JP2003148210A - Fuel supply control device for internal combustion engine - Google Patents

Abstract

PROBLEM TO BE SOLVED: To maintain the excellent control performance of an air-fuel ratio control, by obtaining a highly accurate learning correction value for compensating an effect of characteristic change of an intake air amount sensor. SOLUTION: A corelation parameter vector θ(k) which defines a corelation between an air-fuel ratio correction factor KAF calculated depending on an output of an air-fuel ratio sensor 14 and an intake air amount QAIR detected by the intake air amount sensor is calculated using a sequential statistics processing algorithm (S18). A learning correction factor KREFG relating to the characteristic change of the intake air amount sensor 19 is calculated using the corelation parameter vector θ(k) (S22), and a fuel injection time TOUT is calculated using the calculated learning correction factor (S25).

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a fuel for an internal combustion engine that detects the amount of air taken into the internal combustion engine by an intake air amount sensor and controls the amount of fuel supplied to the internal combustion engine according to the detected amount of intake air. The present invention relates to a supply control device.

[0002]

2. Description of the Related Art A method of detecting the intake air amount of an internal combustion engine using a hot wire anemometer has been conventionally known. Since the characteristics of the hot-wire anemometer change over time, there is a problem that the detection error of the intake air amount increases as the usage period increases. Therefore, Japanese Patent Publication No. 7-23702 discloses a method of calculating a learning correction value in accordance with a change in the characteristics of the intake air amount sensor.

According to this method, the air-fuel ratio negative feedback amount CFB is calculated so that the air-fuel ratio matches the target value in accordance with the output of the air-fuel ratio sensor provided in the exhaust system of the internal combustion engine, and the intake air amount sensor Multiple flow points QL that represent characteristic changes
1, QL2, QL3 air-fuel ratio feedback amount value CL1,
CL2 and CL3 are stored in the memory, and the learning correction value CL is calculated by interpolation calculation or extrapolation calculation based on the data stored in the memory and the intake air amount Q detected by the intake air amount sensor.

A method for detecting characteristic deterioration or abnormality of the intake air amount sensor based on the detected values of the air-fuel ratio sensor of the internal combustion engine, the throttle valve opening sensor and the engine speed sensor is also known in the prior art (special feature: Hei 8-6623).

[0005]

[Problems to be Solved by the Invention] Japanese Patent Publication No. 7-23702
In the method shown in No. 5, since the values CL1 to CL3 of the air-fuel ratio feedback amount CFB at the predetermined flow rate points QL1 to QL3 are stored in the memory and used to calculate the learning correction value CL,
If the value of the air-fuel ratio feedback amount stored in the memory fluctuates due to the change in the engine operating state, there is a problem that it is reflected as it is in the learning correction value CL. Further, in this method, the characteristic change is monitored at a plurality of flow rate points, but if the number is increased, the capacity of the memory increases, so that the number of flow rate points at which the characteristic change is monitored cannot be increased too much.

On the other hand, with the recent strengthening of emission (harmful gas emission) regulations, it is becoming more important that deterioration of components and characteristic changes adversely affect exhaust characteristics. It is desired to obtain a more accurate learning correction value in response to the characteristic change.

Further, the above-described characteristic deterioration determination method (abnormality determination method) of the intake air amount sensor is a determination using the sensor detection value as it is without performing statistical processing on the sensor detection value. However, when the judgment frequency is increased, there is a problem that the judgment accuracy is lowered.

The present invention has been made in consideration of the above points, and obtains a highly accurate learning correction value for compensating the influence of the characteristic change of the intake air amount sensor, and maintains good controllability of the air-fuel ratio control. It is a first object of the present invention to provide a fuel supply control device for an internal combustion engine that can achieve the above. Further, the present invention is
A second object of the present invention is to provide a fuel supply control device for an internal combustion engine that can constantly monitor the operation of the intake air amount sensor and improve the accuracy of abnormality determination.

[0009]

In order to achieve the above object, the invention according to claim 1 provides an intake air amount (QA) of an internal combustion engine.
IR) for detecting an intake air amount, and a basic fuel amount calculating device for calculating a basic fuel amount (TIM) to be supplied to the engine according to the intake air amount (QAIR) detected by the intake air amount detecting means. And an air-fuel ratio sensor provided in the exhaust system of the engine, and an air-fuel ratio correction coefficient for correcting the amount of fuel supplied to the engine so that the air-fuel ratio detected by the air-fuel ratio sensor matches the target air-fuel ratio ( Air-fuel ratio correction coefficient calculation means for calculating KAF), and the basic fuel amount (TIM)
And a fuel amount control means for controlling the fuel amount (TOUT) supplied to the engine by using the air-fuel ratio correction coefficient (KAF). A correlation parameter calculating means for calculating a correlation parameter (A, B) defining a correlation with the intake air amount (QAIR) detected by the intake air amount detecting means using a sequential statistical processing algorithm; Using the parameters (A, B), the learning correction coefficient (KRE) relating to the characteristic change of the intake air amount detecting means.
FG) learning means for calculating the basic fuel quantity (TIM) and the air-fuel ratio correction coefficient (K).
AF) and a learning correction coefficient (KREFG) are used to control the fuel amount.

According to this structure, the air-fuel ratio correction coefficient for correcting the amount of fuel supplied to the internal combustion engine so that the air-fuel ratio detected by the air-fuel ratio sensor matches the target air-fuel ratio, and the intake air amount detecting means detects the amount. The correlation parameter that defines the correlation with the intake air amount is calculated by using the sequential statistical processing algorithm, and the learning correction coefficient related to the characteristic change of the intake air amount detection means is calculated using the correlation parameter. . Then, the fuel amount supplied to the engine is controlled using the basic fuel amount calculated according to the intake air amount detected by the intake air amount detecting means, the air-fuel ratio correction coefficient, and the learning correction coefficient. That is, the correlation parameter is calculated by statistical processing based on a large amount of detection data, and the learning correction coefficient is calculated using the correlation parameter. Therefore, highly accurate learning correction corresponding to an average state of fluctuating engine operating states. The coefficient can be obtained. Further, by using the sequential statistical processing algorithm, it is possible to execute the statistical processing operation with a relatively small memory capacity without requiring a special arithmetic unit (CPU).

According to a second aspect of the present invention, in the fuel supply control device for the internal combustion engine according to the first aspect, abnormality determining means for determining abnormality of the intake air amount detecting means based on the correlation parameter (A). It is characterized by including. According to this configuration, since the abnormality of the intake air amount detecting means is determined based on the correlation parameter, the operation of the intake air amount detecting means is constantly monitored to increase the frequency of abnormality determination and improve the determination accuracy. You can

According to a third aspect of the present invention, in the fuel supply control device for an internal combustion engine according to the first or second aspect, the correlation parameter calculation means is configured to set the correlation parameter (when the engine is in a predetermined operating state). A) and B) are calculated. According to this configuration, the correlation parameter is calculated when the engine is in the predetermined operating state, so that the accuracy of the correlation parameter can be improved and the accuracy of the learning correction can be further improved.

The invention as defined in claim 4 is based on claims 1 to 3.
In the fuel supply control device for the internal combustion engine according to any one of items 1 to 5, the correlation parameter calculation means corrects the air-fuel ratio correction coefficient (KAF) with the learning correction coefficient (KREFG) to correct the air-fuel ratio correction coefficient (KAFMO).
D) is calculated, and instead of the air-fuel ratio correction coefficient (KAF), the corrected air-fuel ratio correction coefficient (KAFMOD) is used to calculate the correlation parameter (A, B).

According to this configuration, the corrected air-fuel ratio correction coefficient is calculated by correcting the air-fuel ratio correction coefficient with the learning correction coefficient, and the corrected air-fuel ratio correction coefficient is used instead of the air-fuel ratio correction coefficient. The correlation parameter is calculated. If the air-fuel ratio correction coefficient is used as it is, the learning control by the learning correction coefficient may be in the hunting state, but such a problem can be avoided by using the modified air-fuel ratio correction coefficient.

According to a fifth aspect of the present invention, an intake air amount detecting means for detecting the intake air amount (QAIR) of the internal combustion engine,
Intake air amount detected by the intake air amount detecting means (Q
Basic fuel amount (TI) to be supplied to the engine according to AIR
M) for calculating the basic fuel amount, an air-fuel ratio sensor provided in the exhaust system of the engine, and the air-fuel ratio detected by the air-fuel ratio sensor is supplied to the engine so as to match the target air-fuel ratio. Air-fuel ratio correction coefficient (KA
F), an air-fuel ratio correction coefficient calculation means, and a fuel quantity control means for controlling the fuel quantity (TOUT) supplied to the engine using the basic fuel quantity (TIM) and the air-fuel ratio correction coefficient (KAF). In a fuel supply control apparatus for an internal combustion engine, the air-fuel ratio correction coefficient (KAF) and the intake air amount (QAI) detected by the intake air amount detecting means (QAI).
R) Correlation parameters (A, B) that define the correlation with
Is provided by using a sequential statistical processing algorithm, and an abnormality determining means for determining an abnormality of the intake air amount detecting means based on the correlation parameter (A).

According to this structure, the air-fuel ratio correction coefficient for correcting the amount of fuel supplied to the internal combustion engine so that the air-fuel ratio detected by the air-fuel ratio sensor coincides with the target air-fuel ratio, and the intake air amount detecting means detects it. The correlation parameter that defines the correlation with the intake air amount is calculated by using the sequential statistical processing algorithm, and the abnormality of the intake air amount detection means is determined based on the correlation parameter. It is possible to constantly monitor the operation of the means and improve the accuracy of abnormality determination.

[0017]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a diagram showing a configuration of an internal combustion engine and a control system therefor according to an embodiment of the present invention. For example, a throttle valve 3 is arranged in the middle of an intake pipe 2 of a 4-cylinder engine 1. A throttle valve opening (THA) sensor 4 is connected to the throttle valve 3 and outputs an electric signal according to the opening of the throttle valve 3 to supply it to an electronic control unit (hereinafter referred to as “ECU”) 5. .

On the upstream side of the throttle valve 3 of the intake pipe 2,
An intake air amount sensor 19 for detecting the intake air amount QAIR is provided, and the output signal of the intake air amount sensor 19 is
It is supplied to the ECU 5. The fuel injection valve 6 is provided for each cylinder between the engine 1 and the throttle valve 3 and slightly upstream of the intake valve (not shown) in the intake pipe 2, and each injection valve is connected to a fuel pump (not shown). At the same time, it is electrically connected to the ECU 5 and the valve opening time of the fuel injection valve 6 is controlled by a signal from the ECU 5.

On the other hand, immediately downstream of the throttle valve 3, an intake pipe absolute pressure (PBA) sensor 7 for detecting the pressure in the intake pipe is provided, and the absolute pressure signal converted into an electric signal by the absolute pressure sensor 7 is provided. Is supplied to the ECU 5. Further, an intake air temperature (TA) sensor 8 is attached downstream thereof, detects the intake air temperature TA, outputs a corresponding electric signal, and supplies it to the ECU 5.

The engine water temperature (TW) sensor 9 mounted on the main body of the engine 1 is composed of a thermistor or the like, detects the engine water temperature (cooling water temperature) TW, outputs a corresponding temperature signal and supplies it to the ECU 5. The engine rotation speed (N
E) A sensor 10 and a cylinder discrimination (CYL) sensor 11 are attached. The engine speed sensor 10 outputs a TDC signal pulse at a crank angle position that is a predetermined crank angle before the top dead center (TDC) at the start of the intake stroke of each cylinder of the engine 1 (every 180 ° of crank angle in a 4-cylinder engine). The cylinder discrimination sensor 11 outputs a cylinder discrimination signal pulse at a predetermined crank angle position of a specific cylinder, and each of these signal pulses is supplied to the ECU 5.

The exhaust pipe 12 has NOx, HC, and
A three-way catalyst 16 for purifying CO is provided, and the three-way catalyst 1
6, the proportional air-fuel ratio sensor 14 (hereinafter referred to as “L
AF sensor 14 ”) is attached to this LA
The F sensor 14 outputs an electric signal substantially proportional to the oxygen concentration (air-fuel ratio) in the exhaust gas and supplies it to the ECU 5.

An exhaust gas recirculation passage 21 is provided between the intake pipe 2 on the downstream side of the throttle valve 3 and the exhaust pipe 12 on the upstream side of the three-way catalyst 16, and in the middle of the exhaust gas recirculation passage 21. Exhaust gas recirculation valve that controls the amount of exhaust gas recirculation (hereinafter referred to as "EGR valve")
22) is provided. The EGR valve 22 is a solenoid valve having a solenoid, and the valve opening degree thereof is controlled by the ECU 5. The EGR valve 22 is provided with a lift sensor 23 that detects the valve opening (valve lift amount) LACT, and the detection signal is supplied to the ECU 5. The exhaust gas recirculation passage 21 and the EGR valve 22 constitute an exhaust gas recirculation mechanism.

A canister 32 connected to a fuel tank (not shown) for storing evaporated fuel generated in the fuel tank
Is provided. The canister 32 contains an adsorbent that adsorbs evaporated fuel. The canister 32 is connected to the intake pipe 2 downstream of the throttle valve 3 via the purge passage 31. A purge control valve 33 is provided in the purge passage 31. The purge control valve 33 is an electromagnetic valve configured to continuously control the flow rate by changing the on-off duty ratio of the control signal, and the operation of the purge control valve 33 is controlled by the ECU 5. To be done. The purge control valve 33 may use an electromagnetic valve whose valve opening can be continuously changed, and the on-off duty ratio is the same as the valve opening continuously variable type solenoid valve. Corresponds to degrees. The purge passage 31, the canister 32, and the purge control valve 33 constitute an evaporated fuel processing device.

The ECU 5 is connected to an atmospheric pressure sensor 17 for detecting an atmospheric pressure PA and a vehicle speed sensor 18 for detecting a vehicle speed VP of a vehicle driven by the engine 1. The detection signals of these sensors are supplied to the ECU 5. To be done. EC
U5 shapes the input signal waveform from the sensor described above,
An input circuit having a function of correcting a voltage level to a predetermined level and converting an analog signal value into a digital signal value, a central processing unit (hereinafter referred to as "CPU"), a CPU
A storage circuit for storing various calculation programs and calculation results to be executed in 1. and an output circuit for supplying a drive signal to the fuel injection valve 6, the EGR valve 22 and the purge control valve 33.

The ECU 5 determines the engine operating state based on the output signal of the above-mentioned sensor, and determines the engine speed N.
EGR set according to E and the absolute pressure PBA in the intake pipe
A control signal is supplied to the solenoid of the EGR valve 22 so that the deviation between the valve opening command value LCMD of the valve 22 and the actual valve opening LACT detected by the lift sensor 23 becomes zero.

The CPU of the ECU 5 discriminates the engine operating state based on the output signal of the above-mentioned sensor, and operates in accordance with the engine operating state according to the following equation (1) to open the valve in synchronization with the TDC signal pulse. The fuel injection time TOUT of the fuel injection valve 6 is calculated. TOUT = TIM × KAF × KREFG × KPURGE × K1 + K2 (1) where TIM is the basic fuel injection time (basic fuel amount) of the fuel injection valve 6, and is set according to the engine speed NE and the intake air amount QAIR. It is determined by searching the TI map. The TI map is the engine speed NE on the map.
And in the operating state corresponding to the intake air amount QAIR,
The air-fuel ratio of the air-fuel mixture supplied to the engine is set to be approximately the stoichiometric air-fuel ratio.

KAF is an air-fuel ratio correction coefficient, and LAF
The air-fuel ratio detected by the sensor 14 is set to match the target air-fuel ratio. When feedback control according to the LAF sensor output is not executed, "1.0"
Is set to. The KREFG compensates for the deviation of the feedback control by the air-fuel ratio correction coefficient KAF when the detection characteristic of the intake air amount differs from the presumed average characteristic due to the characteristic variation of the intake air amount sensor 19 or the change over time. This is a learning correction coefficient introduced for this purpose.
A specific calculation method will be described later.

KPURGE is set to "1.0" when the purge control valve 33 is closed, and when the purge control valve 33 is opened to supply the evaporated fuel to the intake pipe 2, This is a purge correction coefficient that is set to a value smaller than "1.0" in order to reduce the fuel injection amount in response to the increase in the evaporated fuel supply amount.

K1 and K2 are other correction coefficients and correction variables calculated according to the engine operating state, respectively, so that various characteristics such as fuel consumption characteristics and engine acceleration characteristics according to the engine operating state can be optimized. To a predetermined value. The CPU of the ECU 5 supplies the drive signal for opening the fuel injection valve 6 to the fuel injection valve 6 based on the fuel injection time TOUT obtained as described above.

In this embodiment, a new calculation method of the learning correction coefficient KREFG applied to the equation (1) is adopted. The calculation method will be described below. Intake air amount sensor 1
When 9 is normal (not deteriorated), the relationship between the detected intake air amount QAIR and the air-fuel ratio correction coefficient KAF is as shown in FIG. In FIG. 2, the air-fuel ratio correction coefficient KA corresponding to the intake air amount QAIR on the horizontal axis.
The range of the value of F is shown by the hatched region, and even if the intake air amount QAIR changes, the air-fuel ratio correction coefficient KAF maintains a substantially constant value near “1.0”. The intake air amount QAIR shown in the figure is not the actual intake air amount but the intake air amount detected by the intake air amount sensor 19. To distinguish this from the actual intake air amount,
IRA ”.

However, when the intake air amount sensor 19 deteriorates (for example, dust adheres to the heat ray in the hot wire type sensor), the error between the detected intake air amount QAIR and the actual intake air amount QAIRA increases, and the air-fuel ratio increases. Changes in the rich direction or lean direction from the target value, and the air-fuel ratio correction coefficient KAF decreases or increases to correct it. Here, if the detection error is defined as ERR = QAIRA−QAIR, as the intake air amount sensor 19 deteriorates, the actual intake air amount Q
In the range where AIRA is small, the detection error ERR becomes negative (the detected intake air amount QAIR is equal to the actual intake air amount QAI).
When the actual intake air amount QAIRA is large, the detection error ERR tends to be positive (the detected intake air amount QAIR is smaller than the actual intake air amount QAIRA). As a result, the intake air amount QAI
The correlation characteristic between R and the air-fuel ratio correction coefficient KAF becomes a characteristic that rises to the right as shown in FIG. That is, the actual intake air amount Q
In the range where AIRA is small, the detected intake air amount QAIR becomes larger than the actual intake air amount QAIRA, and the basic fuel injection time TIM becomes larger than the optimum value. Therefore, the air-fuel ratio correction coefficient KAF is "1.0" to correct this. Although it becomes smaller, in the range where the actual intake air amount QAIRA is large, the detected intake air amount QAIR becomes smaller than the actual intake air amount QAIRA, and the basic fuel injection time TIM becomes smaller than the optimum value. Therefore, to correct this, the air-fuel ratio The correction coefficient KAF is "1.
It becomes larger than "0". However, depending on the deterioration mode,
There is a possibility that the correlation characteristic between the intake air amount QAIR and the air-fuel ratio correction coefficient KAF may be a characteristic that is lowering to the right, contrary to FIG.

Intake air amount QAIR and air-fuel ratio correction coefficient KA
The correlation characteristic of F is determined by the intake air amount sensor 19 as described above.
Of the basic fuel injection time TIM due to the characteristic variation of the intake air amount sensor 19 is also reflected. Therefore, by calculating the learning correction coefficient based on this correlation characteristic and applying it to the equation (1), not only the deterioration of the intake air amount sensor 19 but also the influence of the characteristic variation of the intake air amount sensor 19 is compensated. You can

In the present embodiment, paying attention to the above points, the intake air amount sensor 19 is abnormal (the degree of deterioration is advanced) based on the correlation characteristic between the detected intake air amount QAIR and the air-fuel ratio correction coefficient KAF. Was decided. Further, the learning correction coefficient KREFG is calculated based on the correlation characteristics of the air-fuel ratio influence parameter QAIR and the air-fuel ratio correction coefficient KAF,
The air-fuel ratio is appropriately corrected according to the degree of deterioration that is not determined to be abnormal, and the influence of the characteristic variation of the intake air amount sensor 19 is compensated.

The correlation characteristic shown in FIG. 3 can be expressed by an approximate expression corresponding to the straight line LST as shown in FIG. That is, it can be defined by the following formula (2). KAF (k) = A × QAIR (kd) + B (2) Here, A and B are correlation parameters that are calculated by the method of least squares and define correlation characteristics. More specifically, as shown in FIG. 4, A corresponds to the slope of the straight line LST, and B corresponds to the air-fuel ratio correction coefficient KAF when the detected intake air amount QAIR is 0. Further, k is a time discretized in the control cycle, and d is a dead time until the influence of the change in the detected intake air amount QIR is reflected in the air-fuel ratio correction coefficient KAF.

Generally, in order to calculate the highly reliable correlation parameters A and B by the least squares method, a large amount of data of the detected intake air amount QAIR (k) and the air-fuel ratio correction coefficient KAF (k) is required. Therefore, it is necessary to store a large amount of data in the memory for calculating the correlation parameter.

Further, in order to execute the least squares method, an inverse matrix calculation is required, and the calculation time of the CPU for engine control becomes long, so that the vehicle is running (the engine is operating).
However, there are problems that the calculation cannot be completed and that calculation for other engine control cannot be executed. In order to avoid such a problem, it is conceivable to provide a dedicated CPU for the inverse matrix calculation, but the cost will increase significantly.

Therefore, in this embodiment, the sequential identification algorithm used for adaptive control or system identification is applied to the calculation of the correlation parameters A and B. The sequential identification type algorithm is an algorithm that uses a recurrence formula.
More specifically, the sequential identification algorithm uses the current value (latest value) QAIR of the processing target data obtained in time series.
(k) and KAF (k) and the previous value A (k-
1), B (k-1) and the current value A of the correlation parameter
This is an algorithm for calculating (k) and B (k).

When the correlation parameter vector θ (k) having the correlation parameters A and B as elements is defined by the following equation (3),
According to the recursive identification algorithm, the correlation parameter vector θ (k) is calculated by the following equation (4). θ (k) ^T = [A (k) B (k)] (3) θ (k) = θ (k-1) + KP (k) × eid (k) (4) eid (k in equation (4) ) Is an identification error defined by the following equations (5) and (6). KP (k) is a gain coefficient vector defined by the following equation (7), and P (k) in the equation (7) is a quadratic square matrix calculated by the following equation (8). eid (k) = KAF (k ) -θ (k-1) T ζ (k) (5) ζ T (k) = [QAIR (kd) 1] (6)

[Equation 1]

By setting the coefficients λ1 and λ2 of the equation (8),
The identification algorithm according to Expressions (4) to (8) is one of the following four identification algorithms. λ1 = 1, λ2 = 0 Fixed gain algorithm λ1 = 1, λ2 = 1 Least square method algorithm λ1 = 1, λ2 = λ Gradual gain algorithm (λ is a predetermined value other than 0 and 1) λ1 = λ, λ2 = 1 Weight With least squares algorithm (λ is a predetermined value other than 0 and 1)

In the present embodiment, the weighted least squares algorithm in which the coefficient λ1 is set to a predetermined value λ between 0 and 1 and the coefficient λ2 is set to 1 is adopted, but other algorithms are adopted. May be. Suitable for statistical processing are the least squares algorithm and the weighted least squares algorithm.

According to the recursive identification algorithm of equations (4) to (8), the inverse matrix operation required in the operation of the batch operation type least squares method described above is unnecessary, and the value to be stored in the memory is Only A (k), B (k), and P (k) (matrix with 2 columns and 2 rows). Therefore, by using the recursive weighted least squares method, the statistical processing operation can be simplified,
CPU for engine control without using a special CPU
Can be calculated by

Further, in the recursive weighted least squares method, a more accurate correlation parameter can be calculated by setting the variation center of the parameter (ζ, KAF) relating to the calculation of the identification error eid to “0”. . Therefore, in the present embodiment, the identification error eid (k) is calculated by the following equation (5a) instead of the equation (5). eid (k) = (KAF (k) −1) −θ (k−1) ^T ζ (k) (5a)

By using the equation (5a), the calculation for obtaining the straight line LST in FIG. 4 is converted into the calculation for obtaining the straight line LSTa in FIG. 5, and the variation center of the parameter (KAF (k) -1) is "0". Therefore, a more accurate correlation parameter can be obtained.

Further, in this embodiment, the correlation parameter A
The values of (k) and B (k) are expressed by the following equations (9) and (1), respectively.
By limiting so as to satisfy 0), more stable calculation of the correlation parameter can be performed. AL <A (k) <AH (9) BL <B (k) <BH (10) Here, AL and AH are the lower limit value and the upper limit value of the correlation parameter A (k). BL and BH are the lower limit value and the upper limit value of the correlation parameter B (k).

Next, the abnormality determination of the intake air amount sensor 19 using the correlation parameter will be described. As described above, when the intake air amount sensor 19 is normal, the
Although the correlation characteristic as shown in (a) is obtained, if an abnormality occurs that has a large degree of deterioration due to adhesion of dust,
The correlation characteristic is as shown in FIG. That is, the slope A of the straight line LST0 changes and the straight line LST0 changes to the straight line LS.
Change to T1. Therefore, the absolute value of the correlation parameter A (k) calculated by the method described above is determined by the determination threshold XQ.
When it is smaller than XNG (| A (k) | <XQXNG),
When it is determined that the intake air amount sensor 19 is normal and is equal to or greater than the determination threshold value XQXNG (| A (k) | ≧ XQXN
G), the intake air amount sensor 19 is determined to be abnormal. The judgment threshold value XQXNG is set to an appropriate value by an experiment.

Next, a method of calculating the learning correction coefficient KREFG will be described. The equation representing the straight line LSTa shown in FIG. 5 is as the following equation (11). KAF-1 = A (k) × QAIR + B (k) (11) By modifying this, the following formula (12) is obtained. KAF = A (k) × QAIR + B (k) +1 (12) In this equation (12), the correlation parameters A (k) and B (k) are
Since it is calculated by the weighted least squares method, the correlation between the detected intake air amount QAIR and the air-fuel ratio correction coefficient KAF obtained by statistical processing is shown. Therefore, when the detected intake air amount QAIR is given, the statistically predicted air-fuel ratio correction coefficient KAFE is given by the equation (12).
It is calculated by the right side of. Therefore, assuming that the predicted air-fuel ratio correction coefficient KAFE is the learning correction coefficient KREFG, the learning correction coefficient KREFG is calculated by the following equation (12a). KREFG = A (k) × QAIR (k) + B (k) +1 (12a)

By applying this learning correction coefficient KREFG to the equation (1) and using it for calculating the fuel injection time TOUT, compensation by the air-fuel ratio correction coefficient KAF becomes unnecessary even when the intake air amount sensor 19 deteriorates. The air-fuel ratio correction coefficient KAF is maintained at a value near "1.0" as in the normal state. That is, it is possible to prevent the control center of the air-fuel ratio feedback control from deviating.

However, when the learning correction coefficient KREFG calculated by the equation (12a) is applied to the equation (1), the following control hunting occurs. 1) The slope of the straight line LST increases from 0 to a larger value (increase of the correlation parameter A (k)) → 2) The learning correction coefficient KREFG increases from 1.0 → 3) decrease of the correlation parameter A (k) (0 → 4) The learning correction coefficient KREFG returns to 1.0 (the slope of the straight line LST returns to 0) → 1) The slope of the straight line LST increases from 0 to a larger value (increase of the correlation parameter A (k) )

Therefore, in order to prevent this hunting,
When calculating the correlation parameters A (k) and B (k), the air-fuel ratio correction coefficient KAF is not used as it is, but the following equation (1)
3) Corrected air-fuel ratio correction coefficient KAFMOD
We decided to use (k). KAFMOD (k) = KAF (k) × KREFG (kd) (13) Equation (13) shows that the change in the air-fuel ratio on the intake side due to the increase in the learning correction coefficient KREFG causes the air-fuel ratio correction coefficient KAF via the LAF sensor 14. This is a consideration of the dead time d until it is reflected in.

Then, instead of the equation (11), the following equation (1
As shown in 1a), the parameter (KAFMOD-1)
And the correlation parameters A (k) and B (k) showing the correlation with the detected intake air amount QAIR are obtained by the above-mentioned recursive least squares method. That is, the straight line LS as shown in FIG.
Correlation parameters A (k) and B (k) that define T are obtained. KAFMOD-1 = A (k) × QAIR + B (k) (11a)

In this case, the identification error eid (k) is calculated by using the following equation (5b) instead of the equation (5a),
The correlation parameter vector θ (k) is calculated by using the equations (4) and (6) to (8) together with the equation (5b). eid (k) = (KAFMOD (k) −1) −θ (k−1) ^T ζ (k) (5b)

In this way, first, the correlation parameters A (k) and B (k) showing the correlation characteristics between the detected intake air amount QAIR and the parameter (KAFMOD-1) are calculated, and then the learning correction coefficient is calculated by the following equation (12a). Ask for KREFG. KREFG = A (k) × QAIR + B (k) +1 (12a)

This makes it possible to obtain a highly accurate learning correction coefficient KREFG while preventing control hunting. By applying the learning correction coefficient KREFG to the equation (1), it is possible to improve the control accuracy of the air-fuel ratio and maintain good exhaust characteristics.

FIG. 8 is a flow chart of a process of calculating the correlation parameters A (k) and B (k) by the above-described method, calculating the learning correction coefficient KREFG, and using this to calculate the fuel injection time TOUT. . Further, in this process, the abnormality determination of the intake air amount sensor 19 is performed based on the correlation parameter A (k). The process of FIG. 8 is executed by the CPU of the ECU 5 in synchronization with the generation of the TDC signal pulse.

In step S1, it is determined whether the engine 1 has been started. If not,
A TIS map set in accordance with the intake pipe absolute pressure PBA and the engine speed NE is searched to calculate a basic fuel amount TIS for starting (step S2). Next, the correction coefficient K1S for starting and the correction variable K2S are calculated (step S
3) Then, the fuel injection time TOUTS at the time of starting is calculated by the following formula (step S4), and this processing is ended. TOUTS = TIS × K1S + K2S

When the engine 1 has been started,
From step S1 to step S13, the intake air amount QAIR (k) detected by the intake air amount sensor 19 is read.

In step S14, the vehicle speed filtering value Vflt (k) is calculated by subjecting the detected vehicle speed VP to low-pass filtering according to the following equation (15). Vflt (k) = af1Vflt (k) + ... + afnVflt (kn) + bf0Vflt (k) + ... + bfmVflt (km) It is a predetermined low-pass filter coefficient.

In the following step S15, the absolute value of the difference between the current value Vflt (k) and the previous value Vflt (k-1) of the vehicle speed filtering value is the predetermined vehicle speed change amount XDVLM (for example, 0.
8 km / h), and if the answer is negative (NO), the process proceeds to step S22. If the answer to step S15 is affirmative (YES), the engine speed NE is the predetermined upper limit value XNEH (for example, 4000 rp).
m) and a predetermined lower limit value XNEL (for example, 400 rpm) are determined (step S16). When the answer is negative (NO), the routine proceeds to step S22, and when the answer at step S16 is affirmative (YES), the intake pipe absolute pressure PBA is a predetermined upper limit value XPBH (for example, 88 kPa) and a predetermined lower limit value XPBL. (For example, 28
kPa) is determined (step S)
17). If the answer is negative (NO), step S
22. If the determination is affirmative (YES), the correlation parameter vector θ (k) (correlation parameter A is calculated by the above equations (4), (5b), (6) to (8) and (11a).
(k) and B (k)) are calculated.

In the following step S19, it is determined whether or not the absolute value of the correlation parameter A (k) is greater than or equal to the determination threshold value XQXNG. If | A (k) | <XQXNG, the process immediately proceeds to step S21. When | A (k) | ≧ XQXNG, it is determined that the intake air amount sensor 19 is abnormal (step S20). In that case, the warning lamp is turned on to warn the driver of the vehicle.

In step S21, the correlation parameter A
The limiting process is performed so that (k) and B (k) satisfy the conditions of Expressions (9) and (10), respectively. That is, equation (9)
And / or when the condition of (10) is not satisfied, the values of the correlation parameters A (k) and / or B (k) are corrected so as to satisfy the conditions of Expressions (9) and / or (10).

In step S22, the above equation (12)
The learning correction coefficient KREFG is calculated according to a). In step S23, the air-fuel ratio correction coefficient KAF is calculated by the air-fuel ratio feedback control according to the output of the LAF sensor 14. That is, the air-fuel ratio correction coefficient KAF is calculated so that the detected air-fuel ratio matches the target air-fuel ratio. In step S24, the purge correction coefficient KPURGE and the other correction coefficient K1 and the correction variable K2 applied to the equation (1).
Is calculated, and then the fuel injection time TOU is calculated by the equation (1).
T is calculated (step S25).

As described above, according to this embodiment, the correlation parameters A (k) and B (k) that define the correlation between the air-fuel ratio correction coefficient KAF and the detected intake air amount QAIR are the sequential statistical processing algorithms. Is calculated using. By using the sequential statistical processing algorithm, the correlation parameters A (k) and B (k) can be calculated by the statistical processing operation with a relatively small memory capacity without requiring a special CPU for the operation. .

Further, since the learning correction coefficient KREFG is calculated using the correlation parameters A (k) and B (k), accurate learning corresponding to the characteristic change of the intake air amount sensor 19 which affects the air-fuel ratio. The correction coefficient KREFG can be obtained over a wide range of engine operating conditions. Then, since the fuel injection time TOUT is calculated using the air-fuel ratio correction coefficient KAF and the learning correction coefficient KREFG, the control center of the air-fuel ratio correction coefficient KAF is maintained in the vicinity of "1.0" to maintain good controllability. can do.

Further, since the abnormality determination of the intake air amount sensor 19 is performed based on the correlation parameter A (k), it is possible to constantly monitor the detection accuracy of the intake air amount sensor 19 and improve the accuracy of the abnormality determination. In addition, there is little fluctuation in vehicle speed, engine speed NE and intake pipe absolute pressure PBA.
Since the correlation parameters A (k) and B (k) are calculated in the operating state where is within the predetermined upper and lower limit values, the accuracy of the correlation parameter can be improved and the learning correction accuracy can be further improved. it can.

In this embodiment, the ECU 5 controls the basic fuel amount calculation means, the air-fuel ratio correction coefficient calculation means, the fuel amount control means,
A correlation parameter calculation means, a learning means, and an abnormality determination means are configured. Specifically, step S23 of FIG. 8 corresponds to the air-fuel ratio correction coefficient calculation means, step S18 corresponds to the correlation parameter calculation means, step S22 corresponds to the learning means, and step S25 corresponds to the basic fuel amount calculation means. It corresponds to the fuel amount control means, and steps S19 and S20 correspond to the abnormality determination means.

In the above embodiment, the correlation characteristic between the detected intake air amount QAIR and the parameter (KAFMOD-1) is approximated by a straight line, but it may be approximated by a quadratic curve instead of a straight line. In that case, the following formula (16)
The correlation characteristics are approximated by. KAFMOD-1 = A (k) QAIR ² + B (k) QAIR + C (k) (16)

Here, the slope F of the approximate curve is expressed by the following equation (17).
Given in. F = 2A (k) QAIR + B (k) (17) Even when approximated by a quadratic curve, the absolute value of the slope of the curve increases when the intake air amount sensor 19 is abnormal. Therefore, when the inclination F when the intake air amount QAIR is the average value QAIRM is equal to or larger than the predetermined threshold value, it is possible to determine that the intake air amount sensor 19 is abnormal.

In step S15 of FIG. 8 described above, it is determined whether or not the amount of change in the filtering value Vflt of the vehicle speed VP is smaller than the predetermined amount of change XDVLM, but instead of this, the engine speed NE is changed. It may be determined whether or not the change amount of the low-pass filtered value of is smaller than the predetermined change amount and / or whether the change amount of the low-pass filtered value of the intake pipe absolute pressure PBA is smaller than the predetermined change amount.

In this case, when the change amount of the low-pass filtered value of the engine speed NE is smaller than the predetermined change amount, when the change amount of the low-pass filtered value of the intake pipe absolute pressure PBA is smaller than the predetermined change amount, or when the engine speed is reduced. When the change amount of the low-pass filtering value of several NE is smaller than the predetermined change amount and the change amount of the low-pass filtering value of the intake pipe absolute pressure PBA is smaller than the predetermined change amount, the process proceeds from step S15 to step S16.

[0070]

As described in detail above, according to the invention described in claim 1, the amount of fuel supplied to the internal combustion engine is corrected so that the air-fuel ratio detected by the air-fuel ratio sensor matches the target air-fuel ratio. A correlation parameter that defines the correlation between the air-fuel ratio correction coefficient and the intake air amount detected by the intake air amount detecting means is calculated using a sequential statistical processing algorithm, and the intake air amount is detected using the correlation parameter. A learning correction coefficient related to the characteristic change of the means is calculated. And
The fuel amount supplied to the engine is controlled using the basic fuel amount, the air-fuel ratio correction coefficient, and the learning correction coefficient calculated according to the intake air amount detected by the intake air amount detecting means. That is, the correlation parameter is calculated by statistical processing based on a large amount of detection data, and the learning correction coefficient is calculated using the correlation parameter. Therefore, highly accurate learning correction corresponding to an average state of fluctuating engine operating states. The coefficient can be obtained. Further, by using the sequential statistical processing algorithm, it is possible to execute the statistical processing operation with a relatively small memory capacity without requiring a special arithmetic unit (CPU).

According to the second aspect of the present invention, since the abnormality of the intake air amount detecting means is determined based on the correlation parameter, the operation of the intake air amount detecting means is constantly monitored,
It is possible to increase the frequency of abnormality determination and improve the determination accuracy. According to the invention described in claim 3, since the correlation parameter is calculated when the engine is in the predetermined operating state, it is possible to improve the accuracy of the correlation parameter and further improve the accuracy of learning correction.

According to the fourth aspect of the present invention, the corrected air-fuel ratio correction coefficient is calculated by correcting the air-fuel ratio correction coefficient with the learning correction coefficient, and the corrected air-fuel ratio is replaced with the corrected air-fuel ratio correction coefficient. The correlation parameter is calculated using the correction coefficient. If the air-fuel ratio correction coefficient is used as it is, the learning control by the learning correction coefficient may be in the hunting state, but such a problem can be avoided by using the modified air-fuel ratio correction coefficient.

According to the invention described in claim 5, an air-fuel ratio correction coefficient for correcting the amount of fuel supplied to the internal combustion engine so that the air-fuel ratio detected by the air-fuel ratio sensor matches the target air-fuel ratio, and the intake air The correlation parameter that defines the correlation with the intake air amount detected by the amount detection means is calculated using the sequential statistical processing algorithm, and the abnormality of the intake air amount detection means is determined based on the correlation parameter. The operation of the intake air amount detecting means can be constantly monitored to improve the accuracy of abnormality determination.

[Brief description of drawings]

FIG. 1 is a diagram showing a configuration of an internal combustion engine and a fuel supply control device thereof according to a first embodiment of the present invention.

FIG. 2 is a diagram showing a relationship (in a normal state) between an air-fuel ratio correction coefficient (KAF) and an intake air amount (QAIR) detected by an intake air amount sensor.

FIG. 3 is a diagram showing a relationship (at the time of abnormality) between an air-fuel ratio correction coefficient (KAF) and an intake air amount (QAIR) detected by an intake air amount sensor.

FIG. 4 is a diagram showing a straight line (LST) that approximates a correlation between an air-fuel ratio correction coefficient (KAF) and an intake air amount (QAIR) detected by an intake air amount sensor.

FIG. 5 shows a parameter (KAF-
It is a figure which shows the relationship between 1) and the intake air amount (QAIR) detected by an intake air amount sensor.

FIG. 6 shows a parameter (KAF-
It is a figure which compares and shows the relationship (normal time and abnormal time) between 1) and the intake air amount (QAIR) detected by an intake air amount sensor.

FIG. 7 shows a parameter (KA depending on a corrected air-fuel ratio correction coefficient).
It is a figure which shows the relationship between FMOD-1) and the intake air amount (QAIR) detected by an intake air amount sensor.

FIG. 8 is a flowchart of a process for calculating a fuel injection time (TOUT).

[Explanation of symbols]

1 internal combustion engine 2 intake pipe 5 electronic control unit (basic fuel amount calculation means, air-fuel ratio correction coefficient calculation means, fuel amount control means, correlation parameter calculation means, learning means, abnormality determination means) 6 fuel injection valve 19 intake air amount sensor (Intake air amount detection means)

Continued front page    F term (reference) 3G084 BA13 DA04 DA30 EA02 EB08                       EB12 EB17 EC04 FA05 FA07                       FA11 FA33                 3G301 HA01 HA06 HA13 HA14 JB01                       LB01 MA01 MA12 NA09 NC02                       ND02 ND21 NE14 PA01Z                       PA04Z PA07Z PB03A PD04Z                       PE01Z PF01Z

Claims (5)

[Claims] 1. An intake air amount detecting means for detecting an intake air amount of an internal combustion engine, and a basic fuel for calculating a basic fuel amount to be supplied to the engine according to the intake air amount detected by the intake air amount detecting means. Amount calculation means, an air-fuel ratio sensor provided in the exhaust system of the engine, and an air-fuel ratio for correcting the amount of fuel supplied to the engine so that the air-fuel ratio detected by the air-fuel ratio sensor matches the target air-fuel ratio. A fuel supply control device for an internal combustion engine, comprising: an air-fuel ratio correction coefficient calculation means for calculating a correction coefficient; and a fuel quantity control means for controlling the fuel quantity supplied to the engine using the basic fuel quantity and the air-fuel ratio correction coefficient. In the above, in the correlation parameter for calculating the correlation parameter defining the correlation between the air-fuel ratio correction coefficient and the intake air amount detected by the intake air amount detecting means using a sequential statistical processing algorithm. A meter calculation unit and a learning unit that calculates a learning correction coefficient relating to a characteristic change of the intake air amount detection unit using the correlation parameter, and the fuel amount control unit includes the basic fuel amount and the air-fuel ratio correction coefficient. And a fuel supply control device for an internal combustion engine, wherein the fuel amount is controlled by using a learning correction coefficient. 2. The fuel supply control device for an internal combustion engine according to claim 1, further comprising abnormality determination means for determining abnormality of the intake air amount detection means based on the correlation parameter. 3. The fuel supply control device for an internal combustion engine according to claim 1, wherein the correlation parameter calculation means calculates the correlation parameter when the engine is in a predetermined operating state. 4. The correlation parameter calculation means calculates a corrected air-fuel ratio correction coefficient by correcting the air-fuel ratio correction coefficient with the learning correction coefficient, and replaces the air-fuel ratio correction coefficient with the corrected air-fuel ratio correction coefficient. The fuel supply control device for an internal combustion engine according to any one of claims 1 to 3, wherein the correlation parameter is calculated using a coefficient. 5. An intake air amount detecting means for detecting an intake air amount of an internal combustion engine, and a basic fuel for calculating a basic fuel amount to be supplied to the engine according to the intake air amount detected by the intake air amount detecting means. Amount calculation means, an air-fuel ratio sensor provided in the exhaust system of the engine, and an air-fuel ratio for correcting the amount of fuel supplied to the engine so that the air-fuel ratio detected by the air-fuel ratio sensor matches the target air-fuel ratio. A fuel supply control device for an internal combustion engine, comprising: an air-fuel ratio correction coefficient calculation means for calculating a correction coefficient; and a fuel quantity control means for controlling the fuel quantity supplied to the engine using the basic fuel quantity and the air-fuel ratio correction coefficient. In the above, in the correlation parameter for calculating the correlation parameter defining the correlation between the air-fuel ratio correction coefficient and the intake air amount detected by the intake air amount detecting means using a sequential statistical processing algorithm. And a meter calculating means, the fuel supply control system for an internal combustion engine, characterized in that it comprises an abnormality determination means for determining an abnormality of the intake air amount detecting means based on the correlation parameter.