School of Electronic, Electrical and Systems Engineering

Chris Ward is a currently a Lecturer in the School of Electronic, Electrical and Systems Engineering, following a period of time as a Research Associate with the Control Systems Group.  His current research work is concerned with fault detection in railway based problems, particularly focusing on the critical wheel/rail contact area.

This work has been funded by RRUK (Rail Research UK) and currently by RSSB with the emphasis on finding in-service methods for estimating such things as the wheel/rail profile contact geometry and areas of low adhesion.  Use is made of advanced filtering methods, system identification and signal analysis.

Prior to moving to Loughborough University Dr Ward received his PhD from the University of Liverpool in automotive engineering, focusing on automotive powertrain controls.  This involved the development of rapid prototyping methods to generate robust controllers in a short time frame.

Expertise
Advanced condition monitoring systems for railway vehicles
Algorithms and architectures for high-performance real-time controllers
Applications of advanced control techniques

Keywords
Condition Monitoring
System identification
Robust control
J-spectral factorisation

Dr Ward, who is originally from Lincoln, studied for a BEng degree at the University of Liverpool in Mechanical Engineering, graduating in 2003.  After graduating he took a role as a Production Engineer at Erlson Engineering (Hampson Group) in Skelmersdale, Lancashire, where he worked in a team planning new production lines for automotive components.

He returned to the Department of Engineering at University of Liverpool in late 2004 to pursue a PhD in automotive powertrain control.  This work involved the use of system identification to produce relevant models directly from engine dynamometers and the development of a linear/nonlinear robust control design algorithm.

Dr Ward became a Research Associate with the Control Systems Group in the School of Electronic, Electrical and Systems Engineering, Loughborough University, in early 2009.  His first research project was funded by RRUK and was concerned with developing a real time method for the estimation of the wheel/rail profile in railway applications.  His subsequent project was funded by RSSB and was concerned with detecting areas of low adhesion in the wheels/rail contact of railway vehicles in real time.

Dr Ward was appointed as a Lecturer in the School of Electronic, Electrical and System Engineering in early 2012, where he is continuing with work based around condition monitoring of railway vehicles.

Professional affiliation

• Associate Member of the Institute of Mechanical Engineers

Current project (Loughborough University)

RSSB project T959: Onboard Detection of Low Adhesion.  The project is a further investigation into the novel concept of detection low adhesion events in the wheel/rail interface (project T614) in real time.  This research is driven by events where rail vehicles that are braking have greatly increased stopping distances, the most common cause of which is the ‘leaves on the line’ phenomena.  The aim of the method is to detect areas of low adhesion in real time so that rail vehicle operation can be adjusted accordingly.  The project specific objectives are:

• To determine the sensing requirements and develop processing techniques that can detect low levels of adhesion arising from the normal running of a rail vehicle
• To evaluate the developed techniques using data derived from a full-complexity non-linear railway vehicle dynamics software package
• To demonstrate the efficacy of the technique by means of a series of full-scale vehicle experiments

Previous project (Loughborough University)

RRUK B8: Dynamic Estimation of the Wheel/Rail Profile – The project is concerned with dynamically finding the wheel rail profile as an alternative to physical measurement, reducing the out of service time of a train set.  Currently investigating advanced filtering and recursive system identification techniques for the application.

PhD project (University of Liverpool)

J-Spectral Factorisation for Automotive Powertrain Controls – Development of a linear/nonlinear robust control design algorithm for automotive powertrain applications.  The method utilises a combined system identification and Newton iteration method of J-spectral factorisation.  Engine models were generated by system identification using data generated from dynamometers through the dSPACE system, reducing costly modelling time.