Real-time and robust estimation of biodiesel blends

Saleh Mirheidari, Matthew Franchek, Karolos Grigoriadis, Javad Mohammadpour, Yue Yun Wang, Ibrahim Haskara

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

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 produced 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 this paper 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.

Original languageEnglish (US)
Pages (from-to)37-48
Number of pages12
JournalFuel
Volume92
Issue number1
DOIs
StatePublished - Feb 1 2012

Keywords

  • Fuel blend estimation
  • Online adaptive model
  • System Identification

ASJC Scopus subject areas

  • Fuel Technology
  • Energy Engineering and Power Technology
  • Chemical Engineering(all)
  • Organic Chemistry

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