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Details of Grant 

EPSRC Reference: GR/K84714/01
Title: IDENTIFICATION OF CATALYTIC CONVERTER DYNAMICS FOR IMPROVED CONTROL ALGORITHMS TO REDUCE TAILPIPE EMISSIONS
Principal Investigator: Roberts, Professor R
Other Investigators:
Childs, Professor P Jackson, Dr RA Peyton-Jones, Dr J
Researcher Co-Investigators:
Project Partners:
Ford Motor Co Johnson Matthey Pre Nexus Migration
Ricardo Group Rover Ltd
Department: Sch of Engineering and Design
Organisation: University of Sussex
Scheme: Standard Research (Pre-FEC)
Starts: 01 April 1997 Ends: 31 March 2000 Value (£): 208,945
EPSRC Research Topic Classifications:
Combustion
EPSRC Industrial Sector Classifications:
Transport Systems and Vehicles
Related Grants:
Panel History:  
Summary on Grant Application Form
Three-way catalytic converters provide the most important and now very common means for reducing the tailpipe emissions of spark ignition gasoline enignes, yet their dynamic behaviour remains one of the last unknowns in the overall vehicle emissions system. This project aims to identify these dynamics form input/output measurements of the actual process using nonlinear system identification techniques, and to obtain empirical models specifically for use in real-time engine control and on-board diagnostic strategies.The ability to integrate the catalyst within the engine control strategy will enable optimisation of the complete engine/catalyst system for improved fuel efficiency and reduced emissions, as well as providing a basis for on-board diagnostics. This work has been identified by Ford, Rover, Johnson Matthry, Ricardo, and Sagemas as vital pre-competitive research for the next generation of clean vehicle technology to meet European Stage III and EOBD legislation and beyond.The model structure and nonlinear system identification techniques will be developed incrementally, starting with the heat transfer process in a dead catalyst, and expanding to normal operation, and then more extreme perturbations such as fuel cut-off and light-off. Finally the use and benefits of these models in real-time control systems will be investigated.
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Organisation Website: http://www.sussex.ac.uk