Description:Field of the invention
[0001] The present disclosure relates to engine exhaust systems of an automobile, and more
particularly to a method and a system for diagnosing a catalytic convertor based on route
prediction.
Background of the invention
[0002] The Diagnosis of Three-Way Catalytic converter (OBD)in the Gasoline Exhaust system at
present is performed by observing the Oxygen Storage Capacity of the Catalyst. Higher the storing
capacity, better the catalyst. Low storage leads to error entry in diagnostic module which in turn
illuminates the Malfunction Indicator Lamp. The OSC for the catalyst is calculated by requesting
Rich and Lean lambda (Air to fuel ratio) multiple times in each driving cycle. This approach leads
to emission peaks, and increased fuel consumption. To overcome the active approach of requesting
Rich and Lean fuel multiple times, the OSC of the Catalyst can be calculated during Fuel Cut off
event (Over Run) when lean gas (O2 rich) is passed into the exhaust system. As the Fuel Cut off
happens several times in a driving cycle, diagnosis during fuel cut-off the saves fuel contrary to
the conventional approach, thereby giving away lesser emissions and improving the In-Use-
Monitor Performance Ratio (IUMPR) substantially.
[0003] The disclosure US2004159094 AA an engine exhaust system includes a catalytic convertor.
An inlet Sensor Senses a first oxygen level of exhaust gases entering the catalytic converter. An
outlet Sensor Senses a Second oxygen level of exhaust gases exiting the catalytic converter. A
controller communicates with a fuel System of an engine, the inlet Sensor, and the outlet Sensor.
The controller initiates a rich condition after a fuel cut-off period and calculates a mass of oxygen
released by the catalytic converter based on a mass air flow into the engine. In the disclosure, the
controller calculates a target oxygen storage capacity (OSC) of the catalytic converter over a target
time period. The OSC diagnostic of the present invention is executed during a fuel cut-off mode
of the engine. The fuel cut-off mode occurs in a vehicle overrun condition.
[0004] While performing the diagnosis of fuel cut-off, the already stored oxygen is not accounted
for the Oxygen Storage capacity measurement leading to erroneous diagnosis. Therefore, there is
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a need to flush the Oxygen stored in the catalyst (preconditioning) to yield accurate Oxygen
Storage Capacity (OSC) measurement during the vehicle overrun phase.
SUMMARY OF THE INVENTION
[0005] The present disclosure relates to engine exhaust systems of an automobile, and more
particularly to a method and a system for diagnosing a catalytic convertor based on route
prediction.
[0006] An object of the disclosure is to furnish a method that enables the diagnoses of a catalytic
converter in an automobile during a fuel cut off condition.
A further object of the invention is to furnish a corresponding system for carrying out the method.
[0007] The object of the disclosure relating to the system can be achieved in that the system
comprises of a control module for an engine exhaust system capable of diagnosing a catalytic
converter in a fuel-cut off condition, the said control module for an engine exhaust system
configured to- communicate with a predictive enabler structure or a predictive logic memory;
communicate with the fuel system of an engine to request rich gas for preconditioning the catalytic
converter at a time before the predicted fuel-cut off condition; and measure oxygen storage
capacity (OSC) during the fuel cut off. The event of fuel cut off the diagnosis of catalyst is
completed after the downstream sensor recognizes Lean lambda.
[0008] Optionally, the occurrence of fuel cut off is predicted by a predictive algorithm designed
based on the predicted vehicle data provided by a predictive enabler structure.
[0009] Optionally, the occurrence of fuel cut off is predicted by storing regular routes in a
predictive logic memory and the occurrence of fuel cut-off event in the said routes are learnt.
[0010] The object of the invention related to the method that enables the diagnoses of a catalytic
converter in an automobile during a fuel cut off condition is achieved with the said method
comprising the steps of preconditioning the catalytic converter by removing defined amount of
oxygen at a time before the predicted Fuel cut off condition; and diagnosing the catalytic converter
by measuring oxygen storage capacity during the fuel cut off condition. The preconditioning of
the catalytic converter is done at a predetermined time before the predicted fuel-cut off condition
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by requesting a rich gas to flush a predefined amount of oxygen from the catalytic converter. The
diagnosis of catalytic converter is done by measuring oxygen storage capacity (OSC) using a
lambda sensor positioned downstream of the catalytic converter.
[0011] Optionally, the prediction of a fuel-cut off condition is done based on the vehicle data
including torque, velocity, power and slope measured taking inputs from the sensors.
[0012] Optionally, the prediction of a fuel-cut off condition is done based on a stored fuel cut-off
information for a learnt route.
BRIEF DESCRIPTION OF DRAWINGS
[0013] The features and advantages of the present disclosure would become more apparent when
read in consonance with the following description of the exemplified embodiments of the
disclosure with reference to the accompanying drawings in which:
[0014] Fig 1 is a schematic diagram of a system that may be used to implement the method of
diagnosing a catalytic converter in an automobile.
[0015] Fig 2 shows a flow diagram of the disclosed method of diagnosing a catalytic converter in
an automobile.
DETAILED DESCRIPTION OF THE DRAWINGS
[0016] The present invention will now be described by way of example, with reference to
accompanying drawings. Throughout all the figures, same or corresponding elements may
generally be indicated by same reference numerals. These depicted embodiments are to be
understood as illustrative of the invention and not as limiting in any way. It should also be
understood that the figures are not necessarily to scale and that the embodiments are sometimes
illustrated by graphic symbols, phantom lines, diagrammatic representations and fragmentary
views. In predetermined instances, details which are not necessary for an understanding of the
present invention, or which render other details difficult to perceive may have been omitted.
[0017] Fig 1 is a schematic diagram of a system that may be used to implement the method of
diagnosing a catalytic converter 2 in an automobile wherein a control module 5 for an engine
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exhaust system 10 capable of diagnosing a catalytic converter 2 in a fuel-cut off condition, the said
control module 5 for an engine exhaust system configured to:
-communicate with a predictive enabler structure 8 or a predictive logic memory unit 9;
-communicate with a fuel system 7 of an engine to request rich gas for preconditioning the catalytic
converter 2 at a time before the predicted fuel-cut off condition; and
-Measure oxygen storage capacity (OSC) during the fuel cut off.
The occurrence of fuel cut off is predicted by a predictive algorithm designed based on the
predicted vehicle data provided by the predictive enabler structure 8 or the occurrence of fuel cut
off is predicted by storing regular routes in the predictive logic memory unit 9 and the occurrence
of fuel cut-off event in the said routes are learnt. In the event of fuel cut off the diagnosis of catalyst
is completed after at least one downstream lambda oxygen sensor 3 recognizes Lean lambda.
[0018] The engine exhaust system 10 comprises of at least one lambda oxygen sensor 1 , the
primary catalytic convertor 2, at least one downstream lambda oxygen sensor 3 and a main
catalytic converter 4. The control module 5 is configured to communicate with either the predictive
enabler structure 8 or the predictive logic memory unit 9 in order to predict a fuel cut-off condition.
The control module 5 is also in communication with the fuel system 7 of an engine control unit in
order to request rich gas for preconditioning (flushing away the stored oxygen) the catalytic
converter at a time before the predicted fuel-cut off condition and perform diagnosis.
[0019] The ‘lambda’ (or air to fuel ratio) can be either rich or lean. When a mixture contains
exactly the amount of oxygen required to burn the amount of fuel present, the ratio will be one to
one and lambda will equal 1.00. For a mixture that contains too much oxygen for fuel, i.e a lean
mixture, lambda will be greater than 1.00. For a mixture that contains too little oxygen for the
amount of fuel, i.e a rich mixture, lambda will be less than 1.00. The lambda oxygen sensor 1
measures the oxygen levels in exhaust gases entering the exhaust system. The primary catalytic
convertor 2 (to be diagnosed) performs catalysis of redox reactions in order to reduce the toxicity
from the exhaust gas released by the internal combustion engine. The downstream lambda oxygen
sensor 3 measures the oxygen slip (excess oxygen after the maximum threshold point to store
oxygen over the catalyst has reached) once sufficient oxygen accumulates over the catalyst.
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[0020] The Control module 5 may include conventional processing apparatus known in the art,
capable of executing pre-programmed instructions stored in an associated memory, all performing
in accordance with the functionality described herein. That is, it is contemplated that the processes
described herein will be programmed in a preferred embodiment, with the resulting Software code
being stored in the associated memory of the control module. Implementation of the present
disclosure, in view of the foregoing enabling description, would require no more than routine
application of programming skills by one of ordinary skill in the art. Such a Control module may
further be of the type having both ROM, RAM, a combination of non-volatile and volatile
(modifiable) memory so that the software can be stored and yet allow storage and processing of
dynamically produced data and/or signals.
[0021] The Predictive enabler structure 8 can be provided as an embedded software within the
control module 5 , the said Predictive enabler structure (PES) will encapsulate functionalities to
receive data regarding the route and the topology which can be transferred using a suitable
protocol, for example via ADASIS. It can further combine the predictive data with surround-sensor
inputs and rework and process the data to provide predictive information to predictive functions.
Thus, the Predictive enabler structure 8 provides the route information and predicts vehicle data
such as slope, velocity, power, torque etc.. From such data, a predictive algorithm can be designed
to find the occurrence of fuel cut off in the given route.
[0022] Optionally, the control module 5 can be configured to be in communication with the
predictive logic memory unit 9. This predictive logic memory unit 9 with an associated software
component can be present in an electronic system, residing within or outside the control module
5, where with the GPS coordinates-based route learning and prediction algorithm, the overrun
state of the vehicle can be learnt on a given route and same can be used to predict fuel cut off
occurrence.
[0023] Predictive logic memory unit 9 can characterize and store the regular routes taken by the
user of the vehicle. The occurrence of Fuel Cut off events in those routes are learnt along with
other vehicle data. Every suitable route segment of learnt route is assigned with prediction
probability, i.e. the probability of Overrun scenario and possible completion of diagnosis in the
route segment. During the next travel, the predictive logic memory unit 9 recognizes that the route
taken by driver is predicted to be one of learnt route pattern. The route segments information-- the
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point where the Fuel cut off will occur with sufficient time for diagnosis- is communicated to the
control module 5 which initiates the preconditioning of the catalyst. During the fuel cut off, oxygen
accumulates in the catalyst to its maximum storage capacity, a lean (oxygen rich) breakthrough
occurs and oxygen slip is sensed by the downstream lambda oxygen sensor 3.
[0024] Fig 2 shows a flow diagram of the disclosed method -
A method of diagnosing a catalytic converter in an automobile, the method comprising steps of:
-Predicting 11 a fuel cut off condition
-Preconditioning 12 the catalytic converter by removing defined amount of oxygen at a time
before the predicted Fuel cut off condition; and
-Diagnoses 13 of the catalytic converter by measuring oxygen storage capacity during the fuel
cut off.
The prediction of the fuel-cut off condition is done based on the vehicle data taking inputs from
the sensors (Predictive enabler structure approach 11a). The prediction 11 of the fuel-cut off
condition is done based on a stored fuel cut-off information for a learnt route (route learning11b).
The preconditioning 12 of the catalytic converter is done at a predetermined time before the
predicted fuel-cut off condition by requesting a rich gas to flush a predefined amount of oxygen
from the catalytic converter. The diagnosis 13 of catalytic converter is done by measuring oxygen
storage capacity (OSC) using the lambda sensor positioned downstream of the catalytic converter.
[0025] The steps involved include the first prediction of the fuel cut off condition 11 either by
obtaining the route information from the predictive enabler structure approach 11a or by route
learning 11b.
[0026] In the predictive enabler structure approach 11a the route information is provided and
predicted on the basis of vehicle data such as slope, velocity, power, torque etc.. From such data,
a predictive algorithm can be designed to find the occurrence of fuel cut off in the given route.
[0027] In the route learning approach 11b, with the GPS coordinates-based route learning and
prediction algorithm, the overrun state of the vehicle can be learnt on a given route and same can
be used to predict fuel cut off occurrence. The regular routes taken by the user of the vehicle are
characterized and stored. The occurrence of Fuel Cut off events in those routes are learnt along
with other vehicle data. Every suitable route segment of learnt route is assigned with prediction
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probability, i.e. the probability of Overrun scenario and possible completion of diagnosis in the
route segment. During the next travel, the predictive logic memory unit (as described in Fig 1)
recognizes that the route taken by driver is predicted to be one of learnt route pattern.
[0028] Once the fuel cut off condition (with sufficient time to diagnose the catalyst) is predicted
11 the same is communicated to the control module (as described in Fig 1) which requests rich
lambda from the fuel system at a time before the predicted fuel cut off to complete the step of
preconditioning 12 which is to essentially flush out a defined amount of oxygen stored in the
catalyst.
[0029] This is followed by the step of diagnosis 13 of the catalyst wherein the diagnosis of
catalytic converter is done by measuring oxygen storage capacity (OSC) using the lambda sensor
positioned downstream (downstream lambda oxygen sensor as described in Fig 1) of the catalytic
converter. By knowing the approximate level of O2 in the catalyst, the amount of Oxygen level
which needs to be decreased for catalyst diagnosis can be calculated. The disclosed method can be
extended to sensors as well for other exhaust components.
[0030] The disclosure advantageously provides accurate Oxygen Storage Capacity (OSC)
measurement during the vehicle overrun phase and reduces the emissions during diagnosis when
compared to the existing method. Further, the disclosure advantageously saves fuel due to
execution of partially active & partially passive diagnosis in addition to improvement of In Use
Monitoring Performance Ratio (catalyst monitoring). , C , Claims:we claim:
1. A method of diagnosing a catalytic converter in an automobile, the method comprising
steps of:
-Predicting 11 a fuel cut off condition
-Preconditioning 12 the catalytic converter by removing defined amount of oxygen at a
time before the predicted Fuel cut off condition; and
-Diagnoses 13 of the catalytic converter by measuring oxygen storage capacity during the
fuel cut off.
2. The method of diagnosing a catalytic converter in an automobile as claimed in claim 1,
wherein the prediction of a fuel-cut off condition is done based on the vehicle data taking
inputs from the sensors by the predictive enabler structure approach 11a .
3. The method of diagnosing a catalytic converter in an automobile as claimed in claim 1,
wherein the prediction of a fuel-cut off condition is done based on a stored fuel cut-off
information for a learnt route by route learning 11b approach.
4. The method of diagnosing a catalytic converter in an automobile as claimed in claim 1,
wherein the preconditioning 12 of the catalytic converter is done at a predetermined time
before the predicted fuel-cut off condition by requesting a rich gas to flush a predefined
amount of oxygen from the catalytic converter.
5. The method of diagnosing a catalytic converter in an automobile as claimed in claim 1,
wherein the diagnosis 13 of catalytic converter is done by measuring oxygen storage
capacity (OSC) using a lambda sensor positioned downstream of the catalytic converter.
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6. A control module 5 for an engine exhaust system 10 capable of diagnosing a catalytic
converter 2 in a fuel-cut off condition, the said control module for an engine exhaust
system configured to:
-communicate with a predictive enabler structure 8 or a predictive logic memory unit 9;
-communicate with the fuel system 7 of an engine to request rich gas for preconditioning
the catalytic converter 2 at a time before the predicted fuel-cut off condition; and
-Measure oxygen storage capacity (OSC) during the fuel cut off.
7. The control module 5 for an engine exhaust system capable of diagnosing a catalytic
converter 2 in a fuel-cut off condition as claimed in claim 6, wherein the occurrence of fuel
cut off is predicted by a predictive algorithm designed based on the predicted vehicle data
provided by a predictive enabler structure 8.
8. The control module 5 for an engine exhaust system 10 capable of diagnosing a catalytic
converter 2 in a fuel-cut off condition as claimed in claim 6, wherein the occurrence of fuel
cut off is predicted by storing regular routes in a predictive logic memory unit 9 and the
occurrence of fuel cut-off event in the said routes are learnt.
9. The control module for an engine exhaust system capable of diagnosing a catalytic
converter in a fuel-cut off condition as claimed in claim 6, wherein in the event of fuel cut
off the diagnosis of catalyst is completed after at least one downstream lambda oxygen
sensor 3 recognizes Lean lambda.