Real-time diagnosis of the exhaust recirculation in Diesel engines using least-squares parameter estimation

Javad Mohammadpour, Karolos Grigoriadis, Matthew Franchek, Benjamin J. Zwissler

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

In this paper, we present a real-time parameter identification approach for diagnosing faults in the exhaust gas recirculation (EGR) system of Diesel engines. The proposed diagnostics method has the ability to detect and estimate the magnitude of a leak or a restriction in the EGR valve, which are common faults in the air handling system of a Diesel engine. Real-time diagnostics is achieved using a recursive-least-squares (RLS) method, as well as, a recursive formulation of a more robust version of the RLS method referred to as recursive total-least-squares method. The method is used to identify the coefficients in a static orifice flow model of the EGR valve. The proposed approach of fault detection is successfully applied to diagnose low-flow or high-flow faults in an engine and is validated using experimental data obtained from a Diesel engine test cell and a truck.

Original languageEnglish (US)
Pages (from-to)1-8
Number of pages8
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume132
Issue number1
DOIs
StatePublished - Jan 1 2010

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Real-time diagnosis of the exhaust recirculation in Diesel engines using least-squares parameter estimation'. Together they form a unique fingerprint.

Cite this