AI-Assisted Drives Research Internship (Bachelor/Master Thesis)

Quick Facts

• Thesis project (Bachelor/Master)
• Focus: AI-assisted control of electrical drive systems
• Duration: 6 months
• Work mode: Hybrid (Bruchsal)

Description

You will investigate data-driven methods to improve the control of electrical drive systems and use machine learning to automate and optimize controller parameterization for frequency-converter-fed motors. The work includes collecting and preparing measurement data, developing modeling and learning approaches, implementing prototypes, and systematically evaluating results for industrial applicability.

Role Description & Responsibilities

• Investigate data-driven improvements for the control of electrical drive systems
• Automate and optimize controller parameterization for frequency-converter-fed motors using targeted machine learning methods
• Support improvements in performance, robustness, and adaptability
• Systematically capture and prepare measurement data
• Develop suitable modeling and learning approaches
• Prototype implementation of the approaches
• Structured evaluation and assessment of results for industrial usability

Requirements

• Studies in Electrical Engineering, Mechatronics, Automation Engineering, Computer Science, or a comparable program
• Interest in drive technology, motor control, and/or industrial automation plus AI methods
• Initial practical programming experience (e.g., Python, MATLAB, C/C++)
• Basic understanding of technical system relationships and interest in experimental work
• Strong German and English skills

Benefits

• Competent mentorship and support
• Seminars via the DriveAcademy
• Student information events and a weekly student meetup
• Modern equipment and high-quality working conditions
• Innovative development projects and flexible deployment times
• Health management, fitness studio cooperation, and leisure offerings
• Opportunity for ongoing financial and technical support through StudentsWorld for outstanding performance