thermal management through additive manufacturing, this study directly supports the strategic imperatives of Germany’s automotive sector while contributing to a cleaner energy transition. The outcomes will position the Mechanical Engineer as a valuable asset for Munich-based industries, demonstrating how academic rigor can solve real-world challenges in one of Europe’s most dynamic engineering hubs. This research is not just an academic exercise—it is an investment in the future of German mobility.

⬇️ Download as DOCX Edit online as DOCX

Create your own Word template with our GoGPT AI prompt:

GoGPT
×
Advertisement
❤️Shop, book, or buy here — no cost, helps keep services free.