Professor Xu is currently primarily working on the control of future powertrains using AI and machine-learning technology. He has research experience in flow/turbulence, fuel spray, mixture preparation, ignition, premixed/diffusion combustion, new combustion modes, emission formation/control, biofuels, engine modelling, and operational control. He also has experience in turbomachinery/turbocharging, engine design and various advanced engine technologies.
Selected major projects as PI (2002-2026): £12 million
Controlled Homogeneous Autoignition Reformed Gas Engine (CHARGE), DTI, 2002 - 2004
Controlled Homogeneous Autoignition Supercharged Engine (CHASE), DTI, 2004 - 2007
Combustion, performance & emissions of biodiesels (COPE), JLR, 2007 - 2008
Flex-diesel Engines with Sustainable Bio-fuels for Clean and Efficient On- and Off-Road Vehicle Engines (SERVE), TSB, 2007- 2010
Impact of DMF on Engine Performance and Emissions as a New Generation of Sustainable Biofuel, EPSRC, 2008 - 2011
HCCI engine technology research, JLR, 2007 - 2012
Thermal Management, JLR, 2007- 2012
Continuous Oxidation using NO2 Combustion for Exhaust Particulate Treatment (CONCEPT), JLR, Nov 2007-2009
Combustion and emissions of ethanol in a direct injection engine, Shell, 2008 - 2009
Combustion mechanism of furan fuels, Royal Society, 2011 – 2013
Biodiesel engine cold start, JLR and EU, 2012 - 2014
Effect of fuel properties on GDI engines, JLR and Shell, 2012 - 2015
Next generation of GDI engines with boosting, JLR, 2012-2015
New control methodology for the next generation of engine management systems, EPSRC, 2013 -2016
X-in-the-loop engine control, JLR, 2013 – 2016
Study of Novel Biofuels from Biomass, EPSRC, 2016 - 2019
Study of diesel particulate matter emissions, EU, 2013 – 2018
AI-based Hybrid vehicle energy management, 2019 -2021
Research on Real-time Optimisation System for Plug-in Hybrid Electric Vehicle based on Artificial Intelligence Digital Twin Technology, JITRI, 2020-2025
Premixed Combustion Flame Instability Characteristics, EPSRC (EP/W002299/1), 2022-2025
AI and machine-learning strategy and models for hybrid dedicated engines, BYD, 2021-2022
Development of Dual-mode Engine AI Emission Prediction and Knock Detection, BYD, 2023-2026
Main research interests include:
1. Research and Development of Thermal Propulsion Systems
2. Connected and Autonomous Systems for Electrified Vehicles (CASE-V):
- Level 1 - Engine/motor level transient control
- Level 2 - Powertrain-level component sizing and energy management
- Level 3 - Vehicle-level driver-machine interaction
- Level 4 - Fleet-level collaborative energy management with vehicle-to-everything (V2X) network.