Data-Driven Engineering: Framework for Optimizing Truck Fleet and Logistics Depot Electrification [ SA / IDP ]

Institut

Lehrstuhl für Fahrzeugtechnik

Typ

Semesterarbeit / Masterarbeit /

Inhalt

theoretisch /  

Beschreibung

Are you passionate about sustainable logistics and eager to contribute to the electrification of heavy-duty truck fleets? Then this thesis could be an exciting opportunity for you.

Telemetry data, capturing operational details such as routes, depot dwell times, and fleet behavior, provides a foundation for data-driven decision-making. This thesis aims to optimize an existing database-backend-frontend toolchain that processes telemetry data from internal combustion engine (ICE) truck fleets stored in a PostgreSQL database. The tool will support mobility data analysis, frontend visualization, and electrification simulations using longitudinal dynamics models to recommend optimal depot charging infrastructure. The output will be step-by-step transformation pathways to guide freight forwarding companies in electrifying their fleets and upgrading depot energy systems.

In this thesis, you will enhance the Python-based toolchain, improve its performance and usability, and develop intuitive visualizations. The work will conclude with validation using real telemetry data and actionable recommendations for electrification strategies.

Task Description: Your thesis is structured into the following work packages:

1. Literature Review

   • Research heavy-duty truck fleet electrification and depot energy infrastructure adaptations.

2. Optimization of Existing Toolchain

   • Enhance the Python-based backend (PostgreSQL) and frontend toolchain for processing telemetry data and simulating electrification pathways.

3. Customization for Freight Forwarding

   • Adapt the framework to freight forwarding needs and develop intuitive visualizations (e.g., dashboards, timelines) for transformation pathways.

4. Validation and Recommendations

   • Test the framework with real telemetry datasets and derive actionable electrification recommendations.

Requirements

• Interest in sustainable logistics and electrification.
• Proficiency in Python and familiarity with PostgreSQL.
• Independent and structured working style.

Learning Outcomes

• Contribute to sustainable logistics with real-world impact.
• Gain experience in data engineering, software optimization, and visualization.
• In case of good work, option to write a master thesis afterward.

Recommended reading: Borlaug, B., Muratori, M., Gilleran, M. et al. Heavy-duty truck electrification and the impacts of depot charging on electricity distribution systems. Nat Energy 6, 673–682 (2021). https://doi.org/10.1038/s41560-021-00855-0

Interested? Please send your application, including CV and transcript of records to:

Anna Paper, M.Sc.
anna.papertum.de
+49 89 289 15769

Verwendete Technologien

Python, SQL

Tags

FTM Studienarbeit, FTM SM, FTM Paper, FTM Informatik

Möglicher Beginn

sofort

Kontakt

Anna Paper, M.Sc.
Raum: MW 3503
Tel.: 089 289 15769
anna.papertum.de

Ausschreibung