EP0370091B1 - Procede et dispositif de regulation, notamment de regulation lambda - Google Patents

Procede et dispositif de regulation, notamment de regulation lambda Download PDF

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Publication number
EP0370091B1
EP0370091B1 EP19890905393 EP89905393A EP0370091B1 EP 0370091 B1 EP0370091 B1 EP 0370091B1 EP 19890905393 EP19890905393 EP 19890905393 EP 89905393 A EP89905393 A EP 89905393A EP 0370091 B1 EP0370091 B1 EP 0370091B1
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EP
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Prior art keywords
variable
value
control
values
classes
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EP19890905393
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German (de)
English (en)
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EP0370091A1 (fr
Inventor
Klaus Heck
Günther PLAPP
Jürgen KURLE
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Robert Bosch GmbH
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Robert Bosch GmbH
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/24—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means
    • F02D41/26—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means using computer, e.g. microprocessor
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/24—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means
    • F02D41/2406—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means using essentially read only memories
    • F02D41/2425—Particular ways of programming the data
    • F02D41/2429—Methods of calibrating or learning
    • F02D41/2451—Methods of calibrating or learning characterised by what is learned or calibrated
    • F02D41/2454—Learning of the air-fuel ratio control
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/24—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means
    • F02D41/2406—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means using essentially read only memories
    • F02D41/2425—Particular ways of programming the data
    • F02D41/2429—Methods of calibrating or learning
    • F02D41/2432—Methods of calibration
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/24—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means
    • F02D41/2406—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means using essentially read only memories
    • F02D41/2425—Particular ways of programming the data
    • F02D41/2429—Methods of calibrating or learning
    • F02D41/2441—Methods of calibrating or learning characterised by the learning conditions

Definitions

  • the invention relates to a method and a device for precontroling and regulating a controlled variable, in particular the lambda value of the air / fuel mixture to be supplied to an internal combustion engine.
  • a method for precontrolling and regulating a variable is known, for example, from regulating the lambda value.
  • the air flow supplied to an internal combustion engine is constant.
  • a quantity of fuel is supplied which should lead to lambda value 1.
  • Compliance with this setpoint is monitored by a lambda probe. If, due to a change in the value of a disturbance variable, the actual lambda value deviates from the desired lambda value, the amount of fuel supplied is changed so that lambda value 1 is set again.
  • the amount of fuel supplied is changed so that lambda value 1 is set again.
  • the air flow In order to determine the correct pilot variable, the air flow must be measured in the example. If the output value of the measuring device changes over time due to aging effects with the same air flow, ie the same input value, the pilot control value is incorrectly determined. This error can also be compensated for by the control, but with the disadvantage already mentioned of the slow reaction compared to the pilot control.
  • adaptation methods have already been developed, for example to take aging effects into account in the feedforward control. In the known adaptation methods, however, only a single adaptation value or a single set of adaptation values is determined for the entire measuring range. This means that the corrected feedforward control only works precisely in the measuring range for which the adaptation value matches the age-related deviation.
  • the same also applies to the precontrol and regulation of a controlled variable on devices other than an internal combustion engine.
  • the influencing variable does not necessarily have to be the air flow, but it can e.g. also the viscosity of the fluid to be pumped or the ventilation of the room to be kept at a certain temperature or any disturbance variable.
  • the calibration does not necessarily have to take place while maintaining the control manipulated variable 0, but this is of particular advantage since the control is then least stressed during operation.
  • the invention is based on the object of specifying a method for piloting and regulating a controlled variable which compensates for aging-related effects in some areas by influencing the pilot variable.
  • the invention is also based on the object of specifying a device for carrying out such a method.
  • the method according to the invention is characterized in that it uses a counter field in which only counter readings are incremented during operation of the controlled system, but which is not evaluated continuously but only when an evaluation condition occurs.
  • the counter field is subdivided into influencing variable classes and control variable classes, with each combination of the two classes belongs to a cell with a counter.
  • the counter field is evaluated in such a way that the distribution over the control variable class is determined for each setpoint variable class, and if the distribution focus for different influencing variable classes lies in different control variable classes, a correction value is calculated for the respective influencing variable class and the value is calculated during operation of the controlled system Control values are influenced by the respective associated correction value, taking into account the respective influencing variable class, the correction values being determined by the evaluation in such a way that the distribution focus for all influencing variable classes should be in the same control variable class. If no further adaptation measures are taken, the correction values are determined in such a way that the distribution focus for all influencing variable classes should lie at the control manipulated variable 0. It is particularly advantageous to use the method together with a relatively fast-acting adaptation.
  • the device according to the invention is characterized in particular by the presence of a counter field of the type mentioned and by means for evaluating the counter field.
  • the control loop has a controlled system 20, on which the actual value of a controlled variable is measured by an actual value sensor 21. This is fed to a comparison point 22 and subtracted from a control variable setpoint there. The resulting control deviation is processed into a control manipulated value by a control device 23, for example a PI control device. This is calculated in such a way that it adjusts an actuator 24 on the controlled system 20 in such a way that conditions are established which adjust the actual value in the direction of the setpoint.
  • the controlled system 20 can be, for example, a pump driven by an electric motor or an internal combustion engine.
  • the setpoint is then, for example, the pump speed or the lambda value of the exhaust gas.
  • the control device calculates a current flow required to achieve the rotational speed or a fuel quantity required to achieve the predetermined lambda value.
  • the actuator is accordingly a current regulator, for example a thyristor or a fuel metering device, for example an injection valve arrangement.
  • control device 23 If the setpoint, i.e. the speed or the lambda value, is suddenly changed, a control deviation results.
  • the control device 23 then calculates a new control manipulated value, which leads to an actual value which corresponds to the desired value. It is important for an understanding of the following that the control manipulated variable thus depends on the setpoint.
  • control manipulated value depends not only on the target value but also on the value of influencing variables which act on the controlled system 20.
  • this can be the viscosity of the fluid to be pumped, the voltage applied to the electric motor and the resistance of bearings.
  • the control device 23 e.g. increase the viscosity of the fluid to be pumped. Then the pump must do more at the same speed, so the control device 23 must ensure a higher current flow by changing the control value.
  • the control manipulated value has therefore changed with a constant setpoint due to the changed value of an influencing variable. This relationship is also important for understanding the following.
  • the relationship between setpoints and manipulated values that are required for the actual value to reach the setpoint is determined by calibration.
  • the size that leads to an immediate change in the manipulated value by pilot control can be the air flow supplied to the internal combustion engine.
  • FIG. 2 Details of a feedforward control are explained with reference to FIG. 2.
  • the exemplary embodiment according to FIG. 2 does not yet represent the invention, but rather leads to this by a combination of measures known per se from the prior art. 2, it should be explained in particular that the control manipulated variable behaves differently in the case of methods with feedforward control when changes in influencing variables than in the case of a control system, and that the behavior is changed even further if an adaptation is additionally present.
  • control device 23 also requires a controlled system 20, an actual value sensor 21, a comparison point 22, a control device 23 and an actuator 24.
  • the control manipulated value output by the control device 23 is no longer passed directly to the actuator 24, but a manipulated value that is then supplied to the actuator 24 is formed from it and a pilot control value at a manipulated value linking point 25.
  • the pre-control value comes about in a relatively complex process, which is, however, only explained in principle with reference to FIG. 2.
  • the disturbance variable input value is, for example, the measured input voltage, for the pump, or the air pressure, for the internal combustion engine
  • the disturbance variable output value is a current that is required for power compensation or a multiplication factor with which a pre-calculated injection time is corrected by the to compensate for a change in air mass caused by a change in air pressure.
  • the disturbance variable output value is introduced into the calculation of the pilot control value by means 27 for disturbance variable correction. This means can, for example, add an additional flow or multiply an injection time correction factor.
  • a task variable is shown in FIG. 2 as a further variable processed in the pre-control value.
  • this can be the speed, ie the pump volume, and in the example of the internal combustion engine, the air volume drawn in.
  • the task size values correspond to target values, while in the second case, they correspond to influencing value values.
  • the respective value of the task variable is fed as an input value to a means 28 for converting the task variable, which outputs an output value.
  • the input value can be a voltage proportional to the setpoint and the output value can be a control value for current control.
  • the input value can be a voltage output by an air volume sensor and the output value can be a preliminary injection time, for example expressed as a counter value. With the Output value, the disturbance variable output value is linked on average 27 for disturbance variable correction.
  • the output value of the task variable corrected by the disturbance variable output value in the means 27 for disturbance variable correction forms the pilot control value, which is linked in the manipulated value linkage point 25 with the control manipulated variable from the control device 23 to the manipulated value supplied to the actuator 24.
  • the calibration of the means 26 for disturbance variable conversion is carried out in the same way as the calibration described above. Namely, the setpoint and all Influencing variables are kept constant apart from the one disturbance variable that is converted. For each disturbance variable input value, the disturbance variable output value is determined which, in combination with the present output value, leads to the control manipulated variable 0. In operation of the controlled system 20, any change in this compensated disturbance variable by the associated disturbance variable output value should then be eliminated in its influence on the controlled system.
  • the control manipulated variable deviating from 0 is made up of partial values that are caused by aging errors of the various converters.
  • the control manipulated variable is still influenced by uncompensated disturbance variables. If, for example, the bearing resistance increased in the named pump, the actual speed value would decrease compared to the target value if the control device 23 were not present, which in this case increases the control manipulated value.
  • an uncompensated disturbance variable can be valve aging, due to which the valve opens more and more slowly. The control device must then ensure an ever longer activation time for the same amount of fuel in each case.
  • control set values not equal to 0 only occur temporarily. This will now be explained.
  • control manipulated variable is typically integrated by the control manipulated variable processing 30 already mentioned. So that the adaptation does not take place based on control manipulated values for special situations, the control manipulated variable processing 30 is preceded by the stationary condition filter 29 in various embodiments.
  • the task variable is fed to this, for example, and it only passes a control manipulated variable to the control manipulated variable processor 30 if the task variable falls below a predetermined rate of change.
  • the adaptation value or typically set of adaptation values calculated by the control manipulated variable processing 30 is fed to the means for adaptive correction 31, which links the adaptation value or the adaptation values with the above-mentioned pre-control value to the current pre-control value.
  • control manipulated variable associated with control deviation 0 need not be 0, as previously assumed. This will expediently be the case if the control manipulated value is additionally linked to the pilot control value. However, the control manipulated variable can also be a control factor. In this case, the control value associated with control deviation 0 is value 1. The above-mentioned calibration processes take place in response to this control control value 1.
  • the task size is the air volume and compensated disturbance variable the air pressure.
  • the device was calibrated with certain injectors. Now these original injectors have been replaced by new ones, which output 5% less fuel with the same manipulated variable.
  • the control manipulated variable In order to compensate for this 5% fuel loss with the same pilot control value, the control manipulated variable must increase from 1 to 1.05 in order to provide a 5% increased manipulated variable after multiplying by the pilot control value.
  • This control manipulated value is integrated by the adaptation method and the adaptation value thus formed is multiplied on average 31 for adaptive correction with the disturbance variable-compensated output value. The integration continues until the control manipulated value returns to 1. Then the adaptation value is 1.05.
  • the adaptation thus has the advantage that disturbance variables which are not recorded by measurement technology are also recorded in the pilot control value, so that control processes are limited to a minimum.
  • the problem with the adaptation is that usually only a single adaptation value is determined for the entire working range of the controlled system 20, for example only a single multiplicative correction factor for all speed and Load ranges of an internal combustion engine. So far, this deficiency has been countered by two methods.
  • One is that a set of adaptation values for effects of different character is determined, for example an additive leakage air adaptation value, a multiplicative adaptation value and an injection time additive adaptation value.
  • the three values are linked in the order mentioned with the starting value from the means 28 for converting the task size, the control factor being incorporated before the last additive linking. In this case too, the set of three values applies to all speed and load ranges.
  • the input variable is plotted in arbitrary units on the abscissa, and the output variable is likewise plotted in arbitrary units on the ordinate. Within a range of 0-100 units of the input variable, the output variable changes between the values 2 and 10 of the unit there.
  • Input variable is e.g. the speed and output variable are a control voltage for a thyristor, or the input variable is the voltage from an air mass sensor and the output variable is a counter value for a counter for determining the injection time. It is pointed out that, in contrast to FIG. 3, in the last example the relationship is actually not linear.
  • the input variable is now divided into four input variable classes, namely the classes 0-25, 25-50, 50-75 and 75-100 units. These classes are intended to be used in a counter field.
  • FIG. 4 An example of the counter field just mentioned is shown in FIG. 4.
  • the four input quantity classes lie one above the other, i.e. in the y direction.
  • there are a total of eight control component size classes next to each other namely a class - IV for manipulated variable deviations of - (6% -8%), - III of - (4% -6%), - II of - (2% -4%), - I from - (0% -2%), I from 0-2.5%, II from 2.5% -5%, III from 5% -7.5% and IV from 7.5% -10% .
  • the field shows due to the overlap between the four input variable classes and the eight control variable classes as a whole 32 cells.
  • a counter is assigned to each cell, ie if the counter field is realized by a RAM, each RAM cell belonging to the counter field can be incremented.
  • the count of each cell is set to "0" at the start of operation of the controlled system 20.
  • actuator 24 for example an injection valve
  • the control value deviation is ideally 0%, i.e. in practice it fluctuates slightly around this value, so that entries are only made in the control variable classes I and - I .
  • FIG. 4 it has been assumed that 3,600 measurements of the manipulated variable deviation have already been carried out.
  • the counts are each evenly distributed over the control manipulated variable classes I and - I, so that, for example, there are 1000 counts in the cell, which is assigned to the controlled manipulated variable class I and the input variable class 25-50 units.
  • the counter readings are entered in the cells in the illustration according to FIG. 4.
  • a meter reading distribution in the form of a normal distribution is also entered in each input size class. The maximum and also the center of gravity of each of these distributions coincide with the y-axis, since the counter readings are symmetrical to this axis. The distribution maxima are different due to the different meter readings mentioned.
  • the invention is based, inter alia, on the consideration that if there are control value deviations due to an aging effect, the counter readings in input variable classes can no longer be symmetrical to the y-axis. Then the focal points of normal distributions calculated from the counter readings must be shifted with respect to the y-axis.
  • the characteristic curve according to FIG. 3 is a 4% lower output variable due to aging over the entire range of the input variable. For example, instead of the final value "10”, 0.4 units less are now displayed, ie "9.6". Since the error is the same over the entire range of the input variable, it has the same effect in all four input variable classes. It is assumed that all input variable classes are approached with the same number of times during the measurement value acquisition, that is to say that the same number of measured values fall into each input variable class. This assumption applies to all further considerations of meter fields. In the case of FIG. 5b, 1500 count values should fall into the control manipulated variable class II for each input variable class and 500 count values into the class III. This leads to normal distributions with the maximum and the focus at around 4%. When evaluating the normal distribution, the x-axis is therefore not used to classify, but in this case it constantly shows the manipulated variable deviation in percent.
  • the example case according to FIGS. 5a and b means, for example, the following.
  • the input variable is the air mass actually flowing through an air mass meter and Output variable for the counter value to determine the injection time. If the counter values for the same air masses decrease by 4%, this means that 4% too little fuel is supplied to the air mass that is actually drawn in. This can be compensated for by multiplying the pilot control value by the control factor, that is the control manipulated variable 1.04. To compensate for the output values that have dropped by 4%, a control manipulated value increased by 4% is therefore necessary, which can be read directly from FIG. 5b.
  • this deviation means percentage deviation of different sizes.
  • the deviation in the lowest input size class A means about 7.5% on average, while it only makes up about 2% in the highest input size class.
  • the maxima and the focal points of the normal distributions of the meter readings are no longer in the same control variable class, but for the input variable classes A, B, C and D, the maxima and focus are in the control variable classes IV, III, II and I .
  • FIG. 7a shows a characteristic curve which, due to aging effects, shows both a constant and a proportional deviation from the output characteristic curve of FIG. 3, namely a shift downwards by approximately 2 units as in FIG. 6a and a proportional increase of 4 %.
  • the maximum focal points of the normal distributions of the counter values lie in the control variable classes IV, III, II and I.
  • FIG. 8a A further variant of an age-related error in the current characteristic compared to the original characteristic of FIG. 3 is shown in FIG. 8a.
  • the values of the output size are 0.15 output size units below the originally measured values.
  • the maxima and focal points of the normal distributions of the meter readings remain unchanged at the control value deviation 0%.
  • the maximum and the focus are on the manipulated variable deviation 2.5%, i.e. they are offset by a control variable class width compared to the values of the unchanged input variable classes.
  • FIG. 9 shows the broken down functional image of control variable processing 30 (see FIG. 2).
  • control variable processing 30 see FIG. 2.
  • counter field 33 shows the broken down functional image of control variable processing 30 (see FIG. 2).
  • the counter field evaluation takes place offline, that is, not every time an error status is incremented in the counter field 33.
  • the evaluation can e.g. in each case after a specified period of time has elapsed, after a total number of counter increments has been reached or after the controlled system 20 has been shut down.
  • Which measure is most sensible to trigger the counter field evaluation depends on the application. In the case of a pump that is operated without interruption and without frequent unsteady states, it makes sense to evaluate each time after a predetermined period of time. If, on the other hand, transient conditions often occur, it may make more sense to wait until an overall incrementation time has been reached.
  • FIGS. 10a, b to 13a, b Various evaluation options will now be explained with reference to FIGS. 10a, b to 13a, b.
  • FIG. 10a represents an overlay the counter fields acc. 7b and 8b.
  • the additive error will now be corrected first by determining how many control deviation percentages the center of gravity of the normal distribution of the lowest input quantity class A is shifted from the center of gravity of the normal distribution least affected by the additive error largest input quantity class D.
  • the normal distribution of the lowest input variable class A is shifted by the amount determined, under the normal distribution of the uppermost input variable class D, so that the two focal points and maxima now lie in the same control variable class, in the example in the control variable class - II.
  • what an additive correction value is calculated for the feedforward control corresponds to the shift made.
  • the slope of the characteristic curve that is to say the multiplicative error
  • FIG. 12b this is done by averaging the centers of gravity of all normal distributions with respect to the line of the manipulated variable deviation 0.
  • the focus of the normal distributions in the input size classes A, B and D is then around - 0.8% and the focus of the normal distribution in the input size class C is around 2.5%.
  • a corresponding additive correction value is output, for example 1.025 if the correction value was previously 1, or 1.128 (1.1 ⁇ 1.025) if the multiplicative correction value was previously 1.1.
  • both the input variable to which reference has so far been made and the output variable can be used to classify influencing variable classes.
  • the input variable and output variable represent variables as they occur on a measuring device, values of the input variable are not directly accessible, but values of the input variable are determined from values of the output variable, which is the point of the measurement.
  • the input variable is the air mass ML and the output variable for further processing is the output voltage U of the air mass sensor.
  • the influencing variable classes are then output variable classes instead of input variable classes, as previously assumed for the explanation.
  • a voltage U is output by an air mass sensor 36, and this is converted into a count value Z, which is used to calculate the injection time, within which an injection valve 37 should be open.
  • the count value Z is divided in a dividing step 38 by the speed n of the internal combustion engine 35 and normalized in a normalizing step 39 by multiplication by a constant factor. Multiplication by a global adaptation factor FG then follows in a slope correction step 40. In a displacement correction step 41, a global adaptation sum SG is added.
  • Area-dependent corrections are made in a structure correction step 42 by multiplication with area-dependent correction factors FA, FB, FC or FD. An adapted pilot control value is thereby formed. This is multiplicatively connected to a control factor FR in a control value linkage point 25, whereby the control value supplied to the injection valve 37 is finally formed.
  • the manipulated value mentioned is exactly the right size, that the lambda value 1 is currently being set due to the air supplied and the amount of fuel injected. This is reported by a lambda probe 43 to a comparison point 22, which subtracts the actual lambda value obtained from a desired lambda value and feeds the resulting control deviation, in the assumed case the control deviation 0, to a control device 23. It is pointed out that the control device in practical use is not realized by a separate device but by calculation steps of a program.
  • the control device 23 outputs the control factor FR as a control manipulated variable. Since the control deviation is "0", the control factor is "1".
  • the control factor FR is not only fed to the manipulated value linkage point 25, but also to a stationary condition filter 29, both as a variable to be transmitted and as a decision variable. Further
  • the decision variable is the output voltage U from the air mass sensor 36. If both the control factor FR and the voltage U only have rates of change below predetermined threshold values, the stationary condition filter 29 passes the control factor FR determined in each computing cycle to a counter field 33 which, according to control factor deviation classes, is used as a control variable class and is divided into classes of influence according to voltage classes. An entry such as that of FIG. 4 then results in this field, since it was assumed that there should be no manipulated variable deviations.
  • a counter field evaluation 34 accordingly shows that the global adaptation factor FG should retain the value 1 and the global adaptation sum SG the value 0, that is to say both values which leave the pilot control value unchanged. Accordingly, the area factors FA, FB, FC and FD are output unchanged with "1".
  • the air mass sensor 36 After some operating time, the air mass sensor 36 has aged to the extent that the air mass ML that actually flows through it and the output voltage U no longer have the relationship according to FIG. 3, but rather that according to FIG. 10a. Counter values then result for the various voltage classes during operation, which lead to normal distributions in accordance with FIG. 10b. If the internal combustion engine 35 is stopped, the counter field evaluation 34 begins to work, ie it carries out the correction steps described above, i.e. determines a global adaptation summation SG (explanation above with reference to FIG. 12), a global adaptation factor FG (explanation above with reference to FIG. 11) ) and range factors FA, FB, FC and FD (explanation above with reference to FIG. 13).
  • the respectively new correction value is superimposed on the old correction value, which calculation steps are shown in FIG. 14 by grinding with sample / hold steps S / H 44. Cheating the old global Adaption summand SG, for example 10 counter steps for the injection time calculation and accordingly the newly determined global adaption summand SG 5 counter steps, then a global adaption summation S of 15 is included in the pilot control value.
  • the relationships for the global adaptation factor FG have already been explained above using an example. The same applies to the area factors FA-FD. In order to show that each area factor must be kept separate and multiplied by the value determined during the evaluation in order to form the new factor, the note "4 ⁇ S / H" is entered in the associated sample / hold step 44. Which of the four individual steps is activated is determined in a range determination step 45 which uses the sensor voltage U.
  • the counter field 33 can also be of a more complex structure than previously explained.
  • a pilot control value memory 46 which is controlled via values of the speed n and the accelerator pedal position FPS (or, equivalent, the throttle valve angle).
  • the pilot control value is multiplicatively linked to a control factor FR in a control value linkage point 25 and the control value thus calculated is fed to an injection valve 37.
  • the control factor FR is calculated as described above with reference to FIG. 14.
  • a stationary condition filter 29 is missing in the block function diagram according to FIG. 15; Actuating factors FR are therefore entered without filtering in a counter field 33.n which contains several individual counter fields, each of which is broken down into accelerator pedal position classes and control factor deviation classes.
  • the counter field evaluation 34 determines correction values for each individual counter field for each accelerator pedal position class. With these correction values, the values of the accelerator pedal position FPS corrected multiplicatively in a position correction step 47. Which correction value is supplied in each case is determined in a selection step 48, depending on the accelerator pedal position class and speed class currently available.
  • the suitable correction point depend on the overall properties of the system, but also the most suitable evaluation method. If it can be assumed that disruptive effects are predominantly multiplicative effects, the evaluation will focus on determining as precisely as possible a factor from the normal distributions. If, on the other hand, it is to be assumed in another system that aging effects or even non-compensated disturbance variables have a predominantly additive effect, the aim is to achieve a state corresponding to that of FIG. 13b by as many additive correction components as possible. It also depends on the type of overall system whether a stationary condition filter is expediently used or not, the conditions under which such a filter works and how control manipulated values are to be evaluated. When using a continuous control device 23, it will be possible, for example, to accept any control manipulated variable without further processing.
  • control manipulated values continuously oscillate around an average value. Either this mean value is then used, or the jump targets that occur during a P jump in a PI control device are then used. It is pointed out that in the case of a two-point controller, “control manipulated variable which corresponds to control deviation 0” is to be understood as an average of the control manipulated variable.
  • FIG. 16 there is an air volume sensor 49 which, depending on the volume flow VL flowing through it, outputs a voltage U which leads to a count value Z for calculating the injection time.
  • this count value Z is again divided by the speed n in a dividing step 38 and normalized in a normalizing step 39.
  • a structure correction step 42 follows, as explained with reference to FIG. 14. This is followed by a leakage air adaptation step 50, a multiplication adaptation step 51, the manipulated value linking step 25 already mentioned several times, an injection-additive correction step 52 and a battery voltage correction step 53. The latter will not be discussed any further.
  • the control value to be supplied to the injection valve 37 is formed by all of these steps.
  • the manipulated variable is not, as described in the previous cases, formed at the manipulated variable link 25 from a pilot control value and a control manipulated variable, but rather at the manipulated variable link 25 a preliminary pilot control value with a control manipulated variable, here again a control factor FR , linked, whereupon the injection additive correction step 52 and the likewise additive battery voltage correction step 53 follow.
  • the control factor is formed with the aid of a lambda probe 43, a comparison point 22 and a control device 23.
  • the leakage air sum for the leakage air adaptation step 50, the compensation factor for the multiplication adaptation step 51 and the injection sum for the correction step 52 are formed in the usual way by means 54 for online adaptation from the control factor FR.
  • the adaptation causes what has already been explained above with reference to FIG. 2 that the control factor FR relatively quickly, even after sudden changes in a disturbance variable, for example due to the changing of injection valves or due to a significantly different air pressure when switching on again than when it was last switched off Value reached which is assigned to the control deviation 0, i.e. the value 1 in the case of the control factor FR.
  • Slowly occurring aging effects have no noticeable effect on the control factor FR, since they are constantly compensated for by the fast online adaptation.
  • a large error can occur in the signal supplied by a measuring device or a signal variable converter, without this leading to a control factor FR, which would indicate this deviation in a counter field 33. Only structural errors, i.e.
  • the leakage air sum, the compensation factor and the injection sum are added to the control factor FR in three summation steps 55.
  • the compensation factor should actually experience a multiplicative link, but an additive link leads to a negligible error, since the deviations from 1 are generally small.
  • the summation has the advantage that the progress of the online adaptation has no effect on the summed value; the sum is, in fact, solely due to the values of variables acting in the respective operating point, which differ from values of this variable at the same operating point at the time of calibration.
  • the distribution shown in FIG. 17 results as an example. There are four control variable classes each, for positive and negative deviations with ranges of 0-5, 5-10, 10-15 and 15-25%.
  • a back-correction step 56 is also shown in broken lines, the execution of which can be advantageous under special conditions.
  • the counter field evaluation 34 determines new range correction values for the structural correction step 42 while the internal combustion engine is at a standstill 42, which, after the internal combustion engine is switched on, provides a different pilot control value for a specific operating state than it did shortly before it was switched off correctly adaptation was used. This results in an overall incorrectly adapted value which has to be compensated for again by the online adaptation 54.
  • the leakage air sum is reduced by the back-correction step 56 by the amount by which the area correction value is increased, or vice versa, the overall effect of the adaptation remains unchanged.
  • the classification made is based on the observation of FIG. 17, namely that the maxima and centers of gravity of the normal distributions are relatively strongly shifted for all classes of influencing variables, but are close to one another in the range between approximately 10% and 25% deviation.
  • the classifications of the manipulated variable deviations are therefore no longer between - 25 and + 25%, but only between + 10 and 25%, but still in eight classes. This enables area differences to be determined with significantly improved resolution.
  • the leftmost control variable class records all values between - 25 and + 10% deviation and the rightmost class all values greater than 22%.
  • the fine division shows that the maxima and focal points due to improved range adaptation only e.g. between 14 and 18%, the division of the counter field for the value acquisition in the next operating cycle is advantageously further refined, so that there are again two large marginal classes and in between six classes, each with only half a percent width.
  • control variable classes and four influencing variable classes were assumed. These class numbers were chosen for reasons of clarity of presentation. In practice, the number of influencing variable classes is preferably chosen to be higher, in order to enable a structuring which is as finely structured as possible, that is to say structured in areas.

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  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Electrical Control Of Air Or Fuel Supplied To Internal-Combustion Engine (AREA)
  • Feedback Control In General (AREA)
  • Combined Controls Of Internal Combustion Engines (AREA)

Abstract

Un procédé d'adaptation d'une valeur de commande pilote d'une régulation se fonde sur le fait que lorsque les conditions de fonctionnement coïncident avec les conditions de calibrage lors de la détermination initiale de valeurs de commande pilote, aucune déviation des valeurs de réglage ne doit se produire dans aucun domaine de fonctionnement, et que par conséquent les déviations qui sont malgré tout observées sont un signe que les conditions de calibrage ne sont plus remplies, que ce soit à cause d'un effet de vieillissement ou de valeurs parasites non compensées. Selon le procédé, les différences entre les déviations des valeurs de réglage servent à les classer en différentes catégories de valeurs d'influence. Une valeur de correction est alors déterminée pour chaque catégorie de valeur d'influence, capable de compenser pendant le fonctionnement du système réglé l'erreur observée dans le domaine correspondant avant la mise en fonctionnement du système. Ce procédé permet d'obtenir une adaptation précise de domaines individuels selon un procédé offline, et il est donc particulièrement utile pour régler par commande pilote la valeur lambda d'un moteur à combustion interne. Les dispositifs d'application de ce procédé sont des microordinateurs peu coûteux à vitesse de travail si limitée qu'ils ne sont pas capables d'appliquer des procédés complexes d'adaptation online; lorsque ces dispositifs disposent toutefois d'un panneau de comptage utilisable offline, ils peuvent eux aussi assurer une adaptation structurelle précise, c'est-à-dire domaine par domaine.

Claims (14)

1. Procédé pour précommander et réguler une grandeur de régulation, dans lequel on mesure au moins une grandeur d'influence et indépendamment du résultat de la mesure une valeur d'une grandeur de précommande est délivrée pour précommander la grandeur de réglage, qui serait déterminée auparavant dans des conditions prédéterminées dans un processus d'étalonnage de telle façon que l'effet de la grandeur d'influence serait compensé dans une mesure prédéfinie, qu'il se produirait donc une valeur de réglage de la régulation prédéterminée, de préférence la valeur de réglage de la régulation correspondant à l'écart de régulation 0, procédé caractérisé en ce que:
― la grandeur d'influence est divisée selon la valeur en classes de grandeurs d'influence,
― une grandeur fonction des grandeurs de réglage de la régulation est divisée en classes de grandeur de réglage de la régulation selon la valeur,
― pendant le fonctionnement du trajet de régulation, on recherche de façon répétée dans quelle classe de grandeurs de réglage de la régulation se trouve précisement la valeur de réglage de la régulation et dans quelle classe des grandeurs d'influence se trouve la valeur de la grandeur d'influence et un compteur est incrémenté dans une cellule, qui fait partie d'un champ de compteur et dont les cellules peuvent être desservies au moyen de numéros d'adresse des deux classes et,
― après apparition d'une condition d'exploitation le champ de compteur est exploité dans un sens tel que pour chaque classe de grandeurs d'influence, on recherche la répartition au moyen des classes de grandeurs de réglage de la régulation et ensuite, quand des centres de gravité de répartition pour des classes différentes de grandeurs d'influence se trouvent dans des classes différentes de grandeurs de réglage de la régulation, on calcule une valeur de correction pour la classe de grandeurs d'influence correspondantes et pendant le fonctionnement du trajet de régulation les valeurs de réglage peuvent être influencées par la valeur de correction respectivement correspondante en prenant en considération la classe de grandeurs d'influence respectivement présente, les valeurs de correction étant déterminées par l'exploitation de telle sorte que les centres de gravité de répartition se trouvent obligatoirement dans la même classe de grandeurs de réglage de la régulation pour toutes les classes de grandeurs d'influence.
2. Procédé selon la revendication 1, caractérisé en ce que l'on réalise en outre une adaptation on-line en exploitant les valeurs de réglage de la régulation, adaptation dans laquelle l'effet global des valeurs d'adaptation et des valeurs de réglage de la régulation demeure essentiellement constant et en ce que dans ce cas les valeurs d'addition des valeurs d'adaptation et des valeurs de réglage de la régulation sont réparties dans les classes des grandeurs de réglage de la régulation.
3. Procédé selon l'une des revendications 1 ou 2, caractérisé en ce que les valeurs de correction sont mesurées de telle façon que les centres de gravité de répartition pour toutes les classes des grandeurs d'influence se trouvent obligatoirement à celle des valeurs de réglage de la régulation, qui correspond à l'écart de régulation 0.
4. Procédé selon l'une des revendications 1 à 3, caractérisé en ce que la condition d'exploitation est l'écoulement d'un intervalle de temps prédéterminé.
5. Procédé selon l'une des revendications 1 à 3, caractérisé en ce que la condition d'exploitation est l'obtention d'un nombre prédéterminé d'incrémentations de compteur.
6. Procédé selon l'une des revendications 1 à 3, caractérisé en ce que la condition d'exploitation est la mise à l'arrêt du trajet de régulation.
7. Procédé selon l'une des revendications 1 à 6, caractérisé en ce que toutes les valeurs de compteur du champ de compteur sont remises à zéro après l'exploitation.
8. Procédé selon l'une des revendications 1 à 7, caractérisé en ce que les valeurs de réglage sont influencées par le fait que les valeurs des grandeurs d'influence sont corrigées avant une conversion.
9. Procédé selon l'une des revendications 1 à 7, caractérisé en ce que les valeurs de réglage sont influencées par le fait que les valeurs des grandeurs d'influence sont corrigées après une conversion.
10. Procédé selon l'une des revendications 1 à 9, caractérisé en ce que les valeurs de réglage indépendamment de chaque classe de grandeurs d'influence disponible est influencée par une valeur partielle de correction de nature additive commune à toutes les classes des grandeurs d'influence.
11. Procédé selon l'une des revendications 1 à 10, caractérisé en ce que les valeurs de réglage indépendamment de chaque classe de grandeurs d'influence disponible est influencée par une valeur partielle de correction de nature multiplicative commune à toutes les classes des grandeurs d'influence.
12. Procédé selon l'une des revendications 1 à 11, caractérisé en ce que la grandeur de réglage est la valeur lambda d'un mélange air/carburant envoyé dans un moteur à combustion, la grandeur d'influence est une grandeur indiquant le débit d'air et la grandeur de précommande est une grandeur de dosage du carburant.
13. Dispositif pour la mise en oeuvre d'un procédé de précommande et de régulation d'une grandeur de régulation, dans lequel est mesurée au moins une grandeur d'influence et indépendamment du résultat de la mesure, il est délivré une valeur d'une grandeur de précommande pour précommander la grandeur de réglage, qui serait déterminée auparavant dans des conditions établies dans un processus d'étalonnage, de telle façon que l'effet de la grandeur d'influence serait compensé dans une mesure prédéterminée, qu'il se produirait donc une valeur de réglage de la régulation prédéterminée, de préférence la valeur de réglage de la régulation correspondant à l'écart de régulation 0, dispositif caractérisé par:
― un champ de compteur (33), qui est subdivisé en classes de grandeurs d'influence et perpendiculairement à celles-ci en classes de grandeurs de réglage de la régulation, d'où il résulte un certain nombre de cellules, qui peuvent être desservies par des numéros d'adresse des deux classes,
― un moyen pour rechercher de façon répétée pendant le fonctionnement du trajet de régulation, dans quelle classe des grandeurs de réglage de la régulation se trouve la valeur de réglage de la régulation et dans quelle classe des grandeurs d'influence se trouve précisement la valeur de la grandeur d'influence, et un compteur est incrémenté dans la cellule correspondante,
― et un moyen pour exploiter le champ de compteur après l'apparition d'une condition d'exploitation, lequel moyen recherche pour chaque classe de grandeurs d'influence la répartition dans les classes des grandeurs de réglage de la régulation et ensuite, quand les centres de gravité de répartition se trouvent dans des classes différentes des grandeurs de réglage de la régulation pour des classes différentes des grandeurs d'influence, une valeur de correction est calculée par la classe de grandeurs d'influence correspondante et pendant le fonctionnement du trajet de régulation les valeurs de réglage, soit influencée par chaque valeur de correction correspondante en prenant en considération la classe disponible correspondante des grandeurs d'influence, les valeurs de correction étant déterminées par l'exploitation, de telle sorte que les centres de gravité de répartition se trouvent obligatoirement dans la même classe de grandeurs de réglage de la régulation pour toutes les classes de grandeurs d'influence.
14. Dispositif selon la revendication 13, caractérisé par un moyen (54) pour exécuter une adaptation on-line.
EP19890905393 1988-05-14 1989-05-10 Procede et dispositif de regulation, notamment de regulation lambda Expired - Lifetime EP0370091B1 (fr)

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DE3816520A DE3816520A1 (de) 1988-05-14 1988-05-14 Regelverfahren und -vorrichtung, insbesondere lambdaregelung
DE3816520 1988-05-14

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JPH02504538A (ja) 1990-12-20
US5079691A (en) 1992-01-07
EP0370091A1 (fr) 1990-05-30
JP3048588B2 (ja) 2000-06-05
KR0141370B1 (ko) 1998-07-01
DE3816520A1 (de) 1989-11-23
KR900702207A (ko) 1990-12-06
WO1989011032A1 (fr) 1989-11-16
DE58900305D1 (de) 1991-10-24

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