PhD Studentship: Optimisation of Power Management Circuit for Self-powered Systems

University of Exeter - ESE

The University of Exeter’s Department of Engineering is inviting applications for a PhD studentship fully funded by the department to commence on September 2026 or as soon as possible thereafter. For eligible students the studentship will cover Home or International tuition fees plus an annual tax-free stipend of at least £20,780 for 3.5 years full-time, or pro rata for part-time study. The student would be based in the Faculty of Environment, Science and Economy at the Streatham Campus in Exeter.

Project Description:

Self-powered systems, which harvest energy from ambient sources (e.g., solar, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more systems can be self-powered. By optimising energy efficiency, waste from disposable batteries and the need for cabling can be reduced, which supports the global Net Zero goals in decarbonisation with minimal environmental impact. However, their practicability is often limited by suboptimal power management circuits (PMC), which need to be optimised or custom-designed on a case-by-case basis. This project seeks to advance energy autonomy by optimising power conversion, storage, and distribution in such systems, enabling broader adoption in real-world applications.

The project aims to develop a PMC design that is applicable to different types of energy harvesters. This project will explore how PMC can be optimised to maximise efficiency, reliability and scalability using novel circuit topologies, adaptive control strategies, and hybrid energy storage solutions to address key challenges in self-powered systems under dynamic environmental conditions by:

• Develop machine learning or heuristic-based control algorithms for whole system efficiency optimisation.
• Design and simulate power management circuits using tools like SPICE or MATLAB/Simulink.
• Prototype and test circuits with real energy harvesters (e.g., thermoelectric, piezoelectric, photovoltaic).

This funded PhD scholarship is suitable for students with a background in Engineering. Students with interests in power management circuits, optimisation, machine learning, AI are encouraged to apply.