Thesis work: 30 hp -Temperature Effects on Magnetic Properties of Electrical Steel

Background:
The magnetic performance of electrical steels is a key factor in the efficiency of electric machines and transformers. Since these machines operate under varying thermal conditions, a thorough understanding of how temperature affects magnetic properties is crucial. Despite its importance, reliable experimental data and validated models are still limited, particularly for application-oriented conditions.

Objective:
This thesis aims to experimentally characterize and model the magnetic properties of electrical steels as a function of temperature. The work combines laboratory measurements with predictive modeling to bridge the gap between material characterization and machine-level performance.

Tasks:

•    Perform temperature-dependent magnetic measurements on electrical steels using a temperature-resistant Epstein frame in a climate chamber.
•    Conduct stator core measurements to evaluate application relevance.
•    Analyze experimental data to extract key magnetic parameters (losses, permeability, hysteresis).
•    Develop and/or adapt models (e.g., loss models, Jiles-Atherton, Preisach, or FEM-based approaches) that incorporate temperature dependence.
•    Validate models against experimental data and assess their predictive capability.
•    Discuss implications for the design of electric machines under thermal load.

Research Questions:

•    How do losses, permeability, and hysteresis characteristics evolve with temperature?
•    Can existing hysteresis and core loss models be extended to reliably capture temperature effects?
•    How transferable are Epstein frame results to real stator cores?

Requirements:

•    Background in Electrical Engineering, Physics, or Materials Science.
•    Interest in magnetic materials, electrical machines, and experimental methods.
•    Strong skills in data analysis and numerical modeling (MATLAB, Python, or FEM tools).
•    Practical experience in lab work is an advantage.

Impact:
The thesis combines fundamental research with direct industrial relevance. Results will support improved efficiency and reliability of electric machines, with potential for scientific publication and industrial implementation.

Application:
Your application must include a CV, personal letter and transcript of grades 
For questions, please contact Atieh Zamani, PhD, atieh.zamani@scania.com.

A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified.