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  PCB Layout Design Automation for Power Electronics

   Department of Electronic and Electrical Engineering

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  Dr Cheng Zhang  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Switched-mode power converters are widely used to transform voltage levels, such as in chargers for mobile phones and laptops. Converter design and development normally requires experienced engineers to manually draft, lay down and optimise the circuit, and several iterations of development and verification are needed before an optimal solution is realised. This is because both high energy efficiency and high-power density are desired at the same time. Automating this process requires complex modelling of multi-domain phenomena including electromagnetics, mechanics, thermodynamics and the interactions among them. It also requires innovative, rapid meshing and solving algorithms for evaluating the enumerated and evolved designs promptly, searching the design space efficiently for the best solution. A software toolchain will be developed and verified in this project, utilising computational performance evaluation programs such as SPICE and Multiphysics FEM and the latest prediction and generation algorithms, to design and optimise a converter with any given specification automatically. This will save not only the costs of labour and material, but also the lead time for industry to develop new converters in the future. The direct outputs of this project will potentially reshape the R&D methodologies for consumer product power supply manufacture. On top of our expertise in power electronics, this project would strengthen the known knowledge by harnessing the latest algorithms of machine learning and underpin the next generation of CAD tools for the electronics industry. It will lead to high impact academic publications in the area of power electronics and the application of AI and machine learning, and will stimulate subsequent research in design automation and optimisation.


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For more information, visit our funding page or search our funding database for specific scholarships, studentships and awards you may be eligible for. 

Before you apply 

We strongly recommend that you contact the lead supervisor for this project before you apply. 

How to apply 

To be considered for this project you’ll need to complete a formal application through our online application portal

When applying, you’ll need to specify the full name of this project, the name of your supervisor, how you’re planning on funding your research, details of your previous study, and names and contact details of two referees

Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.  

If you have any questions about making an application, please contact our admissions team by emailing [Email Address Removed]

Equality, diversity and inclusion 

Equality, diversity and inclusion is fundamental to the success of The University of Manchester and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.

We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status. 

We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder). 

Computer Science (8) Engineering (12) Mathematics (25) Physics (29)

Funding Notes

This program is offered for self-funded or externally funded students only for 3/3.5/4 years