Uncertainty analysis of model based diesel particulate filter Diagnostics

SAE International Journal of Commercial Vehicles

Volumn 1, Issue 1, 2009, Pages 356-362

  van Nieuwstadt, Michiel ^a   Brahma, Avra ^a  

^a FORD MOTOR COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIESEL PARTICULATE FILTERS; MODEL-BASED; NOISE FACTOR; POTENTIAL BENEFITS;

UNCERTAINTY ANALYSIS;

EID: 77953182094     PISSN: 1946391X     EISSN: 19463928     Source Type: Journal    
DOI: 10.4271/2008-01-2648     Document Type: Article

References (8)

1. M. van Nieuwstadt, D. Trudell, Diagnostics for diesel particulate filters, SAE 2004-01-1422
2. M. van Nieuwstadt, D. Upadhyay, M. Goebelbecker, W. Ruona, Experiments in Active Diesel Particulate Filter Regeneration, SAE 2003-01-3360
3. A.G. Konstandopoulos, E. Skaperdas, M. Masoudi, Inertial contributions to the pressure drop of diesel particulate filters, SAE 2001-01-0909.
4. A.G. Konstandopoulos, M. Kostoglou, E. Skaperdas, E. Papaioannou, D. Zarvalis, E. Kladopoulou, Fundamental studies of diesel particulate filters: transient loading, regeneration and aging, SAE 2000-01-1016.
5. E. Kladopoulou, S. Yang, J. Johnson, G. Parker, A. G. Konstandopoulos, A Study Describing the Performance of Diesel Particulate Filters During Loading and Regeneration - A Lumped Parameter Model for Control Applications, SAE 2003-01-0842
6. G. Hauser, Smoke particulate sensors for OBD and high precision measuring, SAE 2006-01-3549
7. EPA Draft Technical Report, A Comprehensive Analysis of Biodiesel Impacts on Exhaust Emissions, EPA420-P-02-001, October 2002.
8. ARB's heavy duty diesel OBD regulations, http://www.arb.ca.gov/msprog/obdprog/hdobdreg.ht m.