EP2812551A1 - Method and device for dynamics monitoring of gas sensors - Google Patents
Method and device for dynamics monitoring of gas sensorsInfo
- Publication number
- EP2812551A1 EP2812551A1 EP13700468.5A EP13700468A EP2812551A1 EP 2812551 A1 EP2812551 A1 EP 2812551A1 EP 13700468 A EP13700468 A EP 13700468A EP 2812551 A1 EP2812551 A1 EP 2812551A1
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- Prior art keywords
- signal
- gas
- parameters
- sensors
- measured
- Prior art date
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- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 18
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Classifications
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0808—Diagnosing performance data
-
- 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
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1438—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor
- F02D41/1493—Details
- F02D41/1495—Detection of abnormalities in the air/fuel ratio feedback system
-
- 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
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1438—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor
- F02D41/1444—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor characterised by the characteristics of the combustion gases
- F02D41/1454—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor characterised by the characteristics of the combustion gases the characteristics being an oxygen content or concentration or the air-fuel ratio
- F02D41/1456—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor characterised by the characteristics of the combustion gases the characteristics being an oxygen content or concentration or the air-fuel ratio with sensor output signal being linear or quasi-linear with the concentration of oxygen
-
- 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
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1438—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor
- F02D41/1444—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor characterised by the characteristics of the combustion gases
- F02D41/1454—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor characterised by the characteristics of the combustion gases the characteristics being an oxygen content or concentration or the air-fuel ratio
- F02D41/1458—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor characterised by the characteristics of the combustion gases the characteristics being an oxygen content or concentration or the air-fuel ratio with determination means using an estimation
-
- 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
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
- F02D2041/1413—Controller structures or design
- F02D2041/1423—Identification of model or controller parameters
-
- 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
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
- F02D2041/1413—Controller structures or design
- F02D2041/1431—Controller structures or design the system including an input-output delay
-
- 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
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
- F02D2041/1413—Controller structures or design
- F02D2041/1432—Controller structures or design the system including a filter, e.g. a low pass or high pass filter
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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
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
- F02D2041/1433—Introducing closed-loop corrections characterised by the control or regulation method using a model or simulation of the system
Definitions
- the invention relates to a method for monitoring the dynamics of gas sensors of an internal combustion engine, which are arranged, for example, as exhaust gas probes in the exhaust passage of an internal combustion engine as part of a Abgasüberwachungs- and -minderungssystems or gas concentration sensors in a supply air duct of the internal combustion engine, the gas sensors depending on geometry, Measuring principle, aging or pollution have a low-pass behavior, wherein when changing the gas state variable to be detected on the basis of a comparison of a modeled and a measured signal, a dynamic diagnosis is performed and wherein the measured signal is an actual value of an output of the gas sensor and the modeled signal a model value is.
- the invention further relates to a device for carrying out the method.
- the air-fuel ratio ⁇ is measured by means of an exhaust gas probe upstream of the exhaust gas purification system.
- the storage capacity of such an exhaust gas purification system for oxygen is utilized to take up oxygen in lean phases and to release it again in the fat phase. This ensures that oxidizable noxious gas components of the exhaust gas can be converted.
- One of the exhaust gas purification downstream exhaust probe serves to monitor the oxygen storage capacity of the emission control system.
- the oxygen Storage capacity must be monitored as part of on-board diagnostics (OBD) as it provides a measure of the convertibility of the emission control system.
- OBD on-board diagnostics
- the exhaust gas purification system In order to determine the oxygen storage capacity, either the exhaust gas purification system is initially filled with oxygen in a lean phase and then emptied in a rich phase with a lambda value known in the exhaust gas, taking into account the amount of exhaust gas passing through, or the exhaust gas purification system is first emptied of oxygen in a fatty phase and then in a Lean phase filled with a known lambda value in the exhaust gas, taking into account the amount of exhaust gas passing through.
- the lean phase is terminated when the exhaust gas probe connected downstream of the exhaust gas purification system detects the oxygen that can no longer be stored by the exhaust gas purification system.
- a rich phase is terminated when the exhaust gas probe detects the passage of rich exhaust gas.
- the oxygen storage capability of the emission control system corresponds to the amount of reducing agent supplied during the rich phase for emptying or during the lean phase for replenishment amount of oxygen supplied.
- the exact quantities are calculated from the signal of the upstream exhaust gas probe and the exhaust gas mass flow determined from other sensor signals.
- the air-fuel ratio can no longer be adjusted with the required precision, so that the conversion efficiency of the exhaust gas purification system is reduced. Furthermore, deviations in the diagnosis of the exhaust gas purification system may result, which can lead to the fact that a properly working exhaust gas purification system is incorrectly assessed as non-functional.
- the legislator requires a diagnosis of the probe properties during driving to ensure that the required air-fuel ratio can continue to be set sufficiently accurately, the emissions do not exceed the permissible limits and the emission control system is monitored correctly.
- the OBDII regulations require that lambda probes and other exhaust probes be monitored not only for their electrical performance, but also for their response, ie, a deterioration in probe dynamics must be recognized, as evidenced by increased time constant and / or dead time can. Dead-time and delay times between a change in the exhaust gas composition and its detection must be checked on-board as to whether they are suitable for the user functions, ie for control, regulation and monitoring purposes. functions which use the probe signal are still permissible.
- the dead time from a mixture change to the signal edge and a certain rise time for example from 0% to 63% or from 30% to 60% of a signal swing, are typically used.
- the dead time also includes the gas running time from the engine outlet to the probe and thus changes in particular in a manipulation of the sensor installation location.
- broadband lambda probes are used as gas sensors or gas concentration sensors and, in conjunction with SCR catalysts, also NO x sensors. The latter also provide a 0 2 signal.
- the 0 2 signal from broadband lambda probe or NO x sensor is not only used in the diesel engine for the operation of exhaust aftertreatment devices, but also for the internal engine emission reduction.
- the measured 0 2 concentration in the exhaust gas or the measured lambda signal is used to dynamically adjust the air-fuel mixture precisely, thus minimizing the dispersion of the raw emissions.
- NSC ⁇ -storage catalytic converter
- a broadband lambda probe before and after the catalytic converter is required for a reliable representation of the rich operation for regeneration.
- a method for monitoring dynamic properties of a broadband lambda probe is known, wherein by means of the broadband lambda probe, a measured lambda signal is determined, which corresponds to an oxygen concentration in the exhaust gas of an internal combustion engine, wherein the internal combustion engine an observer is assigned, which generates a modeled lambda signal from input variables and wherein from the difference of the modeled lambda signal and the measured lambda signal or from the difference between a signal derived from the modeled lambda signal and a signal derived from the measured lambda signal, an estimation error signal is used as the input variable is formed in the observer a model upstream controller. It is envisaged that a measured lambda signal is determined, which corresponds to an oxygen concentration in the exhaust gas of an internal combustion engine, wherein the internal combustion engine an observer is assigned, which generates a modeled lambda signal from input variables and wherein from the difference of the modeled lambda signal and the measured lambda signal or from the difference between a signal derived from the modeled lambd
- a method and a device for the online adaptation of an LSU dynamics model are also described.
- the document relates to a method and a device for adapting a dynamic model of an exhaust gas, which is part of an exhaust passage of an internal combustion engine and with a lambda value is determined for controlling an air-fuel composition, wherein in a control device or in a diagnostic device the internal combustion engine is calculated parallel to a simulated lambda value and is used by a user function, both the simulated and the measured lambda value.
- the filter 1. Order can therefore be described as follows:
- the measured air-fuel ratio in the control unit is symmetrized by a so-called Symmetri réellesfilter in known asymmetric time constant or dead time.
- the non-delayed and / or filtered edge of the signal in the control unit is artificially delayed with an additional dead time and / or filtered with an additional filter, wherein the dead time and / or time constant of the diagnosed asymmetric dead time T + t and / or time constant T used + and the direction of the signal (fat too lean or lean to rich) is determined by a filtered derivative of the measured lambda signal.
- the nominal model G ( s ) is extended by a further first-order filter and a deadtime model:
- the entire signal (fat too lean and lean to rich) is delayed symmetrically by two dead times and / or two time constants.
- This additional delay can be taken into account in the controller by adapting the controller while maintaining its structure to the larger dead times and / or time constants or even taking into account the increase in the model order by increasing the regulator order.
- this method can be combined with a method for the identification of time constants based on the signal energy, which is described in a further parallel application of the applicant with the internal reference R.339892, the results of these two methods being dependent on each other, because a time constant error is also interpreted as a dead time error and vice versa. Furthermore, the influence of the gain is disregarded, so that a gain error affects the identification of the time constant. Furthermore, these methods work iteratively, so that either several measurements are necessary or the measured values must be buffered.
- the object of the invention to provide a corresponding method, which operates on the one hand continuously and on the other hand specially asymmetric parameters of these dynamic systems identified.
- the object relating to the method is achieved by determining the parameters of the low-pass behavior in a direction-dependent manner by minimizing direction-dependent error signals, which are formed by high-pass filtering and association with direction-dependent saturation characteristics, the direction-dependent error signals being obtained by comparing the modeled and the measured signal for one rising and falling signal component are calculated.
- direction-dependent error signals which are formed by high-pass filtering and association with direction-dependent saturation characteristics
- the direction-dependent error signals being obtained by comparing the modeled and the measured signal for one rising and falling signal component are calculated.
- asymmetric parameters of the dynamic behavior separated into increasing and decreasing signal components, can be determined with this method.
- the high-pass filtering of the signals the signals can be freed from a possible offset, so that the offset does not have to be estimated explicitly in the course of the optimization.
- minimization of the direction-dependent error signals is carried out by applying known from the literature method, as mentioned above.
- the minimization takes place in an advantageous manner by means of an adaptation of the parameters in a model for the gas sensor or in separate error models, separated for the rising and for the falling signal component. If the adapted parameters of the model and / or the error models correspond to those of the real gas sensor, a minimal error signal results, with which the adaptation is first completed and a set of parameters, separated for rising and falling signals, is determined as a result of the dynamic diagnosis , A conclusion of the adaptation can be determined, for example, by means of corresponding threshold values for the changes of the parameters.
- a change in the gas state variable to be detected can be effected by excitation of the internal combustion engine.
- changes in the dynamics of gas sensors can be detected and quantified.
- Gas sensors according to the invention are sensors that can measure states of a gas or detect changes. The state of the gas can be replaced by a
- Gas sensors have a typical low-pass behavior, which depends on the geometry of their design. In addition, such sensors can be due to aging or external influences (eg due to sooting in diesel engines) change their response.
- the method further provides that for the identification of the direction-dependent parameters any excitations with a sufficiently large signal-to-noise ratio are used, in which the gas state variable to be measured is varied.
- an air-fuel ratio of an air-fuel mixture supplied to the internal combustion engine is varied for the dynamic diagnosis of the gas sensor, wherein the variation by means of a forced excitation which periodically varies the air-fuel ratio by small sudden changes in an injection quantity , or a swinging control loop takes place.
- a forced excitation which periodically varies the air-fuel ratio by small sudden changes in an injection quantity , or a swinging control loop takes place.
- Control in which the control intervention is the input signal for an online identification.
- a system gain so that a changed system gain has no influence on the identification of dead time and time constant.
- the method can be used as direction-dependent parameters, a time constant T, a dead time T t , a gain K, each separately for a rising and falling signal component, or any combinations of these parameters are evaluated.
- the direction-dependent error signals are formed as difference values or squares of these difference values, wherein the difference value for an increasing signal consists of a high-pass filtered, modeled signal for a rising value and a high-pass filtered, measured signal for a rising value and the difference value for determining a falling signal from a high pass filtered modeled falling value signal and a high pass filtered measured falling value signal, which facilitates the adaptation of the parameters.
- the square of the respective difference values corresponds to a quality criterion and is proportional to a signal energy of these filtered signal components.
- Another advantage results from an extension of the method to an operating point-dependent identification.
- the adapted parameters are taught after each adaptation step in operating point dependent characteristics or multi-dimensional characteristic maps. This is made possible by the recursive optimization, which supplies newly adapted parameter sets for each adaptation step.
- the optimization can e.g. gradient methods, such as the "steepest slope” method or the Gauss-Newton method, which are also available in recursive variants for online optimization
- the calculation of the gradients is performed analytically by filtering and dead time delay of the modeled and
- an adaptation speed is given separately by a learning gain for each of the parameters to be optimized using a covariance matrix, which results in a faster adaptation, using a recursive forgetting factor, which in this case represents the only application parameter, and this forgetting factor can also be varied depending on the current excitation defuse faster stimulation and noise reduction.
- This will be u.a. it is possible to slow down the adaptation in the case of a low excitation or to stop completely or not to start at all. The latter is particularly useful if only one oscillating control loop due to a sensor deceleration serves as the excitation.
- the inventive diagnostic method can be used particularly advantageously with gas sensors which are used as gas pressure sensors, gas temperature sensors, gas mass flow sensors or gas concentration sensors as exhaust gas probes in the exhaust gas sensor.
- Gas sensors which are used as gas pressure sensors, gas temperature sensors, gas mass flow sensors or gas concentration sensors as exhaust gas probes in the exhaust gas sensor.
- These emission-relevant gas sensors must be monitored in terms of their dynamics and general function due to the requirements mentioned above. For example, the response of a gas pressure sensor can be monitored and a decrease in dynamics can be detected if, for example, the connection of the gas pressure sensor to an intake manifold is clogged or bent.
- Gas temperature sensors or gas mass flow sensors can be embodied, for example, as a hot-film air mass meter within a supply air duct of the internal combustion engine and in which a loss of momentum is recorded as a result of contamination. If a suitable model can be specified for the signals of such sensors, the method according to the invention, as described above in its method variants, can be used advantageously.
- Suitable gas sensors are in particular exhaust gas probes in the form of broadband lambda probes (LSU probes) or NO x sensors with which an oxygen content in a gas mixture can be determined.
- LSU probes broadband lambda probes
- NO x sensors NO x sensors with which an oxygen content in a gas mixture can be determined.
- the measured oxygen concentration is preferably compared with a modeled oxygen concentration in accordance with the method variants described above for diagnosis.
- the reciprocal lambda value can be used for this comparison since it is approximately proportional to the oxygen concentration.
- electrical quantities which are proportional to the oxygen concentration, ie a voltage or a current in the sensor or in the associated circuit. That to
- Comparison used model signal must then be converted accordingly.
- the output value of the nitrogen oxide sensor is evaluated as an actual value, the model value being determined from a modeled NO x value.
- This diagnosis can therefore be used particularly advantageously in gasoline engines or lean-burn engines whose exhaust gas purification system has a catalyst and / or devices for nitrogen oxide reduction.
- the influence of the exhaust gas purification on the gas concentration of interest has to be considered in the model.
- the method, as described above in its variants can not only for systems 1. But can also be applied to arbitrary directional systems of any order, with or without dead time, where identification of asymmetric dynamic parameters is important.
- the object relating to the device is achieved by providing a diagnostic unit for carrying out the method according to the invention, as described above, which has high-pass filters, subtractors and memory units for direction-dependent saturation characteristics for determining the direction-dependent error values.
- the functionality of the diagnostic unit can be executed at least partially software-based, which may be provided as a separate unit or as part of a higher-level engine control.
- the diagnostic unit has memory units for operating point-dependent characteristic curves or characteristic diagrams for carrying out an operating point-dependent identification of the parameters.
- Figure 1 shows a schematic representation of the technical environment in which the inventive method can be applied
- Figure 2 is a block diagram of a dynamic diagnostic function according to the invention.
- FIG. 1 shows diagrammatically an example of an Otto engine, the technical environment in which the method according to the invention for the diagnosis of an exhaust gas probe 15 can be used.
- An internal combustion engine 10 air is supplied via an air supply 1 1 and determines their mass with an air mass meter 12.
- the air mass meter 12 may be designed as a hot-film air mass meter.
- the exhaust gas of the internal combustion engine 10 is discharged via an exhaust passage 18, wherein in the flow direction of the exhaust gas behind the internal combustion engine 10, an emission control system 16 is provided.
- the exhaust gas purification system 16 usually comprises at least one catalyst.
- an engine control 14 which supplies fuel to the internal combustion engine 10 via a fuel metering 13 and to the other the signals of the air mass meter 12 and arranged in the exhaust duct 18 exhaust gas probe 15 and one in the exhaust gas discharge line 18 arranged Exhaust gas probe 17 are supplied.
- the exhaust gas probe 15 determines a lambda actual value of a fuel-air mixture supplied to the internal combustion engine 10. It can be designed as a broadband lambda probe or continuous lambda probe.
- the exhaust gas probe 17 determines the exhaust gas composition after the exhaust gas purification system 16.
- the exhaust gas probe 17 may be formed as a jump probe or binary probe.
- the air-fuel ratio (LCC) in the combustion chamber is usually adjusted abruptly and determined within a certain period of time after the jump, the absolute maximum magnitude of the measured air-fuel ratio.
- a continuously operating method is proposed especially for the detection of asymmetrical dead times and time constants, which does not evaluate individual large jumps in the air-fuel ratio but uses any excitation with a sufficiently large signal-to-noise ratio.
- This can e.g. be the forcible excitation, which periodically varies the air-fuel ratio by small sudden changes in the injection, or a swinging control loop.
- FIG. 2 shows in a block diagram 20 the functionality of the method in a preferred variant of the method.
- the model input is filtered with a lambda value 21 A mod modeled according to a nominal model, and the process output to be identified is filtered with a measured lambda value 22 A meas with an identical high-pass filter 23.
- the signals are freed from a possible offset, so that the offset does not have to be estimated explicitly in the course of the optimization.
- the high-pass filtering provides a separation into an increasing and decreasing signal by combining the high-pass-filtered signals with saturation characteristics 26, 27, 28, 29 and thus separating rising and falling signals, wherein a
- Saturation characteristic 26 is provided for a rising modeled signal component, a saturation characteristic 27 for a rising measured signal component, a saturation characteristic 28 for a falling modeled signal component and a saturation characteristic 29 for a falling measured signal component.
- This combination of high-pass filter 23 and saturation characteristics 26, 27, 28, 29 makes it possible to distinguish between signal components with increasing (positive) and falling (negative) edges and thus the identification of asymmetrical time constants and dead times.
- the saturation members can be defined as follows: for the saturation characteristics 26, 27 for the saturation characteristics 28, 29.
- the identification takes place online with the aid of recursive, continuously running optimization methods, so that no storage of the signals is necessary.
- the identification is based on a comparison of the modeled and measured signal, separated for rising and falling signal components, subtracting each time a difference and minimizing this difference, the gain K, the dead time T t and / or the time constant to be optimized Parameters are.
- These differences are ⁇ defined as error values for a rising signal and a falling signal 31, 32 (e p0 s, e neg) as follows - A measured p OS - A mo d, pos (4a) EnEG - A measured ne g - A moc
- This squared error value represents a quality criterion, based on which the lambda model directly and / or additionally via error models 24, 25 for the rising and the falling signal (FM pos , FM neg ) by means of a parameter adaptation for the rising and falling signal 36, 37, wherein the respective error model 24, 25 after the high-pass filter 23, as shown in Figure 2, or even before the high-pass filter 23 may be provided in the functional sequence.
- a parameter adaptation for the rising signal 36 an adaptation of the time constant T pos , the dead time T t pos and / or the gain K pos is provided.
- the parameter adaptation for the falling signal 37 provides for an adaptation of the time constant T neg , the dead time T tn eg and / or the gain K neg .
- the optimization can e.g. by means of gradient methods, such as the "steepest slope” method or the Gauss-Newton method, whereby these are also available in recursive variants for online optimization
- the calculation of the gradients is carried out analytically by filtering and delaying the dead time modeled and measured signals.
- the adapted parameters can also be taught in at the present time in characteristic curves or multi-dimensional maps, so that an operating point-dependent identification is also possible.
- the current parameters of the error model 24, 25 (FM pos , FM neg ) operating point depending on the characteristics or the maps read, based on these parameters, the adaptation performed and the newly adapted values again operating point-dependent in the curves or maps learned.
- the invention is not limited to systems whose dynamic behavior, as mentioned above, can be described with a low-pass 1st order. Likewise, this identification method is also applicable to systems of any order, with and without dead time.
Abstract
Description
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Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE102012201767A DE102012201767A1 (en) | 2012-02-07 | 2012-02-07 | Method and device for monitoring the dynamics of gas sensors |
PCT/EP2013/050018 WO2013117350A1 (en) | 2012-02-07 | 2013-01-02 | Method and device for dynamics monitoring of gas sensors |
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EP2812551A1 true EP2812551A1 (en) | 2014-12-17 |
EP2812551B1 EP2812551B1 (en) | 2021-03-10 |
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EP13700468.5A Active EP2812551B1 (en) | 2012-02-07 | 2013-01-02 | Method for dynamic monitoring of gas sensors |
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US (1) | US9704306B2 (en) |
EP (1) | EP2812551B1 (en) |
JP (1) | JP2015511286A (en) |
KR (1) | KR20140133514A (en) |
DE (1) | DE102012201767A1 (en) |
WO (1) | WO2013117350A1 (en) |
Families Citing this family (15)
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DE102012204353A1 (en) * | 2012-03-20 | 2013-09-26 | Robert Bosch Gmbh | Method and device for monitoring gas sensors |
DE102012019907B4 (en) * | 2012-10-11 | 2017-06-01 | Audi Ag | Method for operating an internal combustion engine with an exhaust gas purification device and corresponding internal combustion engine |
DE102013216223A1 (en) * | 2013-08-15 | 2015-02-19 | Robert Bosch Gmbh | Universally applicable control and evaluation unit, in particular for operating a lambda probe |
DE202015004194U1 (en) * | 2015-06-11 | 2016-09-13 | GM Global Technology Operations LLC (n. d. Ges. d. Staates Delaware) | Computer program for operating an internal combustion engine |
KR101786659B1 (en) * | 2015-06-30 | 2017-10-18 | 현대자동차주식회사 | Fault diagnosis system and mehtod of exhaust gas temperature sensor of hybrid vehicle |
DE102016006328A1 (en) * | 2016-05-24 | 2017-11-30 | GM Global Technology Operations LLC (n. d. Ges. d. Staates Delaware) | Method and device for checking an oxygen sensor |
GB2550597B (en) * | 2016-05-24 | 2020-05-13 | Delphi Automotive Systems Lux | Method of modelling afr to compensate for wraf sensor |
DE102016124328A1 (en) | 2016-12-14 | 2018-06-14 | Dspace Digital Signal Processing And Control Engineering Gmbh | Test rig for simulating the electrical response of a broadband lambda probe |
DE102017200350A1 (en) | 2017-01-11 | 2018-07-12 | Robert Bosch Gmbh | Method and device for dynamic diagnosis of exhaust gas probes |
US10578040B2 (en) | 2017-09-15 | 2020-03-03 | Toyota Motor Engineering & Manufacturing North America, Inc. | Smoothed and regularized Fischer-Burmeister solver for embedded real-time constrained optimal control problems in automotive systems |
DE102017218327B4 (en) * | 2017-10-13 | 2019-10-24 | Continental Automotive Gmbh | Method for operating an internal combustion engine with three-way catalytic converter and lambda control |
US10739768B2 (en) | 2018-08-08 | 2020-08-11 | Toyota Motor Engineering & Manufacturing North America, Inc. | Smoothed and regularized Fischer-Burmeister solver for embedded real-time constrained optimal control problems in autonomous systems |
JP7158339B2 (en) * | 2019-06-04 | 2022-10-21 | ロベルト・ボッシュ・ゲゼルシャフト・ミト・ベシュレンクテル・ハフツング | MODEL λ VALUE COMPENSATION METHOD AND VEHICLE OPERATION CONTROL DEVICE |
DE102019126069B4 (en) * | 2019-09-27 | 2022-01-20 | Dr. Ing. H.C. F. Porsche Aktiengesellschaft | System and method for calibrating a control and regulating device for regulating the injection pressure in an internal combustion engine |
DE102020211108B3 (en) * | 2020-09-03 | 2021-11-04 | Robert Bosch Gesellschaft mit beschränkter Haftung | Method and computing unit for adapting the modeled reaction kinetics of a catalyst |
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JP4432722B2 (en) | 2004-10-21 | 2010-03-17 | 株式会社デンソー | Control device |
DE102008001569B4 (en) | 2008-04-04 | 2021-03-18 | Robert Bosch Gmbh | Method and device for adapting a dynamic model of an exhaust gas probe |
DE102008001121A1 (en) | 2008-04-10 | 2009-10-15 | Robert Bosch Gmbh | Method for diagnosing an exhaust gas probe arranged in the exhaust system of an internal combustion engine and device for carrying out the method |
DE102008001213A1 (en) | 2008-04-16 | 2009-10-22 | Robert Bosch Gmbh | Method and device for diagnosing the dynamics of an exhaust gas sensor |
DE102008026741B4 (en) | 2008-06-04 | 2013-07-11 | Audi Ag | Method for detecting the functionality of a lambda probe in a controlled system |
DE102008040737A1 (en) | 2008-07-25 | 2010-01-28 | Robert Bosch Gmbh | Method and apparatus for monitoring the dynamics of a broadband lambda probe |
JP2010190089A (en) * | 2009-02-17 | 2010-09-02 | Toyota Motor Corp | Abnormality diagnostic device for multicylinder internal combustion engine |
DE102011081894A1 (en) | 2011-08-31 | 2013-02-28 | Robert Bosch Gmbh | Method and device for dynamic diagnosis of an exhaust gas probe |
DE102011088296A1 (en) | 2011-12-12 | 2013-06-13 | Robert Bosch Gmbh | Method and device for monitoring the dynamics of gas sensors |
DE102012200032B4 (en) | 2012-01-03 | 2023-12-28 | Robert Bosch Gmbh | Method and device for dynamic diagnosis of sensors |
DE102012201033A1 (en) | 2012-01-25 | 2013-07-25 | Robert Bosch Gmbh | Method and control unit for determining a dead time of an exhaust gas sensor |
-
2012
- 2012-02-07 DE DE102012201767A patent/DE102012201767A1/en not_active Withdrawn
-
2013
- 2013-01-02 EP EP13700468.5A patent/EP2812551B1/en active Active
- 2013-01-02 JP JP2014555130A patent/JP2015511286A/en active Pending
- 2013-01-02 US US14/377,098 patent/US9704306B2/en active Active
- 2013-01-02 KR KR1020147021946A patent/KR20140133514A/en not_active Application Discontinuation
- 2013-01-02 WO PCT/EP2013/050018 patent/WO2013117350A1/en active Application Filing
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DE102012201767A1 (en) | 2013-08-08 |
KR20140133514A (en) | 2014-11-19 |
EP2812551B1 (en) | 2021-03-10 |
US9704306B2 (en) | 2017-07-11 |
WO2013117350A1 (en) | 2013-08-15 |
JP2015511286A (en) | 2015-04-16 |
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