The Job

Master Thesis: Predictive maintenance for alternators

Teknik, data och digitalt · Mjukvaru- och webbutveckling · Mjukvaruutveckling · Datavetenskap

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I korthet

Master thesis project at Volvo Penta in Göteborg, Sweden, focusing on developing predictive maintenance algorithms for alternators. The project involves data collection, health status determination, and remaining useful life prediction using AI/ML or physics-based models. The thesis is for 30 ECTS points and starts in January 2027.

Ansvarsområden

  • Develop an algorithm and predictive model for alternator health status and remaining useful life (RUL).
  • Collect data from a test rig or create a MATLAB model considering parameters like current, voltage, temperature, duty cycle, rotor speed, load history, and environmental conditions.
  • Create an algorithm to determine the alternator's health status based on collected parameters.
  • Develop a solution to predict RUL and continuously improve prediction accuracy using test data or the MATLAB model.
  • Explore different approaches including data-driven analytics, AI/ML methods, and physics-based models.

Krav

  • Master student in Electrical Machines / Power Engineering or Computer Science / AI fields.
  • Specializations: Sustainable electric power engineering & electromobility, Electric Power Engg; Maintenance engineering, Systems, control and mechatronics, Mobility engineering.
  • Specializations: Information Technology – Data Science, AI and Machine Learning; Data Science – Machine Learning and Statistics.
  • Interest in AI/ML and embedded systems.

Önskade kvalifikationer

  • Knowledge of rotating electrical machines and condition monitoring.
  • Experience with signal processing or predictive maintenance applications.
  • Experience with MATLAB, Python, or Machine Learning.
  • Knowledge of CAN/LIN topology.
  • One student with a Motor(s) background and one with a computer background are sought.

Förmåner

  • Opportunity to shape sustainable transport and infrastructure solutions.
  • Work with next-gen technologies and collaborative teams.
  • Gain experience in predictive maintenance and advanced analytics.
  • Thesis duration: approx. 5-6 months.
  • Thesis level: Master (30 ECTS points).
#predictive maintenance#alternators#electrical components#data analysis#AI#machine learning
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Företag

Volvo Group

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för 2 veckor sedan

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Erfarenhetsnivå

Student

Platser

Göteborg, Sweden

Kvalifikation

Masterexamen

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