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Passive Cooling for Thermal Management of Batteries for Next Generation Urban Electric Vehicles

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Stoke on Trent, United Kingdom

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Passive Cooling for Thermal Management of Batteries for Next Generation Urban Electric Vehicles

About the Project

Project Summary:

This project investigates a novel Phase Change Material (PCM) jacket system for improving the thermal management of Lithium-ion batteries (LiBs) used in next-generation urban electric vehicles (EVs). The proposed integrated solution aims to address current thermal limitations such as thermal runaway, degradation, and safety issues while optimizing system weight, performance, and cost.

The research builds upon an existing body of successful works [1-5] and aims to take the concept to the next level by developing and optimizing a full cell-to-pack-level solution. This includes CFD simulations, thermo-electro-chemical modelling, and machine learning-driven multi-objective optimization.

The project will develop a real-time digital twin for the battery-PCM system and ultimately deliver a 3D printed prototype for experimental validation. It aligns with UK national priorities around clean transportation and energy storage and has the potential to feed directly into REF outputs and funding proposals for Innovate UK or EPSRC.

Entry Requirements:

Essential:

  • Minimum upper second-class undergraduate degree (2:1) or a good Master's degree in a relevant engineering or physical sciences discipline
  • Solid knowledge of heat transfer and fluid mechanics
  • Proficiency in ANSYS Fluent
  • Strong written and oral communication skills
  • Teamwork, self-motivation, and a proactive attitude
  • The standard minimum IELTS Academic requirement is 6.5 overall with no less than 6.0 in each band. Some International students are also required to meet UKVI requirements for the appropriate study visa. A valid ATAS certificate (where required) must be secured as a prerequisite to enrolment.

Desirable:

  • Knowledge of electrical energy storage systems and phase change materials
  • Familiarity with two-phase flow phenomena
  • Experience with machine learning and multi-objective optimization techniques
  • Background in electric vehicle systems
  • Previous publications in peer-reviewed journals

How to Apply:

If you are interested in applying for this self-funded opportunity, then please send your CV and cover letter to the principal supervisor to Dr Mohammad Moghimi Ardekani:

m.moghimi-ardekani@staffs.ac.uk

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