Advanced Manufacturing of Copper Conductors for Electric Machines

University of Sheffield

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Supervisory team:

Prof Hassan Ghadbeigi (Mechanical Engineering)

Prof Geraint Jewell (Electrical and Electronic Engineering)

Overview

Applications are invited for a fully funded PhD position (at UK student rates) focusing on the development and optimization of manufacturing processes for copper conductors used in next-generation electrical machines. This project sits at the intersection of advanced manufacturing, materials science, and data-driven process optimization.

Project Description

Electrical machines are crucial components in various applications, from electric vehicles to industrial drives. The efficiency and performance of these motors heavily depend on the thermal management of their copper windings. This PhD project aims to:

  1. Develop novel forming technologies for manufacturing rectangular section copper conductors with a degree of precision beyond current industry practice
  2. Create adaptive optimization frameworks for process parameters
  3. Establish relationships between manufacturing conditions and conductor performance
  4. Implement real-time process control strategies using sensor data and machine learning

Research Objectives

  • Design and validate forming processes for copper conductors
  • Develop finite element models to simulate the forming process
  • Investigate material behaviour and microstructural evolution during forming and its effect on the functional performance
  • Create adaptive optimization algorithms for process parameters
  • Implement data-driven approaches for process control and quality assurance
  • Establish design guidelines for scalable manufacturing

Methodology

The research will employ a comprehensive approach combining:

  • Experimental work on forming processes and material characterization
  • Advanced finite element modelling using commercial and custom software
  • Data acquisition and processing from manufacturing trials
  • Machine learning techniques for process optimization
  • Industrial validation of developed technologies

Required Qualifications

  • Higher 2.1 or a 1st  MEng degree in Mechanical Engineering, Materials Science and Engineering, Metallurgy, Civil and Structural Engineering, or related field
  • Adequate knowledge of metal forming processes and manufacturing processes
  • Experience with finite element modelling software and mechanical testing is preferred (e.g., Abaqus)
  • Programming skills (Python, MATLAB, or similar)
  • Knowledge of materials science and metallurgy

Desired Skills

  • Experience with data analysis and machine learning
  • Knowledge of electric motor design principles
  • Familiarity with instrumentation and sensor systems
  • Background in process control and optimization
  • Good communication and technical writing skills

Industrial Collaboration

The project will be conducted in collaboration with leading manufacturers of electric motors and aerospace OEMs, providing exposure to industrial applications and potential career opportunities.

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