Fully-funded PhD Studentship in Thermal Management System Development using AI Methods for Traction Electrical Machines

Overview

Qualification type: Bachelor’s or Master’s degree in Electrical/Automotive/Computer Engineering

Subject area: Automotive, Energy Conversion Systems, Power, Electric Vehicles

Location/Campus: Hatfield/College Lane

Duration: 3-year fully funded PhD on a Full-Time basis.

Start date: 01 September 2022

Closing application date: 01 May 2022

Programme outline

To develop a thermal management system for traction EMs used in EV, accurate modelling of the energy dissipation and applying real coefficients are required. Therefore, the EMs can be modelled in the transient state, considering the impact of electromagnetic fields. Applied artificial intelligence (AI) methods, can be employed to predict the boundary conditions and the heat transfer coefficients of different parts of the machines.

The heat transfer coefficient significantly affects the thermal characteristic and the temperature rise of different parts. The proposed AI based thermal management system will be able to predict the temperature rise when the EV is under various operation modes, such as starting torque, hill climbing, urban driving, motorway driving, etc. Mapping the temperature changes enables the software to also vary the loading rates among all the electrical machines employed in the powertrain (two- and four-wheel drive).

The main benefit of such a proposed system is to ensure that the thermal losses are reduced, and the EMs are always operating at the higher efficiency region. Additionally, the proposed thermal management system can be simulated using multiple standard drive cycles to validate the overall energy consumption reduction in targeted EV.

Supervisors

Principal supervisor: Dr Pedram Asef

Supervisory team: Dr Amin Paykani

Entry requirements

Applications are invited from individuals with a 1st or 2:1 Bachelor’s degree in Electrical/Automotive/Computer Engineering or related disciplines. A Master’s degree or equivalent in electrical engineering and industrial experience would be desirable.

We are seeking applicants with good understanding of:

  • electromagnetic analysis and thermal analysis for EMs, using FEM
  • machine learning methods for prediction purposes
  • electric vehicle powertrain development
  • test and validation methods to verify the numerical model and software.

Eligibility

Open to both UK and International applicants, including EU applicants.

How to apply

Please download and complete an application form

With your application please also submit a research proposal not exceeding two A4 pages, a CV and cover letter. You will also need to provide:

  • two academic references to be provided by referee directly to the doctoral college
  • copies of qualification certificates and transcripts
  • Certification of English language competence (minimum IELTS 6.5 or equivalent) for candidates for whom English is not their first language.

Your completed application should be emailed to the Doctoral College Admissions team: doctoralcollegeadmissions@herts.ac.uk

  • Interviews will take place: week beginning 20/03/2022
  • Informal enquires can be made to Dr Pedram Asef

Funding information

Annual tax-free bursary of approximately £ 15,609, plus tuition fees (£5,590 for UK or £ 14,905 for International and EU applicants)