[CCoE Notice] Dissertation Defense - Mirheidari

[Khator, Suresh]

Model‒Based Estimation and Fault Diagnosis in Diesel Engine Applications

Saleh Mirheidari

November 21st at 11 am, Large Conference Room, Mechanical Engineering Department
Committee members: Dr. M. A. Franchek, Dr. K. M. Grigoriadis, Dr. M. P. Harold, Dr. J. R. Rao, Dr. J. Mohammadpour

Abstract
Diesel engines are used in a variety of applications from small sedan diesel cars to heavy duty applications in huge generators and hydraulic pumps. Different types of research are done on engine control and fault diagnosis and design. Presented in this work are two parts. The first part is on biodiesel blend estimation and the second one is on cylinder fault diagnosis. Biodiesel as a renewable alternative fuel produces lower exhaust emissions with the exception of nitrogen oxides (NOx) when compared to the conventional diesel fuel. Reducing nitrogen oxides emitted from engines running on biodiesel requires proper engine controller adaptations that are linked to the specifics of the fuel blend.  Therefore, online estimation of fuel blend is a critical step in allowing diesel engines to maintain performance while simultaneously meeting emission requirements when operating on biodiesel blends. Presented in the first part of this work are three different model‒based biodiesel blend estimation strategies using: (i) crankshaft torsionals, (ii) NOx emissions measurement from the exhaust stream, and (iii) oxygen content measurement of the exhaust stream using a wide-band UEGO sensor. Each approach is investigated in terms of the accuracy and robustness to sensor errors. A sensitivity analysis is conducted for each method to quantify robustness of the proposed fuel blend estimation methods.


-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://Bug.EGR.UH.EDU/pipermail/engi-dist/attachments/20111118/b99043f0/attachment.html