Embarking on a thesis project at Scania offers a unique opportunity to bridge academic knowledge with practical industry applications. This project not only provides a platform to engage into cutting-edge research but also serves as a step for future professional endeavours. Many professionals in the field have launched their careers through similar thesis projects, establishing valuable connections and gaining hands-on experience that is highly regarded in the industry. 

Background:

Stringent emission regulations, such as Euro 7, are driving the automotive industry to enhance the precision of their fuel management systems. Accurate fuel injection is crucial to meet these new standards, requiring advanced models of the injection system.

While traditional high-fidelity models, such as those derived from computer fluid dynamics (CFD), are accurate, they are also computationally expensive and impractical for real-time control of fuel systems. Reduced order models (ROMs) present a promising alternative by simplifying complex systems while retaining essential dynamics. This thesis project aims to leverage data-driven techniques to develop ROMs for fluid mechanical systems in fuel injection.

Objectives:

•    Conduct 1D fluid system simulations of sections of the fuel injection system subject to different boundary conditions. 

•    Using data driven-driven techniques such as sparse identification of nonlinear dynamics (SINDy), derive ROMs for the corresponding sections of the fuel injection system.

•    Compare the performance of the developed ROMs against the 1D models to ensure accuracy and computational efficiency.

Practicalities:

The prospective candidate should have a strong foundation in fluid mechanics and at least a basic understanding of numerical methods for solving partial differential equations (PDEs), such as finite difference, finite element, or finite volume methods.

Knowledge of data driven methods for system identification such as sparse regression or SINDY is an advantage. 

The project will primarily use Python and/or MATLAB for simulations and model development, so familiarity with these tools is expected.

 
Education/program/focus:

The prospective candidate should be pursuing a Master’s degree in Mechanical Engineering, Engineering Physics, Applied Mathematics, Aerospace Engineering, or a related field. 

Number of students: 1
Start date for the thesis work: January 2025
Estimated time required: 20 weeks (HT22), full time 40 hours per week
Credits: 30hp

Contact persons and supervisors:

José G. Aguilar, System Controls Engineer, +46737157404, jose.guillermo.aguilar.perez@scania.com

Niclas Wiker, System Integration and Performance Manager, +46855352745, niclas.wiker@scania.com

Application:
Your application should include a CV, a cover letter and transcripts of records.

A background check might be conducted for this position.