Dr Guang Li
PhD

 
 
 

Research Funding

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Current Funded Research Projects

Hierarchical optimal energy management of electric vehicles

Funding source: EU Commission - Horizon 2020
Start: 01-07-2019  /  End: 30-06-2021
Amount: £179947

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.

Launch & Recovery Enhanced Sea States

Funding source: E.P.S.R.C.
Start: 01-08-2017  /  End: 04-12-2020
Amount: £303819

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

Funding source: WES Wave Energy Scotland
Start: 13-05-2019  /  End: 12-11-2020
Amount: £461346

Previous Funded Research Projects

Newton Advanced Fellowship: Professor Wei He

Funding source: Royal Society
Start: 01-03-2017  /  End: 28-02-2020

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.

Adaptive hierarchical model predictive control of wave energy converter

Funding source: WES Wave Energy Scotland
Start: 01-04-2018  /  End: 04-04-2019

This project proposes a hierarchical adaptive optimal control framework to maximise wave energy conversion efficiency while guaranteeing safe operation for a large range of sea states. The framework combines the strengths of several key promising technologies in control and wave prediction to adaptively achieve the best trade-off between energy maximisation ...

International Exchanges Scheme - 2015 China

Funding source: The Royal Society
Start: 01-04-2016  /  End: 03-01-2019

wave energy

Other Research Projects

Renewable Energy

Current work is mainly on sea wave energy: Ocean waves provide a vast, persistent and spatially concentrated energy compared with other renewable energy resources (e.g. solar and wind energies). Although enormous efforts have been made for decades in modern marine energy generation, it is still a relatively immature technology ...

Fast adaptive optimal control with application to sustainable energy systems

International Exchange Scheme - Royal Society

Dynamically Substructured Systems

Dynamically substructured system (DSS) is a testing method used in the dynamics testing community. The uses of the DSS concept can be found in diverse areas such as civil engineering, robotics, automotive and aerospace. A DSS contains both physical components (called physical substructure) and numerical components (called numerical substructure), which ...

Control System Theory

Design novel control strategies for practical uses, with special interests in constrained optimal control such as model predictive control (MPC) and anti-windup compensation. Development of control system analysis methods for nonlinear systems, such as absolute stability analysis of Lure systems, robustness and stability analysis of MPC. The techniques used include ...

Control of Launch and Recovery in Enhanced Sea-States: Part of the Launch and Recovery Co-Creation Initiative

The project aims to develop a novel approach to predicting a suitable time instant at which to initiate an L&R operation, together with a confidence measure (provided as advice to a human operator), and then to control the execution of the subsequent lift operation once initiated, using a novel form of Model Predictive Control. The research overarching vision is to create the new science that can be exploited to provide the underpinnings of a new generation of high added-value products to upgrade the performance and prolong the service life of existing naval vessels.

Control of Floating Wave Energy Converters with Mooring Systems

Under the scheme "Royal Society-Newton Advanced Fellowship", 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 Guang Li, QMUL) with expertise in WEC control and the Chinese team (lead by Prof Wei He, University of Science and Technology Beijing) in mooring control. Besides the direct impact on wave energy industry, the control framework has promising wider applications such as robotics, optimal power management and marine engineering. The project will last for 3 years. The project is jointly supported by the Royal Society (providing £111K) and NSFC (providing 500K RMB). The award will enhance the collaborations between Dr Guang Li’s group in QMUL and Prof Wei He’s group in USTB.

Adaptive hierarchical model predictive control of wave energy converters - Stage 1

This project proposes a hierarchical adaptive optimal control framework to maximise wave energy conversion efficiency while guaranteeing safe operation for a large range of sea states. The framework combines the strengths of several key promising technologies in control and wave prediction to adaptively achieve the best trade-off between energy maximisation and survivability.

Adaptive hierarchical model predictive control of wave energy converters

The project aims to develop a reliable and efficient control strategy to improve the wave energy converter (WEC) conversion efficiency and survivability over a wide range of sea states. This is to be achieved by integrating some enabling technologies in control and wave prediction into a hierarchical control framework, so that it can be equipped with several important features: maximum energy output, robustness to modelling uncertainties, and survivability at different sea states.

4) Battery Power Management System

Battery power management has wide and important applications in automotive engineering, renewable energy, and aerospace engineering, etc. We are interested in using control methods to improve the battery efficiency and reduce the degradation process. Current works include optimal charging, SOC estimation, and the integration of...