Urea quality detection method and device, computer device and storage medium

Abstract

The present application relates to the technical field of Internet of Vehicles big data analysis, and discloses a urea quality detection method and device, computer equipment and a storage medium, the method comprising: in the case where it is determined that the to-be-detected data of a vehicle is not tampered with, obtaining the emission amount of a preset compound of the vehicle within a preset time length; determining whether the emission amount of the preset compound is within a preset range, and taking the vehicle corresponding to the emission amount of the preset compound that is not within the preset range as a to-be-detected vehicle; determining whether a preset fault code of the to-be-detected vehicle is received, and if not, determining that the to-be-detected vehicle is a target vehicle, wherein the target vehicle has a urea quality abnormality problem, and the preset fault code is generated after a problem other than the urea quality abnormality problem of the vehicle occurs. The present application solves the problem that it is difficult to efficiently determine whether the vehicle has tampered with data and to detect the quality of the urea of the vehicle to determine the vehicle having a urea quality abnormality problem.

Description

Technical Field

[0001] This invention relates to the field of vehicle networking big data analysis technology, specifically to a urea quality detection method, device, computer equipment, and storage medium. Background Technology

[0002] Nitrogen oxides (NOx) emissions from heavy commercial vehicles such as diesel trucks are a significant contributor to urban air pollution, making them a key target for emissions monitoring. The primary technology for controlling exhaust emissions from heavy commercial vehicles involves installing a Selective Catalytic Reduction (SCR) device at the exhaust tailpipe to reduce NOx concentrations. However, diesel trucks using SCR for exhaust purification consume urea, increasing operating costs. To reduce these costs, some vehicles reduce urea injection or use substandard urea. Therefore, efficiently testing the quality of urea used in vehicles, identifying urea quality issues, and tracing the source of problematic urea remain challenging problems.

[0003] Therefore, the relevant technologies have the problem of being unable to efficiently determine whether a vehicle's data has been tampered with and to perform quality testing on the vehicle's urea to identify vehicles with abnormal urea quality. Summary of the Invention

[0004] In view of this, the present invention provides a urea quality detection method, apparatus, computer equipment, and storage medium to solve the problem of difficulty in efficiently determining whether vehicle data has been tampered with and performing urea quality detection on vehicles to identify vehicles with abnormal urea quality.

[0005] In a first aspect, the present invention provides a method for detecting urea quality, the method comprising:

[0006] Assuming the vehicle's test data has not been tampered with, obtain the vehicle's preset compound emissions within a preset time period;

[0007] Determine whether the preset compound emission level is within the preset range, and designate vehicles with preset compound emission levels that are not within the preset range as vehicles to be tested;

[0008] Determine whether a preset fault code for the vehicle under test has been received. If not, then the vehicle under test is identified as the target vehicle. The target vehicle has a urea quality abnormality problem. The preset fault code is generated after the vehicle has a problem other than the urea quality abnormality problem.

[0009] The urea quality detection method provided in this embodiment first determines whether the vehicle's data to be tested has been tampered with. If not, it identifies the vehicle to be tested using preset compound emission levels and then filters out target vehicles with urea quality abnormalities from the list of vehicles to be tested using preset fault codes. It features high real-time performance, wide application range, low detection cost, and the ability to complete urea quality detection even when the vehicle is stationary. It can determine the urea quality used by vehicles within a wide range. This solves the problem of related technologies struggling to efficiently determine whether vehicle data has been tampered with and to perform urea quality testing to identify vehicles with urea quality abnormalities.

[0010] In one alternative implementation, before obtaining the preset compound emissions of the vehicle over a preset time period, the method further includes:

[0011] Acquire the vehicle's bus simulation data, which is included in the data to be detected;

[0012] Determine whether the bus simulation data is consistent with the preset data. If they are inconsistent, determine that the vehicle is a vehicle whose data to be tested has been tampered with.

[0013] Acquire vehicle operating data and selective catalytic reduction unit status data, wherein the operating data and status data are included in the data to be detected;

[0014] The system determines whether the status data has been tampered with based on the operational data. If so, the vehicle is identified as having had its data tampered with.

[0015] Acquire the vehicle's bus data, which is included in the data to be detected;

[0016] Based on the bus data, determine whether the urea level in the bus data has been tampered with. If so, determine that the vehicle is a vehicle whose data to be detected has been tampered with.

[0017] In this embodiment, the system sequentially determines whether a vehicle has had its data tampered with based on bus simulation data, operational data, status data, and bus data. This provides high real-time performance, enabling timely and effective detection of data tampering. Furthermore, identifying which vehicles have tampered with data is beneficial for subsequent urinalysis.

[0018] In one optional implementation, determining whether the urea level in the bus data has been tampered with, based on the bus data, includes:

[0019] The vehicle's urea level, urea consumption, mileage, and running time are obtained from the bus data.

[0020] Determine whether the urea level is the same at different times during vehicle operation. If it is the same, the urea level has been tampered with.

[0021] Based on mileage and urea consumption, the vehicle's urea consumption per unit mileage is obtained.

[0022] The vehicle's urea consumption per unit time is obtained based on the running time and urea consumption.

[0023] Determine whether the urea consumption per unit mileage falls within the first preset range. If not, the urea level has been tampered with. Alternatively, determine whether the urea consumption per unit time falls within the second preset range. If not, the urea level has been tampered with.

[0024] In this embodiment, the relationship between urea level, urea consumption and mileage, and urea consumption and duration is used to determine whether the urea level has been tampered with, which is highly real-time and accurate.

[0025] In one alternative implementation, before determining whether a preset fault code for the vehicle to be tested has been received, the method further includes:

[0026] When the temperature of the selective catalytic reduction device is higher than the preset temperature, the average concentration of the preset compound in the emission gas of the vehicle to be tested is obtained within a preset time period.

[0027] Vehicles with concentrations less than or equal to the first preset threshold are selected as candidate vehicles.

[0028] Candidate vehicles are removed from the list of vehicles to be tested.

[0029] In this embodiment, the average concentration of preset compounds in the vehicle's exhaust gas is used to further determine whether the vehicle is emitting too many preset compounds. Candidate vehicles with normal emissions are removed from the list of vehicles to be tested, reducing the number of vehicles to be tested and improving the efficiency of urea quality testing and subsequent determination of the target urea addition location.

[0030] In one alternative implementation, after determining that the vehicle to be detected is the target vehicle, the method further includes:

[0031] Obtain the location information and urea level of all vehicles at different times, including the target vehicle;

[0032] Based on the urea level at different times, the change in urea level at each time relative to the previous time is obtained.

[0033] The moment when the change in urea level exceeds the second preset threshold is taken as the moment when urea is added to the vehicle.

[0034] Based on the location information and the time of urea refill, the location for refilling urea for the vehicle is determined;

[0035] The amount of urea added to the vehicle is obtained based on the urea level and the time of urea addition.

[0036] The target urea addition location was determined based on the location and amount of urea added, where the target urea addition location had an abnormal urea quality issue.

[0037] In this implementation, the time when urea is added to the vehicle is first determined, followed by the location and amount of urea added. Finally, based on the location and amount of urea added, the target urea addition location with abnormal urea quality is identified. This completes the tracing of the source of the problematic urea, facilitating subsequent treatment of the problematic urea.

[0038] In one optional implementation, determining the target urea addition location based on the urea addition location and the amount of urea added includes:

[0039] The locations and amounts of urea added to vehicles are clustered to obtain the first clustering result, which is used to determine the total amount of urea added at different locations.

[0040] The locations and amounts of urea added to the target vehicles are clustered to obtain a second clustering result, which is used to identify the locations where urea quality is abnormal.

[0041] Based on the results of the first and second clustering, the target location for adding urea is obtained.

[0042] In one alternative implementation, before obtaining the preset compound emissions of the vehicle over a preset time period, the method further includes:

[0043] Obtain vehicle operating condition data;

[0044] Based on the changing trends and correlation coefficients of different parameters in the working condition data, determine whether the working condition data meets the preset conditions.

[0045] If the operating data meets the preset conditions, the preset compound emissions can be obtained based on the operating data.

[0046] In this embodiment, the authenticity of the operating condition data is determined based on the changing trends and correlation coefficients of different parameters in the operating condition data. The preset compound emission amount is obtained based on the actual operating condition data, improving the accuracy of subsequent urine quality testing.

[0047] In a second aspect, the present invention provides a urea quality detection device, the device comprising:

[0048] The first acquisition module is used to acquire the preset compound emissions of the vehicle within a preset time period, provided that the vehicle's test data has not been tampered with.

[0049] The first judgment module is used to determine whether the preset compound emission amount is within the preset range, and to identify vehicles with preset compound emission amounts that are not within the preset range as vehicles to be tested.

[0050] The second judgment module is used to determine whether a preset fault code of the vehicle to be tested has been received. If not, the vehicle to be tested is determined to be the target vehicle. The target vehicle has a urea quality abnormality problem. The preset fault code is generated after the vehicle has a problem other than the urea quality abnormality problem.

[0051] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the urea quality detection method of the first aspect or any corresponding embodiment described above.

[0052] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the urea quality detection method of the first aspect or any corresponding embodiment described above. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of the present invention, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0054] Figure 1 This is a schematic flowchart of a urea quality testing method according to an embodiment of the present invention;

[0055] Figure 2 This is a schematic diagram of the process for determining whether a vehicle has tampered with the data to be detected, according to an embodiment of the present invention;

[0056] Figure 3 This is a schematic diagram of urea level jump according to an embodiment of the present invention;

[0057] Figure 4 This is a structural block diagram of a urea quality testing device according to an embodiment of the present invention;

[0058] Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] For commercial vehicles today, due to increasing customer demands, engine software is becoming increasingly complex and diverse, and user scenarios vary considerably. To meet emission requirements, some vehicles may tamper with engine data. Accurately and promptly determining whether engine software data has been tampered with or falsified presents a significant challenge. Furthermore, after confirming a urea quality issue in a vehicle, further identifying the source of the abnormal urea is also an urgent need.

[0061] Based on the above, this invention provides a urea quality detection method. First, it determines whether the vehicle's engine software data awaiting detection has been tampered with. If the data is confirmed to be unaltered, it determines whether the vehicle's exhaust emissions exceed standards based on a preset compound emission level within a preset time period. If emissions exceed standards, the cause is determined. If causes other than urea quality issues can be ruled out, then the vehicle's excessive emissions are due to a urea quality problem. This achieves the effect of using actual vehicle operating data to detect the vehicle's urea quality in real time.

[0062] According to an embodiment of the present invention, a method for detecting urea quality is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer device with data processing capabilities, such as a computer, server, etc. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0063] This embodiment provides a method for detecting urea quality, which can be used with the aforementioned computer equipment. Figure 1 This is a flowchart of a urea quality detection method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0064] Step S101: If it is determined that the vehicle's test data has not been tampered with, obtain the vehicle's preset compound emissions within a preset time period.

[0065] Specifically, the first step is to determine whether the vehicle's data to be tested has been tampered with. This data could include, for example, data uploaded to the vehicle networking platform by the TBOX (telematics box, remote / vehicle communication module) or data such as the urea level in the vehicle's CAN (Controller Area Network) bus. Virtual data can be generated at the vehicle end, and the TBOX can send this virtual data to the vehicle networking platform. The platform then compares the received data with the correct data to determine if the TBOX has tampered with the data. Alternatively, the data in the CAN bus can also be considered to determine tampering. For example, as the vehicle's mileage / duration increases, it consumes urea, and the corresponding urea level changes. If the urea level remains unchanged, then data tampering has occurred.

[0066] The preset compounds are, for example, nitrogen oxides (NOx), and the preset time periods are, for example, 1 minute, 5 minutes, etc. Assuming the vehicle's data to be tested has not been tampered with, the emission amount of the preset compounds within the preset time periods is obtained. The steps include: calculating the average NOx emission rate over a continuous period using a moving average method; and multiplying the average emission rate by the preset time period to obtain the corresponding NOx emission amount for each preset time period. Specifically, the moving average method first calculates the total NOx emissions from the vehicle in the known data using integration, and then divides this by time to calculate the average NOx emission rate.

[0067] Step S102: Determine whether the preset compound emission level is within the preset range, and designate vehicles with preset compound emission levels that are not within the preset range as vehicles to be tested.

[0068] Specifically, the preset range is, for example, 0-50 mg, with the exact range set according to actual needs. If the preset compound emission level is within the preset range, it indicates that the vehicle's exhaust emissions are within acceptable limits. If the preset compound emission level is outside the preset range, it indicates that the vehicle's exhaust emissions exceed acceptable limits. It is necessary to investigate the cause of the excessive exhaust emissions and determine if the cause is an abnormality in urea quality. Therefore, vehicles with preset compound emission levels outside the preset range will be selected as the vehicles to be tested.

[0069] Step S103: Determine whether a preset fault code for the vehicle to be tested has been received. If not, determine that the vehicle to be tested is the target vehicle. The target vehicle has a urea quality abnormality problem. The preset fault code is generated after the vehicle has a problem other than the urea quality abnormality problem.

[0070] Specifically, the causes of excessive exhaust emissions include: abnormal urea quality, fuel quality issues, SCR inlet temperature problems, lack of urea, and failure to inject urea. Among these, when a vehicle experiences problems with fuel quality, SCR inlet temperature, lack of urea, or failure to inject urea, corresponding fault codes, i.e., preset fault codes, will be generated.

[0071] If the vehicle under test is confirmed to have generated the aforementioned preset fault code, then the cause of the excessive exhaust emissions is not a problem with the urea quality. However, if no preset fault code is received from the vehicle under test, meaning the vehicle has not generated a preset fault code, then the cause of the excessive exhaust emissions can only be a problem with the urea quality. In this case, the urea in the vehicle under test is substandard and has a quality issue.

[0072] In addition, when the urea concentration is not within the range of 28.5%-32.5%, the engine of some vehicles will report an abnormal urea concentration fault code. If the vehicle networking platform receives the abnormal urea concentration fault code, it can directly determine that the vehicle has an abnormal urea quality problem.

[0073] The vehicle-to-everything (V2X) platform outputs detection results via portable devices such as mobile phones and tablets, including the target vehicle and the target urea refill location. Through the vehicle's OBD interface, it can meet needs such as determining whether vehicle data has been tampered with, performing quality checks on the vehicle's urea, and identifying the source of abnormal urea. OBD (On-Board Diagnostics) refers to the on-board automatic diagnostic system.

[0074] The urea quality detection method provided in this embodiment first determines whether the vehicle's data to be tested has been tampered with. If not, it identifies the vehicle to be tested using preset compound emission levels and then filters out target vehicles with urea quality abnormalities from the list of vehicles to be tested using preset fault codes. It features high real-time performance, wide application range, low detection cost, and the ability to complete urea quality detection even when the vehicle is stationary. It can determine the urea quality used by vehicles within a wide range. This solves the problem of related technologies struggling to efficiently determine whether vehicle data has been tampered with and to perform urea quality testing to identify vehicles with urea quality abnormalities.

[0075] In some alternative implementations, the method further includes, before obtaining the preset compound emissions of the vehicle over a preset time period:

[0076] Acquire the vehicle's bus simulation data, which is included in the data to be detected;

[0077] Determine whether the bus simulation data is consistent with the preset data. If they are inconsistent, determine that the vehicle is a vehicle whose data to be tested has been tampered with.

[0078] Acquire vehicle operating data and selective catalytic reduction unit status data, wherein the operating data and status data are included in the data to be detected;

[0079] The system determines whether the status data has been tampered with based on the operational data. If so, the vehicle is identified as having had its data tampered with.

[0080] Acquire the vehicle's bus data, which is included in the data to be detected;

[0081] Based on the bus data, determine whether the urea level in the bus data has been tampered with. If so, determine that the vehicle is a vehicle whose data to be detected has been tampered with.

[0082] Specifically, in combination Figure 2 This embodiment will now be described. The data to be detected in this embodiment includes: bus simulation data, vehicle operating data, selective catalytic reduction (SCR) status data, and bus data.

[0083] Simulate CAN bus data on the vehicle side to generate bus simulation data, such as... Figure 2 As shown, the bus simulation data includes, for example, data within the normal range, data exceeding the limit, and invalid data. The bus simulation data is sent to the vehicle networking platform via the TBOX.

[0084] The vehicle-to-everything (V2X) platform acquires simulated bus data from the vehicle. For example, simulating normal range data is 111, simulating out-of-range data is 1111, and simulating invalid data is 000. Simultaneously, the platform stores these same values ​​as preset data. If the bus-to-everything (TBOX) has been tampered with, it will change the out-of-range and invalid data to normal data before uploading the simulated bus data to the V2X platform. Therefore, by comparing the simulated bus data with the preset data, it's possible to determine if the TBOX in the vehicle has been tampered with. For example, if the TBOX changes 1111 to 111 when uploading simulated out-of-range data, which is inconsistent with the preset data stored on the V2X platform, it can be determined that the vehicle has tampered with the data to be detected. Figure 2 As shown, it determines whether the simulated data has been tampered with. If so, it marks TBOX as tampered; otherwise, it re-simulates the CAN bus data.

[0085] Acquire vehicle operating data and SCR status data. Operating data includes, for example, engine running time. Status data includes, for example, SCR temperature rise data. Based on the operating data, determine if the status data has been tampered with. Engine running time and SCR temperature rise are closely related. If the engine running time reaches 30 minutes, the SCR temperature rise can reach 200 degrees Celsius. Based on this relationship, determine if the status data has been tampered with. For example, if the engine running time reaches 30 minutes, but the temperature rise is only 100 degrees Celsius, it can be determined that the status data has been tampered with, and the vehicle has been identified as having its data manipulated. Figure 2 As shown, determine whether the SCR has been tampered with.

[0086] Acquire vehicle bus data, such as urea level, urea consumption, vehicle mileage, and engine running time. Based on this data, determine if the urea level has been tampered with. For example, if the urea level remains unchanged during vehicle operation, it indicates tampering; similarly, if the urea consumption is significantly lower or higher than the vehicle mileage / engine running time, the urea level has been tampered with. If urea level tampering is confirmed, the vehicle has had its data modified.

[0087] Additionally, assuming the urea level has not been tampered with, the quality of the vehicle's urea can be tested, such as... Figure 2 As shown, it is determined whether the urea level has been tampered with. If not, it is determined whether there is a urea quality problem in the vehicle. The determination process is steps S101-S103. If there is no urea quality problem, the CAN bus data is received again. If there is a urea quality problem, the urea addition position is marked and the urea tampering position is marked.

[0088] In this embodiment, the system sequentially determines whether a vehicle has had its data tampered with based on bus simulation data, operational data, status data, and bus data. This provides high real-time performance, enabling timely and effective detection of data tampering. Furthermore, identifying which vehicles have tampered with data is beneficial for subsequent urinalysis.

[0089] In some optional implementations, determining whether the urea level in the bus data has been tampered with based on the bus data includes:

[0090] The vehicle's urea level, urea consumption, mileage, and running time are obtained from the bus data.

[0091] Determine whether the urea level is the same at different times during vehicle operation. If it is the same, the urea level has been tampered with.

[0092] Based on mileage and urea consumption, the vehicle's urea consumption per unit mileage is obtained.

[0093] The vehicle's urea consumption per unit time is obtained based on the running time and urea consumption.

[0094] Determine whether the urea consumption per unit mileage falls within the first preset range. If not, the urea level has been tampered with. Alternatively, determine whether the urea consumption per unit time falls within the second preset range. If not, the urea level has been tampered with.

[0095] Specifically, such as Figure 2 As shown, the system receives CAN bus data, calculates the urea level change from the bus data to obtain the vehicle's urea level, calculates urea consumption to obtain the vehicle's urea consumption amount, and calculates mileage and runtime to obtain the vehicle's mileage and runtime.

[0096] Urea level can be used to determine if it has been tampered with. For example, it can be determined whether the urea level is the same at different times during vehicle operation. If it is the same, it indicates that the urea level has not changed with mileage and fuel consumption and has remained constant, thus confirming that the urea level has been tampered with. Figure 2 As shown, the system statistically analyzes changes in urea level to determine if the urea level has been tampered with. If so, it marks the urea level as tampered; otherwise, it receives CAN bus data.

[0097] The vehicle-to-everything (V2X) platform analyzes the ratio of urea consumption of multiple vehicles to mileage and runtime, allowing it to pinpoint the maximum and minimum urea consumption values ​​and identify false urea consumption data curves. For example, based on the mileage of multiple vehicles and the urea consumption per unit mileage, the maximum and minimum urea consumption per unit mileage can be calculated, resulting in a first preset range, such as 0.01 liters / km - 0.02 liters / km. Similarly, based on the runtime of multiple vehicles and the urea consumption during runtime, the maximum and minimum urea consumption per unit time can be calculated, resulting in a second preset range, such as 0.6 liters / hour - 1.2 liters / hour.

[0098] Based on the vehicle's current mileage and urea consumption, the vehicle's urea consumption per unit mileage is calculated. Based on the vehicle's current running time and urea consumption, the vehicle's urea consumption per unit time is calculated.

[0099] For vehicles with high mileage, such as freight trucks, the system determines whether the urea consumption per unit mileage falls within a first preset range. If it does, the vehicle's urea consumption is correct; otherwise, the urea consumption has been tampered with, and the urea level has also been altered. For vehicles like mud trucks and mixer trucks that operate for extended periods but with lower mileage, the system uses urea consumption per unit time to determine if the urea level has been tampered with. The system then determines whether the urea consumption per unit time falls within a second preset range. If it does, the vehicle's urea consumption is correct; otherwise, the urea level has been tampered with. Figure 2 As shown, the system counts urea consumption, mileage, and runtime, and determines whether the urea level has been tampered with. If so, it marks the urea level as tampered; otherwise, it receives CAN bus data.

[0100] In this embodiment, the relationship between urea level, urea consumption and mileage, and urea consumption and duration is used to determine whether the urea level has been tampered with, which is highly real-time and accurate.

[0101] In some alternative implementations, the method further includes, before determining whether a preset fault code for the vehicle under test has been received:

[0102] When the temperature of the selective catalytic reduction reactor is higher than the preset temperature, the average concentration of a preset compound in the exhaust gas of the vehicle to be tested is obtained within a preset time period.

[0103] Vehicles with concentrations less than or equal to the first preset threshold are selected as candidate vehicles.

[0104] Candidate vehicles are removed from the list of vehicles to be tested.

[0105] Specifically, while using only preset compound emission levels to determine if a vehicle's emissions exceed standards is highly efficient, it may detect multiple vehicles, leading to more time spent testing urea quality subsequently. This embodiment uses the average concentration of preset compounds to further determine if a vehicle's emissions exceed standards, reducing the number of vehicles to be tested.

[0106] The preset temperature is, for example, 200 degrees Celsius; the preset compound is, for example, nitrogen oxides (NOx); and the preset time period is, for example, 30 seconds. The downstream gas of the selective catalytic reduction (SCR) is the gas purified by the SCR, and it is directly discharged, becoming part of the vehicle's emissions. The vehicle's emissions will also contain the preset compound. Using a moving average method, the average concentration of the preset compound in the vehicle's emissions is calculated over the preset time period.

[0107] The calculated average concentration is compared with a first preset threshold, for example, 400 ppm (parts per million). Vehicles with an average concentration of preset compounds less than or equal to the first preset threshold are selected as candidate vehicles. Candidate vehicles do not have excessive exhaust emissions, so their urea quality does not need to be checked. Candidate vehicles are then removed from the list of vehicles to be tested.

[0108] In this embodiment, the average concentration of preset compounds in the vehicle's exhaust gas is used to further determine whether the vehicle is emitting too many preset compounds. Candidate vehicles with normal emissions are removed from the list of vehicles to be tested, reducing the number of vehicles to be tested and improving the efficiency of urea quality testing and subsequent determination of the target urea addition location.

[0109] In some alternative implementations, after determining that the vehicle to be detected is the target vehicle, the method further includes:

[0110] Obtain the location information and urea level of all vehicles at different times, including the target vehicle;

[0111] Based on the urea level at different times, the change in urea level at each time relative to the previous time is obtained.

[0112] The moment when the change in urea level exceeds the second preset threshold is taken as the moment when urea is added to the vehicle.

[0113] Based on the location information and the time of urea refill, the location for refilling urea for the vehicle is determined;

[0114] The amount of urea added to the vehicle is obtained based on the urea level and the time of urea addition.

[0115] The target urea addition location was determined based on the location and amount of urea added, where the target urea addition location had an abnormal urea quality issue.

[0116] Specifically, currently, most commercial vehicles record route information, from which the location information of all vehicles at different times can be obtained. The urea level of the vehicle at different times can be obtained from the vehicle's CAN bus data.

[0117] The urea level data was filtered and sampled using a 15-minute window to obtain peak / trough sequences, and detection windows were selected based on thresholds, such as... Figure 3 As shown, Figure 3The x-axis represents time (in seconds), and the y-axis represents urea level (in %), indicating the current level as a percentage of the vehicle's maximum permissible urea level. A urea level change curve will be plotted based on the urea level and the corresponding time. Based on the urea level at different times on the curve, the change in urea level at each time point relative to the previous time point is obtained. The moment when the change in urea level exceeds a second preset threshold is designated as the urea level jump point, such as... Figure 3 As shown, the moment corresponding to the urea level jump point is taken as the urea addition time for the vehicle, or the urea level threshold before and after the jump point can be used to filter the urea addition time. The second preset threshold is, for example, 60%, 65%, etc.

[0118] Based on the time of urea addition, the location where the vehicle was added for urea is identified from the vehicle's location information at different times. Furthermore, based on the time of urea addition and the corresponding change in urea level, the amount of urea added to the vehicle can be calculated.

[0119] The target vehicle has an abnormal urea quality issue, so the locations where it refills urea may also have abnormal urea quality. Based on the amount of urea added to the target vehicle, several refill locations that have the highest urea levels can be selected as candidate refill locations. These candidate refill locations are then compared with those of other vehicles at different locations, and the amount of urea added by other vehicles at these locations is also considered. This allows for the selection of candidate refill locations with abnormal urea quality, which are then designated as target refill locations. For example, if only the target vehicle uses a particular candidate refill location, and other vehicles rarely use it or add very little urea, then that candidate refill location has an abnormal urea quality issue and should be selected as the target refill location.

[0120] In this implementation, the time when urea is added to the vehicle is first determined, followed by the location and amount of urea added. Finally, based on the location and amount of urea added, the target urea addition location with abnormal urea quality is identified. This completes the tracing of the source of the problematic urea, facilitating subsequent treatment of the problematic urea.

[0121] In some alternative implementations, the target urea addition location is determined based on the urea addition location and the amount of urea added, including:

[0122] The locations and amounts of urea added to vehicles are clustered to obtain the first clustering result, which is used to determine the total amount of urea added at different locations.

[0123] The locations and amounts of urea added to the target vehicles are clustered to obtain a second clustering result, which is used to identify the locations where urea quality is abnormal.

[0124] Based on the results of the first and second clustering, the target location for adding urea is obtained.

[0125] Specifically, the locations and amounts of urea added for all identified vehicles are clustered to obtain the first clustering result. The cluster area and total amount of urea added in the first clustering result are calculated. The optimal parameters are selected using Grid-Search and the results are output. The output results include: the number of vehicles adding urea at each urea location, the total amount of urea added at different urea locations, and the latitude and longitude of each urea location. For example, the urea locations include urea location A and urea location B. There are 200 vehicles adding urea at urea location A, with a total amount of 100 tons of urea added. There are 100 vehicles adding urea at urea location B, with a total amount of 50 tons of urea added.

[0126] The target vehicle has an abnormal urea quality issue, so the urea refill locations for the target vehicle may also have abnormal urea quality issues. The urea refill locations and urea amounts for the target vehicles are clustered to obtain a second clustering result. The cluster area and total urea amount added in the second clustering result are calculated. Grid-Search is used to select the optimal parameters and output the results. The output includes: the number of target vehicles refilling urea at each location, the total urea amount added by the target vehicles at different locations, and the latitude and longitude of each location. For example, 10 target vehicles refilled urea at location A, with a total urea amount of 3 tons, and 10 target vehicles refilled urea at location B, with a total urea amount of 5 tons.

[0127] Based on the results of the first and second clustering, target urea refill locations were identified. For example, at urea refill location A, a total of 200 vehicles went to refill location A, of which 10 were target vehicles. The total amount of urea refilled at location A was 100 tons, of which 3 tons were added by target vehicles. The target vehicles accounted for 5% of the total number of vehicles and 3% of the total amount of urea refilled. At urea refill location B, a total of 100 vehicles went to refill location B, of which 10 were target vehicles. The total amount of urea refilled at location B was 50 tons, of which 5 tons were added by target vehicles. The target vehicles accounted for 10% of the total number of vehicles and 10% of the total amount of urea refilled. By comparison, location B has a higher percentage of target vehicles and more vehicles refilling urea, indicating a higher probability of urea quality abnormalities. Therefore, it was selected as a target urea refill location. It should be noted that the 5% percentage of target vehicles is the primary criterion for selecting target urea refill locations.

[0128] In some alternative implementations, the method further includes, before obtaining the preset compound emissions of the vehicle over a preset time period:

[0129] Obtain vehicle operating condition data;

[0130] Based on the changing trends and correlation coefficients of different parameters in the working condition data, determine whether the working condition data meets the preset conditions.

[0131] If the operating data meets the preset conditions, the preset compound emissions can be obtained based on the operating data.

[0132] Specifically, it acquires vehicle operating data, such as vehicle speed, engine speed, engine torque, fuel consumption, and preset compound emission rates.

[0133] Based on the changing trends of different parameters in the operating condition data, it is determined whether the operating condition data meets preset conditions. For example, the preset condition is that the vehicle speed increases accordingly after the engine speed increases. By comparing the changing trends of vehicle speed and engine speed, it can be determined whether the vehicle speed increases accordingly after the engine speed increases. If the preset condition is met, the operating condition data can be considered authentic. Preset conditions also include: whether fuel consumption increases accordingly when vehicle speed is increasing; whether engine torque decreases when engine speed increases, etc. The preset conditions can be adjusted according to actual needs.

[0134] The correlation coefficient is used to determine whether the operating condition data meets the preset conditions. The correlation coefficient is calculated based on the engine's universal characteristic curve. The engine's universal characteristic curve is a curve plotted with engine speed as the x-axis and mean effective pressure or torque as the y-axis, integrating parameters such as load characteristic curves, speed characteristic curves, power, and fuel consumption at various engine speeds. From the universal characteristic curve, one can read the torque, fuel consumption rate, and other parameters at different power states of the engine at each specific engine speed. The correlation coefficient is used to determine whether the vehicle speed and fuel consumption values ​​conform to the correlation coefficient between them, whether the engine speed and vehicle speed values ​​conform to the correlation coefficient between them, and whether other operating condition data meet the correlation coefficient. Ultimately, this determines whether the operating condition data meets the preset conditions. If it does, the operating condition data is considered authentic.

[0135] If the operating data meets the preset conditions, the preset compound emissions are calculated based on the operating data. Taking NOx as the preset compound, the moving average method is used to calculate the average NOx emission rate over a continuous period. Multiplying the average emission rate by the preset duration yields the corresponding NOx emissions for each preset duration. The moving average method first uses integration to calculate the total NOx emissions from vehicles in the known data, and then divides by time to calculate the average NOx emission rate.

[0136] In this embodiment, the authenticity of the operating condition data is determined based on the changing trends and correlation coefficients of different parameters in the operating condition data. The preset compound emission amount is obtained based on the actual operating condition data, improving the accuracy of subsequent urine quality testing.

[0137] This embodiment also provides a urea quality detection device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0138] This embodiment provides a urea quality detection device, such as... Figure 4 As shown, it includes:

[0139] The first acquisition module 401 is used to acquire the preset compound emissions of the vehicle within a preset time period, provided that the vehicle's data to be tested has not been tampered with.

[0140] The first judgment module 402 is used to determine whether the preset compound emission amount is within the preset range, and to identify vehicles with preset compound emission amounts that are not within the preset range as vehicles to be tested.

[0141] The second judgment module 403 is used to determine whether a preset fault code of the vehicle to be tested has been received. If not, the vehicle to be tested is determined to be the target vehicle. The target vehicle has a urea quality abnormality problem. The preset fault code is generated after the vehicle has a problem other than the urea quality abnormality problem.

[0142] In some alternative embodiments, the device further includes:

[0143] The second acquisition module is used to acquire the vehicle's bus simulation data, which is included in the data to be detected.

[0144] The third judgment module is used to determine whether the bus simulation data is consistent with the preset data. If they are inconsistent, the vehicle is determined to be a vehicle whose data to be detected has been tampered with.

[0145] The third acquisition module is used to acquire the vehicle's operating data and the status data of the selective catalytic converter, wherein the operating data and status data are included in the data to be detected;

[0146] The fourth judgment module is used to determine whether the status data has been tampered with based on the running data. If so, the vehicle is determined to be a vehicle whose data to be detected has been tampered with.

[0147] The fourth acquisition module is used to acquire the vehicle's bus data, which is included in the data to be detected.

[0148] The fifth judgment module is used to determine whether the urea level in the bus data has been tampered with. If so, the vehicle is determined to be a vehicle whose data to be detected has been tampered with.

[0149] In some optional implementations, the fifth determination module includes:

[0150] The first obtaining unit is used to obtain the vehicle's urea level, urea consumption, vehicle mileage, and running time based on bus data.

[0151] The first judgment unit is used to determine whether the urea level is the same at different times during vehicle operation. If it is the same, the urea level has been tampered with.

[0152] The second obtaining unit is used to obtain the vehicle's urea consumption per unit mileage based on mileage and urea consumption.

[0153] The third obtaining unit is used to obtain the vehicle's urea consumption per unit time based on the running time and urea consumption.

[0154] The second judgment unit is used to determine whether the urea consumption per unit mileage belongs to the first preset range. If not, the urea level has been tampered with. Alternatively, it can determine whether the urea consumption per unit time belongs to the second preset range. If not, the urea level has been tampered with.

[0155] In some alternative embodiments, the device further includes:

[0156] The fifth acquisition module is used to acquire the average concentration of a preset compound in the emission gas of the vehicle to be tested within a preset time period when the temperature of the selective catalytic reducer is greater than the preset temperature.

[0157] The first setting module is used to select vehicles to be detected that have a concentration average value less than or equal to a first preset threshold as candidate vehicles.

[0158] The rejection module is used to remove candidate vehicles from the vehicles to be tested.

[0159] In some alternative embodiments, the device further includes:

[0160] The sixth acquisition module is used to acquire the location information and urea level of all vehicles at different times, including the target vehicle;

[0161] The first module is used to obtain the change in urea level at each time relative to the previous time, based on the urea level at different times.

[0162] The second setting module is used to take the moment when the change in urea level is greater than the second preset threshold as the moment when the vehicle adds urea.

[0163] The second module is used to obtain the urea refill location of the vehicle based on the location information and the urea refill time.

[0164] The third module is used to obtain the amount of urea added to the vehicle based on the urea level and the time of urea addition.

[0165] The determination module is used to determine the target urea addition location based on the urea addition location and the amount of urea added, wherein the target urea addition location has an abnormal urea quality problem.

[0166] In some alternative implementations, the determining module includes:

[0167] The first clustering unit is used to cluster the urea addition location and urea addition amount of the vehicle to obtain the first clustering result, wherein the first clustering result is used to determine the total amount of urea added at different urea addition locations.

[0168] The second clustering unit is used to cluster the urea addition locations and urea addition amounts of the target vehicles to obtain the second clustering results. The second clustering results are used to determine the urea addition locations where there are urea quality abnormalities.

[0169] The fourth unit is used to obtain the target urea addition location based on the first clustering result and the second clustering result.

[0170] In some alternative embodiments, the device further includes:

[0171] The seventh acquisition module is used to acquire the vehicle's operating condition data;

[0172] The sixth judgment module is used to determine whether the working condition data meets the preset conditions based on the changing trends and correlation coefficients of different parameters in the working condition data.

[0173] The fourth module is used to obtain the preset compound emission amount based on the operating condition data if the operating condition data meets the preset conditions.

[0174] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0175] In this embodiment, the urea quality detection device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0176] This invention also provides a computer device having the above-described features. Figure 4The urea quality testing device shown.

[0177] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 5 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 5 Take a processor 10 as an example.

[0178] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0179] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0180] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0181] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0182] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0183] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0184] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for detecting urea quality, characterized in that, The method includes: If it is determined that the vehicle's test data has not been tampered with, the vehicle's emissions of a preset compound within a preset time period are obtained. Determine whether the preset compound emission level is within a preset range, and designate the vehicle corresponding to the preset compound emission level that is not within the preset range as the vehicle to be tested; Determine whether a preset fault code for the vehicle under test has been received. If not, determine that the vehicle under test is the target vehicle. The target vehicle has a urea quality abnormality problem. The preset fault code is generated after the vehicle has a problem other than the urea quality abnormality problem.

2. The method according to claim 1, characterized in that, Before obtaining the preset compound emissions of the vehicle within a preset time period, the method further includes: Obtain bus simulation data of the vehicle, wherein the bus simulation data is included in the data to be detected; Determine whether the bus simulation data is consistent with the preset data. If they are inconsistent, determine that the vehicle is a vehicle whose data to be detected has been tampered with. Acquire the vehicle's operating data and the selective catalytic reduction unit's status data, wherein the operating data and the status data are included in the data to be detected; Based on the operational data, it is determined whether the status data has been tampered with. If so, the vehicle is determined to be the vehicle whose data to be detected has been tampered with. Acquire the bus data of the vehicle, wherein the bus data is included in the data to be detected; Based on the bus data, determine whether the urea level in the bus data has been tampered with. If so, determine that the vehicle is a vehicle whose data to be detected has been tampered with.

3. The method according to claim 2, characterized in that, The step of determining whether the urea level in the bus data has been tampered with based on the bus data includes: The vehicle's urea level, urea consumption, mileage, and running time are obtained based on the bus data. Determine whether the urea level is the same at different times during the operation of the vehicle. If it is the same, the urea level has been tampered with. The urea consumption per unit mileage of the vehicle is obtained based on the mileage and the urea consumption. The urea consumption of the vehicle per unit time is obtained based on the running time and the urea consumption. Determine whether the urea consumption based on unit mileage belongs to a first preset range. If not, the urea level has been tampered with. Alternatively, determine whether the urea consumption based on unit time belongs to a second preset range. If not, the urea level has been tampered with.

4. The method according to claim 2, characterized in that, Before determining whether a preset fault code for the vehicle under test has been received, the method further includes: When the temperature of the selective catalytic reduction device is higher than the preset temperature, the average concentration of the preset compound in the emission gas of the vehicle to be tested is obtained within a preset time period. The vehicles to be tested with a concentration average value less than or equal to a first preset threshold are selected as candidate vehicles. The candidate vehicle is removed from the vehicles to be tested.

5. The method according to claim 1, characterized in that, After determining that the vehicle to be detected is the target vehicle, the method further includes: Obtain the location information and urea level of all the vehicles at different times, wherein the vehicles include the target vehicle; Based on the urea level at different times, the change in urea level at each time relative to the previous time is obtained; The moment when the change in urea level is greater than the second preset threshold is taken as the moment when urea is added to the vehicle; Based on the location information and the time of urea addition, the location for adding urea to the vehicle is determined; The amount of urea added to the vehicle is obtained based on the urea level and the time of urea addition. The target urea addition location is determined based on the urea addition location and the amount of urea added, wherein the target urea addition location has an abnormal urea quality problem.

6. The method according to claim 5, characterized in that, Determining the target urea addition location based on the urea addition location and the urea addition amount includes: The locations and amounts of urea added to the vehicle are clustered to obtain a first clustering result, wherein the first clustering result is used to determine the total amount of urea added at different locations. The locations where urea was added and the amount of urea added to the target vehicle were clustered to obtain a second clustering result, wherein the second clustering result was used to determine the locations where urea was added due to abnormal urea quality. Based on the first clustering result and the second clustering result, the target urea addition location is obtained.

7. The method according to claim 1, characterized in that, Before obtaining the preset compound emissions of the vehicle within a preset time period, the method further includes: Obtain the operating condition data of the vehicle; Based on the changing trends and correlation coefficients of different parameters in the operating condition data, determine whether the operating condition data meets the preset conditions; If the operating condition data meets the preset conditions, then the preset compound emission amount is obtained based on the operating condition data.

8. A urea quality testing device, characterized in that, The device includes: The first acquisition module is used to acquire the preset compound emissions of the vehicle within a preset time period, provided that the vehicle's test data has not been tampered with. The first judgment module is used to determine whether the preset compound emission amount is within a preset range, and to identify the vehicle corresponding to the preset compound emission amount that is not within the preset range as the vehicle to be tested. The second judgment module is used to determine whether a preset fault code of the vehicle to be tested is received. If not, the vehicle to be tested is determined to be the target vehicle. The target vehicle has a urea quality abnormality problem. The preset fault code is generated after the vehicle has a problem other than the urea quality abnormality problem.

9. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the urea quality detection method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the urea quality testing method according to any one of claims 1 to 7.

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