| EPSRC Reference: |
EP/C005457/1 |
| Title: |
Dynamic Nonlinear Fault Diagnosis for Internal Combustion Engines |
| Principal Investigator: |
Irwin, Professor GW |
| Other Investigators: |
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| Department: |
Sch of Electronics, Elec Eng & Comp Sci |
| Organisation: |
Queen's University of Belfast |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 June 2005 |
Ends: |
31 May 2008 |
Value (£): |
239,634
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Summary on Grant Application Form |
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The regulations associated with current on-board diagnostic (OBD) systems demand very strict monitoring of engine performance to diagnose any fault causing the tailpipe emissions to rise above legislated values. The objective of this project is to produce a new statistical technique, capable of analysing the highly dynamic and non-linear signals provided by sensors currently available on a production vehicle, in order to detect emissions faults. Preliminary work on a VW 1.9 litre TDI diesel engine points to the following advantages of our approach: (i) no assumptions about the internal combustion engine are made in identifying the statistical representation, as compared to current physical model-based techniques, (ii) the approach is entirely based on practical measured data which is already available in a production engine, therefore no additional hardware is required, (iii) the technique is specific to the engine under investigation, thus it will be robust to manufacturing tolerances (iv) since MSPC can accurately represent steady-state operating conditions, it can therefore be used immediately for the routine maintenance checks required under existing legislation (OBDII, EURO3) and (iv) the scheme can be implemented on-line in conjunction with existing on-board diagnosis systems. Moreover, variable reconstruction techniques offer the potential to correct faulty sensor readings, due to drift or bias for example, by replacing the recorded values with those predicted by the reconstruction model.While the results to date are exciting and, to our knowledge constitute a completely new approach, our research has been confined to a steady-state framework. For full monitoring that can be applied on-line and integrated into the vehicle on-board-diagnostics, it is essential to research dynamic and nonlinear MSPC. Further, to meet the latest OBD legislation it is necessary to address catalyst, as well as engine faults.The research will involve new theoretical developments in multivariate statistical process control (MSPC), specifically on dynamic nonlinear PCA and sub-space identification algorithms, coupled with experimental testing on 1.8 litre, 4-cylinder, 16-valve gasoline automotive engine manufactured by Nissan Motor Co.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Further Information: |
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| Organisation Website: |
http://www.qub.ac.uk |