Method for identifying and prioritizing monitoring units to be replaced

Abstract

The invention relates to a method for identifying and prioritizing monitoring units (22, 28, 30, 32) that need to be replaced when there is an interaction between the monitoring units (22, 28, 30, 32), in which an expected increase in the travel distance of the emission quality of at least one emission component is calculated on the basis of driving parameters and diagnostic parameters of the monitoring units, whereby a first priority list (45) is created, the first priority list is changed by means of an interaction matrix (46) and a correction factor (KF) in such a way that a second priority list (50) can be created, on the basis of which the monitoring units (22, 28, 30, 32) can be replaced.

Description

Technical Field

[0001] The present invention relates to a method for identifying and prioritizing monitoring units to be replaced when there is an interaction between monitoring units. Background Art

[0002] Modern vehicle internal combustion engines have a large number of monitoring units or sensors through which optimal combustion and subsequent exhaust gas aftertreatment are controlled. Therefore, faulty monitoring units and sensors lead to malfunctions in engine control and thus to increased exhaust gas emissions and non-optimal combustion processes.

[0003] For this reason, today's vehicles have on-board diagnostic systems that are used to identify faulty sensors or monitoring units. These diagnostics include, for example, checking the plausibility of measured values, i.e., whether the values of the monitoring units are within the permitted range for the respective operating state, whether the corresponding values of the monitoring units match each other, and whether the measured increase in these values is within the actually possible range. These monitoring units are used for system diagnostics and component diagnostics. On the one hand, these checks are intended to ensure the normal operation of the engine, and on the other hand, to prevent engine damage and ensure compliance with legally permitted limit values. If a corresponding fault is detected, a so-called emergency operation program is then activated to prevent subsequent damage.

[0004] In addition, this on-board diagnostics is used to simplify maintenance by identifying faulty monitoring units by reading the engine control unit in a repair shop.

[0005] However, it has proven that the monitoring units replaced in a repair shop are often not defective, and other monitoring units then have to be replaced until the correct fault is identified. The reason for this incorrect replacement lies particularly in the fact that the individual monitoring units influence each other in part, whereby one sensor is shown as faulty, yet its value is incorrect due to the fault of another sensor. Here, the influence of the oxygen sensor or lambda probe on the fuel injection system and the detection of occurring misfires are mentioned by way of example. Summary of the Invention

[0006] Therefore, the aim is to create a method for identifying and prioritizing monitoring units to be replaced when there is an interaction between monitoring units, by means of which the probability of correctly identifying and correspondingly replacing the actually defective monitoring units is significantly increased. Correspondingly, the aim is to avoid, as far as possible, replacing sensors or monitoring units that are still working properly.

[0007] In the method according to the invention for identifying and prioritizing monitoring units to be replaced when there is an interaction between the monitoring units, first, the driving parameters of the vehicle are collected and stored over a defined number of driving cycles. This is typically done in the engine control unit of the vehicle. Additionally, over a defined number of driving cycles of the vehicle, the diagnostic parameters of each monitoring unit are collected and stored from the diagnostic statistics of the monitoring units, and thereby the damage state of the corresponding monitoring unit is determined. Here, the monitoring units monitor both individual components and the entire system, or only the existing parameters. This is done during on-vehicle monitoring of the vehicle. Next, the expected change over the travel distance of the emission quality of at least one defined emission component is determined and stored, taking into account not only the driving parameters but also the damage state and aging factor of the monitoring units of the vehicle. Thus, this change is typically an increase, as when damage or aging of the monitoring unit is determined, a deterioration of combustion or a decrease in the efficiency of the exhaust gas aftertreatment unit is expected. Furthermore, a first priority list is created based on the existing damage state of the individual monitoring units. This means that for each monitoring unit there is a value based on the frequency and magnitude of the faults during the stored driving cycles, which represents the degree of damage present at that monitoring unit. Additionally, an interaction matrix is saved and stored, in which it is determined whether the damage state of a monitoring unit affects the damage state of another monitoring unit. This matrix remains constant and only contains the possible influence of one monitoring unit on another due to the damage of the latter. Additionally, a correction factor is stored, which is used to correct the expected increase over the travel distance of the emission quality of the affected monitoring unit when such an interaction exists and the damage state of the influencing monitoring unit exceeds a threshold. Thus, the correction factor is determined for any possible cross-influence between the monitoring units. Next, a second priority list is created for the monitoring units based on the magnitude of the corrected expected increase in emission quality. Next, the monitoring units are replaced according to the order of this second priority list. Thus, in this method step, the previously calculated increase in the emission load of the affected monitoring unit due to the damage of another monitoring unit is corrected. The affected monitoring unit is correspondingly shifted in the priority list due to the correction factor. As a result, when the damage state of a certain monitoring unit has been determined, if another monitoring unit that also has a cross-influence on this monitoring unit also has a damage state exceeding the defined threshold, it no longer directly leads to the replacement of this monitoring unit. Since additional influences, such as known, frequently occurring damage to the corresponding monitoring unit, can also be saved in the priority list or the correction factor, in this way a tool is provided for the repair shop, with which the frequency of replacing faultless monitoring units can be significantly reduced.

[0008] Thus, in addition to the second priority list, the cost of replacing the monitoring unit is preferably considered in the repair logic. This can be done via a correction factor or can be considered as an additional factor in the second priority list. Thus, unnecessary replacements of spare parts that are very costly are mainly reduced.

[0009] Advantageously, the load state, speed and distance traveled of the vehicle are considered as the driving parameters on which the calculation of the emission load is based. These values are generally sufficient to enable a reliable emission load to be determined via an exhaust gas model.

[0010] Preferably, a driving data acquisition matrix is created based on the driving parameters and the integrated air quality, and this driving data acquisition matrix is used as an input value for calculating the expected change or increase over the travel distance of the emission quality of the at least one defined emission component. Correspondingly, the increase in emission quality is always obtained from the actual driving parameters.

[0011] Furthermore, preferably a misfire matrix is created based on the engine speed, load and number of misfires, and this misfire matrix is used as an input value for calculating the expected increase over the travel distance of the emission quality of the at least one defined emission component. This is also used for calculating the actually occurring emissions.

[0012] In another advantageous embodiment, an emission impact diagram for the emission load is stored for each monitoring unit, in which the load related to the respective emission component expected at the respective monitoring unit based on the load state and engine speed is saved in the case of the assumption of a completely damaged state and complete aging of the respective monitoring unit, the data of which is corrected by the determined damage state and aging factor, and then the increase in the emission load related to the respective exhaust gas component at the respective monitoring unit is calculated by performing a matrix multiplication operation with the driving data acquisition matrix. The emission impact diagram can be obtained via an exhaust gas model or actual measurement and is thus used as a basis for calculating the following estimated emission impact due to the aging or damage state of the monitoring unit.

[0013] The monitoring unit preferably comprises at least a monitoring unit for measuring the oxygen concentration, a monitoring unit for the fuel supply system, a monitoring unit for determining combustion interruption or misfire, and a monitoring unit for determining the air-fuel ratio of each cylinder. These monitoring units can in particular be constituted by an oxygen sensor or lambda probe, a misfire detector for detecting combustion interruption or misfire (by means of which the unevenness between cylinders can be determined) and a lambda probe with a corresponding detector (for determining the unevenness of the engine operation), wherein in the latter case the unevenness of the air-fuel ratio in the cylinder can be determined based on the data. These sensors and monitoring units in particular constitute the most important sensors for calculating emissions and correctly controlling the internal combustion engine.

[0014] Advantageously, the repair logic is connected via a network to repair statistics in which the failure frequencies of the monitoring units are collected. These failure frequencies can then also be taken into account in the priority list, whereby known failures can be considered, which results in a further optimization of the order of the monitoring units to be replaced.

[0015] Furthermore, it is preferred that a plurality of driving cycles are stored in the storage unit, wherein the stored data at least includes the driving data acquisition matrix and the damage state data from on-board diagnostics. Correspondingly, more data is provided, which again enables the improvement of the priority list.

[0016] In a particularly preferred embodiment, a defined number of driving cycles are stored in which at least one of the emission measurement values exceeds a threshold value. Wherein, when the number of driving cycles exceeds the defined number, the respective oldest driving cycle is overwritten with the latest driving cycle. In this way, only the driving cycles in which a fault occurs are considered. In this way, the total number of driving cycles to be stored can be reduced, and thus the storage space used can be reduced.

[0017] In another advantageous design, the aging factor is determined based on the oxygen storage capacity of the catalytic converter and correspondingly taken into account.

[0018] Preferably, the driving data acquisition matrix, the emission influence diagram, the interaction matrix and the correction factor table with correction factors are stored on the repair logic of a computer or saved based on a website. Correspondingly, these data can be provided to these repair workshops on the computers in the repair workshops, and these data can be collected in order to also improve the correction factors by artificial intelligence if necessary.

[0019] Therefore, a method for identifying and prioritizing the monitoring units to be replaced when there is an interaction between the monitoring units is provided, by which method the interaction existing between the respective damage states of the monitoring units is considered, whereby the actually defective monitoring units can be identified more accurately. Description of the Drawings

[0020] Embodiments of the method according to the invention for identifying and prioritizing the monitoring units to be replaced when there is an interaction between the monitoring units will be described below with reference to the drawings.

[0021] Figure 1 The flow of the method according to the invention is schematically shown.

[0022] Figure 2 An example for creating a priority list in the event of a fault at the oxygen sensor is schematically shown.

[0023] Figure 3Schematically shows an example of creating a priority list when two faults occur at a monitoring unit and there are multiple dependencies. Detailed implementation

[0024] In the method according to the invention, first, in the vehicle 10, the engine control unit 12 records and stores driving parameters during a driving cycle N. In this embodiment, these driving parameters include the load state 14, speed 16, and traveled distance 18 of the internal combustion engine, and include the resulting driving performance. In addition, a misfire event 20 is detected by a monitoring unit 22 for detecting misfires. A driving data acquisition matrix 24 is created based on the driving parameters, which includes the engine speed 21 and load state 14 related to the corresponding cumulative air quality. To monitor misfires, a matrix 26 regarding the detected misfires can also be plotted.

[0025] Additionally, during on-vehicle monitoring, the internal combustion engine and the exhaust gas equipment are monitored by a large number of monitoring units. In this embodiment, in addition to the aforementioned monitoring unit 22 for detecting misfires, these monitoring units are also an oxygen sensor or a lambda probe 28, a monitoring unit 30 of the fuel system (which may include, for example, a fuel pressure sensor and a sensor for measuring fuel consumption or valve opening time), and a monitoring unit 32 for monitoring the unevenness of the air-fuel ratio of each cylinder. If one or more of the monitoring units 22, 28, 30, 32 output unreasonable values, this situation is stored as a damage state SOD in the diagnostic statistics 33 as a diagnostic parameter. Reasonableness involves checking whether the values of the monitoring units are within the defined range in the corresponding operating state, whether the corresponding values match each other, and whether the measured increase in these values is within the actually possible range. The more frequently the monitoring units 22, 28, 30, 32 output unreasonable values and the higher the deviation from the actual expected values, the higher the determined damage state SOD of the corresponding monitoring units 22, 28, 30, 32.

[0026] For each driving cycle N, the information stored in the engine control unit 10 in this way is stored. For this purpose, the storage unit 34 always contains, for example, ten driving cycles, in which cases where the emission measurement values exceed the limit values are determined and thus the damage state SOD of one of the monitoring units 22, 28, 30, 32 can be inferred. After storing more than ten driving cycles N, the oldest driving cycle is always deleted and replaced with the latest driving cycle.

[0027] Now, if the driver of the vehicle 10 becomes aware of a fault in the system, for example, through the engine light coming on, he will then take his vehicle to a repair shop.

[0028] In the repair shop, the stored driving cycles from N to N+9 are read out on a computer, and the emission loads of the monitoring units 22, 28, 30, 32 are calculated for the stored driving cycles from N to N+9 by means of an exhaust gas model. First, the emissions are calculated according to the driving data acquisition matrix 24. For this purpose, emission impact diagrams 38, 40, 42, 44 are saved for each monitoring unit 22, 28, 30, 32, from which the expected emissions in such driving cycles from N to N+9 can be read, wherein these emission impact diagrams 38, 40, 42, 44 are created based on: the corresponding monitoring units 22, 28, 30, 32 no longer have a function, are in a 100% damaged state or are completely aged. Now these emissions that define the emission components are corrected according to the damage state SOD and the aging factor AF of the corresponding monitoring units 22, 28, 30, 32. This means that in the case where the monitoring units 22, 28, 30, 32 have a damage state of less than 100%, the corresponding value of the emission load at this monitoring unit is corrected downwards. By subsequently performing a matrix multiplication operation with the driving data acquisition matrix 24, the estimated emission impact EMI of the defined emission components is calculated, in mg / km. Thereby, an emission table is created, which, for example, shows by how many mg / km of nitrogen oxides the emission loads of the monitoring units 22, 28, 30, 32 have increased due to the previous calculation. Thereby, a first priority list 45 is created, in which the monitoring units 22, 28, 30, 32 with the largest increase based on the emission table occupy the first place in the priority list 45. The following monitoring units 22, 28, 30, 32 are arranged in descending order of emission increase.

[0029] In addition, the computer contains a repair logic 36 with an interaction matrix 46, in which the degree to which the damage state SOD of one monitoring unit 22, 28, 30, 32 affects the determined damage state SOD of another monitoring unit 22, 28, 30, 32 is saved. This interaction matrix 46 represents the damage limit beyond which one monitoring unit affects another monitoring unit. Here, the y-axis represents the monitoring units 22, 28, 30, 32 in the damage state SOD, and the x-axis represents those monitoring units 22, 28, 30, 32 that can be affected. If the damage state SOD exceeds the threshold specified in the interaction matrix 46, the corresponding monitoring unit 22, 28, 30, 32 specified on the x-axis is considered to be affected.

[0030] In Figure 2A corresponding example is shown. The first table shows a first priority list 45, which contains the determined damage states SOD of the four monitoring units 22, 28, 30, 32 specified here by way of example and the calculated increase in nitrogen oxide emissions. In the interaction matrix 46, a limit value for the damage state SOD of one of the monitoring units 22, 28, 30, 32 is specified, beyond which another monitoring unit 22, 28, 30, 32 is affected. The only monitoring unit that exceeds one of the specified limit values is the lambda probe 28 with a (damage state SOD of) 80%, which exceeds the limit value of 75 that may affect the monitoring unit 22 for detecting misfires. Therefore, in each row of the interaction matrix 46, it is read whether the determined damage state of the corresponding monitoring unit 22, 28, 30, 32 exceeds one of the thresholds specified there. This only occurs for the misfire monitoring unit 22, the threshold of which is specified as 75%, while the damage state of the lambda probe 28 reaches 80% and has exceeded this threshold. Accordingly, the value of the misfire monitoring unit 22 must be corrected.

[0031] For this purpose, a correction factor table 48 with correction factors KF is used, which can depend on different factors and are measured or defined during the development of the vehicle 10. The correction factors can subsequently be modified on-site according to new on-site data by artificial intelligence, since the relevant software does not run in the vehicle, but on the repair logic 36 of a computer or based on a website. Therefore, it can also be considered here whether it is known from the on-site data that the monitoring units 22, 28, 30, 32 are more error-prone or experience faster aging.

[0032] In this example, the relevant correction factor KF for the affected misfire monitoring unit 22 is 0.4. For the misfire monitoring unit 22, an increase in the emission component nitrogen oxide of 10 mg / km is calculated, which means that this value is listed in the first position in the first priority list 45. By multiplying by the correction factor KF 0.4, this increase is reduced to 4 mg / km, whereby the misfire monitoring unit 22 for determination is moved to the third position in the newly created second priority list 50, and now, due to the damage state, the monitoring unit 32 for determining the air-fuel ratio of each cylinder with an increase of 8 mg / km is moved to the first position. Therefore, the monitoring unit 32 for determining the air-fuel ratio of each cylinder may be the first monitoring unit to be replaced for troubleshooting in the repair shop.

[0033] In Figure 3Another embodiment of creating and calculating the second priority list 50 is shown. The calculated growth of nitrogen oxides due to measurement data is successively 10 mg / km for the monitoring unit 22 for determining misfires, 8 mg / km for the monitoring unit 32 for air-fuel balance, 5 mg / km for the monitoring unit 28 for measuring the oxygen concentration (i.e., the oxygen concentration of the oxygen sensor or lambda probe), and 1 mg / km for the monitoring unit 30 for the fuel system. Here, the damage states of both the monitoring unit 28 for measuring the oxygen concentration and the monitoring unit 32 for air-fuel balance partially exceed the specified thresholds. Here, both values are 80%. This results in, as in the first embodiment, that the determined growth of nitrogen oxides of the monitoring unit 22 for determining misfires must be corrected by the damage state SOD of the monitoring unit 28 for measuring the oxygen concentration. The damage state SOD of the monitoring unit 32 for measuring the air-fuel ratio of each cylinder results in that, in addition to the determined growth of nitrogen oxides of the monitoring unit 22 for detecting misfires, the determined growth of nitrogen oxides of the monitoring unit 28 for measuring the oxygen concentration and the monitoring unit 30 for the fuel system must also be corrected. Therefore, only the growth value of the monitoring unit 32 for measuring the air-fuel ratio remains unaffected, while the other three values are corrected by the correction factor KF. Thus, by multiplying by the correction factor of 0.5 for the monitoring unit 28 for measuring the oxygen concentration, the value is 2.5 mg / km, by multiplying by the correction factor of 0.2 for the monitoring unit 30 for the fuel system, the value is 0.2 mg / km, and by multiplying by the correction factor of 0.4 for the monitoring unit 22 for determining misfires, the value is 4 mg / km. Thereby, the monitoring unit 32 for measuring the air-fuel ratio moves from the second place to the first place in the second priority list 50, the monitoring unit 22 for determining misfires moves from the first place to the second place, and the monitoring units 28 for determining the oxygen concentration and 30 for the fuel system remain unchanged in the third and fourth places.

[0034] Thus, by this method, the priority for replacing the monitoring unit can be shifted by taking into account the mutual influence of the individual monitoring units in the repair shop in addition to the existing determined damage states. This is carried out depending on the existing driving data and, if necessary, when referring to additional statistical data for the correction factor or otherwise, also depending on the existing experience of the occurring faults.

[0035] It should also be clear that in addition to the described monitoring units, all other monitoring units and sensors can be considered. Furthermore, in addition to the influence of the growth of the nitrogen oxide content, the growth of any other emission components can be calculated and considered. Here, the ammonia content is specifically mentioned, and this ammonia content is equally applicable to this method. Additionally, the costs arising from the replacement can also be additionally considered during the final priority ranking.

Claims

1. A method for identifying and prioritizing monitoring units (22, 28, 30, 32) to be replaced when there is an interaction between the monitoring units (22, 28, 30, 32), the method comprising the following steps: - Collecting and storing driving parameters during a defined number (N) of driving cycles of the vehicle (10); - During the defined number (N) of driving cycles of the vehicle (10), collecting and storing diagnostic parameters of each monitoring unit (22, 28, 30, 32) from the diagnostic statistics (33) of the monitoring units (22, 28, 30, 32) to determine the damage state (SOD) of the corresponding monitoring unit (22, 28, 30, 32); - Based on the driving parameters, the damage state (SOD) and the aging factor (AF) of the monitoring units (22, 28, 30, 32) of the vehicle (10), determining and storing the expected increase in the emission quality of at least one defined emission component with the traveled distance; - Determining a first priority list (45) according to the corresponding damage state (SOD) of the monitoring units (22, 28, 30, 32); - Storing an interaction matrix (46), and determining in the interaction matrix whether the damage state (SOD) of one monitoring unit among the monitoring units (22, 28, 30, 32) affects the damage state (SOD) of another monitoring unit (22, 28, 30, 32); - Storing a correction factor (KF), and when there is such an interaction and the damage state (SOD) of the influencing monitoring unit (22, 28, 30, 32) exceeds a threshold, using the correction factor to correct the determined expected increase in the emission quality of the affected monitoring unit (22, 28, 30, 32) with the traveled distance; - Creating a second priority list (50) according to the magnitude of the expected increase in the emission quality of the monitoring units (22, 28, 30, 32) corrected by means of the correction factor (KF), and replacing the monitoring units (22, 28, 30, 32) according to the second priority list.

2. The method for identifying and prioritizing monitoring units to be replaced according to claim 1, characterized in that in addition to the second priority list (50), the cost of replacing the monitoring units (22, 28, 30, 32) is also considered in the repair logic (36).

3. The method for identifying and prioritizing monitoring units to be replaced according to claim 1 or 2, characterized in that the load state (14), the speed (16) and the traveled distance (18) of the vehicle (10) are considered as the driving parameters for calculating the emission load.

4. The method for identifying and prioritizing monitoring units to be replaced according to one of the preceding claims, characterized in that Create a driving data acquisition matrix (24) based on driving parameters and cumulative air quality, and use the driving data acquisition matrix as an input value to calculate the expected increase in the emission mass of the at least one defined emission component over the driving distance.

5. The method for identifying and prioritizing monitoring units to be replaced according to one of the preceding claims, characterized in that create a misfire matrix (26) based on the engine speed (21), the load state (14) and the number of misfires, and use the misfire matrix as an input value to calculate the expected increase in the emission mass of the at least one defined emission component over the driving distance.

6. The method for identifying and prioritizing monitoring units to be replaced according to one of the preceding claims, characterized in that store the emission impact diagrams (38, 40, 42, 44) of the emission load for each monitoring unit (22, 28, 30, 32). In the emission impact diagrams, the loads related to the corresponding emission components expected at the corresponding monitoring unit (22, 28, 30, 32) according to the load state (14) and the engine speed (21) are stored under the assumption of a complete failure state (SOD) and complete aging of the corresponding monitoring unit (22, 28, 30, 32). The data is corrected by the determined failure state (SOD) and aging factor (AF), and then the increase in the emission load of the corresponding exhaust gas components at the corresponding monitoring unit (22, 28, 30, 32) is calculated by performing a matrix multiplication operation with the driving data acquisition matrix (24).

7. The method for identifying and prioritizing monitoring units to be replaced according to one of the preceding claims, characterized in that the monitoring unit (22, 28, 30, 32) at least includes a monitoring unit (28) for measuring the oxygen concentration, a monitoring unit (30) of the fuel system, a monitoring unit (22) for determining combustion interruption or misfire, and a monitoring unit (32) for determining the air-fuel ratio of each cylinder.

8. The method for identifying and prioritizing monitoring units to be replaced according to one of the preceding claims, characterized in that the repair logic (36) is connected to the repair statistics data through a network, and the failure frequencies of the monitoring units (22, 28, 30, 32) are collected in the repair statistics data.

9. The method for identifying and prioritizing monitoring units to be replaced according to one of the preceding claims, characterized in that store a plurality of driving cycles in the storage unit (34), wherein the stored data includes the driving data acquisition matrix (24) and the failure state data (SOD) from on-board diagnostics.

10. The method for identifying and prioritizing monitoring units to be replaced according to one of the preceding claims, characterized in that Store a limited number of driving cycles in which at least one of the emission measurements exceeds a threshold value, wherein when the number of driving cycles exceeds the limited number, the oldest driving cycle is overwritten with the latest driving cycle.

11. The method for identifying and prioritizing monitoring units to be replaced according to one of the preceding claims, characterized in that the aging factor (AF) is determined based on the oxygen storage capacity of the catalytic converter.

12. The method for identifying and prioritizing monitoring units to be replaced according to one of the preceding claims, characterized in that the driving data acquisition matrix (24), the emission impact diagrams (38, 40, 42, 44), the interaction matrix (46) and the correction factor table (48) with the correction factor (KF) are stored on the repair logic (36) of a computer or stored based on a website.

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