Hierarchical optimal energy management of electric vehicles

It has been widely recognized that vehicle electrification provides a potential way for the EU to move towards a more decarbonized transport system and sustainable circular economy. The overarching objective of this project is to develop a novel computationally efficient hierarchical adaptive optimal control framework incorporating transportation information and drivers’ habits suitable for energy management of multi-source EVs.

The National Centre for Nuclear Robotics (NCNR)

Nuclear facilities require a wide variety of robotics capabilities, engendering a variety of extreme RAI challenges. NCNR brings together a diverse consortium of experts in robotics, AI, sensors, radiation and resilient embedded systems, to address these complex problems. In high gamma environments, human entries are not possible at all. In alpha-contaminated environments, air-fed suited human entries are possible, but engender significant secondary waste (contaminated suits), and reduced worker capability. We have a duty to eliminate the need for humans to enter such hazardous environments wherever technologically possible. Hence, nuclear robots will typically be remote from human controllers, creating significant opportunities for advanced telepresence. However, limited bandwidth and situational awareness demand increased intelligence and autonomous control capabilities on the robot, especially for performing complex manipulations. Shared control, where both human and AI collaboratively control the robot, will be critical because i) safety-critical environments demand a human in the loop, however ii) complex remote actions are too difficult for a human to perform reliably and efficiently.

Predictive Modelling for Nuclear Engineering (Early Career Fellowship)

To develop numerical models that predict the coupled neutronics-thermal hydraulics physics with nuclear reactor cores and to quantify the uncertainties in these predictions.

Launch & Recovery Enhanced Sea States

The project aims to develop a novel approach to predicting a suitable time instant at which to initiate an Launch and Recovery operation, together with a confidence measure, and then to control the execution of the subsequent lift operation once initiated.

Adaptive hierarchical model predictive control of wave energy converter - Stage 3

Bimodule material in highway construction and computational study

Finite element method and meshless finite block method are developed to study composites with bimodule materials.

WormBot

In this project, in collaboration with our partner, Q-bot, a London-based robotic company, we aim to design, manufacture and validate robust, soft robots to remotely apply insulation below the ground floor of domestic dwellings.

Organic Rankine Cycle

The project aims at bridging the gap between fundamental heat transfer and sustainable thermal systems by investigating expertise at both Queen Mary University of London and Guangdong University of Technology.

Newton Advanced Fellowship: Professor Wei He

The project is on Control of Floating Wave Energy Converters with Mooring Systems. This project aims to resolve a fundamental control problem for floating wave energy converters (WEC) with mooring lines. The project will be collaboratively conducted by the UK team (lead by Dr Li) with expertise in WEC control and the Chinese team (lead by Prof He) in mooring control.

Automated remote monitoring of lower limb disorders to improve treatments and rehabilitation outcome

Thermally Driven Heat Pump Based on Integrated Thermodynamic Cycles for Low Carbon Domestic Heating

Jet noise: characteristics of the instantaneous emission patterns

To develop a model which is consistent with jet noise far field measurements of both spectra measured at different angles and 2-point far field correlations of the sound pressure.