PhD in Reliability and Health Monitoring of Power Electronics

University of Cranfield

School of Aerospace, Transport and Manufacturing (SATM)

Project Description

Applications are invited for a PhD degree in the area of Reliability and Health Monitoring of Power Electronics. The research would focus on devising innovative and novel reliability testing and health monitoring algorithms to evaluate the performance of wide bad-gap power semiconductor devices through lab-based experiments under varying environmental and operating conditions. This will be in the context of the next generation more-electric and all-electric aircraft(MEA/AEA) configurations.

With the global drive towards carbon-free and green environment, electrification in transportation, manufacturing, aerospace, and energy is becoming essential. This transformation implies a growing role of Power Electronics in each one of these areas. Accordingly, the requirements of reliability and robustness of power semiconductor devices have also increased. In particular, the wide band-gap (WBG) devices such as silicon carbide (SiC) MOSFETs and gallium nitride (GaN)-based high-electron mobility transistors are now gradually replacing their silicon-based counterparts (IGBTs) in several high-end applications. In spite of their much higher thermal conductivity and switching frequencies, the industries are reluctant in fully deploying the WBG devices across various critical applications.

This research project aims at investigating the existing reliability and condition monitoring methods for wide band-gap power semiconductor devices and developing advanced reliability-physics (physics of failure-PoF) models and robustness validation algorithms to increase their real-time/field deployment. The research will involve an in-depth analysis of failure mechanisms, optimisation of experimental setup for different accelerated life tests under selected mission profiles, and the development of reliability-physics based test and measurement circuits for a wider range of power devices and modules. Machine learning/ Pattern recognition tools such as curve fitting, neural networks or recursive tracking algorithms such as Kalman filters could also be used on test data to approximate the failure models.

Start date: 07 Jun 2021

Duration of award: 3 years

Eligibility: UK, EU, Rest of World

Funding Information

This is a self-funded project only.

Eligibility Requirements

Graduate and post-graduate students with a degree in Engineering or Physics (preferably exposure to power electronics), and Researchers and Engineers with a background/interest in reliability and health monitoring. Familiarity with MATLAB/Simulink is desired but not essential. Above all, research aspirants with an innovative approach, high motivation and willingness to learn are welcomed.

Application Process

For further information please contact:

Name: Suresh Perinpanayagam
Email: [email protected]
T: (0) 1234 750111 Ext: 2377

Academic profile link:

If you are eligible to apply for this studentship, please complete the online application form.

Supplementary Information

Cranfield is a unique learning environment with world-class programmes, unrivalled facilities and close links with business, industry and governments, all combining to attract the best students and teaching staff from around the world. In 2014, 81% of research at Cranfield was rated as world-leading or internationally excellent in the Research Excellence Framework (REF).

The Integrated Vehicle Health Management (IVHM) Centre is in its 12th year of operation. Founded by Boeing and a number of aerospace partners (BAE Systems, Rolls-Royce, Meggitt and Thales) in 2008, it has grown to perform work in sectors such as transport, aerospace, and manufacturing. The Centre integrates a multidisciplinary research effort to develop cost-effective component and system health management technologies capable of supporting ground and on-board applications of high-value, high-complexity systems.

IVHM Centre is a member of Digital Aviation Research and Technology Centre (DARTeC), which focuses its researchon aircraft electrification, connected systems, unmanned traffic management, seamless journey, distributed airport/airspace management, and conscious aircraft. Research England, Thales, Saab, Aveillant IVHM Centre and Boxarr are some of the prominent members of DARTec. IVHM Centre also works in close collaboration with Aerospace Integration Research Centre (AIRC), founded in partnership with Airbus and Rolls-Royce. The potential PhD candidate will have access to the facilities held by AIRC and DARTeC in addition to having interactive sessions with experts at AIRC and DARTeC.

The successful culmination of this project envisages the availability of well-tested and validated novel reliability-physics and condition monitoring models and algorithms for wide band-gap power semiconductor devices.

The IVHM lab as well as other research centres house excellent lab facilities (environmental chamber, high-fidelity test equipment etc.) and state-of-the-art modelling and simulation software. Specialised training on these software would be provided in addition to the coordinated external learning and training sessions with industrial partners. The IVHM Centre encourages and supports ample opportunities for presenting research papers in high profile conferences exist within the UK and across the globe. More significantly, the potential candidate will have the opportunity to present his research work during quarterly in-house technical reviews to wider research community from within the university and the industrial partners (Boeing, Thales, Meggitt, and BAE systems). It also provides a networking platform for the promising researchers to lay the foundations of their professional relationship with key representatives from various companies.

Upon successful completion of the project, the potential candidate will be able to carry out research activities independently and more vigorously. You will have the requisite expertise and an in-depth current knowledge of the power electronics domain coupled with working familiarity with state-of-the-art simulation and modelling techniques. These would add to the candidate’s employability.