JP2008267883A - Abnormality diagnosis device of air-fuel ratio sensor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To appropriately diagnose abnormality of each property involved in an air/fuel ratio sensor. <P>SOLUTION: A system from a fuel injection valve to an air/fuel ratio sensor is modeled with a plurality of primary delay elements, and a plurality of first delay elements are identified based on the input u(t) and the output y(t) to the air/fuel ratio sensor. The abnormality of predetermined property of the air/fuel ratio sensor is determined based on the identified parameters. Mere abnormality in the air/fuel ratio sensor but the abnormality in the predetermined property of the air/fuel ratio sensor is determined, so, the abnormality diagnosis can be executed more precisely and in details. This is especially effective for the case when modeled with a plurality of primary delay is more accurate than modeled with a simple primary delay for an actual system. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an apparatus for diagnosing abnormality of an air-fuel ratio sensor that detects an air-fuel ratio of exhaust gas of an internal combustion engine.

  In an internal combustion engine equipped with an exhaust gas purification system using a catalyst, in order to effectively remove harmful components of exhaust gas by the catalyst, the mixture ratio of air and fuel in the air-fuel mixture burned in the internal combustion engine, that is, the air-fuel ratio is reduced. Control is essential. In order to perform such control of the air-fuel ratio, an air-fuel ratio sensor for detecting the air-fuel ratio is provided in the exhaust passage of the internal combustion engine based on the concentration of a specific component of the exhaust gas, and the detected air-fuel ratio is set to a predetermined target air-fuel ratio. Feedback control is carried out so that it can approach.

  By the way, if an abnormality such as deterioration or failure occurs in the air-fuel ratio sensor, accurate air-fuel ratio feedback control cannot be performed, and exhaust gas emission deteriorates. Therefore, it has been conventionally performed to diagnose abnormality of the air-fuel ratio sensor. In particular, in the case of an engine mounted on an automobile, it is requested by the laws and regulations of each country to detect an abnormality in the air-fuel ratio sensor in an on-board state (onboard) in order to prevent traveling in a state where exhaust gas has deteriorated. ing.

  Patent Document 1 discloses an abnormality of an air-fuel ratio sensor that detects an abnormality of the air-fuel ratio sensor based on a trajectory length or area of an air-fuel ratio sensor output that periodically increases and decreases by open-loop control. A detection device is disclosed. Further, in Patent Document 2, a system from fuel injection to an air-fuel ratio sensor output downstream of the catalyst is modeled, and the transfer function of this model is expressed by a first-order lag element and a dead time element, which are sequentially identified in this model. It is disclosed that the air-fuel ratio feedback control gain is successively changed based on the identification parameters (proportional constant, delay time constant, dead time). The identified dead time is also used for diagnosis of catalyst deterioration.

JP 2005-30358 A Japanese Patent Laid-Open No. 2004-360591

  However, although the technique described in Patent Document 1 can determine whether the air-fuel ratio sensor itself is normal or abnormal, it cannot determine which of the characteristics of the air-fuel ratio sensor is normal or abnormal. That is, the air-fuel ratio sensor includes a plurality of characteristics. However, with the technique described in Patent Document 1, it is impossible to determine which of these characteristics is abnormal. The technique described in Patent Document 2 is aimed at optimizing the control gain of the air-fuel ratio feedback control, and accompanying this, although the deterioration of the catalyst can be diagnosed, the abnormality diagnosis of the air-fuel ratio sensor is performed. I can't.

  The present invention has been made in view of such circumstances, and an object of the present invention is to provide an abnormality diagnosis device for an air-fuel ratio sensor that can preferably diagnose abnormality of individual characteristics included in the air-fuel ratio sensor. It is in.

According to the first aspect of the present invention,
An air-fuel ratio sensor abnormality diagnosis device for detecting an air-fuel ratio of exhaust gas of an internal combustion engine,
A system from the fuel injection valve to the air-fuel ratio sensor is modeled by a plurality of first-order lag elements, and parameters in the plurality of first-order lag elements are identified based on an input given to the air-fuel ratio sensor and an output obtained from the air-fuel ratio sensor. An identification means;
There is provided an abnormality diagnosis device for an air-fuel ratio sensor, comprising abnormality determination means for determining an abnormality of a predetermined characteristic of the air-fuel ratio sensor based on the parameter identified by the identification means.

  According to the first embodiment, the abnormality of the air-fuel ratio sensor is not simply determined, but the abnormality of the predetermined characteristic of the air-fuel ratio sensor is determined. Therefore, it can be determined which of the plurality of characteristics of the air-fuel ratio sensor is abnormal, and the abnormality diagnosis of the air-fuel ratio sensor can be executed more precisely and in detail. In some cases, it is more accurate to express the system from the fuel injection valve to the air-fuel ratio sensor with a plurality of first-order delays rather than a simple first-order delay. In this case, the first embodiment is very effective.

According to a second aspect of the present invention, in the first aspect,
The abnormality determination means determines at least two abnormalities among the characteristics of the air-fuel ratio sensor based on at least four parameters of the two first-order lag elements identified by the identification means.

  According to the second embodiment, since at least two abnormalities among the characteristics of the air-fuel ratio sensor are determined, abnormalities in the at least two characteristics can be individually determined, which is extremely suitable as an abnormality diagnosis of the air-fuel ratio sensor. Can be.

According to a third aspect of the present invention, in the second aspect,
The at least four parameters are at least a first gain and a second gain, a first time constant and a second time constant, and at least two of the characteristics of the air-fuel ratio sensor are at least output and responsiveness. It is characterized by being.

  Among the characteristics of the air-fuel ratio sensor, output and responsiveness are important characteristics that influence the performance of the sensor. According to the third embodiment, at least the abnormality of these two important characteristics can be diagnosed, so that it is extremely suitable as an abnormality diagnosis of the air-fuel ratio sensor.

According to a fourth aspect of the present invention, in the third aspect,
The identification means identifies the first gain and the second gain, and the first time constant and the second time constant at the same time.

According to a fifth aspect of the present invention, in the fourth aspect,
The abnormality determination means simultaneously determines an abnormality in the output of the air-fuel ratio sensor and the responsiveness based on the identified first gain and second gain, the first time constant and the second time constant. To do.

  According to the fourth and fifth embodiments, the identification of the four parameters is performed simultaneously and the two abnormality determinations are performed simultaneously, so that the identification and abnormality determination can be performed efficiently.

According to a sixth aspect of the present invention, in the third aspect,
The identifying means identifies a first gain and a second gain, a first time constant and a second time constant in the two first-order lag elements;
The abnormality determining means is
When the first gain is greater than a predetermined first gain increase abnormality determination value or the second gain is greater than a predetermined second gain increase abnormality determination value, the air-fuel ratio sensor is determined to be an output increase abnormality. ,
When the first gain is smaller than a predetermined first gain reduction abnormality determination value or the second gain is smaller than a predetermined second gain reduction abnormality determination value, the air-fuel ratio sensor is determined as an output decrease abnormality. ,
When the first time constant is larger than a predetermined first time constant abnormality determination value or the second time constant is larger than a predetermined second time constant abnormality determination value, the air-fuel ratio sensor is determined to be responsive abnormality. It is characterized by judging.

  The first gain, the second gain, the first time constant, and the second time constant in the two first-order lag elements have a numerical range that can be regarded as normal for each of them. According to the sixth aspect, when any of the four parameters is out of the normal range, it is determined that the output of the air-fuel ratio sensor or the responsiveness is abnormal, so that the abnormality diagnosis can be executed more precisely.

According to a seventh aspect of the present invention, in any one of the first to sixth aspects,
The system is characterized by being modeled by the sum of a plurality of first-order lag elements.

  In some cases, the system from the fuel injection valve to the air-fuel ratio sensor can be modeled by the sum of a plurality of first-order lag elements. In this case, the seventh embodiment is very effective.

According to an eighth aspect of the present invention, in any one of the first to seventh aspects,
There is provided a dead time correcting means for calculating a dead time from the input to the output and shift-correcting at least one of the input and the output by the dead time.

  As a result, the influence of transport delay can be eliminated, and the parameter identification accuracy can be improved.

According to a ninth aspect of the present invention, in the eighth aspect,
The dead time correction means calculates the dead time according to a predetermined map or function based on at least one parameter relating to the operating state of the internal combustion engine.

According to a tenth aspect of the present invention, in the eighth aspect,
The dead time correction means calculates a variance value between the input and the output, and when the variance value peak of the output is larger than a predetermined value, a time difference between the variance value peak of the input and the variance value peak of the output is calculated. Based on this, the dead time is calculated.

In an eleventh aspect of the present invention, in the tenth aspect,
The dead time correction means calculates the dead time based on a time difference between extreme values of the input and the output when the output dispersion value peak is equal to or less than the predetermined value.

According to a twelfth aspect of the present invention, in the eighth aspect,
The dead time correction means calculates a first dead time according to a predetermined map based on at least one parameter relating to the operating state of the internal combustion engine, and a time difference of a dispersion value peak between the input and the output, or the Based on the time difference between the extreme values of the input and the output, a second dead time is calculated, and when the amount of deviation of the second dead time with respect to the first dead time is larger than a predetermined value, the second dead time The time is determined as the final dead time, and the map data is updated with the second dead time.

According to a thirteenth aspect of the present invention, in any one of the first to twelfth aspects,
Bias correcting means for correcting at least one of the input and the output so as to remove a bias between the input and the output is provided.

  As a result, robustness against load fluctuation, learning deviation, and the like can be improved.

In a fourteenth aspect of the present invention, in any one of the first to thirteenth aspects,
Fuel correction means for correcting the input based on the amount of fuel wall surface adhesion and the amount of evaporation is provided.

  This makes it possible to improve parameter identification accuracy.

According to a fifteenth aspect of the present invention, in any one of the first to fourteenth aspects,
Active control means for executing active control for forcibly oscillating the input is provided, and the identification means identifies a parameter in the plurality of first-order lag elements based on the input and the output during the active control. It is characterized by.

  According to the present invention, an excellent effect that an abnormality of each characteristic included in the air-fuel ratio sensor can be suitably diagnosed is exhibited.

  The best mode for carrying out the present invention will be described below with reference to the accompanying drawings.

  FIG. 1 is a schematic view of an internal combustion engine according to the present embodiment. As shown in the figure, the internal combustion engine 1 generates power by burning a mixture of fuel and air inside a combustion chamber 3 formed in a cylinder block 2 and reciprocating a piston 4 in the combustion chamber 3. To do. The internal combustion engine 1 of the present embodiment is a vehicular multi-cylinder engine (for example, a four-cylinder engine, only one cylinder is shown), and is a spark ignition internal combustion engine, more specifically a gasoline engine.

  In the cylinder head of the internal combustion engine 1, an intake valve Vi for opening and closing the intake port and an exhaust valve Ve for opening and closing the exhaust port are provided for each cylinder. Each intake valve Vi and each exhaust valve Ve are opened and closed by a camshaft (not shown). A spark plug 7 for igniting the air-fuel mixture in the combustion chamber 3 is attached to the top of the cylinder head for each cylinder.

  The intake port of each cylinder is connected to a surge tank 8 serving as an intake air collecting chamber via a branch pipe for each cylinder. An intake pipe 13 that forms an intake manifold passage is connected to the upstream side of the surge tank 8, and an air cleaner 9 is provided at the upstream end of the intake pipe 13. An air flow meter 5 for detecting the intake air amount and an electronically controlled throttle valve 10 are incorporated in the intake pipe 13 in order from the upstream side. An intake passage is formed by the intake port, the branch pipe, the surge tank 8 and the intake pipe 13.

  An injector (fuel injection valve) 12 that injects fuel into the intake passage, particularly into the intake port, is provided for each cylinder. The fuel injected from the injector 12 is mixed with intake air to form an air-fuel mixture. The air-fuel mixture is sucked into the combustion chamber 3 when the intake valve Vi is opened, compressed by the piston 4, and ignited and burned by the spark plug 7. It is done.

On the other hand, the exhaust port of each cylinder is connected to an exhaust pipe 6 forming an exhaust collecting passage through a branch pipe for each cylinder. An exhaust passage is formed by the exhaust port, the branch pipe, and the exhaust pipe 6. Catalysts 11 and 19 made of a three-way catalyst are attached to the exhaust pipe 6 on the upstream side and the downstream side. Air-fuel ratio sensors 17 and 18 for detecting the air-fuel ratio of the exhaust gas, that is, pre-catalyst sensors and post-catalyst sensors 17 and 18 are installed at positions before and after the upstream catalyst 11, respectively. These pre-catalyst sensors and post-catalyst sensors 17 and 18 detect the air-fuel ratio based on the oxygen concentration in the exhaust gas. The pre-catalyst sensor 17 is a so-called wide-area air-fuel ratio sensor, can continuously detect an air-fuel ratio over a relatively wide area, and outputs a current signal proportional to the air-fuel ratio. On the other hand, the post-catalyst sensor 18 is a so-called O ₂ sensor, and has a characteristic that the output voltage changes suddenly at the theoretical air-fuel ratio.

  The spark plug 7, the throttle valve 10, the injector 12, and the like described above are electrically connected to an electronic control unit (hereinafter referred to as ECU) 20 as control means. The ECU 20 includes a CPU, a ROM, a RAM, an input / output port, a storage device, and the like, all not shown. In addition to the air flow meter 5, the pre-catalyst sensor 17, and the post-catalyst sensor 18, the ECU 20 includes a crank angle sensor 14 that detects the crank angle of the internal combustion engine 1 and an accelerator that detects the accelerator opening, as shown in the figure. The opening sensor 15 and other various sensors are electrically connected via an A / D converter or the like (not shown). The ECU 20 controls the ignition plug 7, the throttle valve 10, the injector 12, etc. so as to obtain a desired output based on the detection values of various sensors, etc., and the ignition timing, fuel injection amount, fuel injection timing, throttle opening. Control the degree etc. The throttle opening is normally controlled to an opening corresponding to the accelerator opening.

  The catalysts 11 and 19 simultaneously purify NOx, HC and CO when the air-fuel ratio A / F of the exhaust gas flowing into the catalyst 11 and 19 is the stoichiometric air-fuel ratio (stoichiometric, for example, A / F = 14.6). In response to this, the ECU 20 controls the air-fuel ratio so that the air-fuel ratio A / F of the exhaust gas flowing into the catalysts 11 and 19 becomes equal to the stoichiometric air-fuel ratio during normal operation of the internal combustion engine (so-called stoichiometric). control). Specifically, the ECU 20 sets a target air-fuel ratio A / Ft that is equal to the stoichiometric air-fuel ratio, and makes the basic injection amount such that the air-fuel ratio of the air-fuel mixture flowing into the combustion chamber 3 matches the target air-fuel ratio A / Ft. Is calculated. Then, the basic injection amount is feedback-corrected according to the difference between the actual air-fuel ratio detected by the pre-catalyst sensor 17 and the target air-fuel ratio A / Ft, and the injector 12 is operated for the energization time corresponding to the corrected injection amount. Energize (turn on). As a result, the air-fuel ratio of the exhaust gas supplied to the catalysts 11 and 19 is maintained near the stoichiometric air-fuel ratio, and the maximum purification performance is exhibited in the catalysts 11 and 19. Thus, the ECU 20 feedback-controls the air-fuel ratio (fuel injection amount) so that the actual air-fuel ratio detected by the pre-catalyst sensor 17 approaches the target air-fuel ratio A / Ft. The post-catalyst sensor 18 is provided to correct the air-fuel ratio deviation in such air-fuel ratio feedback control.

  Next, abnormality diagnosis of the air-fuel ratio sensor in the present embodiment will be described. The object of diagnosis in this embodiment is an air-fuel ratio sensor installed on the upstream side of the upstream catalyst 11, that is, a pre-catalyst sensor 17.

  In the abnormality diagnosis, the system from the injector 12 to the pre-catalyst sensor 17 is modeled by a plurality of first-order lag elements, and based on the input given to the pre-catalyst sensor 17 and the output obtained from the pre-catalyst sensor 17, The parameters in the first order lag element are identified (estimated). Then, based on the identified parameter, an abnormality of a predetermined characteristic of the pre-catalyst sensor 17 is determined.

  As an input, the ratio Ga / Q between the fuel injection amount Q calculated based on the energization time of the injector 12 and the intake air amount Ga calculated based on the output of the air flow meter 5, that is, the input air-fuel ratio A / Fu is Used. Hereinafter, the input is represented by u (t) (u (t) = A / Fu = Ga / Q). On the other hand, the air-fuel ratio converted from the output current value of the pre-catalyst sensor 17, that is, the output air-fuel ratio A / Fy is used as the output. Hereinafter, the output is represented by y (t) (y (t) = A / Fy). A parameter in a plurality of first-order lag elements is identified from how the output y (t) is output when the input u (t) is applied to the pre-catalyst sensor 17, and a predetermined value of the pre-catalyst sensor 17 is determined based on the identified parameter. A characteristic abnormality is determined.

  As shown in FIG. 2, in the present embodiment, active control for forcibly oscillating the input u (t) is executed at the time of abnormality diagnosis of the air-fuel ratio sensor. In this active control, the target air-fuel ratio A / Ft, and hence the input u (t), is vibrated at a constant period so as to swing by the same amplitude on the lean side and the rich side with a predetermined center air-fuel ratio A / Fc as a boundary. Along with this, the air-fuel ratio detected by the pre-catalyst sensor 17, that is, the output y (t) is vibrated so as to follow the vibration of the input u (t). The center air-fuel ratio A / Fc in the vibration of the target air-fuel ratio A / Ft and the input u (t) is made equal to the theoretical air-fuel ratio, and the amplitude of the vibration is larger than that in the normal air-fuel ratio control. 5 etc.

  The reason why the active control is executed at the time of abnormality diagnosis is to make it easier to diagnose the abnormality of the pre-catalyst sensor 17 by changing the air-fuel ratio more drastically and suddenly than usual, and the active control is performed in a steady state of the engine. This is because each control amount and each detected value is stabilized and diagnostic accuracy is improved because it is executed during operation. However, abnormality diagnosis may be executed during normal air-fuel ratio control.

  Here, before describing a plurality of first-order lags, the description will be given assuming that the system is a simple first-order lag system. As shown in FIG. 2, when a step-like input u (t) is given, the waveform of the output y (t) becomes a waveform with a first-order lag. In the figure, L is a dead time based on a transport delay from the input u (t) to the output y (t). This dead time L corresponds to the time difference from the time when the air-fuel mixture existing in the combustion chamber 3 in the cylinder burns to the time when the exhaust gas based on this combustion reaches the pre-catalyst sensor 17. Practically, the start point of the dead time L can be set, for example, at the time of ignition or when the exhaust valve is opened. However, since the time from ignition to opening the exhaust valve is extremely short compared to the entire dead time, there is no particular problem in terms of accuracy even if it is set at any time.

  Here, it is assumed that the system from the injector 12 to the pre-catalyst sensor 17 is modeled by a first-order lag element G (s) = k / (1 + Ts). k is a gain of the pre-catalyst sensor 17, and T represents a time constant of the pre-catalyst sensor 17. The gain k is a parameter related to output among the characteristics of the pre-catalyst sensor 17, while the time constant T is a parameter related to responsiveness among the characteristics of the pre-catalyst sensor 17. In FIG. 2, a solid line representing the output y (t) indicates a case where the pre-catalyst sensor 17 is normal. On the other hand, when an abnormality occurs in the output characteristics of the pre-catalyst sensor 17, the gain k becomes larger than normal, and the sensor output increases (expands) as indicated by a, or the gain k becomes smaller than normal. As shown by b, the sensor output decreases (reduces). Therefore, an increase abnormality or a decrease abnormality of the sensor output can be specified by comparing the identified gain k with a predetermined value. On the other hand, if an abnormality occurs in the responsiveness of the pre-catalyst sensor 17, in most cases, the time constant T becomes larger than normal, and the sensor output comes out with a delay as shown by c. Therefore, the responsiveness abnormality of the sensor can be specified by comparing the identified time constant T with a predetermined value.

  Actually, the waveform of the output y (t) may be a waveform based on a plurality of primary delays instead of a simple primary delay waveform as shown in FIG. That is, when modeling a system, it is convenient to approximate a simple first-order lag system, but there are cases in which parameter identification and abnormality diagnosis can be performed more accurately when represented by a plurality of first-order lags. Corresponding to such a case, the present invention performs modeling using a plurality of first-order lag elements. Hereinafter, a case where two first order lag elements are used will be described as an example using a plurality of first order lag elements.

  In the present embodiment, the transfer function H (s) using two first order lag elements is expressed by the following equation.

That is, the transfer function H (s) includes two first-order lag elements, that is, a first first-order lag element H ₁ (s) = k ₁ / (1 + T ₁ s) and a second first-order lag element H ₂ (s) = k. ₂ / (1 + T ₂ s). Hereinafter, k ₁ and k ₂ will be referred to as a first gain and a second gain, respectively, and T ₁ and T ₂ will be referred to as a first time constant and a second time constant, respectively. In general, the transfer function H (s) is represented by the sum of _n first-order lag elements H ₁ (s),... H _n (s) from the first to the n-th (n ≧ 2). Is done.

In the present embodiment, as will be described below, these parameters k ₁ , k ₂ , T ₁ , and T ₂ are sequentially identified simultaneously, and the output abnormality and responsiveness abnormality of the pre-catalyst sensor 17 are simultaneously determined. Therefore, the abnormality of the two characteristics of the pre-catalyst sensor 17 can be diagnosed simultaneously and individually.

  Identification of these parameters is executed by the ECU 20 according to the following basic algorithm.

  First, since Expression (1) is expressed as a continuous system, it is expressed as a discrete system with a sampling interval Δ. Substituting equation (2) into equation (1) and bilinear transformation is performed to obtain equation (3).

  Here, (t) represents the current sample time, (t-1) represents the previous sample time, and (t-2) represents the last sample time.

In this way, the parameters k ₁ , k ₂ , T ₁ , T ₂ are sequentially identified by the sequential least square method, and these values are updated at every sampling interval Δ. In this sequential identification method, a large number of sample data is acquired and temporarily stored, and the calculation load can be reduced as compared with the method of performing identification, and the capacity of the buffer for temporarily storing data can be reduced. It is suitable for mounting on an ECU (particularly an automotive ECU).

Based on the parameters k ₁ , k ₂ , T ₁ , T ₂ thus identified, the ECU 20 performs an abnormality determination as follows. First, the identified first time constant T ₁ is greater than a predetermined first time constant abnormality determination value Ts ₁ , or the identified second time constant T ₂ is a predetermined second time constant abnormality. When it is larger than the determination value Ts ₂ , it is determined that the pre-catalyst sensor 17 is responsive abnormality. On the other hand, the identified first time constant T ₁ is equal to or less than the first time constant abnormality determination value Ts ₁ , and the identified second time constant T ₂ is the second time constant abnormality determination value Ts _2. In the following cases, the pre-catalyst sensor 17 is determined to be normal with respect to responsiveness.

Also, the identified first gain k ₁ is greater than a predetermined first gain increase abnormality determination value Ksh ₁ , or the identified second gain k ₂ is a predetermined second gain increase abnormality determination value. If it is greater than ksh ₂ , it is determined that the pre-catalyst sensor 17 has an abnormal output increase. Further, the identified first gain k ₁ is smaller than a predetermined first gain reduction abnormality determination value Ksl ₁ (<Ksh ₁ ), or the identified second gain k ₂ is a predetermined _second gain. When it is smaller than the gain reduction abnormality determination value ksl ₂ (<Ksh ₂ ), it is determined that the pre-catalyst sensor 17 has an output decrease abnormality. On the other hand, the identified first gain k ₁ is equal to or less than the first gain increase abnormality determination value Ksh _{1 and} equal to or greater than the first gain decrease abnormality determination value Ksl ₁ , and the identified second gain k _2. Is less than or equal to the second gain increase abnormality determination value Ksh ₂ and greater than or equal to the second gain decrease abnormality determination value Ksl ₂ , the pre-catalyst sensor 17 is determined to be normal with respect to the output.

As described above, according to the abnormality diagnosis according to the present embodiment, the abnormality of the individual characteristics of the air-fuel ratio sensor is diagnosed, not just the abnormality of the air-fuel ratio sensor itself. Then, abnormalities in the two sensor characteristics of output and responsiveness are diagnosed, particularly simultaneously and individually. Therefore, it is possible to realize a very suitable abnormality diagnosis for the air-fuel ratio sensor. Furthermore, regarding the output abnormality, the normality / abnormality of the two gains k ₁ and k ₂ are individually determined, and for the response abnormality, the normality / abnormality of the two time constants T ₁ and T ₂ are individually determined. This makes it possible to diagnose the characteristic abnormality in detail and improve the diagnostic accuracy.

FIG. 3 shows the test results in which the gains k ₁ and k ₂ and the time constants T ₁ and T ₂ are sequentially identified by the above-described method using the successive least square method. This test was performed while the vehicle was running at a steady speed of 60 km / h with the engine mounted on the vehicle. FIG. 3A shows an input (broken line) and an output (solid line) that are forcibly vibrated by active control. The input and output shown in the figure are values after performing each correction described later. FIGS. 3B and 3C show transitions of identification values of gain and time constant, respectively.

The gain and time constant are updated every sampling time and gradually converge to a constant value. According to this test result, the gain and time constant converge in about 5 seconds from the start of sampling of input / output data (t = 0). Therefore, in practice, a time point at which such convergence is observed, for example, a time point 5 seconds after the start of sampling is determined in advance as a determination time, and the ECU 20 identifies the identification values k ₁ , k ₂ , T _{1 at the} determination time. , T ₂ are acquired, and the acquired identification values k ₁ , k ₂ , T ₁ , T ₂ are compared with the above-described abnormality determination values, and output and responsiveness abnormality determinations are made.

According to the test results, the identified value after the convergence is k ₁ is about 1.2, k ₂ is approximately 0, T ₁ is about 0.16, T ₂ was about 0. In other words, as a result, the result was almost the same as the case of a simple first-order lag. However, there is a possibility that some types of air-fuel ratio sensor does not become k _2, T ₂ is a near 0, k _1, who k _2, T ₂ rather than T ₁ is, the sensor deterioration, easily deviates from the normal value A case can also be assumed. In this case, the present invention is particularly effective. Although two examples of the first-order delay are shown here, three first-order delays can be used in accordance with the actual characteristics of the air-fuel ratio sensor.

  By the way, an actual engine has various disturbances such as load fluctuations, and the identification accuracy and robustness cannot be improved unless these are properly considered. For this reason, in the abnormality diagnosis according to the present embodiment, various corrections for the following input / output are performed.

FIG. 4 is a block diagram of the abnormality diagnosis system, and this system is constructed in the ECU 20. In order to identify the parameters k ₁ , k ₂ , T ₁ , and T ₂ as described above in the identification unit (identification unit) 50, an input calculation unit (fuel correction unit) 52, a bias correction unit (bias correction unit) 54, and A dead time correction unit (dead time correction means) 56 is provided. Note that an active control flag output unit 58 is also provided because abnormality diagnosis is performed during active control. An abnormality determination unit (abnormality determination unit) 60 is also provided to perform each abnormality determination based on the parameters identified by the identification unit 50.

  The input calculation unit 52 calculates the input u (t). In the above example, the input u (t) is the ratio of the fuel injection amount Q calculated based on the energization time of the injector 12 and the intake air amount Ga calculated based on the output of the air flow meter 5 (that is, the input u (t) Air / fuel ratio) Ga / Q. However, here, the fuel injection amount Q calculated based on the injector energization time is corrected based on the fuel wall adhesion amount and the evaporation amount, and the input u (t) is calculated using the corrected fuel injection amount Q ′. Calculated. u (t) = Ga / Q ', and as a result, the input u (t) is corrected based on the amount of fuel adhering to the wall and the amount of evaporation.

  When fuel is injected from the injector 12, most of the fuel is sucked into the in-cylinder combustion chamber 3, but the remaining portion adheres to the inner wall surface of the intake port and does not enter the combustion chamber 3. Therefore, if the fuel amount injected from the injector 12 is fi, and the fuel adhesion rate for all cylinders is R (<1), the amount of the injected fuel amount fi that adheres to the wall surface of the intake port is R · fi, The amount entering the combustion chamber 3 is represented by (1-R) · fi.

  On the other hand, some of the fuel adhering to the wall surface of the intake port evaporates and enters the combustion chamber 3 in the next intake stroke, but the rest remains and remains attached. Therefore, if the fuel amount adhering to the wall surface of the intake port is fw and the fuel residual ratio for all cylinders is P (<1), the amount of fuel adhering to the wall surface of the wall surface adhering fuel amount fw is P · fw, The amount that enters the combustion chamber 3 is represented by (1-P) · fw.

Each cycle of intake, compression, expansion, and exhaust of the 4-cycle engine is completed once to make one cycle (that is, 1 cycle = 720 ° crank angle), the current cycle is ks, and the next cycle is ks + 1. Further, when the fuel amount entering the in-cylinder combustion chamber 3 is fc, the following relationship is established.
fw (ks + 1) = P.fw (ks) + R.fi (ks) (16)
fc (ks) = (1-P) .fw (ks) + (1-R) .fi (ks) (17)

  The meaning of the equation (16) is that the wall-attached fuel amount fw (ks + 1) of the next cycle is the residual amount P · fw (ks) of the wall-attached fuel amount fw (ks) of the current cycle and the injected fuel of the current cycle. That is, it is expressed as the sum of the amount fi (ks) and the wall surface adhesion R · fi (ks). Further, the expression (17) means that the inflow fuel amount fc (ks) flowing into the combustion chamber 3 in the current cycle is the evaporation amount (1-) of the wall surface adhering fuel amount fw (ks) in the current cycle. P) · fw (ks) and the sum (1-R) · fi (ks) of the injected fuel amount fi (ks) of this cycle that flows directly into the combustion chamber 3 without adhering to the wall surface. That is.

  Thus, when calculating the input u (t), the value of the inflow fuel amount fc is used as the value of the fuel injection amount Q ′. This inflow fuel amount fc is nothing but a correction of the fuel injection amount calculated based on the energization time of the injector 12 based on the amount of fuel adhering to the wall and the evaporation amount. Therefore, by using the value of the inflow fuel amount fc for the calculation of the input u (t), the input value can be set to a more accurate value close to the actual situation, and the parameter identification accuracy can be improved. .

  Note that the higher the engine temperature and the intake air temperature, the more the fuel vaporization is promoted, so the fuel adhesion amount decreases and the fuel evaporation amount increases. Therefore, the fuel residual rate P and the fuel adhesion rate R are preferably functions of at least one of the engine temperature (or water temperature) and the intake air temperature. The correction based on the fuel wall adhesion amount and the evaporation amount as described herein is referred to as “fuel dynamics correction”.

  FIG. 5 shows a test result in which a difference in input during active control is examined when there is no fuel dynamics correction (dashed line) and when there is a fuel dynamics correction (solid line). As shown in the circle in the figure, the waveform of the input air-fuel ratio tends to be slightly rounded immediately after the input air-fuel ratio is reversed, compared to the case where there is no fuel dynamics correction.

  Next, the bias correction unit 54 will be described. In the bias correction unit 54, both the input u (t) and the output y (t) are shift-corrected so as to remove the bias between the input u (t) and the output y (t).

  When the input u (t) and the output y (t) are biased to the lean side or the rich side with respect to one side (deviation) due to factors such as load fluctuation, learning deviation, and sensor value deviation. There is. FIG. 6 is a test result showing the state of the bias. In the figure, u (t) c and y (t) c represent values obtained by passing the input u (t) and the output y (t) through a low-pass filter, or their moving averages. Since the air-fuel ratio detected by the pre-catalyst sensor 17 is controlled to be close to the theoretical air-fuel ratio (A / F = 14.6), the output y (t) that is the detection value of the pre-catalyst sensor 17 is theoretically. It fluctuates around the air-fuel ratio, and the value passed through the low-pass filter or the moving average y (t) c is also kept near the theoretical air-fuel ratio. On the other hand, the input u (t) is biased to the lean side in the illustrated example for the reason described above.

  Since it is not preferable to perform identification in such a bias state, a correction that removes the bias is performed. Specifically, as shown in FIG. 7, the data of the input u (t) and the output y (t) are passed through a low-pass filter or a moving average is calculated, and the bias values u (t) c, y ( t) c is calculated sequentially. Then, sequentially, the difference Δu (t) (= u (t) −u (t) c) between the input u (t) and its bias value u (t) c, and the output y (t) and its bias A difference Δy (t) (= y (t) −y (t) c) from the value y (t) c is calculated, and these differences Δu (t) and Δy (t) are replaced with zero reference values. These differences Δu (t) and Δy (t) are collectively displayed as ΔA / F.

  Thus, the bias is removed, and the input / output values Δu (t) and Δy (t) after the bias correction are changed to zero reference values as shown in FIG. That is, the center of both fluctuations is set to zero, and influences such as load fluctuations and learning deviation can be eliminated. As a result, robustness against load fluctuation, learning deviation, and the like can be improved.

  In this example, both the input and output are corrected, and the bias is removed by adjusting the input and output fluctuation centers to zero. However, other methods can also be used. For example, it is possible to correct only the input and align the fluctuation center with the output fluctuation center, or vice versa. The correction target may be at least one of input and output.

  Next, the dead time correction unit 56 will be described. As described above, there is a dead time L due to transport delay between the input u (t) and the output y (t). However, in order to accurately identify the model parameter, it is preferable to perform correction so as to remove this dead time L. Therefore, such a correction is performed by the dead time correction unit 56. Specifically, the dead time L is calculated by the method described later, and the input u (t) is delayed so as to approach the output y (t) by this dead time L.

  FIG. 9 shows the input before the dead time correction (broken line), the input after the dead time correction (solid line), and the output (dashed line). Note that values after bias correction are used as input and output. When the input is delayed by the dead time L, the input vibration and the output vibration are synchronized without a time difference, thereby improving the identification accuracy of the model parameters.

  As a first aspect of the dead time calculation, there is a method of calculating the dead time according to a predetermined map or function based on at least one parameter relating to the engine operating state. FIG. 10 shows an example of such a dead time calculation map. In this map, the dead time L is calculated based on the detected value of the engine speed Ne. The engine speed Ne is calculated by the ECU 20 based on the output of the crank angle sensor 14.

  There is the following as a second mode of dead time calculation. First, the variance values of the input and output during active control are sequentially obtained by the following equations.

η is an input or output value, and η _avg is a moving average of M times, that is, an average value of data from this time (t) to (M−1) times before (t− (M−1)). For example, M is 5 or the like. The greater the change in input or output, the greater the variance value.

  FIG. 11 shows a test result regarding the dead time correction, and shows a case of a normal sensor. The upper graph shows a: input when there is no fuel dynamics correction, b: input when there is fuel dynamics correction, and c: output. These inputs and outputs are values after bias correction. The middle graph shows d: variance value of input when there is fuel dynamics correction, and e: variance value of output. In the lower graph, the sawtooth waveform f is the dead time counter value, the horizontal line g at the high position is the dead time calculated as described later, and the horizontal line h at the lower position is the dead time g ¼. Each of the values is shown.

  FIG. 12 shows only b, c, d, and e in FIG. 11 in a simplified manner. As can be seen from FIG. 12, the input variance value d and the output variance value e generate peaks dp and ep at the timing when the input b and the output c are inverted. Therefore, the time difference (ep−dp) between these peaks is calculated as the dead time g. Returning to FIG. 11, when the input dispersion value peak dp occurs, the dead time counter f starts counting time from the time when the input dispersion value peak dp occurs. Then, when the output dispersion value peak ep occurs, the count is stopped and the count value is held as a dead time g. This dead time g is updated every inversion of the input, and the dead time h after annealing is calculated for each inversion. The reason for calculating the dead time h after annealing is to remove the influence of noise. The value of the dead time h after annealing will eventually converge to a certain value. Therefore, the dead time h after the annealing is acquired at the time after the predetermined time when the dead time h after the annealing converges to a substantially constant value from the start of the active control, and the obtained value Is determined as the final dead time L.

  By the way, although the above calculation method demonstrated by FIG.11 and FIG.12 is a case of a normal sensor, when it is a case of an abnormal sensor, it is not necessarily appropriate to employ | adopt the same method. That is, as shown in FIGS. 13 and 14, for example, in the case of an abnormal sensor in which a response delay occurs, a sufficiently large value cannot be obtained as the output dispersion value e, and the timing at which the peak ep appears is also obtained. The error increases.

  Therefore, the output dispersion value peak ep is compared with a predetermined threshold value eps, and when the dispersion value peak ep is larger than the threshold value eps (in the case of FIGS. 11 and 12), the input / output is performed as described above. A time difference (ep−dp) between the dispersion value peaks dp and ep is defined as a dead time g. On the other hand, as shown in FIGS. 13 and 14, when the output dispersion value peak ep is less than or equal to the threshold value eps, the time difference (cp−bp) between the extreme values bp and cp of the input and output b and c itself is wasted. Let time g. Thereby, even in the case of an abnormal sensor, the dead time can be calculated accurately.

  Now, it is possible to calculate the dead time using only one of the first and second modes and correct the dead time of the input. In the third mode described below, the first mode is used. And calculating the dead time using both of the second aspect. In the third aspect, the first dead time calculated from the map according to the first aspect is compared with the second dead time calculated from the dispersion value or the extreme value according to the second aspect, and both are approaching. If so, the first dead time calculated from the map is used. On the other hand, if the two deviate from each other, the second dead time calculated from the variance value or the extreme value is used, and the map data is updated using the second dead time. Originally, the optimum time delay value does not deviate greatly from the map value, but the optimum time delay value may deviate greatly from the map value for some reason. On the other hand, the second dead time calculated from the variance value or the extreme value can be said to be an actual value reflecting the current situation. Therefore, by performing such a map update, it becomes possible to cope with unforeseen situations, and it is possible to always maintain the map data at an optimum value in accordance with the current situation.

  FIG. 15 schematically shows the procedure of the third aspect. First, in step S101, according to the first mode, a first dead time L1 is calculated from a map as shown in FIG. Next, in step S102, according to the second mode, the second dead time L2 is calculated from the input / output variance or extreme value. Thereafter, in step S103, a dead time deviation amount L12 which is an absolute value of the difference between the first and second dead times L1 and L2 is calculated, and the dead time deviation amount L12 is compared with a predetermined value L12s. If the dead time deviation amount L12 is equal to or smaller than the predetermined value L12s, the first dead time L1 calculated from the map is determined as the final dead time L in step S104, assuming that the deviation between the two is small.

  On the other hand, if the dead time deviation amount L12 is larger than the predetermined value L12s, the second dead time L2 calculated from the dispersion value or extreme value of the input / output air-fuel ratio is determined as the final value in step S105, assuming that the deviation between the two is large. The dead time L is determined. In step S106, the first dead time L1 in the map corresponding to the second dead time L2 is replaced with the second dead time L2, and the map data is updated.

  By the way, in the above-described dead time correction, the input is delayed by the dead time and the correction is performed so that the output coincides with the timing. However, other methods can be adopted. For example, if you do not perform sequential identification, for example, if you acquire a lot of sample data and store it temporarily, then perform identification, you can make the output coincide with the timing by delaying the output by the dead time or delay the input. In addition, the output can be advanced and the timings of both can be matched. The correction target may be at least one of input and output.

  3A shows the input / output data after the dead time correction unit 56 has performed the dead time correction.

  Next, an air-fuel ratio sensor abnormality diagnosis procedure including all the above-described corrections will be described with reference to FIG. First, in step S201, active control for forcibly oscillating the input is executed. In step S202, the value of the input u (t) after the fuel dynamics correction is calculated. In step S203, FIGS. As shown in FIG. 5, the values of the input u (t) and the output y (t) are shift-corrected so that the bias between the input and output is eliminated.

In the following step S204, the dead time L is calculated, and the value of the input u (t) after the bias correction is shift-corrected by the dead time L so that the dead time L is eliminated in step S205. In the next step S206, the time constant T which is a model parameter based on the input u (t) after the dead time correction obtained in step S205 and the output y (t) after the bias correction obtained in step S203. ₁ and T ₂ and gains k ₁ and k ₂ are identified. In step S207, the identified parameters T ₁ , T ₂ , k ₁ , k ₂ are compared with each abnormality determination value corresponding to each parameter, and the response of the pre-catalyst sensor 17 and the normality / abnormality of the output are compared. Is determined.

The preferred embodiment of the present invention has been described in detail above, but various other embodiments of the present invention are conceivable. For example, the above-mentioned internal combustion engine is an intake port (intake passage) injection type, but the present invention can also be applied to a direct injection type engine. However, in this case, it is not necessary to consider fuel adhesion to the wall surface of the intake passage, so that fuel dynamics correction is omitted. Although in the above embodiment shows an example of application to a so-called wide-range air-fuel ratio sensor, the present invention is also applicable to a so-called O ₂ sensor, such as a post-catalyst sensor 18. A sensor for detecting the air-fuel ratio of exhaust gas including such an O ₂ sensor is referred to as an air-fuel ratio sensor according to the present invention. In the embodiment, abnormality of two characteristics of output and responsiveness among the characteristics of the air-fuel ratio sensor is diagnosed. However, the present invention is not limited to this, and abnormality of one or more characteristics may be diagnosed. . Similarly, the parameter of the plurality of first-order lag elements to be identified may be only one of the gain and the time constant, or another parameter may be added in addition to the gain and the time constant. In the embodiment, a plurality of parameters are simultaneously identified and a plurality of abnormalities are simultaneously determined. However, the present invention is not limited thereto, and a plurality of parameters may be identified with a time difference, or a plurality of abnormalities may be determined with a time difference. You may go.

  The embodiment of the present invention is not limited to the above-described embodiment, and includes all modifications, applications, and equivalents included in the concept of the present invention defined by the claims. Therefore, the present invention should not be construed as being limited, and can be applied to any other technique belonging to the scope of the idea of the present invention.

It is the schematic of the internal combustion engine which concerns on this embodiment. It is a graph which shows the mode of the change of the input and output at the time of active control, and is a case where it is assumed that it is a first order lag system. It is a graph which shows the result of having identified the gain and the time constant. It is a block diagram of an abnormality diagnosis system. This is a test result comparing the input with and without the fuel dynamics correction. It is a test result which shows the mode of a change with an input and an output, and is the state before bias correction. It is the schematic for demonstrating the method of bias correction. It is a test result which shows the mode of a change with an input and an output, and is the state after bias correction. It is a test result which shows the input before and behind dead time correction. It is a dead time calculation map. It is a test result for demonstrating the 2nd aspect of dead time calculation, and is a case of a normal sensor. It is the schematic corresponding to FIG. 11 for demonstrating a dead time calculation method. It is a test result for demonstrating the 2nd aspect of dead time calculation, and is a case of an abnormal sensor. It is the schematic corresponding to FIG. 13 for demonstrating a dead time calculation method. It is a flowchart which concerns on the 3rd aspect of dead time calculation. It is a flowchart which shows roughly the procedure of abnormality diagnosis of an air fuel ratio sensor.

Explanation of symbols

1 Internal combustion engine 3 Combustion chamber 5 Air flow meter 6 Exhaust pipe 7 Spark plug 12 Injector 14 Crank angle sensor 15 Accelerator opening sensor 17 Pre-catalyst sensor 20 Electronic control unit (ECU)
50 identification unit 52 input calculation unit 54 bias correction unit 56 dead time correction unit 58 active control flag output unit 60 abnormality determination unit A / F air-fuel ratio u (t) input y (t) output k ₁ first gain k ₂ first 2 gain T ₁ first time constant T ₂ second time constant L dead time L1 first dead time L2 second dead time

Claims (15)

An air-fuel ratio sensor abnormality diagnosis device for detecting an air-fuel ratio of exhaust gas of an internal combustion engine,
A system from the fuel injection valve to the air-fuel ratio sensor is modeled by a plurality of first-order lag elements, and parameters in the plurality of first-order lag elements are identified based on an input given to the air-fuel ratio sensor and an output obtained from the air-fuel ratio sensor. An identification means;
An abnormality determination device for an air-fuel ratio sensor, comprising: an abnormality determination means for determining an abnormality of a predetermined characteristic of the air-fuel ratio sensor based on the parameter identified by the identification means.   2. The abnormality determination unit determines at least two abnormalities of the characteristics of the air-fuel ratio sensor based on at least four parameters of two first-order lag elements identified by the identification unit. The abnormality diagnosis device for the air-fuel ratio sensor described.   The at least four parameters are at least a first gain and a second gain, a first time constant and a second time constant, and at least two of the characteristics of the air-fuel ratio sensor are at least output and responsiveness. The abnormality diagnosis device for an air-fuel ratio sensor according to claim 2, wherein the abnormality diagnosis device is provided.   4. The abnormality diagnosis apparatus for an air-fuel ratio sensor according to claim 3, wherein the identification unit simultaneously identifies the first gain and the second gain, and the first time constant and the second time constant.   The abnormality determination means simultaneously determines an abnormality in the output of the air-fuel ratio sensor and the responsiveness based on the identified first gain and second gain, the first time constant and the second time constant. The abnormality diagnosis device for an air-fuel ratio sensor according to claim 4. The identifying means identifies a first gain and a second gain, a first time constant and a second time constant in the two first-order lag elements;
The abnormality determining means is
When the first gain is greater than a predetermined first gain increase abnormality determination value or the second gain is greater than a predetermined second gain increase abnormality determination value, the air-fuel ratio sensor is determined to be an output increase abnormality. ,
When the first gain is smaller than a predetermined first gain reduction abnormality determination value or the second gain is smaller than a predetermined second gain reduction abnormality determination value, the air-fuel ratio sensor is determined as an output decrease abnormality. ,
When the first time constant is larger than a predetermined first time constant abnormality determination value or the second time constant is larger than a predetermined second time constant abnormality determination value, the air-fuel ratio sensor is determined to be responsive abnormality. The abnormality diagnosis device for an air-fuel ratio sensor according to claim 3, wherein the determination is made. The abnormality diagnosis device for an air-fuel ratio sensor according to any one of claims 1 to 6, wherein the system is modeled by a sum of a plurality of first-order lag elements.   8. A dead time correction means for calculating a dead time from the input to the output and shift-correcting at least one of the input and the output by the dead time. The abnormality diagnosis device for an air-fuel ratio sensor according to any one of the above.   9. The air-fuel ratio sensor abnormality diagnosis according to claim 8, wherein the dead time correction means calculates the dead time according to a predetermined map or function based on at least one parameter relating to an operating state of the internal combustion engine. apparatus.   The dead time correction means calculates a variance value between the input and the output, and when the variance value peak of the output is larger than a predetermined value, a time difference between the variance value peak of the input and the variance value peak of the output is calculated. 9. The abnormality diagnosis device for an air-fuel ratio sensor according to claim 8, wherein the dead time is calculated based on the dead time.   11. The time delay correction unit calculates the time delay based on a time difference between extreme values of the input and the output when a dispersion value peak of the output is equal to or less than the predetermined value. An air-fuel ratio sensor abnormality diagnosis device.   The dead time correction means calculates a first dead time according to a predetermined map based on at least one parameter relating to the operating state of the internal combustion engine, and a time difference of a dispersion value peak between the input and the output, or the Based on the time difference between the extreme values of the input and the output, a second dead time is calculated, and when the amount of deviation of the second dead time with respect to the first dead time is larger than a predetermined value, the second dead time 9. The abnormality diagnosis apparatus for an air-fuel ratio sensor according to claim 8, wherein the time is determined as a final dead time, and the data of the map is updated with the second dead time.   The air-fuel ratio according to any one of claims 1 to 12, further comprising bias correction means for correcting at least one of the input and the output so as to remove a bias between the input and the output. Sensor abnormality diagnosis device.   The abnormality diagnosis device for an air-fuel ratio sensor according to any one of claims 1 to 13, further comprising fuel correction means for correcting the input based on an amount of fuel adhering to a wall surface and an evaporation amount.   Active control means for executing active control for forcibly oscillating the input is provided, and the identification means identifies a parameter in the plurality of first-order lag elements based on the input and the output during the active control. The air-fuel ratio sensor abnormality diagnosis device according to any one of claims 1 to 14.

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