Internal-combustion engines – Charge forming device – Including exhaust gas condition responsive means
Reexamination Certificate
2002-11-08
2004-12-28
Gimie, Mahmoud (Department: 3747)
Internal-combustion engines
Charge forming device
Including exhaust gas condition responsive means
C123S479000, C701S109000
Reexamination Certificate
active
06834645
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates to a fuel supply control system for an internal combustion engine, and more particularly to a fuel supply control system in which an intake air flow rate of the internal combustion engine is detected by an intake air flow rate sensor, and an amount of fuel to be supplied to the engine is controlled according to the detected intake air flow rate.
A method of detecting an intake air flow rate of the internal combustion engine with a hotwire flow meter is conventionally known. The characteristic of the hotwire flow meter changes due to aging. Therefore, there is a problem of a detection error of the intake air flow rate increasing, if the hotwire flow meter is being used for a long time. To cope with this problem, a method of calculating a learning correction value according to changes in the characteristic of the hotwire flow meter is shown in Japanese Patent Laid-Open (Kokoku) Hei 7-23702.
According to this method, an air-fuel ratio negative feedback amount CFB is calculated according to an output of an air-fuel ratio sensor provided in an exhaust system of the internal combustion engine, so that the detected air-fuel ratio coincides with a target value. Further, a plurality of values CL1, CL2, and CL3 of the air-fuel ratio negative feedback amount CFB, which correspond respectively to a plurality of flow rate points QL1, QL2, and QL3, representative of the characteristic change in the hotwire flow meter, are stored in a memory. The learning correction value is calculated by means of the interpolation or extrapolation according to the data stored in the memory and the intake air flow rate Q detected by the hotwire flow meter.
In the method shown in Japanese Patent Laid-Open (Kokoku) Hei 7-23702, the values CL1, CL2, and CL3 of the air-fuel ratio negative feedback amount CFB corresponding to the predetermined flow rate points QL1, QL2, and QL3 are stored in the memory, and the stored data are used for calculation of the learning correction value. Accordingly, if the values CL1, CL2, and CL3 of the air-fuel ratio negative feedback amount CFB in the memory change due to a change in the engine operating condition, the learning correction value directly reflects the changes in the values CL1, CL2, and CL3, which results in a large variation in the learning correction value. In addition, according to this method, the characteristic change in the hotwire flow meter is monitored in the plurality of flow rate points QL1, QL2, and QL3. When increasing the number of the monitoring points in order to improve accuracy of the learning correction value, the memory capacity increases. Accordingly, from the view point of manufacturing costs, it is not preferable to greatly increase the number of the monitoring points.
The recent tightening of emission regulations (harmful gas emission) has highlighted that the deterioration or the characteristic change in parts of the engine or the engine control devices, causes an adverse effect on the exhaust characteristics of the engine. Therefore, it is desirable to obtain the learning correction coefficient with a higher degree of accuracy depending on the characteristic change in the intake air flow rate sensor.
A method of determining an abnormality or a deterioration in the intake air flow rate sensor is known from Japanese Patent Laid-Open (Kokoku) Hei 8-6623. In this method, the abnormality or the deterioration is detected based on the detected values of the air-fuel ratio sensor, the throttle valve opening sensor, and the engine rotational speed sensor.
According to this determining method of the characteristic deterioration (abnormality) of the intake air flow rate sensor, the determination is performed not with the statistically processed data of the sensor detected values, but with the sensor detected values themselves. Therefore, there is a problem of the determination accuracy becoming lower, when the frequency of the determination is increased.
BRIEF SUMMARY OF THE INVENTION
A first object of the present invention is to provide a fuel supply control system for an internal combustion engine, which can obtain an accurate learning correction value that compensates for an influence of the characteristic change in the intake air flow rate sensor, to thereby maintain good controllability of the air-fuel ratio control.
A second object of the present invention is to provide a fuel supply control system for an internal combustion engine, which can regularly monitor an operation of the intake air flow rate sensor to accurately determine an abnormality in the intake air flow rate sensor.
To achieve the first object, the present invention provides a fuel supply control system for an internal combustion engine, including intake air flow rate detecting means, basic fuel amount calculating means, an air-fuel ratio sensor provided in an exhaust system of the engine, air-fuel ratio correction coefficient calculating means, correlation parameter calculating means, learning means, and fuel amount control means. The intake air flow rate detecting means detects an intake air flow rate (QAIR) of the engine. The basic fuel amount calculating means calculates a basic fuel amount (TIM) supplied to the engine, according to the intake air flow rate (QAIR) detected by the intake air flow rate detecting means. The air-fuel ratio correction coefficient calculating means calculates an air-fuel ratio correction coefficient (KAF) for correcting an amount of fuel to be supplied to the engine so that the air-fuel ratio detected by the air-fuel ratio sensor coincides with a target air-fuel ratio. The correlation parameter calculating means calculates at least one correlation parameter vector (&thgr;1, &thgr;2) which defines a correlation between the air-fuel ratio correction coefficient (KAF) and the intake air flow rate (QAIR) detected by the intake air flow rate detecting means, using a sequential statistical processing algorithm. The learning means calculates a learning correction coefficient (KREFG) relating to a change in characteristics of the intake air flow rate detecting means, using the at least one correlation parameter vector (&thgr;1, &thgr;2). The fuel amount control means controls an amount (TOUT) of fuel to be supplied to the engine, using the basic fuel amount (TIM), the air-fuel ratio correction coefficient (KAF), and the learning correction coefficient (KREFG).
With this configuration, at least one correlation parameter vector which defines a correlation between the air-fuel correction coefficient, which corrects an amount of fuel supplied to the engine so that the air-fuel ratio coincides with the target air-fuel ratio, and the intake air flow rate detected by the intake air flow rate detecting means, can be calculated using the sequential statistical processing algorithm. Further, the learning correction coefficient relating to a change in characteristics of the intake air flow rate detecting means can be calculated using the at least one correlation parameter vector. The amount of fuel to be supplied to the engine is controlled using the air-fuel ratio correction coefficient, the learning correction coefficient, and the basic fuel amount, which can be set according to the intake air flow rate detected by the intake air flow rate detecting means. That is, at least one correlation parameter vector is calculated with the statistical processing based on many detected data, and the learning correction coefficient is calculated using the calculated correlation parameter vector. Therefore, it is possible to obtain the learning correction coefficient with a high degree of accuracy that corresponds to an averaged state of the ever-changing engine operating conditions. In addition, since the sequential statistical processing algorithm is used, no special computing device such as a CPU is required for statistical processing, and the computation for the statistical processing can be executed with a relatively small memory capacity.
Preferably, the fuel supply control system further includes abnormality determin
Takizawa Osamu
Yasui Yuji
Castro Arnold
Gimie Mahmoud
Honda Giken Kogyo Kabushiki Kaisha
Squire Sanders & Dempsey LLP
LandOfFree
Fuel supply control system for internal combustion engine does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Fuel supply control system for internal combustion engine, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Fuel supply control system for internal combustion engine will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3331279