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Production engine emission sensor modeling for in-use measurement and on-board diagnostics
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- Author / Creator
- Masoud Aliramezani
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Production engine emission sensors have become essential for on-board measurement in the exhaust gas and for engine feedback control.
To help design future amperometric sensors, first the diffusion mechanism of a zirconia-based amperometric NOx sensor was examined by studying the effect of sensor temperature on sensor output. The multi component molecular diffusion mechanism was experimentally found to be the dominant diffusion mechanism that affects the diffusive flow through the sensor diffusion barriers. A sensor model was developed
based on this dominant diffusion mechanism to predict NOx concentration which was validated with the experiments at different Diesel engine operating conditions with different species concentrations.
Then, a physics-based sensor model that includes diffusion and electrochemical submodels is developed. It is shown that NO is partly reduced in the O2 sensing chamber which affects NO concentration in the O2 sensing chamber and in the NOx sensing chamber. Therefore, the electrochemical model is developed to simulate partial reduction of NOx on the O2 sensing electrode and reduction of NOx on the NOx sensing electrode. A transport model that simulates diffusion of the gas species through the sensor diffusion barriers and sensor chambers is coupled to the electrochemical submodels. Experiments at different engine operating conditions with
different NOx concentrations from 0 to 2820 ppm have been performed to validate the model accuracy at different operating conditions. The model results closely match
the experiments with a maximum 12% error for the NOx sensing pumping current.
Cross-sensitivity of electrochemical sensors to the other exhaust gas contaminations, especially NH3 , is still a challenge for the automotive industry. A dynamic NOx sensor model is developed to remove ammonia cross sensitivity from production NOx sensors mounted downstream of Diesel engine selective catalytic reduction (SCR) systems. The model is validated for large amounts of ammonia slip during different engine transients. A three-state nonlinear control oriented SCR model is also developed to predict the NH3 concentration downstream of the SCR (NH3 slip).
NH3 slip is then used as an input for modeling the cross sensitivity of a production NOx sensor and calculating the actual NOx concentration in the presence of NH3 contamination.
A limiting-current-type amperometric hydrocarbon sensor for rich conditions (in the absence of O2 ) is also developed. The transient performance and stability of the sensor are optimized by changing the sensor temperature, the reference cell potential, and the stabilizing cell potential at a high propane concentration (5000 ppm - balanced with nitrogen). Then, the sensor steady state behavior is studied to find the diffusion-rate-determined operating region. The sensor is shown to have a linear sensitivity to propane concentration from 0 to 3200 ppm. The sensor response time to different
step changes from zero propane concentration to 5000 ppm propane concentration is studied. It is shown that propane concentration does not have a significant effect on the sensor response time.
Sensor and engine On Board Diagnostics (OBD) is the last part of this thesis. A physics-based model was developed and then employed to predict the sensor output for oxygen as a function of sensor temperature and oxygen concentration. A temperature perturbation method was also developed based on the model to calibrate the sensor output with respect to oxygen concentration. The model accurately matched the experimental results in steady state and transient. A two step sensor diagnostics procedure based on the sensor temperature perturbation method was then proposed.
A self-calibration procedure was also implemented inside the diagnostics procedure using temperature perturbation at engine-off. This self-recalibration only requires an external relative humidity measurement.
Finally, based on experimental data, a Multi-Input Multi-Output (MIMO) control oriented diesel engine model is developed to predict engine NOx emission and
brake mean effective pressure (BMEP). The steady state engine NOx is modeled as a function of the injected fuel amount, the injection rail pressure and the engine speed.
The BMEP is assumed to be a function of the injected fuel amount and engine speed.
Then, an engine dynamic model was developed by adding first order lags to the static NOx and BMEP models. This two-state control oriented model is used to represent
the dynamic model. The engine response to step changes of injection pressure and injected fuel amount are examined and compared with the experimental data. The developed control oriented model can be used for both engine and NOx sensor on board diagnostics and for engine control with NOx sensor feedback. -
- Graduation date
- Fall 2019
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- Type of Item
- Thesis
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- Degree
- Doctor of Philosophy
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- License
- Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.