Koenigsegg - MATLAB Based Multi-Objective Genetic Algorithm Optimization Solver for Axial Flux Machines

MATLAB based Multi-Objective Genetic Algorithm Optimization solver for Axial Flux Machines

Axial flux machines with their inherent high torque density and power density have been the main machine topology in electric and hybrid supercars. With diverse objectives for these kinds of machines such as high peak torque as well as peak efficiency at low torque and high speeds, need for a multi-objective genetic algorithm optimization solver is high.

If MSc thesis: 6-months
If MSc thesis + 6-8 ECTS internship: 7-8 months
(If 6-8 ECTS internship alone: 5 months)

Additional info is in the attached job posting description.

2022_ThesisOptimization (187.85 kB)

PLEASE CONTACT PROF. PELLEGRINO BEFORE ANY CONTACT WITH THE COMPANY.