Abstract:
A method of generating a metric data set for determining a performance of a catalytic converter includes sampling data from a post catalytic converter oxygen sensor to provide a raw data set and generating a revised data set based on the raw data set. Data within the revised data set is eliminated based on characteristics of data points of the revised data set and the revised data set is filtered to provide the metric data set.

Description:
FIELD OF THE INVENTION  
       [0001]     The present invention relates to diagnostic systems for vehicles, and more particularly to a method for diagnosing catalytic converter efficiency.  
       BACKGROUND OF THE INVENTION  
       [0002]     During the combustion process, gasoline is oxidized and hydrogen (H) and carbon (C) combine with air. Various chemical compounds are formed including carbon dioxide (CO 2 ), water (H 2 O), carbon monoxide (CO), nitrogen oxides (NO x ), unburned hydrocarbons (HC), sulfur oxides (SO x ), and other compounds. Automobile exhaust systems include a catalytic converter that reduces the levels of CO, HC, and NOx in the exhaust gas by chemically converting these gasses into carbon dioxide, nitrogen, and water. Diagnostic regulations require periodic monitoring of the catalytic converter for proper conversion capability.  
         [0003]     Typical monitoring methods employ two exhaust gas oxygen sensors and infer the conversion capability of the catalytic converter using the sensor signals. One sensor monitors the oxygen level associated with an inlet exhaust stream of the catalytic converter. This inlet O 2  sensor is also the primary feedback mechanism that maintains the fuel-to-air (F/A) ratio of the engine at the chemically correct, or stoichiometric F/A ratio needed to support the catalytic conversion processes. A second or outlet O 2  sensor monitors the oxygen level concentration of the exhaust stream exiting the catalytic converter.  
         [0004]     Traditional monitoring methods relate the empirical relationships that exist between the inlet and outlet O 2  sensor to quantify catalyst conversion capability. These methods compare sensor amplitude, response time, response rate, and/or frequency content data. All of these measurements are affected by a property of a catalytic converter known as Oxygen Storage Capacity (OSC). OSC refers to the ability of a catalytic converter to store excess oxygen under lean conditions and to release oxygen under rich conditions. The amount of oxygen storage and release decreases as the conversion capability of the catalytic converter is reduced. Therefore, the loss in OSC is related to the loss in conversion capability.  
         [0005]     Traditional methods for diagnosing catalytic converter performance based on OSC are intrusive. More specifically, traditional diagnostic methods manipulate the F/A ratio and monitor the resultant sensor signal.  
       SUMMARY OF THE INVENTION  
       [0006]     Accordingly, the present invention provides a method of generating a metric data set for determining the performance of a catalytic converter. The method includes sampling data from a post catalytic converter oxygen sensor to provide a raw data set and generating a revised data set based on the raw data set. Data within the revised data set is eliminated based on characteristics of data points of the revised data set and the revised data set is filtered to provide the metric data set.  
         [0007]     In one feature, the step of generating the revised data set includes taking a derivative of data within the raw data set.  
         [0008]     In another feature, the step of eliminating data within the revised data set based on characteristics of data points of the revised data set includes eliminating a data point based on values of subsequent data points.  
         [0009]     In another feature, the step of eliminating data within the revised data set based on characteristics of data points of the revised data set includes eliminating a data point if said data point is greater than a maximum value.  
         [0010]     In another feature, the step of eliminating data within the revised data set based on characteristics of data points of the revised data set includes eliminating a data point if the data point is negative.  
         [0011]     In still other features, the method further includes eliminating data within the revised data set based on air flow data corresponding to the revised data set. The step of eliminating data within the revised data set based on air flow data corresponding to the revised data set includes eliminating data points that correspond to transient air flow. Alternatively, the step of eliminating data within the revised data set based on air flow data corresponding to the revised data set includes eliminating data points that correspond to air flows that exceed a maximum air flow value.  
         [0012]     In yet another feature, the step of filtering includes filtering the revised data set with a first order filter.  
         [0013]     Further areas of applicability of the present invention will become apparent from the detailed description provided hereinafter. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0014]     The present invention will become more fully understood from the detailed description and the accompanying drawings, wherein:  
         [0015]      FIG. 1  is a functional block diagram of a vehicle including a controller that performs a catalytic converter performance diagnostic according to the present invention;  
         [0016]      FIG. 2  is a graph illustrating exemplary outlet oxygen sensor signals associated with first and second exemplary catalytic converters;  
         [0017]      FIG. 3  is a graph illustrating first derivative data of the exemplary outlet oxygen sensor signals;  
         [0018]      FIG. 4  is a graph illustrating reduced first derivative data based on sample analysis according to the present invention;  
         [0019]      FIG. 5  is a graph illustrating air flow data and filtered air flow data that corresponds to the first derivative data of the exemplary outlet oxygen sensor signals;  
         [0020]      FIG. 6  is a graph illustrating reduced first derivative data based on transient air flow analysis according to the present invention;  
         [0021]      FIG. 7  is a graph illustrating limited first derivative data based on maximum positive and negative values according to the present invention;  
         [0022]      FIG. 8  is a graph illustrating positive first derivative data of the exemplary oxygen sensor signals;  
         [0023]      FIG. 9  is a graph illustrating reduced first derivative data based on corresponding high air flows according to the present invention;  
         [0024]      FIG. 10  is a graph illustrating filtered first derivative data that defines an OSC metric according to the present invention; and  
         [0025]      FIG. 11  is a flowchart detailing steps of the catalytic converter performance diagnostic according to the present invention.  
     
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS  
       [0026]     The following description of the preferred embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses. For purposes of clarity, the same reference numbers will be used in the drawings to identify similar elements.  
         [0027]     Referring now to  FIG. 1 , an exemplary vehicle  10  includes an engine  12 , an exhaust system  14  and a control module  16 . The engine  12  includes an intake manifold  17  and a throttle  18 . Air is drawn into the intake manifold  17  through the throttle  18  and is combusted within the engine  12  to produce drive torque. The combustion process also produces exhaust. The exhaust system  14  includes a catalytic converter  22 , a pre-catalyst or inlet oxygen sensor  24 , and a post-catalyst or outlet oxygen sensor  26 . The inlet and outlet oxygen sensors  24 ,  26  communicate with the control module  16  to provide inlet and outlet F/A ratio signals, respectfully. A mass air flow (MAF) sensor  27  communicates with the control module  16  to provide a MAF signal. The control module  16  communicates with a fuel system  28  to regulate fuel flow to the engine  12 . In this manner, the control module  16  regulates the F/A ratio of the engine  12 .  
         [0028]     The control module  16  processes the outlet oxygen sensor signal to determine catalytic converter performance according to the diagnostic of the present invention. More specifically, the control module  16  converts outlet oxygen sensor signal data into a unit-less metric or figure of merit that is used to indicate the oxygen storage capacity (OSC) of the catalytic converter  22 . The outlet oxygen sensor data can be collected upon initiating the catalytic converter performance diagnostic. Alternatively, the outlet oxygen sensor data can be continuously stored in a memory buffer and the catalytic converter performance diagnostic can be processed based on the historical data. As the OSC of the catalytic converter decreases, the figure of merit of the present invention correspondingly increases, as explained in further detail below. Therefore, the figure of merit can be compared to a threshold level that corresponds to an under-performing catalytic converter.  
         [0029]     Referring now to  FIGS. 2 through 10 , conversion of outlet oxygen sensor signal data for two exemplary catalytic converters into respective figures of merit will be described in detail. The first exemplary catalytic converter has experienced less drive cycles (i.e., is younger) than the second exemplary catalytic converter.  FIG. 2  is a graph illustrating the outlet oxygen sensor data for the exemplary catalytic converters, vehicle speed data and air flow data over a plurality of exemplary drive cycles. As illustrated, the signal data of the second exemplary catalytic converter is more erratic than the signal data of the first exemplary catalytic converter.  
         [0030]     Referring now to  FIG. 3 , the first derivative of the signal data of the exemplary catalytic converters taken. The first-derivative of the signal data corresponds to the rate of change of the signal data. The first derivative of the signal data for both exemplary catalytic converters is illustrated in  FIG. 3  over the corresponding vehicle speed and air flow data for the exemplary drive cycles. Because the signal data of the second exemplary catalytic converter is more erratic than that of the first catalytic converter, the first derivative of the signal data of the second exemplary catalytic converter is greater than that of the first catalytic converter in both the positive and negative directions.  
         [0031]     Referring now to  FIG. 4 , a slope analysis is performed to remove undesired portions of the first derivative data. More specifically, the slope analysis removes first derivative data that continuously slopes in one direction over a relatively long period of time (i.e., low frequency portions of the first derivative data). The slope analysis compares the sum of n data points to the sum of n+1 data points. If the sum of the n data points is greater than the sum of the n+1 data points, then data points  1  through n define a low frequency portion of the first derivative data. In this case, data point  1  is deleted and slope analysis continues until each of the data points has been correspondingly analyzed.  
         [0032]     Referring now to  FIGS. 5 and 6 , the first derivative data for each of the exemplary catalytic converters is further reduced based on a delta air flow analysis. More specifically, the air flow data is analyzed to determine periods transient air flow.  FIG. 5  provides a more detailed illustration of the air flow data for the exemplary drive cycles. The graph of  FIG. 5  also includes filtered air flow data that is generated using a first order filter. As can be seen, the filtered air flow data lags the non-filtered air flow data when the air flow data changes or is transient.  
         [0033]     The delta air flow analysis determines the difference between each non-filtered air flow data point and the corresponding filtered air flow data point. If the difference exceeds a threshold value, the particular air flow data point is deemed transient and the corresponding first derivative data points for each of the exemplary catalytic converters is removed. If the difference does not exceeds the threshold value, the particular air flow data point is not deemed transient and the corresponding first derivative data points for each of the exemplary catalytic converters remain.  FIG. 6  illustrates the first derivative data remaining after the delta air flow analysis has been performed for the exemplary drive cycles.  
         [0034]     Referring now to  FIGS. 7 and 8 , the first derivative data is limited by maximum values and negative values of the first derivative data are removed, respectively. More specifically, the first derivative data is limited in both the positive and negative directions by maximum values (e.g., 200 mV/s and −200 mWs) (see  FIG. 7 ). The negative values of the first derivative data are deleted (see  FIG. 8 ).  
         [0035]     Referring now to  FIG. 9 , the first derivative data is further reduced based on a maximum air flow analysis to eliminate high air flow affects. More specifically, each air flow data point is compared to a threshold value (e.g., 30 g/s). If an air flow data point exceeds the threshold value, the corresponding first derivative data is removed. If the air flow data point exceeds the threshold value, the corresponding first derivative data remains.  FIG. 9  illustrates the remaining first derivative data after the maximum air flow analysis has been performed.  
         [0036]     Referring now to  FIG. 10 , figure of merit data is provided by filtering the remaining first derivative data points using a first order filter. In this manner, a figure of merit data point is generated for each of the remaining first derivative data points. The figure of merit data set can be regarded as an OSC metric data set. More specifically, the figure of merit data set indicates the OSC of the catalytic converters. For example, the OSC metric data set of the first exemplary catalytic converter has lower values than that of the OSC metric data set of the second exemplary catalytic converter.  
         [0037]     The OSC metric data set of each catalytic converter can be compared to a threshold to determine whether the OSC of the particular catalytic converter is insufficient and the catalytic converter needs to be replace. The threshold can be constructed in various manners. In one manner, the average value of the OSC metric data points can be determined over a predefined period of time. If the average metric value exceeds a threshold value, the OSC of the catalytic converter is deemed insufficient. In another manner, a threshold level is provided. If the OSC metric data exceeds the threshold level a threshold number of times, the OSC of the catalytic converter is deemed insufficient.  
         [0038]     Referring now to  FIG. 11 , the steps performed by the catalytic converter performance diagnostic are summarized. In step  100 , control determines whether the diagnostic is to be initiated. The diagnostic is preferably initiated after the engine has been running for a period of time and the catalytic converter has been warmed to a desired operating temperature. The diagnostic can be initiated at any time during engine operation. If the diagnostic is to be initiated, control continues in step  102 . If the diagnostic is not to be initiated, control ends.  
         [0039]     In step  102 , control records outlet oxygen sensor data and air flow data. The data is recorded for a predetermined period of time to provide a outlet oxygen sensor signal data set and a corresponding air flow data set. In step  104 , control generates a first derivative data set by taking the first derivative of the outlet oxygen sensor signal data. Control eliminates select data points from the first derivative data set based on the slope analysis in step  106 .  
         [0040]     In step  108 , control eliminates select data points from the first derivative data set based on the transient air flow analysis. Control limits the maximum value of the first derivative data set in step  110 . In step  112 , control eliminates all of the negative data points from the first derivative data set. Control eliminates the first derivative data points that correspond to high air flow in step  114 . In step  116 , control filters the remaining first derivative data to provide an OSC metric data set. In step  118 , control determines whether the OSC metric data set exceeds the threshold. If the OSC metric data set does not exceed the threshold, control loops to step  100 . If the OSC metric data set does exceed the threshold, control initiates an alert in step  120  and loops to step  100 .  
         [0041]     Those skilled in the art can now appreciate from the foregoing description that the broad teachings of the present invention can be implemented in a variety of forms. Therefore, while this invention has been described in connection with particular examples thereof, the true scope of the invention should not be so limited since other modifications will become apparent to the skilled practitioner upon a study of the drawings, the specification and the following claims.