Real-time and robust estimation of biodiesel blends using nox sensor

S. Mirheidari; Matthew Franchek; K. M. Grigoriadis; J. Mohammadpour; Y. Y. Wang; I. Haskara

doi:10.1115/DSCC2011-6073

Real-time and robust estimation of biodiesel blends using nox sensor

S. Mirheidari, Matthew Franchek, K. M. Grigoriadis, J. Mohammadpour, Y. Y. Wang, I. Haskara

Research Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

Biodiesel as a renewable alternative fuel produces lower exhaust emissions with the exception of nitrogen oxides (NO_x) when compared to the conventional diesel fuel. Reducing nitrogen oxides produced from engines running on biodiesel is a challenging task to be able to meet the emission requirements. Knowledge of fuel blend could be very helpful for control and adaptation purposes to tune the engine control system parameters leading to lower NO_x emission and improved engine performance. Proposed in this paper is a NO_x sensor-based biodiesel blend estimation strategy. This strategy is fitted in a robust adaptive estimation structure for achieving a robust estimation. Sensitivity analysis has been done to check the robustness of the estimators against measurement errors.

Original language	English (US)
Title of host publication	ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, DSCC 2011
Pages	891-898
Number of pages	8
Volume	1
DOIs	https://doi.org/10.1115/DSCC2011-6073
State	Published - Dec 1 2011
Event	ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, DSCC 2011 - Arlington, VA, United States Duration: Oct 31 2011 → Nov 2 2011

Other

Other	ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, DSCC 2011
Country	United States
City	Arlington, VA
Period	10/31/11 → 11/2/11

ASJC Scopus subject areas

Fluid Flow and Transfer Processes
Control and Systems Engineering

Access to Document

10.1115/DSCC2011-6073

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Real-time and robust estimation of biodiesel blends using nox sensor. / Mirheidari, S.; Franchek, Matthew; Grigoriadis, K. M.; Mohammadpour, J.; Wang, Y. Y.; Haskara, I.

ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, DSCC 2011. Vol. 1 2011. p. 891-898.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mirheidari, S, Franchek, M, Grigoriadis, KM, Mohammadpour, J, Wang, YY & Haskara, I 2011, Real-time and robust estimation of biodiesel blends using nox sensor. in ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, DSCC 2011. vol. 1, pp. 891-898, ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, DSCC 2011, Arlington, VA, United States, 10/31/11. https://doi.org/10.1115/DSCC2011-6073

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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 is a challenging task to be able to meet the emission requirements. Knowledge of fuel blend could be very helpful for control and adaptation purposes to tune the engine control system parameters leading to lower NOx emission and improved engine performance. Proposed in this paper is a NOx sensor-based biodiesel blend estimation strategy. This strategy is fitted in a robust adaptive estimation structure for achieving a robust estimation. Sensitivity analysis has been done to check the robustness of the estimators against measurement errors.",

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AB - 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 is a challenging task to be able to meet the emission requirements. Knowledge of fuel blend could be very helpful for control and adaptation purposes to tune the engine control system parameters leading to lower NOx emission and improved engine performance. Proposed in this paper is a NOx sensor-based biodiesel blend estimation strategy. This strategy is fitted in a robust adaptive estimation structure for achieving a robust estimation. Sensitivity analysis has been done to check the robustness of the estimators against measurement errors.

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