JP3405128B2 - Engine air-fuel ratio control device - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an engine air-fuel ratio control system.

[0002]

2. Description of the Prior Art Improving engine fuel economy and at the same time NO
In order to reduce x, the fuel supply amount is controlled so that the air-fuel ratio, which is the ratio of air and fuel, becomes leaner than the stoichiometric air-fuel ratio, and the engine stability (combustion fluctuation amount) during lean operation is controlled. When it becomes worse than the control target value of the stability,
A method of operating an engine in which the air-fuel ratio is corrected to the rich side (or the ignition timing and the EGR rate are corrected to the side where combustion is stabilized) to ensure combustion stability is disclosed in Japanese Patent Laid-Open No. 58-16.
No. 0530 has been proposed.

[0003]

By the way, the stability shows a relatively flat characteristic with respect to the change of the air-fuel ratio in the region where there is a margin to the stability allowable limit, but the air-fuel ratio approaches the stability allowable limit. As the stability changes sharply with changes in the air-fuel ratio, overcorrection is likely to occur in excess of the target near the stability tolerance limit, and this overcorrection causes the stability to exceed the tolerance limit. Inevitable hesitation and stumble. Therefore, in the conventional device that only performs the feedback control based on the stability during lean operation, the response speed of the feedback control is increased in order to suppress the overcorrection and increase the control stability, as the nearer the stability allowable limit is approached. It is necessary to slow down, and in this case, feedback control based on stability may not be sufficiently performed under transient operating conditions.

Therefore, in order to enable control in the vicinity of the stability allowable limit even in such an operating region, it is possible to use learning control in combination with feedback control based on stability. Explaining this, after the feedback control based on the stability is sufficiently performed in the steady state (which is the feedback control condition based on the stability) (see the left side of FIG. 2), the feedback correction amount of the air-fuel ratio (simply in FIG. 2). The control with the target stability becomes possible by means of the correction amount), and this feedback correction amount is stored as a learning value.
Then, at the time of operation (for example, during gradual acceleration) where the feedback control condition based on the stability is not satisfied even during lean operation, this learned value is used as a correction amount (see FIG. 2).
That is, the target stability can be controlled even if the stability-based feedback control is not performed. In FIG. 2, the ignition timing is ADV and the air-fuel ratio is A.
/ F is abbreviated.

On the other hand, however, when the learning value becomes an inappropriate value due to some reason such as the influence of the purge gas, the response of feedback control based on the stability is slow, so that the stability converges to a good state. In the meantime, the driver feels uncomfortable due to unstable combustion.

In order to prevent the stability from deteriorating when the learning value becomes an inappropriate value due to the influence of the purge gas, etc., a base learning value is introduced separately from the normal learning value, and 1) start After that, prohibit lean operation and introduction of purge gas, perform feedback control of the air-fuel ratio with the theoretical air-fuel ratio as the target value, and update the base learning value during the air-fuel ratio feedback control. 2) After the base learning value has converged Start the introduction of purge gas and update the learning value at normal time. 3) At lean operation, select the learning value that makes the air-fuel ratio to the richer side, and use this selected learning value. Since there is an open control system (see Japanese Patent Laid-Open No. 7-217470),
It is applied to a combination of feedback control based on the above stability and learning control. 1) Prohibit the introduction of purge gas after starting and perform feedback control based on the stability during lean operation, and perform the base control during the feedback control. Update learning value, 2) Start introduction of purge gas after convergence of base learning value and update learning value at normal time (hereinafter referred to as normal learning value), 3) Change base learning value before convergence of base learning value Also, after the base learning value has converged, it is conceivable to select a normal learning value and use this selected learning value to open-control the air-fuel ratio when the feedback control condition based on the stability during lean operation is not satisfied. .

However, since the normal learning value changes greatly under the influence of temporary disturbance due to introduction of purge gas, etc., an overcorrected state occurs when the temporary disturbance is eliminated.

In order to reduce the adverse effects such as leaning due to the air-fuel ratio exceeding the surge limit due to this overcorrection, it has been conventionally used to provide an upper limit value and a lower limit value for the normal learning value.

Here, the air-fuel ratio error that needs to be corrected by the learned value is mainly due to the following items, <1> variation of parts such as fuel injection valve and air flow meter, and <2> influence of environment (pressure and humidity). Because the change in the required air-fuel ratio (air-fuel ratio at the stable combustion limit) due to <3> and the influence of temporary disturbance due to the introduction of purge gas, etc. Therefore, the normal learning value must be set so as not to exceed the practically possible range. But,
If all of these terms are taken into consideration, the range in which the learning value can be taken becomes wide, and overcorrection cannot be sufficiently suppressed. For example, the air-fuel ratio error is <1> and <2>
When it is considered to be about ± 10% in total, it is necessary to set the upper limit value and the lower limit value of learning to be wider than that, so it is assumed to be set to ± 15%. In this case,
If the air-fuel ratio target is set to about 20 during lean operation, and if the air-fuel ratio is made lean by 15%, the air-fuel ratio becomes 23, combustion fluctuations become large, and the driver feels uncomfortable.

Therefore, according to the present invention, by setting the upper limit value and the lower limit value of the normal learning value with the base learning value as a reference,
The purpose is to minimize overcorrection due to the effect of purge gas.

[0011]

As shown in FIG. 21, a first invention is a means 21 for initializing an air-fuel ratio during lean operation, and a means 22 for storing a normal learning value LRLDML.
And means 23 for storing the base learning value BSLDML,
A means 24 for determining whether or not the base learning value BSLDML has converged, and a base learning value BS based on the determination result.
Means 25 for selecting the base learning value before the LDML converges and the normal learning value after the base learning value converges.
And means 26 for judging whether or not the condition is to perform feedback control based on stability during lean operation, and the learning value of the selected one when the feedback control condition based on stability during lean operation is not satisfied from the result of this judgment. Means 27 for correcting the initially set air-fuel ratio during lean operation
A means 28 for controlling the amount of fuel supplied to the engine so as to obtain the corrected air-fuel ratio during lean operation, a means 29 for detecting the stability FILDMP of the engine, and a stability during lean operation based on the determination result. When the feedback control condition based on the above is satisfied and the base learning value BSLDML
Means 30 for updating the base learning value BSLDML so that the stability FILDMP of the engine matches the control target value LLSL for the stability before convergence, and a predetermined value based on the updated base learning value BSLDML. The value obtained by subtracting the value LRCHG # is the normal learning value LR.
Means 31 for setting as the lower limit value LDMLMN of LDML
According to the determination result, when the feedback control condition based on the stability during lean operation is satisfied, and the base learning value B
Engine stability FIL after SLDML converges
A means 32 for updating the normal learning value LRLDML so that the DMP matches the stability control target value LLSL, and the updated normal learning value LRLDML is the lower limit value LD.
A means 33 for limiting the normal learning value LRLDML to the lower limit value LDMLMN when the value becomes equal to or lower than MLMN is provided.

As shown in FIG. 22, a second aspect of the present invention is a means 21 for initializing the air-fuel ratio during lean operation, a means 22 for storing a normal learning value LRLDML, and a base learning value B.
Means 23 for storing SLDML and this base learning value B
Means 24 for determining whether SLDML has converged;
From this determination result, means 25 for selecting the base learning value before the base learning value BSLDML converges, and the normal learning value after the base learning value converges, and the condition for performing feedback control based on the stability during lean operation. Means 26 for determining whether or not, and based on this determination result, when the feedback control condition based on the stability during lean operation is not satisfied, the selected learning value is used to correct the initially set air-fuel ratio during lean operation. Means 27, means 28 for controlling the fuel supply amount to the engine so as to obtain this corrected air-fuel ratio during lean operation, and engine stability FILDM
A means 29 for detecting P, and a stability control target value of the stability FILDMP of the engine when the feedback control condition based on the stability during lean operation is satisfied from the determination result and before the base learning value BSLDML converges. LL
Means 30 for updating the base learning value BSLDML to match SL and the updated base learning value BS
A value obtained by adding a predetermined value LRCHG # to LDML as a reference is used as an upper limit value LDMLM of the normal learning value LRLDML.
The means 41 for setting as X and the stability control target value LLSL of the engine stability FILDMP when the feedback control condition based on the stability during lean operation is satisfied from the determination result and after the base learning value BSLDML converges. To match the normal learning value LRLDML
For updating the normal learning value LR
Means 42 for limiting the normal learning value LRLDML to the upper limit value LDMLMX when the LDML becomes equal to or higher than the upper limit value LDMLMX.

In a third aspect of the invention, the predetermined value LRCHG # is set for the purpose of changing the environment due to the time difference between the base learning value and the normal learning value in the first or second aspect.

In a fourth aspect of the invention, in any one of the first to third aspects of the invention, the predetermined value LRCHG # is set according to the starting temperature.

According to a fifth aspect of the present invention, in the fourth aspect, the predetermined value LRCHG # is increased at the cold start.

In a sixth aspect of the present invention, in the fourth aspect, the predetermined value LRCHG # is reduced when restarting from a completely warmed-up state (when hot restarting).

In a seventh aspect of the present invention, the predetermined value LRCHG # is increased as the starting water temperature becomes lower at the time of restarting from the state of not being completely warmed up in the fourth aspect.

In an eighth invention, in the invention of any one of the first to seventh inventions, the normal learning value is a value for each learning region.

According to a ninth aspect of the present invention, in any one of the first to eighth aspects, the base learning value includes a learning value at the time of purge cut, and the normal learning value includes a time when the purge cutting is not performed and a time when the purge cutting is not performed. It is a learning value.

In a tenth aspect of the invention, in any one of the first to ninth aspects of the invention, the stability detection value is an engine rotation fluctuation amount.

[0021]

The air-fuel ratio error that needs to be corrected by the learning value (base learning value, normal learning value) is mainly due to the following items:
[1] Variations in parts such as fuel supply means (for example, fuel injection valve) and intake air amount detection means (for example, air flow meter), [2] required air-fuel ratio (air at stable combustion limit due to influence of environment (pressure and humidity) (3) changes in the fuel ratio, [3] the influence of temporary disturbance due to introduction of purge gas, etc., so when the base learning value is updated in the absence of temporary disturbance in [3], It is possible to absorb the part variation of [1] and the environmental change of [2] above, and the difference between the base learning value and the normal learning value is [4] the amount of change in the environment due to the time difference between the two and 3] It is due to the influence of the temporary disturbance.

Therefore, when the lower limit value and the upper limit value of the normal learning value are set based on the base learning value according to the first and second inventions, in addition to the above [1] and [2], [3] and Compared with the conventional case where the lower limit value and the upper limit value of the normal learning value are set in consideration of [4] as well, the range that the normal learning value can take can be narrowed, and this causes a temporary disturbance. Overcorrection can be minimized.

In the third invention, it is not considered that the influence of the temporary disturbance of the above [3] is absorbed by the normal learning value.
Since the predetermined value is set by the normal learning value for the purpose of absorbing the environmental change in [4] above, the lower limit value and the upper limit value of the normal learning value are set in consideration of both [3] and [4] above. Compared with the case, the range that the normal learning value can take can be further narrowed.

It may be determined that the base learning value has converged before the engine has completed warming up, and the base learning value that has converged in the state where the engine is not completely warming up has an air-fuel ratio variation due to wall-flow fuel. The influence becomes stronger, and the difference from the normal learning value that is updated in the subsequent fully warmed-up state becomes large. Therefore, if the predetermined value used when the base learning value converges in the state where it is not completely warmed up is set to be the same as when the base learning value converges in the state where it is completely warmed up, the normal learning value is restricted more than necessary. However, in the fifth aspect, the predetermined value is set to a large value at the cold start when the base learning value is updated in a state where the base learning value is not completely warmed up, so that the normal learning value is not restricted more than necessary.

According to the sixth aspect of the invention, since the predetermined value is reduced when restarting from the completely warmed-up state, the influence of erroneous learning can be minimized.

According to the eighth aspect of the invention, the learning value is a value for each learning region, so that the control accuracy to the target stability is improved when the feedback control based on the stability is not performed during lean operation.

[0027]

DESCRIPTION OF THE PREFERRED EMBODIMENTS In FIG. 1, reference numeral 1 is an engine body, and intake air is supplied from an air cleaner to an intake pipe 8 to a cylinder. The fuel is a control unit (C / U in the figure) so that it has a predetermined air-fuel ratio according to the operating conditions.
The fuel is injected from the fuel injection valve 7 toward the intake port of the engine 1 based on the injection signal from the fuel injection valve 7.

The control unit 2 includes a Ref signal and a 1-degree signal from a crank angle sensor 4 incorporated in the distributor, an intake air amount signal from an air flow meter 6, and an O ₂ sensor 3 installed upstream of the three-way catalyst 10. Air-fuel ratio (oxygen concentration) signal from the water temperature sensor 15, cooling water temperature signal from the water temperature sensor 15, throttle valve opening signal from the throttle sensor, gear position signal from the transmission gear position sensor, vehicle speed signal from the vehicle speed sensor 16, etc. Is input, and the lean air-fuel ratio and the stoichiometric air-fuel ratio are controlled according to the conditions while determining the operating state based on these.

A three-way catalyst 10 is installed in the exhaust pipe 9 to reduce NOx in the exhaust gas and oxidize HC and CO with maximum conversion efficiency when operating at the stoichiometric air-fuel ratio. The three-way catalyst 10 oxidizes HC and CO when the air-fuel ratio is lean, but the NOx reduction efficiency is low. However, the more the air-fuel ratio shifts to the lean side, the smaller the amount of NOx generated, and at a predetermined air-fuel ratio or higher, the NOx can be reduced to the same level as purification by the three-way catalyst 10, and at the same time, the lean air-fuel ratio is reduced. Fuel economy is improved as On the other hand, when operating with a lean air-fuel ratio, combustion tends to become unstable depending on operating conditions.

Therefore, operation with a lean air-fuel ratio is performed in a predetermined operation range where the load is not so large,
At the same time, the stability of the engine (combustion fluctuation amount) is detected, and feedback control based on the stability at the lean air-fuel ratio is performed so that this stability matches the control target value.
It is possible to ensure stability.

In this case, the stability shows a relatively flat characteristic with respect to changes in the air-fuel ratio (or ignition timing) in a region where there is a margin to the stability allowable limit, but the air-fuel ratio (or ignition timing) is As the stability becomes steeper as the air-fuel ratio (or ignition timing) changes, the overcorrection is likely to occur in the vicinity of the stability allowance, as in the conventional device. If the stability exceeds the allowable limit due to this overcorrection, hesitation and stumble cannot be avoided. Therefore, the closer you try to approach the stability limit, the more
In the conventional device that needs to slow down the response speed of feedback control based on stability in order to suppress overcorrection and increase control stability, feedback control based on stability cannot be sufficiently performed under transient operating conditions.

Therefore, in order to enable control in the vicinity of the stability allowable limit even in such an operating region, it is conceivable to use learning control in combination with feedback control based on stability. Explaining this, after sufficiently performing feedback control based on stability during steady state (which is a feedback control condition based on stability) (see the left side of FIG. 2), the target stability is controlled by the feedback correction amount of the air-fuel ratio. Control becomes possible, and this feedback correction amount is stored as a learning value. Then, when the feedback control condition based on the stability is not satisfied even during lean operation (for example, during slow acceleration), the learning value is used as a correction amount (see the right side of FIG. 2) to perform feedback based on the stability. Even if the control is not performed, the control with the target stability can be performed.

However, on the other hand, when the learning value becomes an inappropriate value for some reason such as the influence of the purge gas, the response of the feedback control based on the stability is slow, so that the stability converges to a good state. In the meantime, the driver feels uncomfortable due to unstable combustion.

In order to prevent the deterioration of the stability when the learning value becomes an inappropriate value due to the influence of the purge gas, etc., a base learning value is introduced separately from the normal learning value, and 1) start After that, prohibit lean operation and introduction of purge gas, perform feedback control of the air-fuel ratio with the theoretical air-fuel ratio as the target value, and update the base learning value during the air-fuel ratio feedback control. 2) After the base learning value has converged Start the introduction of purge gas and update the learning value at normal time. 3) At lean operation, select the learning value that makes the air-fuel ratio to the richer side, and use this selected learning value. Since there is a conventional device that performs open control, this conventional device is applied to a device that uses learning control in addition to feedback control based on the above stability, and 1) purge gas after starting. Is prohibited, feedback control is performed based on the stability during lean operation, and the base learning value is updated during the feedback control. 2) After the base learning value has converged, introduction of purge gas is started and learning in normal times is performed. Update the value (hereinafter referred to as the normal learning value). 3) Select the base learning value before the convergence of the base learning value and the normal learning value after the convergence of the base learning value, and use this selected learning value. It is possible to open-control the air-fuel ratio when the feedback control condition based on the stability during lean operation is not satisfied.

However, since the normal learning value is greatly changed by the influence of a temporary disturbance due to introduction of purge gas or the like, an overcorrected state occurs when the temporary disturbance is eliminated.

In order to reduce the adverse effect such that the air-fuel ratio exceeds the surge limit and becomes lean due to this overcorrection, it has been conventionally used to provide an upper limit value and a lower limit value for the normal learning value.

Here, the air-fuel ratio error that needs to be corrected by the learned value is mainly due to the following items, <1> Variation of parts such as fuel injection valve and air flow meter, and <2> Influence of environment (pressure and humidity). Because the change in the required air-fuel ratio (air-fuel ratio at the stable combustion limit) due to <3> and the influence of temporary disturbance due to the introduction of purge gas, the upper and lower limits of the learning value are taken into consideration. Normally, the learning value must be set so as not to exceed the range that can be realistically taken. But,
If all of these terms are taken into consideration, the range in which the learning value can be taken becomes wide, and overcorrection cannot be sufficiently suppressed. For example, the air-fuel ratio error is <1> and <2>
When it is considered to be about ± 10% in total, it is necessary to set the upper limit value and the lower limit value of learning to be wider than that, so it is assumed to be set to ± 15%. In this case,
If the air-fuel ratio target value is set to about 20 during lean operation, and if the air-fuel ratio is leaned to 15%, the air-fuel ratio becomes 23 and the combustion fluctuation becomes large, which causes the driver to feel uncomfortable.

To deal with this, in the present invention, the upper limit value and the lower limit value of the normal learning value are set with reference to the convergent value of the base learning value.

The contents of this control executed by the control unit 2 will be described with reference to the following flow chart.

The flowchart of FIG. 3 is for calculating the target fuel-air ratio Tdml for controlling the air-fuel ratio to a predetermined value, and is executed at regular time intervals (for example, every 10 ms) or as a background job. In the following flowchart, when the job is executed at regular time intervals or as a background job, it is simply described as 10 ms in the figure, and the control cycle is omitted.

In step 1, it is judged by the flag #FLEAN whether or not it is the lean operation condition. # FLEAN = 1
Is a lean operating condition, and # FLEAN = 0 is a non-lean operating condition. Although the determination of the lean operating condition will not be described, it may be a known one disclosed in Japanese Patent Laid-Open No. 6-272591.

Under lean operating conditions, the routine proceeds to step 2, where a map value of an air-fuel ratio thinner than the stoichiometric air-fuel ratio is obtained by referring to a predetermined map (MDMLL map) with the rotation speed Ne and the load Tp.

In step 3, the learning value is referenced. The reference of the learning value will be described with reference to the flowcharts of FIGS.

In FIGS. 4 and 5, first, at step 11, the base learning value BSLDML is calculated from the flag #FBLLTD.
See if has converged. As will be described later with reference to FIG.
# FBLLTD = 0 means that the base learning value BSLDML has not yet converged, and # FBLLTD = 1 means that the base learning value BSLDML has converged. Therefore, B
When SLDML has not converged, in principle, the process proceeds from step 11 to step 15 and the base learning value BSLDML is
After BSLDML has converged, as a general rule, as long as the stabilized fuel-air ratio correction coefficient LLDML is updated, which will be described later with reference to FIG. 10, step 11 of FIG. 4, step 21 of FIG. 5 to step 24 of FIG. In step 27, the normal learning value LRLDML (k) for each learning area is selected.

The base learning value BSLDML is shown in FIG.
As will be described later, one piece of data has no relation to the operating area. Further, the learning region of the normal learning value LRLDML (k) has a rotation speed Ne and a load T as shown in FIG. 16 described later.
It is divided into a plurality of areas using p as a parameter, and independent learning values are stored for each learning area. LRLDML
K in (k) is a number given to distinguish each learning area from 0 to 15 shown in FIG.

However, the reference learning values are slightly different under the following conditions.

<1> When the base learning value is not converged (see FIG. 4)
In case of proceeding to step 12 and after in step 12) If it is in the update region of BSLDML but is not in the update permission state of the stabilized fuel-air ratio correction coefficient LLDML (described later), proceed to step 18 from step 12 and 14 and proceed to BS
The value obtained by adding the error margin LRMGN to LDML is put in the reference learning value.

BS is in the LLDML update permission state
When it is not in the update region of LDML, the routine proceeds from steps 12 and 13 to steps 16 and 17, where the normal learning value LRLDML of the learning region to which the rotation speed Ne and the load Tp belong
Select (k) and insert this LRLDML (k) into the reference learning value.

B is not in the LLDML update permission state
If it is not the update area of SLDML, steps 12 and 1
The procedure proceeds from step 4 to step 19 and is 10 which is the central value of the learning values
0% is put in the reference learning value.

<2> After the base learning value has converged (when proceeding to step 21 onward in FIG. 5) When the normal learning value LRLDML (k) at that time is larger than the value obtained by subtracting the predetermined value SLLDML # from BSLDML (BSLDML-SLLDML # ≦ LR
If LLDML (k)) is not in the LLDML update permission state, the process proceeds from step 22 and step 23 to step 25.
The value obtained by adding the error margin LRMGN to LRLDML (k) is put into the reference learning value.

BSLDML-L than SLLDML #
When RLDML (k) becomes small (BSLDML-
When SLLDML #> LRLDML (k) is not in the LLDML update permission state, the process proceeds from step 22 and 26 to step 28, and error margin LRM is added to BSLDML.
The value obtained by adding GN is put in the reference learning value.

In this case, the reason why the base learning value is selected without selecting the normal learning value is that the air-fuel ratio becomes too lean if the normal learning value is selected up to this case. , To avoid this.

Error margin LRMG in the case of
The reason why N is added is as follows.

The following two operating conditions 1) The first operating condition: when the learning value is updated while performing feedback control based on the stability during lean operation, 2) The second operating condition: the same lean operation Even when the feedback control based on the stability is not performed, the case where the initially set air-fuel ratio is corrected by the learning value stored in the storage means will be considered. Note that the learning value at this time is, to be exact, the learning value referred to in accordance with FIG. 4 before the convergence of the base learning value,
After the base learning value has converged, the learning value is referred to according to FIG. However, simply, the base learning value may be considered before the convergence of the base learning value, and the normal learning value may be considered after the convergence of the base learning value.

In this case, when the air-fuel ratio error (hereinafter simply referred to as the air-fuel ratio error) when the target air-fuel ratio is kept constant and the intake air amount is changed is a uniform magnitude regardless of the operating conditions, or the air-fuel ratio When there is no error (in an ideal state), the stability under the second operating condition matches the stability under the first operating condition (that is, the air-fuel ratio under the second operating condition is The target stability is controlled), but the air-fuel ratio error depends on the operating conditions (for example, load and rotation speed).
, The stability under the second operating condition deviates from the stability under the first operating condition by the difference in the air-fuel ratio error between the two operating conditions. When this stability causes the stability under the second operating condition to become worse than that under the first operating condition (that is, the air-fuel ratio becomes richer than the target stability equivalent value), the combustion fluctuation increases. Then, the discomfort given to the driver is increased.

More specifically, the left side of FIG. 6 shows an example in which the air-fuel ratio error changes to the lower right with respect to the intake air amount (when the intake air amount is small, the air-fuel ratio error is positive, (The air-fuel ratio error changes to the negative side as the intake air amount increases). In this case, the steady position (indicated by a black circle) corresponds to the above first operating condition, the position of slow acceleration (indicated by a white circle) corresponds to the above second operating condition, and the characteristic of the air-fuel ratio error is right. Since it is falling, there is a difference in the air-fuel ratio error between the two positions. Even in the steady position, if stability-based feedback control is not performed and learning is not advanced, the stability will deviate from the target stability due to an air-fuel ratio error, but in the steady position, feedback based on the stability will be performed. Since the control is performed, as shown in the upper right part of FIG. 6, the stability is controlled to the target stability even if there is an air-fuel ratio error, and the feedback correction amount at this time is stored as a learning value.

On the other hand, at the slow acceleration position where the air-fuel ratio error is larger than the steady-state position by minus, the air-fuel ratio becomes leaner than the initially set air-fuel ratio by the difference of the air-fuel ratio error from the steady position. Therefore, when the default air-fuel ratio deviated by this difference is corrected by using the learning value stored at the steady position as the correction amount, the air-fuel ratio becomes lower than the target stability equivalent value as shown in the lower right part of FIG. It becomes too lean.

Incidentally, this means that the characteristic of the air-fuel ratio error rises to the right on the left side of FIG.
The same is true when the slow acceleration position is on the plus side and the slow acceleration position is on the plus side rather than the steady position.) At this time, the error of the air-fuel ratio between the first operating condition and The air-fuel ratio under the second operating condition becomes excessively richer than the target stability equivalent value by the difference.

Therefore, when the feedback control based on the stability in lean operation is not established, the learning value is shifted to the side where the torque generated by the engine increases by the difference in the air-fuel ratio error between the operating condition and the learning representative point at that time. To do so, an error margin LRMGN is introduced. Learning value (BSLDM
L, LRLDML) are values that the air-fuel ratio becomes richer as this value increases, and the error margin LRMGN is the air-fuel ratio error between the two operating conditions (the first operating condition and the second operating condition described above). Since LRMGN is given a value of 0 or a positive value, the addition of LRMGN shifts the initially set air-fuel ratio during lean operation to the rich side.

Specifically, as shown in FIG. 7, the LRMGN is the load Tp and the learning representative point (the steady position or the first position shown on the left side of FIG. 6) when the feedback control based on the stability is not performed even during lean operation. Value of the load LRTP) is used as a parameter, and when | Tp-LRTP | is 0, the minimum value becomes 0, and the larger the | Tp-LRTP | becomes, the larger the value becomes. Is.

As shown on the left side of FIG. 6, (i) when the air-fuel ratio error at the steady position is negative and the air-fuel ratio error at the slow acceleration position is negative and larger than the steady position, When the learning value is referred to at the position of slow acceleration and is used as the correction amount, the air-fuel ratio becomes excessively lean by exceeding the target stability equivalent value by the difference in the air-fuel ratio error from the steady position. Conversely, if (ii) the air-fuel ratio error at the steady position is on the negative side and the air-fuel ratio error at the slow acceleration position is negative and smaller than the steady position (not shown), slow acceleration is performed. When referring to the learned value at the position of, and using this as the correction amount, the air-fuel ratio becomes richer than the target stability equivalent value (that is, the side where combustion fluctuations are contained) by the difference of the air-fuel ratio error from the steady position. Therefore, in this case, the driver's discomfort is not increased. Therefore, the air-fuel ratio must be shifted to the lean side in order to eliminate the discomfort to the driver due to the increase in combustion fluctuation, only in the above case (i). However, since the control unit cannot distinguish between the case of (i) and the case of (ii), (i),
Also in the case of (ii), since the air-fuel ratio is shifted to the rich side, the absolute value of the difference between Tp and LRTP is used as a parameter as shown in FIG.

When the cases (i) and (ii) can be distinguished in advance, the air-fuel ratio is shifted to the lean side only in the case of (i), and in the case of (ii), the air-fuel ratio is reversed. Is shifted to the rich side, the air-fuel ratio can be controlled to the target stability equivalent value even in the case of (ii).

The steady position (learning representative point) shown on the left side of FIG. 6 is set by selecting a condition where the load is in the middle in the lean operation region. The reason is as follows. If the error margin is large, the air-fuel ratio will change greatly. Therefore, the smaller the error margin, the more preferable it is. Also, the difference in the air-fuel ratio error between the two positions (steady position and slow acceleration position) is large. Since it is necessary to increase the error margin as much as possible, when the steady position is in the middle of the load in the lean operation region, the difference in the air-fuel ratio error between the two positions (hence the error margin) is minimized in total. It is supposed to be.

When the air-fuel ratio error changes depending on the operating condition, the intake air amount is shown on the left side of FIG. 6 as a representative operating condition. However, the air-fuel ratio error may change depending on the engine speed. Therefore, as shown in FIG. 7, the error margin also uses the absolute value | Ne-LRNE | of the difference between the rotation speed Ne and the rotation speed LRNE of the learning representative point as a parameter, and | Ne-LRNE | is large. I see LRMGN
The value of is increased.

In this way, the error margin LRMGN
Therefore, the learning value is shifted to the rich side by the difference in the air-fuel ratio error between the second operating condition and the first operating condition under the second operating condition, so that the first operating condition and the second operating condition are Even if there is an air-fuel ratio error difference between them, the air-fuel ratio can be controlled to the target stability equivalent value. For example, FIG. 8 is a rewrite of the characteristic on the right side of FIG. 6, and when the learning amount is referred to during the slow acceleration (second operating condition) and this is set as the correction amount, when the air-fuel ratio is in the steady state (first However, in the present embodiment, the difference between the air-fuel ratio error and the target stability degree equivalent value exceeds the target stability and becomes excessively lean. Since the difference between the air-fuel ratio errors is shifted to the rich side (see the right side of FIG. 8), even if there is a difference in the air-fuel ratio errors between the two operating conditions, the air-fuel ratio is controlled to the target stability equivalent value. You can do it.

After referring to the learned value in this way, the process returns to step 4 in FIG. 3 and the reference learned value is multiplied by the map fuel-air ratio under the lean operating condition, that is, Tdml = Mdml × reference learned value. The target fuel air ratio Tdml is calculated by the equation (1).

Since the reference learning value increases as the engine rotation fluctuation amount increases during feedback control based on the stability, the target fuel air ratio Tdml increases as the combustion fluctuation amount increases, that is, the target fuel air ratio becomes It will be shifted to the rich side. If the lean operation condition is not satisfied, the stoichiometric air-fuel ratio or a map fuel-air ratio that is a higher value than the stoichiometric air-fuel ratio is referred to in accordance with a predetermined map (MDMLS map) in the same manner as the above MDMLL map. In step 6, the fuel-air ratio Mdml is directly added to Tdml.

Although not shown here, in order to prevent a sudden change in torque by gently switching the air-fuel ratio and to ensure the stability of the operating performance, the target fuel-air ratio Tdml is changed when the air-fuel ratio is switched. The fuel-air ratio correction coefficient DML may be obtained by performing a damper operation (JP-A-6-
272591).

Next, the flowchart of FIG. 9 is for detecting the stability and is executed every time the Ref signal is input, independently of FIG. The Ref signal is a signal generated every 180 ° in crank angle in a 4-cylinder engine and every 120 ° in crank angle in a 6-cylinder engine.

At steps 31 and 32, the Ref signal period T
REF is measured, and the reciprocal of REF is multiplied by a constant K1 to convert it into an engine speed R0. In step 33, band reject filter processing is performed to remove noise generated at a specific frequency due to an error of the crank angle sensor. Subsequently, a bandpass filter process for extracting a vehicle resonance frequency component which is felt as vibration by a human body is performed in step 3
4, further absolute value processing is performed in step 35, and the result is filtered output F in step 36.
ILOUT. By the bandpass filter processing, the DC component and the high frequency component are removed from the time series data of the engine speed, and only the fluctuation component of the vehicle resonance frequency band is left. In addition, the magnitude of the fluctuation is extracted by the absolute value processing. Therefore, the filter output FILOUT
Represents the magnitude of the fluctuation component included in the vehicle resonance frequency band in the engine rotation fluctuation.

In step 37, this filter output FIL
A weighted average process is performed on OUT, and the result is the stability index F.
ILDMP.

The flowcharts of FIGS. 10 and 11 are for calculating the stabilized fuel-air ratio correction coefficient LLDML as the stability correction amount, and are executed independently of FIG. However,
It is premised that the stability index FILDMP is obtained according to FIG. 9 immediately before the operation of step 42 of FIG. 10 is executed.

In step 41 of FIG. 10, it is judged whether or not the update of the stabilized fuel-air ratio correction coefficient LLDML is permitted. The specific content for this is shown in FIG. This determination is made by checking the contents of the steps in FIG. 11 one by one, and when all of the items are satisfied, L
Allow LDML update, LLD if any one goes against
ML update is not allowed.

That is, step 51: flag # FLEAN = 1 (lean operating condition), step 52: absolute value | ΔTp | of change amount of load Tp from 50 ms before is less than or equal to a predetermined value LLDTP #, step 53 : Absolute value | ΔNe | of the change amount of the rotation speed Ne from 50 ms before is equal to or less than a predetermined value LLDNE #, Step 54: 50 ms of throttle valve opening TVO
The absolute value of the amount of change | ΔTVO | is the predetermined value LLDT
VO # or less, Step 55: No fuel is being cut in any cylinder, Step 56: No abnormality in crank angle sensor (abbreviated as NG in the figure), Step 57: Flag # FCNST = 1 (during slow acceleration or steady state) ), The update of the LLDML is permitted in step 58, and if not, the process proceeds to step 59 and the update of the LLDML is not permitted.

The above steps 51 to 57 are conditions for accurately updating LLDML (including detection of stability). In the method of estimating the combustion fluctuation from the rotation fluctuation using the correlation between the combustion fluctuation and the rotation fluctuation as in the present embodiment,
If the engine speed goes up or down due to acceleration / deceleration, there is concern that the amount of rotational change due to acceleration / deceleration cannot be separated from the rotational fluctuation due to combustion fluctuation and the magnitude of combustion fluctuation may be estimated larger than it actually is. Steps 52, 53, 5 above
4, 57 due to unsteady condition (during sudden acceleration or sudden deceleration)
The update of LDML is prohibited. In addition, step 5
The flag #FCNST of 7 is ΔVSP <LLCDVH by comparing the vehicle speed change amount ΔVSP with a predetermined value LLCDVH.
This flag is set to "1" (during slow acceleration or steady state) (see FIG. 12) and set to "0" when ΔVSP≥LLCDVH (during rapid acceleration).

When it is determined in this way whether to permit the update of LLDML, the process returns to step 41 of FIG. 10 and step 42 is performed only when the update of LLDML is permitted.
Continue below.

In step 42, the stability index FILDM
P (which has already been obtained in step 37 of FIG. 9) is read, in step 43 the stability target value LLST is obtained by referring to a predetermined map from the load and the number of revolutions, and LLDML is used in step 44 by using these values. (New) = LLDML (old) + GLLLFB # × (FILDMP-LLSL) (2) where LLDML (new): stabilized fuel-air ratio correction coefficient LLDML (old) after update: stabilized fuel-air ratio before update Correction coefficient GLLFB #: The stabilized fuel-air ratio correction coefficient (initially set to 100% at startup) LLDML is updated by the gain formula.

From the equation (2), the stabilized fuel-air ratio correction coefficient LLD
The stability index FILDMP is the stability target value LLS.
It is a value that increases as it exceeds T, that is, as combustion deteriorates.

The gain GLLFB # in the equation (2) is a value that determines the response speed of feedback control based on stability, and is a relatively small value in order to suppress overcorrection and improve control stability, as in the conventional device. (The response speed of feedback control is slowed).

At step 45, the lower limit limiter LDMLM
Read N and upper limit limiter LDMLMX, step 4
At 6, the LLDML limiter processing is performed. This limiter processing will be described with reference to the flowchart of FIG.

In FIG. 13, in step 61, the base learning value BSLDML is referred to, and the predetermined value LRCH is calculated from this.
The value obtained by subtracting G # is set as the lower limit limiter LDMLMN in step 61, and the predetermined value L is set from BSLDML.
The value to which RCHG # is added is set as the upper limit limiter LDMLMX in step 63. As a result, after the base learning value has converged, between the lower limit limiter and the upper limit limiter based on the convergence value of the base learning value as shown in FIG.
As will be described later in 9, the normal learning value will be limited.

The lower limit limiter and the upper limit limiter of the normal learning value are set based on the convergence value of the base learning value for the following reason.

The air-fuel ratio error that needs to be corrected by the learning value (base learning value, normal learning value) is mainly the following items:
<1> Variation of parts such as fuel injection valve and air flow meter, <2> Change of required air-fuel ratio (air-fuel ratio at stable combustion limit) due to influence of environment (pressure and humidity), <3> Temporary due to introduction of purge gas, etc. Because it is caused by the influence of a general disturbance,
When the base learning value is updated with the introduction of the purge cut prohibited, the base learning value can absorb the component variation of <1> and the environmental change of <2>.
The difference between the base learning value and the normal learning value is due to <4> the change in the environment due to the time difference between the two and the influence of the purge gas in <3> above.

Therefore, if the lower limit limiter and the upper limit limiter of the normal learning value are set with reference to the base learning value,
It is no longer necessary to consider the component variation <1> and the environmental change <2>.

Therefore, the limiter should be set in consideration of the influence of the remaining <3> purge gas and the influence of <4> environmental change. Further, in the present embodiment, the limiter of the purge gas of <3> above is set. It is not considered that the influence amount is absorbed by the normal learning value, and the predetermined value LRCHG # is set for the purpose of absorbing the environmental change of <4> by the normal learning value.

As described above, in this embodiment, the lower limiter and the upper limiter of the normal learning value are used as the reference for the convergence value of the base learning value, and the predetermined value LRCHG # for defining the range is set by the environmental change of <4>. Since it is set for the purpose of absorption of <3> and <4> in addition to <1> and <2> above.
The lower limit limiter and the upper limit limiter for the normal learning value are also set in consideration of the above, and the range that the normal learning value can take can be narrowed, which minimizes overcorrection due to the effect of purge gas. Can be suppressed to

Returning to FIG. 10, in step 47, the learning value is updated. This will be described with reference to the flowchart of FIG.

First, in step 71, a learning counter (initially set to 0 at the time of starting) CBSLDM and a predetermined value NBSLDM.
Compare #. The learning counter CBSLDM is for measuring the number of times the base learning value BSLDML is updated. When CBSLDM <NBSLDM #, it is determined that the base learning value BSLDML has not converged, and the process proceeds to step 72, where "0" is set in the flag #FBLLTD.
The flag # FBLLTD = 0 indicates that BSLDML has not converged. On the other hand, #FBLL
TD = 1 indicates that BSLDML has converged as described later.

At steps 73 and 74, it is determined whether the load Tp is in a predetermined region (LLCTPL≤Tp≤LLCTPH), and the rotational speed Ne is in a predetermined region (LLCNEL≤Ne≤).
LLCNEH), if both are in a predetermined area, "1" is put in the flag #FLRLLC in step 75. The flag # FLRLLC = 1 indicates that the base learning value is in the update region (see FIG. 15). On the other hand, if either the load or the rotation speed is not within the predetermined range, the flag # FLRLLC = 0 (described later).

In steps 76 and 77, the stabilized fuel-air ratio correction coefficient LLDML at that time is set to the base learning value BSLDM.
In addition to L, the learning counter CBSLDM is incremented.

That is, when the lean operation is first performed after the engine is started and the feedback control based on the stability is started and the base learning value BSLDML is not converged, before the normal learning value LRLDML (k) is updated. Since the base learning value BSLDML is updated by cutting the purge, the base learning value BSLDML converges to the required value of the stabilized fuel-air ratio correction coefficient LLDML that is determined only by the engine characteristics without being affected by the purge. Further, after the base learning value BSLDML converges, the base learning value is not updated and the normal learning value LRLDML (k) is updated.

However, the purging must be continued to be cut until the base learning value BSLDML converges, so it is necessary to converge the base learning value BSLDML in the shortest possible time. Therefore, the base learning value BSLDM
L does not have a learning map like the normal learning value LRLDML (k), and is composed of one data regardless of operating conditions.

On the other hand, since the same base learning value BSLDML is updated and referred to regardless of the operating conditions, when the operating conditions at the time of updating the base learning value BSLDML and at the time of reference differ greatly, the air-fuel ratio at the time of reference There is concern that the control accuracy will deteriorate. However, the base learning value BSLD
The base learning value BSLDML is referred to when the ML is updated and when the operating conditions are significantly different from each other when the state becomes unstable due to the influence of introduction of the purge gas (specifically, after the base learning value converges, BSLDML- SLLDM
Since L #> LRLDML (k) and the update permitted state of LLDML are not referred to, BSLDML is referred to in step 28 of FIG. 5), and the reference period thereof is also temporary, so there is no big problem.

The base learning value BSLDML is stored in the backup memory. BS updated during operation this time
The LDML is retained as it is until the next operation. The initial setting value of BSLDML is 100% which is the central value of the learning value.

At step 78, the base learning value BSLDM
The same value of the stabilized fuel-air ratio correction coefficient LLDML as that put in L is put in the normal learning value LRLDML (k) of all learning regions. The learning region of the normal learning value LRLDML (k) is
As shown in FIG. 16, it is divided into a plurality of regions using the rotation speed Ne and the load Tp as parameters, and independent learning values are stored for each learning region. K of the normal learning value LRLDML (k)
Is a number given to distinguish each learning area from 0 to 15 shown in FIG. 16 described later. Therefore, by the operation of step 78, the normal learning value L of all learning regions is obtained.
The converged value of the base learning value is stored in RLDML (k) as an initial value.

When CBSLDM <NBSLDM # and the base learning value update region continues, steps 75 to 78 are repeated until CBSLDM ≧ NBS.
When it becomes LDM #, it means that the base learning value BSLDML has converged.
"1" is put in LTD, and then the routine proceeds to steps 81 and 82 to update the normal learning value LRLDML (k) for each learning region. When the rotation speed Ne and the load Tp belong to the learning region of 5 shown in FIG. 16, the stabilized fuel-air ratio correction coefficient LLDML is added only to the normal learning value LRLDML (5) of the determined learning region of 5. .

Here, the learning region of the normal learning value LRLDML (k) is obtained by dividing the entire operating region into a plurality of regions using the rotation speed Ne and the load Tp as parameters as shown in FIG. Independent learning values are stored in. LRLDML (k) represents a learning value for each learning area. K of LRLDML (k) is a number assigned to distinguish each learning region, and when there are 16 learning regions, k can take an integer from 0 to 15.

On the other hand, if CBSLDM <NBSLDM # and it is not the update region of the base learning value BSLDML, the routine proceeds from step 73 or 74 to step 79 and flag #F.
Put "0" in BLDTD.

At this time, the operations of steps 81 and 82 are further performed. By this operation, the value of LLDML enters the normal learning value, and as a result, LLDML also enters the reference learning value (see steps 11, 12, 13, 16, and 17 in FIG. 4). In other words, in the flowchart of FIG. 14, the stabilized fuel-air ratio correction coefficient LLDML is always stored once as a learning value.
It is advancing to the operations of 1 and 82. According to FIGS. 14, 4 and 5, as a result, the learning value simultaneously enters the reference learning value, and the air-fuel ratio correction uses only the reference learning value (see steps 3 and 4 in FIG. 3). It has the same function as the feedback control of. Before the convergence of BSLDML (that is, the update permission status of LLDML is
When not in the DML communication area), the normal learning value is used as a dummy.

The flowchart of FIG. 17 shows the contents of the control operation for calculating and outputting the fuel injection pulse width using the target fuel-air ratio Tdml thus obtained, and is executed subsequent to FIG.

First, at step 81, using the target fuel-air ratio Tdml, the target fuel-air ratio equivalent amount Tfbya is calculated by the equation Tfbya = Dml + Ktw + Kas (3).

Here, Ktw is the amount of fuel increase corresponding to the cooling water temperature, and Kas is the amount of fuel increase immediately after the start. In addition,
The unit of Tfbya in the formula (3) is%, but the unit of Tfbya in the formula (4) described later is an anonymous number.

Next, at step 82, the output of the air flow meter is A / D converted and linearized to obtain the intake air flow rate Q.
To calculate. Then, in step 83, the basic injection pulse width Tp that gives a theoretical air-fuel ratio is obtained from the intake air flow rate Q and the engine speed Ne as Tp = K × Q / N. Note that K is a constant.

Then, at step 84, based on this Tp, the fuel injection pulse width Ti for one time of the sequential injection is Ti = (Tp + Kathos) × Tfbya × (α + αm−1) × 2 + Ts (4) Calculate with.

Here, Kathos is the transient correction amount, α is the air-fuel ratio feedback correction coefficient, αm is the air-fuel ratio learning correction coefficient calculated based on α, and Ts is the valve actually opened after the injection signal is received. This is an ineffective pulse width for compensating for the operation delay until the operation. Further, since the formula (4) is a formula for sequential injection (in four cylinders, injection is performed once every two revolutions of the engine, injection is performed according to the ignition order of each cylinder).
There is a number 2 in front of Ts. However, under the lean condition, α and αm are fixed to predetermined values.

As described above, the basic injection pulse width T
p is used as the engine load. Although this Tp is used here for the sake of simplicity, a value obtained by performing a weighted average on this Tp in consideration of the intake pipe volume may be used instead of Tp.

Next, in steps 85 and 86, it is determined whether or not the fuel is cut, and in steps 87 and 88, if the fuel cut condition is satisfied, the invalid injection pulse width Ts is stored. If not, Ti is stored in the output register. Prepare for injection at a predetermined injection timing according to the output of.

The flow chart of FIG. 18 is for controlling the opening and closing of the purge valve, and is executed independently of FIG. 3, FIG. 10 and FIG.

Open / close control of the purge valve is performed in steps 91 and 9
It is carried out by checking the contents of Nos. 2, 93 and 94 one by one. When all the items are satisfied, the purge valve is opened, and when any of them is contrary, the purge valve is closed.

That is, step 91: the idle switch is not ON, step 92: the cooling water temperature Tw is within a predetermined range (TWCPL).
≦ Tw ≦ TWCPH), Step 93: The load Tp is in a predetermined region (TPCPL ≦ T)
p ≦ TPCPH), Step 94: Flag # FBLLTD = 1 (BS
(After convergence of LDML) Sometimes, the purge valve is opened in step 95, and if not, the routine proceeds to step 96, where the purge valve is closed. That is, the base learning value BSLDML is updated during the purge cut. The update of the base learning value BSLDML at the time of purging is prohibited only by the base learning value BSLDML only the air-fuel ratio error due to the variation in the flow rate characteristics of the parts (fuel injection valve and air flow meter) related to the basic air-fuel ratio and deterioration over time. This is because I want to absorb it.

Now, the operation of this embodiment will be described. As shown in FIG. 19, the purge gas is introduced from the canister after performing the purge cut for a while after the start of the lean operation, and the operating condition moves from the learning area 1 to the learning area 2 during the purging, and the learning area 1 Think back to. However, the base learning value BSLDML has a central value of 10
0% is the normal learning value LRLDML for each learning area
It is assumed that (k) contains 100% of the central value in all learning regions. Note that the learning areas 1 and 2 in FIG. 19 merely mean that the learning areas are different, and the normal learning values in the learning areas 1 and 2 are LRLDML (1) and LRL.
It is not DML (2).

When the base learning value, the normal learning value, and the stabilized fuel-air ratio correction coefficient LLDML are all 100%, the air-fuel ratio during lean operation (and the ignition timing) is initialized so that a stable state is always obtained. Therefore, at the start timing of the lean operation of t1, the air-fuel ratio becomes richer than the target air-fuel ratio (the stability index FILDMP becomes smaller than the stability target value LLSL), so that the base learning value becomes smaller. The base learning value converges to the value of a immediately before the timing of t2, and the air-fuel ratio at this time matches the target air-fuel ratio (see the solid line in the third stage).

On the other hand, when updating the base learning value, the stabilized fuel-air ratio correction coefficient LLDML stored in the base learning value.
Since the same value as the value of is stored in the normal learning values of all learning areas, each normal learning value of the learning areas 1 and 2 also follows the same change as the base learning value (not shown), but immediately before the timing of t2. Becomes the value of a.

At the timing of t2 when the base learning value has converged, when the normal learning value is updated and the purge is started,
The air-fuel ratio becomes temporarily richer than the target air-fuel ratio, and the stability improves accordingly (again, the stability index FILD
Since MP is smaller than the stability target value LLSL), the normal learning value in the learning area 1 is the convergence value of the base learning value a.
It is updated to a smaller side (see the solid line in the third row).

When the base learning value is updated to the normal learning value in the same learning area 1, the initial value of the converged value a of the base learning value is set to the initial value instead of 100% which is the central value of the learning value. Since the update of the normal learning value is started as, the normal learning value is closer to the required value than when starting the update of the normal learning value from 100% which is the central value of the learning value. Therefore, the air-fuel ratio does not become excessively richer than the target stability-equivalent value, or conversely becomes lean.

In order to maintain the target air-fuel ratio with respect to the change in the purge gas concentration shown in the figure, the normal learning value must change abruptly like the required value, but the gain of the above equation (2) is Since a relatively small value is set in order to suppress overcorrection and enhance control stability, there is a response delay in the normal learning value with respect to the required value.

From the timing of t3, the normal learning value falls below the lower limit limiter of the learning value, so the normal learning value is limited to b, which is the lower limit limiter of the learning value (see the third solid line).

In this case, the lower limit value of the learning value is different from the conventional one, and is a value obtained by subtracting a predetermined value LRCHG # (indicated by a normal learning limiter in the figure) from the convergence value a of the base learning value as a reference. Is. Since the air-fuel ratio error due to <1> and <2> described above can be absorbed in the state where the base learning value has converged, the lower limit limiter for the normal learning value is the above based on the convergence value of the base learning value. It is sufficient to set <3> and <4> as targets, and since the predetermined value LRCHG # is set only for <4> without considering <3> among them,
The lower limit limiter is located at a position relatively close to a, which is the convergence value of the base learning value.

During the period from t4 to t5, the operating condition becomes unsteady (the LLDML update permission state disappears). Therefore, the feedback control condition based on the stability is not controlled (open control in the figure). Then, either the base learning value or the normal learning value is referred to according to the flow of FIGS. 4 and 5. In the period from t4 to t5, BSLDML-SLLDML #> LRLDML (k)
Therefore, the flow proceeds to steps 22, 26, and 28 of FIG. 5, and a value obtained by adding the error margin LRMGN to the convergence value a of the base learning value BSLDML is referred to (third part).
See the solid line in the step).

When the learning area 1 is switched to the learning area 2 at the timing of t5, the normal learning value of the learning area 1 is b.
Of the normal learning value of the learning region 2 is updated. The normal learning value of the learning area 2 at this time contains a which is the same value as the converged value of the base learning value BSLDML.

However, during the period from t5 to t6, since the operating condition is not steady (not in the LLDML update permission state), the control is performed when the feedback control condition based on the stability is not established, and the flow shown in FIGS. Therefore, the learning value is referred to. During the period from t5 to t6, BSLD
Since ML-SLLDML # <LRLDML (k), the flow proceeds to steps 22, 23 and 25 of FIG. 5, and the error margin LRM is added to the initial value a of the normal learning value of the learning area 2.
The value obtained by adding GN is referred to (see the solid line in the third row).

The normal learning value in the learning area 2 is updated with the value of a, which is the convergence value of the base learning value, as the initial value from the timing of t6 which becomes steady, but the learning area 2 is also affected by the purge gas and becomes empty. Since the fuel ratio becomes rich, the normal learning value in the learning region 2 is updated to a value smaller than a and matches the required value at the timing of t7 (see the solid line in the third row). In this way, the value of a, which is the convergence value of the base learning value, is also set as the initial value of the normal learning value of the learning area 2. Than when starting to update the learning value,
The normal learning value becomes closer to the required value, and the air-fuel ratio will not be unnecessarily made rich. This can suppress the increase of NOx.

The value c of the normal learning value at the timing of t8 when the operating conditions are not steady (the LLDML is not in the update permission state) is held as the normal learning value of the learning region 2, and the stability is maintained from t8 to t9. The control shifts to the control when the feedback control condition based on is not satisfied, and the learning value is referred to according to the flows of FIGS. At this time BSL
From DML-SLLDML # <LRLDML (k), FIG.
That is, the value is obtained by adding the error margin LRMGN to c, which is the value of the normal learning value of the learning region 2 held at the timing of t8, in the flow of Steps 22, 23, and 25 of (3rd stage). See the solid line).

Returning to the learning area 1 at the timing of t9,
The process moves to updating the normal learning value in the learning area 1. The normal learning value of the learning area 1 at this time includes the value of b which is the normal learning value of the learning area 1 held at the timing of t4.

However, the operating condition is not steady during the period from t9 to t10 (not in the LLDML update permission state).
Therefore, the learning value is referred to according to the flow of FIGS. 4 and 5 by the control when the feedback control condition based on the stability is not established. At this time, BSLDML-SLLDM
From L #> LRLDML (k), steps 22 and 2 in FIG.
6, 28, and the value obtained by adding the error margin LRMGN to the initial value a of the base learning value is referred to (third value).
See the solid line in the step).

From the timing of steady t10, t4
The normal learning value in the learning area 1 is updated with the lower limit limiter value b held at the timing of as the initial value. t
Since the purge gas concentration at t10 is smaller than the purge gas concentration at the timing of 4, at the beginning of restarting the update of the normal learning value in the learning region 1 from the timing of t10, the air-fuel ratio is reduced by the decrease in the purge gas concentration. Becomes lean at once. Since the leanness reduces the stability (the stability index FILDMP becomes larger than the stability target value LLSL), the side where the normal learning value in the learning region 1 becomes larger than the value of b (the side that makes the air-fuel ratio rich). To the required value at the timing of t11 (see the solid line in the third row).

In this case, the normal learning value from the timing of t10 is relatively a as described above at the timing of t3.
The air-fuel ratio is not overcorrected to the lean side because it is limited to b at a position close to. As shown in FIG. 19 in which the learning value changes when the learning limiter of the present embodiment is not provided (see the third stage of FIG. 19), in this case, the air-fuel ratio becomes large and lean at the timing of t10. It is overcorrected to the side (see the fourth row in FIG. 19).

In the third row of FIG. 19, the open margin is LRMGN, the open learning value selection get is SLLDML #, and the open learning value selection slice level is BSLDML-SLLD.
It is ML #.

As described above, in the present embodiment, the lower limiter and the upper limiter of the normal learning value are used as the reference value of the convergence value of the base learning value, and the predetermined value LRCHG is defined.
Since # is set for the purpose of absorbing only the environmental change of <4> described above, the above-mentioned <1>, <2>, <3>,
Compared to the conventional case in which the lower limit limiter and the upper limit limiter of the normal learning value are set in consideration of all of <4>, the range of the normal learning value can be narrowed, which allows the disturbance of the purge gas or the like to be reduced. Overcorrection due to the influence can be suppressed to the minimum.

FIG. 20 shows the second embodiment. The predetermined value LRCHG that defines the range of the learning limiter is a fixed value in the first embodiment, whereas it is a variable value according to the starting water temperature in the second embodiment.

Although the air-fuel ratio varies because the wall-flow fuel varies from engine to engine, the wall-flow fuel amount is strongly affected by the intake port wall temperature. In the first embodiment, when the learning counter CBSLDM reaches a predetermined value NBSLDM #,
Since it is determined that the base learning value has converged, it may be determined that the base learning value has converged before the engine has finished warming up. , The influence of the air-fuel ratio variation due to the wall flow fuel appears more strongly, and the difference from the normal learning value that is updated after that in the complete warm-up state increases. Therefore, if the predetermined value LRCHG # used when the base learning value converges in the state where the warming is not complete warming is made the same as when the base learning value converges in the state where the warming up is complete, the normal learning value is limited more than necessary. Will be done.

Therefore, in the second embodiment, the environment in which the base learning value is updated, that is, whether the base learning value is updated in a state where it is not completely warmed up or is updated in a state where it is completely warmed up (that is, the water temperature at startup) ) To match LRCHG
For example, as shown in FIG. 20, the value of # is changed, and at the time of cold start, the value of LRCHG # is set large due to the large difference between the base learning value and the normal learning value. The value of LRCHG # is reduced at the time of restart (at the time of hot restart).

Note that simply restarting in the center of FIG. 20 is a case where the engine is stopped before the complete warm-up and is restarted immediately thereafter.

As described above, in the second embodiment, the LR is adjusted in accordance with the environment (water temperature at startup) in which the base learning value is updated.
The CHG # value is changed so that the difference between the base learning value and the normal learning value is large at the time of cold start so that the LRCHG # value is set to a large value to prevent the normal learning value from being unnecessarily limited. At the time of restarting from the state (at the time of hot restart), the effect of erroneous learning can be minimized by reducing the value of LRCHG #.

Expression (2) above (expression for updating LLDML)
In the above, the integral control method has been described, but a proportional control method or a proportional integral method may be used.

In the embodiment, the base learning value BSLDM
Although the case where the means for storing L and the normal learning value LRLDML (k) is a backup memory (for example, backup RAM) has been described, a simple RAM may be used. Even in this case, if the base learning value converges during lean operation and feedback control based on stability and then ceases during feedback control based on stability even during lean operation, the convergence value of the base learning value is set to the initial value. By starting the update of the normal learning value, the convergence of the normal learning value can be accelerated.

In the embodiment, the normal learning value is a value for each learning area, but it may be composed of one data.

Finally, 11 in FIG. 1 is lean NOx.
It is a catalyst. In the control using this catalyst, when it is necessary to once release the NOx which has been adsorbed to the limit by the storage material of this catalyst, HC, C which are unburned components in the exhaust gas
The amount of O is all NOx (NO released from the occlusion material)
x and NOx in the exhaust gas), the air-fuel ratio is made rich so as to exceed the necessary amount for reducing just enough, and immediately thereafter, the air-fuel ratio is returned to the theoretical air-fuel ratio at a predetermined recovery speed. Since it is not directly related, the description is omitted (see Japanese Patent Application No. 7-101149).

[Brief description of drawings]

FIG. 1 is a control system diagram of a first embodiment.

FIG. 2 is a characteristic diagram for explaining the principle of stability learning control.

FIG. 3 is a flowchart for explaining calculation of a target fuel-air ratio Tdml.

FIG. 4 is a flowchart for explaining reference of a learning value.

FIG. 5 is a flowchart for explaining reference of a learning value.

FIG. 6 is a characteristic diagram showing the influence on the stability learning control due to the difference in air-fuel ratio error.

FIG. 7 is a characteristic diagram of an error margin LRMGN.

FIG. 8 is a characteristic diagram for explaining an effect of an error margin LRMGN.

FIG. 9 is a flowchart for explaining detection of stability.

FIG. 10 is a flowchart for explaining calculation of a stabilized fuel-air ratio correction coefficient LLDML.

FIG. 11 is a flowchart for explaining determination of permission for updating the stabilized fuel-air ratio correction coefficient LLDML.

FIG. 12 is a waveform diagram for explaining a flag #FCNST.

FIG. 13 is a flowchart for explaining calculation of a learning limiter.

FIG. 14 is a flowchart for explaining updating of learning values.

FIG. 15 is an explanatory diagram of a base learning value update area.

FIG. 16 is a region diagram of a normal learning value.

FIG. 17 is a flowchart for explaining calculation of a fuel injection pulse width and its output.

FIG. 18 is a flowchart for explaining purge valve control.

FIG. 19 is a waveform diagram for explaining the operation of the first embodiment.

FIG. 20 is a characteristic diagram of a predetermined value LRCHG # according to the second embodiment.

FIG. 21 is a diagram corresponding to the claims of the first invention.

FIG. 22 is a diagram corresponding to claims of the second invention.

[Explanation of symbols]

1 engine body 2 control unit 4 Crank angle sensor 6 Air flow meter 7 Fuel injection valve

─────────────────────────────────────────────────── ─── Continuation of front page (51) Int.Cl. ⁷ Identification code FI F02D 45/00 324 F02D 45/00 324 340 340C F02M 25/08 301 F02M 25/08 301L (58) Fields investigated (Int.Cl . ⁷ , DB name) F02D 41/00-45/00

Claims (10)

(57) [Claims] 1. A means for initializing an air-fuel ratio during lean operation, a means for storing a normal learning value, a means for storing a base learning value, and a means for determining whether or not the base learning value has converged. Based on the result of this judgment, means for selecting the base learning value before the base learning value converges, and means for selecting the normal learning value after the base learning value converges, and a condition for performing feedback control based on stability during lean operation. Means for determining whether or not, and means for correcting the initially set air-fuel ratio during lean operation with the learning value selected when the feedback control condition based on the stability during lean operation is not satisfied based on the result of this determination , Means for controlling the amount of fuel supplied to the engine so as to obtain the corrected air-fuel ratio during lean operation, means for detecting the stability of the engine, and Means for updating the base learning value so that the stability of the engine matches the control target value of the stability when the feedback control condition based on the stability during the engine operation is satisfied and before the base learning value converges. A means for setting a value obtained by subtracting a predetermined value from the updated base learning value as a reference as a lower limit value of the normal learning value; and a feedback control condition based on the stability during lean operation based on the determination result. When established and after the base learning value has converged, a means for updating the normal learning value so that the stability of the engine matches the control target value of the stability, and the updated normal learning value is less than or equal to the lower limit value. And a means for limiting the normal learning value to this lower limit value. 2. A means for initializing an air-fuel ratio during lean operation, a means for storing a normal learning value, a means for storing a base learning value, and a means for determining whether or not the base learning value has converged. Based on the result of this judgment, means for selecting the base learning value before the base learning value converges, and means for selecting the normal learning value after the base learning value converges, and a condition for performing feedback control based on stability during lean operation. Means for determining whether or not, and means for correcting the initially set air-fuel ratio during lean operation with the learning value selected when the feedback control condition based on the stability during lean operation is not satisfied based on the result of this determination , Means for controlling the amount of fuel supplied to the engine so as to obtain the corrected air-fuel ratio during lean operation, means for detecting the stability of the engine, and Means for updating the base learning value so that the stability of the engine matches the control target value of the stability when the feedback control condition based on the stability during the engine operation is satisfied and before the base learning value converges. A means for setting a value obtained by adding a predetermined value to the updated base learning value as a reference as an upper limit value of the normal learning value; and a feedback control condition based on the stability during lean operation based on the determination result. When established and after the base learning value has converged, a means for updating the normal learning value so that the stability of the engine matches the control target value of the stability, and the updated normal learning value is greater than or equal to the upper limit value. And a means for limiting the normal learning value to this upper limit when the above condition is satisfied. 3. The engine empty space according to claim 1, wherein the predetermined value is set for the purpose of changing the environment due to a time difference between the base learning value and the normal learning value. Fuel ratio control device. 4. The air-fuel ratio control device for an engine according to claim 1, wherein the predetermined value is set according to a starting temperature. 5. The air-fuel ratio control device for an engine according to claim 4, wherein the predetermined value is increased at the cold start. 6. The engine air-fuel ratio control apparatus according to claim 4, wherein the predetermined value is reduced when the engine is restarted from a completely warmed-up state. 7. The air-fuel ratio control system for an engine according to claim 4, wherein the predetermined value is increased as the starting water temperature becomes lower when the engine is restarted from a state where the engine is not completely warmed up. 8. The engine air-fuel ratio control device according to claim 1, wherein the normal learning value is a value for each learning region. 9. The base learning value is a learning value at the time of purge cut, and the normal learning value is a learning value at the time of purge cut and at the time of not being purge cut. An air-fuel ratio control device for an engine according to any one of the above. 10. The air-fuel ratio control apparatus for an engine according to claim 1, wherein the stability detection value is an engine rotation fluctuation amount.