Estimation of the Switch Point of an Exhaust Gas Oxygen Sensor in General Exhaust Environments

1995 ◽  
Author(s):  
A. D. Brailsford ◽  
E. M. Logothetis ◽  
M. Yussouff ◽  
J. T. Woestman
Keyword(s):  
Oxygen Sensor ◽  
Exhaust Gas ◽  
Switch Point

Experimental Investigation of Switching Oxygen Sensor Behavior Due to Exhaust Gas Effects

2006 ◽  
Author(s):  
Adam Vosz ◽  
Shawn Midlam-Mohler ◽  
Yann Guezennec ◽  
Steve Yurkovich
Keyword(s):  
Equivalence Ratio ◽  
Oxygen Sensor ◽  
Low Voltage ◽  
Operating Conditions ◽  
Feedback Signal ◽  
Exhaust Gas ◽  
Engine Exhaust ◽  
Switch Point ◽  
Fuel Ratio ◽  
The Impact

Switching type exhaust gas oxygen sensors are critical to the performance of air-to-fuel ratio control in stoichiometric SI engines. Controlling the air-to-fuel ratio around stoichiometry is necessary for adequate three-way catalyst performance to meet government emissions regulations. However, the feedback signal from the sensor does not always truly depict the actual chemical mixture present in the exhaust gasses, which intrinsically affects the catalyst performance. A sensor may not provide correct air-to-fuel ratio feedback due to certain species in the exhaust gas which affect the equivalence ratio that the sensor switches from the high to low voltage or vice versa. This work attempts to characterize the impact of gas on fresh and aged sensors and builds upon earlier work in the field by using real engine exhaust rather simulated exhaust gas. In these experiments, the air-to-fuel ratio of a stoichiometric gasoline engine is incrementally increased from a lean to rich mixture to elicit the full switching response of the oxygen sensor. Additional sensor output curves are generated in the presence of external additive gases such as hydrogen, carbon monoxide, propane, and gasoline vapor. An automotive emissions analyzer and a hydrogen analyzer detect the concentrations of the exhaust gases and the chemical equivalence ratio is calculated using a carbon balance. This equivalence ratio creates a reference to examine the accuracy of the switch point of the sensor to actual stoichiometry. Using these data sets, it is possible to determine observe the effect of various gas species on the air to fuel ratio at which the sensor switches. The sensitivity of the different sensors to gas concentrations are quantified and presented, which form an elementary model to predict the sensor switch point in the presence of these gas species. Primary findings indicate that the impact of species on the sensor switch point is linearly related to the concentration of the species; sensor type and sensor age have an effect on a sensor's sensitivity to species; and different hydrocarbon species affect sensors differently. The findings support the simulated exhaust gas results reported in the literature in that the degree of interference of a species is related to the diffusion rate of the species with respect to oxygen through the sensor. The results also point toward the importance of the species of hydrocarbons in the engine exhaust, which are uncontrolled and can vary with engine operating conditions. This feature is critical to the application of this knowledge to automotive control.

Estimation of Ethanol Content in Flex-Fuel Vehicles Using an Exhaust Gas Oxygen Sensor: Model, Tuning and Sensitivity

2008 ◽  
Author(s):  
Kyung-Ho Ahn ◽  
Anna G. Stefanopoulou ◽  
Mrdjan Jankovic
Keyword(s):  
Oxygen Sensor ◽  
Control Process ◽  
Engine Management System ◽  
Exhaust Gas ◽  
Fuel Blend ◽  
Analysis And Design ◽  
Sensor Model ◽  
Ethanol Content ◽  
Model Tuning ◽  
Adaptation Law

Throughout the history of the automobile there have been periods of intense interest in using ethanol as an alternative fuel to petroleum-based gasoline and diesel derivatives. Currently available flexible fuel vehicles (FFVs) can operate on a blend of gasoline and ethanol in any concentration of up to 85% ethanol. In all these FFVs, the engine management system relies on the estimation of the ethanol content in the fuel blend, which typically depends on the estimated changes in stoichiometry through an Exhaust Gas Oxygen (EGO) sensor. Since the output of the EGO sensor is used for the air-to-fuel ratio (AFR) regulation and the ethanol content estimation, several tuning and sensitivity problems arise. In this paper, we develop a simple phenomenological model of the AFR control process and a simple ethanol estimation law which can be representative of the currently practiced system in FFVs. Tuning difficulties and interactions of the two learning loops are then elucidated using classical control techniques. The sensitivity of the ethanol content estimation with respect to sensor and modeling errors is also demonstrated via simulations. The results point to an urgent need for model-based analysis and design of the AFR controller, the ethanol adaptation law and the fault detection issues in FFVs. Tuning and sensitivity issues are demonstrated via simulations and limitations are also discussed.

Tolerant Ethanol Estimation in Flex-Fuel Vehicles During MAF Sensor Drifts

2009 ◽  
Author(s):  
Kyung-ho Ahn ◽  
Anna G. Stefanopoulou ◽  
Mrdjan Jankovic
Keyword(s):  
Oxygen Sensor ◽  
Air Flow ◽  
Intake Manifold ◽  
Absolute Pressure ◽  
Exhaust Gas ◽  
Fuel Ratio ◽  
Ethanol Content ◽  
Sensor Drift ◽  
Flex Fuel ◽  
The Difference

Flexible fuel vehicles (FFVs) can operate on a blend of ethanol and gasoline in any volumetric concentration of up to 85% ethanol (93% in Brazil). Existing FFVs rely on ethanol sensor installed in the vehicle fueling system, or on the ethanol-dependent air-to-fuel ratio (AFR) estimated via an exhaust gas oxygen (EGO) or λ sensor. The EGO-based ethanol detection is desirable from cost and maintenance perspectives but has been shown to be prone to large errors during mass air flow sensor drifts [1, 2]. Ethanol content estimation can be realized by a feedback-based fuel correction of the feedforward-based fuel calculation using an exhaust gas oxygen sensor. When the fuel correction is attributed to the difference in stoichiometric air-to-fuel ratio (AFR) between ethanol and gasoline, it can be used for ethanol estimation. When the fuel correction is attributed to a mass air flow (MAF) sensor error, it can be used for sensor drift estimation and correction. Deciding under which condition to blame (and detect) ethanol and when to switch to sensor correction burdens the calibration of FFV engine controllers. Moreover, erroneous decisions can lead to error accumulation in ethanol estimation and in MAF sensor correction. In this paper, we present a cylinder air flow estimation scheme that accounts for MAF sensor drift or bias using an intake manifold absolute pressure (MAP) sensor. The proposed fusion of the MAF, MAP and λ sensor measurements prevents severe mis-estimation of ethanol content in flex fuel vehicles.

Heated Zirconia Exhaust Gas Oxygen Sensor Having a Sheet-Shaped Sensing Element

1985 ◽  
Author(s):  
Noboru Higuchi ◽  
Shunzo Mase ◽  
Atsushi Iino ◽  
Nobuhide Kato
Keyword(s):  
Oxygen Sensor ◽  
Exhaust Gas ◽  
Sensing Element

Study of Heated Exhaust Gas Oxygen sensor downstream of the catalyst as an emissions calibration tool

2008 ◽  
Author(s):  
Eduardo Mizuho Miyashita ◽  
Manuel Dimitri Ruivo ◽  
Robson Higa
Keyword(s):  
Oxygen Sensor ◽  
Exhaust Gas ◽  
Calibration Tool

scholarly journals Universal Exhaust Gas Oxygen Sensor and Other Sensors for Engine Control

2004 ◽  
Vol 39 (11) ◽  
pp. 759-764
Author(s):  
Shigeru Miyata
Keyword(s):  
Oxygen Sensor ◽  
Exhaust Gas ◽  
Engine Control

Analysis of abnormal output of zirconia oxygen sensor in exhaust gas at low excess air ratio

1993 ◽  
Vol 14 (1-3) ◽  
pp. 501-503 ◽  
Author(s):  
Tatsuo Suemasu ◽  
Yohichi Kurumiya ◽  
Kohsei Ishibashi
Keyword(s):  
Oxygen Sensor ◽  
Exhaust Gas ◽  
Excess Air

Estimating IC engine exhaust gas lambda and oxygen from the response of a universal exhaust gas oxygen sensor

2013 ◽  
Vol 24 (9) ◽  
pp. 095101 ◽  
Author(s):  
N Collings ◽  
J A Harris ◽  
K Glover
Keyword(s):  
Oxygen Sensor ◽  
Exhaust Gas ◽  
Engine Exhaust ◽  
Ic Engine
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