Vehicle Nitrogen Oxide Emission Detection Method, Device and Computer Equipment

Abstract

This application relates to a method, device, computer device, storage medium, and computer program product for detecting vehicle nitrogen oxide emissions. The method includes: obtaining engine operation data and post-nitrogen oxide emission sensor data of different vehicles; identifying high-emission vehicles based on the engine operation data and the post-nitrogen oxide emission sensor data; generating a depth detection prompt message for performing in-depth detection of nitrogen oxides on the high-emission vehicles; and pushing the depth detection prompt message, which is used to prompt the use of a dedicated on-vehicle emission device to detect the nitrogen oxide emissions of the high-emission vehicles. In the entire vehicle nitrogen oxide emission detection process, high-emission vehicles can be quickly identified based on the vehicle nitrogen oxide emission detection data; for the identified high-emission vehicles, a depth detection prompt message is pushed to prompt the use of a dedicated on-vehicle emission device for emission detection, enabling efficient vehicle nitrogen oxide emission detection.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle emission testing, and particularly to a method and device for detecting nitrogen oxide emissions from vehicles, a computer device, a storage medium, and a computer program product. Background Art

[0002] In order to reduce the harm of automotive pollutant emissions to the atmospheric environment, the state promulgated the "Limits and Measurement Methods for Pollutant Emissions from Heavy-Duty Diesel Vehicles (China Phase VI)" (GB17691-2018) (hereinafter referred to as the National VI emission standard) in 2018. With the implementation of this emission standard, vehicle manufacturers have higher and higher requirements for on-vehicle emission tests.

[0003] Traditional on-vehicle emission testing of a whole vehicle requires the vehicle to be equipped with expensive and complex on-vehicle emission equipment for testing on real roads, and the emission situation of the produced vehicles is evaluated according to the test results. Facing a large number and variety of vehicles, the efficiency of traditional on-vehicle emission testing of a whole vehicle is low. Summary of the Invention

[0004] Based on this, it is necessary to provide an efficient method and device for detecting nitrogen oxide emissions from vehicles, a computer device, a computer-readable storage medium, and a computer program product for the above technical problems.

[0005] In a first aspect, the present application provides a method for detecting nitrogen oxide emissions from vehicles. The method includes:

[0006] Obtain engine operation data and post-nitrogen oxide emission sensor data of different vehicles;

[0007] Identify high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data;

[0008] Generate a depth detection prompt message for performing in-depth detection of nitrogen oxides on high-emission vehicles;

[0009] Push the depth detection prompt message, which is used to prompt to perform nitrogen oxide emission detection on high-emission vehicles using dedicated on-vehicle emission equipment.

[0010] In one embodiment, identifying high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data includes:

[0011] Perform a transient nitrogen oxide emission exceedance test on the vehicle according to the engine operation data and the post-nitrogen oxide emission sensor data to obtain a transient nitrogen oxide emission exceedance test result;

[0012] Identify the preferred high-emission vehicles and non-preferred high-emission vehicles among different vehicles according to the transient nitrogen oxide emission exceedance test result;

[0013] Obtain on-road test data of non-preferred high-emission vehicles. The on-road test includes PEMS on-road test or C-WTVC on-road test under laboratory conditions;

[0014] Based on the on-road test data, identify the high-emission vehicles that are secondarily identified among the non-preferred high-emission vehicles.

[0015] In one embodiment, the on-road test includes PEMS on-road test;

[0016] Based on the on-road test data, identifying the high-emission vehicles that are secondarily identified among the non-preferred high-emission vehicles includes:

[0017] Obtain the engine WHTC cycle work of the non-preferred high-emission vehicles;

[0018] Divide the work-based window based on the work-based window method and the engine WHTC cycle work, and count the average power percentage of all work-based windows;

[0019] Obtain the power percentage threshold of the non-preferred high-emission vehicles;

[0020] Obtain the effective windows based on the average power percentage of the work-based windows and the power percentage threshold;

[0021] Count the specific emission values of nitrogen oxides in the effective windows;

[0022] Based on the specific emission values of nitrogen oxides in the effective windows, identify the high-emission vehicles that are secondarily identified among the non-preferred high-emission vehicles.

[0023] In one embodiment, the on-road test further includes C-WTVC on-road test under laboratory conditions;

[0024] Based on the on-road test data, identifying the high-emission vehicles that are secondarily identified among the non-preferred high-emission vehicles further includes:

[0025] Obtain the weighted coefficient corresponding to the vehicle type of the non-preferred high-emission vehicles;

[0026] Based on the average value method, count the average specific emission value of nitrogen oxides in the C-WTVC test road condition range;

[0027] Based on the average specific emission value of nitrogen oxides and the weighted coefficient corresponding to the vehicle type of the non-preferred high-emission vehicles, obtain the final average specific emission value of nitrogen oxides;

[0028] Based on the final average specific emission value of nitrogen oxides, identify the high-emission vehicles that are secondarily identified among the non-preferred high-emission vehicles.

[0029] In one embodiment, after obtaining the engine operation data and the post-nitrogen oxide emission sensor data of different vehicles, it further includes:

[0030] Obtain the control system data of different vehicles;

[0031] According to the engine operation data, control system data and post-nitrogen oxide emission sensor data of different vehicles, monitor the fault status of the vehicle in real time.

[0032] In one embodiment, before identifying high-emission vehicles according to the engine operation data and post-nitrogen oxide emission sensor data, it further includes:

[0033] Eliminate the engine operation data and post-nitrogen oxide emission sensor data corresponding to the abnormal moments of the post-nitrogen oxide emission sensor data.

[0034] In a second aspect, the present application also provides a vehicle nitrogen oxide emission detection device. The device includes:

[0035] A data acquisition module, configured to acquire the engine operation data and post-nitrogen oxide emission sensor data of different vehicles;

[0036] An identification module, configured to identify high-emission vehicles according to the engine operation data and post-nitrogen oxide emission sensor data;

[0037] A message generation module, configured to generate a depth detection prompt message for performing in-depth nitrogen oxide detection on high-emission vehicles;

[0038] A message push module, configured to push the depth detection prompt message, and the depth detection prompt message is used to prompt to use a dedicated on-vehicle emission device to detect the nitrogen oxide emission of high-emission vehicles.

[0039] In a third aspect, the present application also provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0040] Obtain the engine operation data and post-nitrogen oxide emission sensor data of different vehicles;

[0041] Identify high-emission vehicles according to the engine operation data and post-nitrogen oxide emission sensor data;

[0042] Generate a depth detection prompt message for performing in-depth nitrogen oxide detection on high-emission vehicles;

[0043] Push the depth detection prompt message, and the depth detection prompt message is used to prompt to use a dedicated on-vehicle emission device to detect the nitrogen oxide emission of high-emission vehicles.

[0044] In a fourth aspect, the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the following steps are implemented:

[0045] Obtain the engine operation data and the post-NOx emission sensor data of different vehicles;

[0046] Identify high-emission vehicles based on the engine operation data and the post-NOx emission sensor data;

[0047] Generate a depth detection prompt message for performing in-depth NOx detection on high-emission vehicles;

[0048] Push the depth detection prompt message, which is used to prompt the use of dedicated on-vehicle emission equipment to detect the NOx emissions of high-emission vehicles.

[0049] In a fifth aspect, the present application also provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0050] Obtain the engine operation data and the post-NOx emission sensor data of different vehicles;

[0051] Identify high-emission vehicles based on the engine operation data and the post-NOx emission sensor data;

[0052] Generate a depth detection prompt message for performing in-depth NOx detection on high-emission vehicles;

[0053] Push the depth detection prompt message, which is used to prompt the use of dedicated on-vehicle emission equipment to detect the NOx emissions of high-emission vehicles.

[0054] For the above vehicle NOx emission detection method, device, computer device, storage medium, and computer program product, obtain the engine operation data and the post-NOx emission sensor data of different vehicles; identify high-emission vehicles based on the engine operation data and the post-NOx emission sensor data; generate a depth detection prompt message for performing NOx detection on high-emission vehicles; push the depth detection prompt message, which is used to prompt the use of dedicated on-vehicle emission equipment to detect the NOx emissions of high-emission vehicles. In the entire vehicle NOx emission detection process, high-emission vehicles can be quickly identified based on the vehicle NOx emission detection data; for the identified high-emission vehicles, a depth detection prompt message is pushed to prompt the use of dedicated on-vehicle emission equipment for emission detection, which can achieve efficient vehicle NOx emission detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is an application environment diagram of the vehicle NOx emission detection method in an embodiment;

[0056] Figure 2Schematic flow diagram of a vehicle nitrogen oxide emission detection method in an embodiment;

[0057] Figure 3 Schematic flow diagram of a vehicle nitrogen oxide emission detection method in another embodiment;

[0058] Figure 4 Schematic overall architecture diagram of the application scenario of a vehicle nitrogen oxide emission detection method in an embodiment;

[0059] Figure 5 Block diagram of the structure of a vehicle nitrogen oxide emission detection device in an embodiment;

[0060] Figure 6 Internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0061] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0062] The vehicle nitrogen oxide emission detection method provided by the embodiments of the present application can be applied to an application environment as Figure 1 shown. Among them, the in-vehicle terminal 102 communicates with the data platform center 104 through a network to achieve efficient vehicle nitrogen oxide emission detection. The in-vehicle terminal 102 collects the engine operation data and the post-nitrogen oxide emission sensor data of different vehicles to the data platform center 104. The data platform center 104 obtains the engine operation data and the post-nitrogen oxide emission sensor data of different vehicles, and then identifies high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data; at the same time, the data platform center 104 generates a depth detection prompt message for performing in-depth detection of nitrogen oxides on high-emission vehicles; finally, the depth detection prompt message is pushed to the in-vehicle terminal 102, and the depth detection prompt message is used to prompt to use a dedicated in-vehicle emission device to perform nitrogen oxide emission detection on high-emission vehicles. Further, after receiving the depth detection prompt message, the management personnel can use a dedicated in-vehicle emission device to perform nitrogen oxide emission detection on high-emission vehicles.

[0063] In one embodiment, as Figure 2 shown, a vehicle nitrogen oxide emission detection method is provided. Taking this method applied to the data platform center 104 in Figure 1 as an example for description, the method includes the following steps:

[0064] S202: Obtain the engine operation data and the post-nitrogen oxide emission sensor data of different vehicles.

[0065] Among them, the engine operation data refers to the real-time status data of the engine during vehicle driving, including engine speed, maximum reference torque of the engine, actual torque percentage of the engine, friction torque percentage of the engine, engine coolant temperature, engine fuel consumption rate, engine intake air flow, engine WHTC cycle work, and engine rated power; the post-nitrogen oxide emission sensor data specifically refers to the output value of the SCR downstream NOx sensor.

[0066] In practical applications, the data platform center communicates with the in-vehicle terminal to obtain the engine operation data and post-nitrogen oxide emission sensor data during vehicle driving in real time.

[0067] S204: Identify high-emission vehicles based on the engine operation data and post-nitrogen oxide emission sensor data.

[0068] Among them, high-emission vehicles refer to vehicles that do not meet the National VI emission standards evaluated by the data platform center after online processing of the engine operation data and post-nitrogen oxide emission sensor data. High-emission vehicles are screened out based on the uploaded data information without installing a dedicated in-vehicle emission device.

[0069] Specifically, the data platform center calculates and processes the engine operation data and post-nitrogen oxide emission sensor data uploaded by the in-vehicle terminal according to the National VI emission standards, evaluates the emission situation of the vehicle in the actual environment, and identifies vehicles that do not meet the National VI emission standards as high-emission vehicles.

[0070] S206: Generate a depth detection prompt message for deep nitrogen oxide detection of high-emission vehicles.

[0071] Among them, the depth detection prompt message refers to the prompt message for further detection generated by the data platform center for vehicles that do not meet the National VI emission standards. Since high-emission vehicles are screened out based on the uploaded engine operation data and post-nitrogen oxide emission sensor data without installing the dedicated in-vehicle emission device adopted by the National VI emission standards, after the above vehicles are initially evaluated as high-emission, a depth detection prompt message needs to be generated to prompt the detection personnel.

[0072] Specifically, the data platform center generates a depth detection prompt message for the high-emission vehicles identified online, prompting the detection personnel to install a dedicated in-vehicle emission device based on the National VI emission standards for deep detection.

[0073] S208: Push the depth detection prompt message, which is used to prompt the use of a dedicated in-vehicle emission device to detect the nitrogen oxide emissions of high-emission vehicles.

[0074] Among them, pushing the depth detection prompt message refers to the data platform center pushing a message to prompt the use of a dedicated in-vehicle emission device for detection.

[0075] Specifically, the depth detection prompt message can be specifically pushed in the form of sound, light or display to prompt the detector to install a dedicated on-vehicle emission device based on the National VI emission standard for in-depth detection. For example, if a display screen is connected to the data platform center, "Transient nitrogen oxide emission exceeds the standard! Conduct in-depth detection" can be displayed in the detection result column of high-emission vehicles.

[0076] The above vehicle nitrogen oxide emission detection method obtains the engine operation data and the post-nitrogen oxide emission sensor data of different vehicles; identifies high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data; generates a depth detection prompt message for nitrogen oxide detection of high-emission vehicles; and pushes the depth detection prompt message, which is used to prompt the use of a dedicated on-vehicle emission device to detect the nitrogen oxide emission of high-emission vehicles. In the whole vehicle nitrogen oxide emission detection process, high-emission vehicles are quickly identified according to the vehicle nitrogen oxide emission detection data; a depth detection prompt message is pushed for the identified high-emission vehicles to prompt the use of a dedicated on-vehicle emission device for emission detection, so as to achieve efficient vehicle nitrogen oxide emission detection.

[0077] In one embodiment, as Figure 3 shown, identifying high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data includes:

[0078] S302: Conduct a transient nitrogen oxide emission exceedance test on the vehicle according to the engine operation data and the post-nitrogen oxide emission sensor data to obtain a transient nitrogen oxide emission exceedance test result;

[0079] S304: Identify the preferred high-emission vehicles and non-preferred high-emission vehicles among different vehicles according to the transient nitrogen oxide emission exceedance test result;

[0080] S306: Obtain the working condition test data of non-preferred high-emission vehicles, and the working condition test includes PEMS working condition test or C-WTVC working condition test under laboratory conditions;

[0081] S308: Identify the high-emission vehicles that are secondarily identified among the non-preferred high-emission vehicles according to the working condition test data.

[0082] The transient nitrogen oxide emission exceedance test means that the data platform center eliminates the engine operation data and the post-nitrogen oxide emission sensor data of the test vehicle during the cold start stage to obtain the effective SCR downstream NOx sensor output value, and then counts the data of the effective SCR downstream NOx sensor output value greater than 500 ppm of the vehicle during the test time period. When the proportion of the test vehicle sensor output value greater than 500 ppm data exceeds 5% of the test data, it is directly determined that the above test vehicle belongs to the preferred high-emission vehicle.

[0083] In addition, in this embodiment, vehicles whose transient nitrogen oxide emissions do not exceed the standard, i.e., non-preferred high-emission vehicles, are further processed. The data platform center obtains data of PEMS working condition tests or C-WTVC working condition tests under laboratory conditions for non-preferred high-emission vehicles, and performs secondary identification of high-emission vehicles on non-preferred high-emission vehicles based on the data of the above working condition tests.

[0084] In this embodiment, vehicles with excessive nitrogen oxide emissions are identified twice. If the vehicle's transient nitrogen oxide emissions exceed the standard, the test vehicle is determined to be a preferred high-emission vehicle, otherwise it is a non-preferred high-emission vehicle; a working condition test is performed on the above non-preferred high-emission vehicles. If the nitrogen oxide emissions of the non-preferred high-emission vehicle in the working condition test exceed the standard, the vehicle is determined to be a secondary identified high-emission vehicle. When a vehicle is determined to be a preferred high-emission vehicle, there is no need to process the data of subsequent working condition tests, which greatly simplifies the data processing steps and realizes fast and efficient vehicle nitrogen oxide emission detection.

[0085] In one embodiment, the operating condition test includes a PEMS operating condition test; and according to the operating condition test data, identifying the secondary identified high emission vehicles among the non-preferred high emission vehicles includes:

[0086] Obtaining engine WHTC cycle work for non-preferred high emission vehicles;

[0087] Divide the power base window based on the power base window method and the engine WHTC cycle power, and calculate the average power percentage of all power base windows;

[0088] Obtaining power percentage thresholds for non-preferred high-emission vehicles;

[0089] Obtain a valid window according to the average power percentage of the power base window and the power percentage threshold;

[0090] Calculate the effective window nitrogen oxide emission ratio value;

[0091] Based on the effective window nitrogen oxide ratio emission value, high emission vehicles that are secondary identified among non-preferred high emission vehicles are identified.

[0092] The PEMS operating condition test uses the power basis window method to evaluate the vehicle's nitrogen oxide emissions. Before using the power basis window method, the data platform center will eliminate the test vehicle's engine operation data during the cold start phase and the post-nitrogen oxide emission sensor data. The power basis window method divides the operating condition test data into different subsets for processing. These subsets are called power basis windows. The National VI Emission Standard stipulates that the power basis windows are divided based on the vehicle's engine WHTC cycle power, and the interval between the starting points of each power basis window is 1s. The power basis window is divided as shown in the following equations (1) and (2):

[0093] W(t 2,i ) - W(t 1,i ) ≥ W ref (1)

[0094] W(t 2,i - Δt) - W(t 1,i ) < W ref (2)

[0095] Among them, the period (t 2,i - t 1,i ) of the i-th window is judged by Equation (1), and the termination time t 2,i is judged by Equation (2); W(t j,i ) is the cumulative cycle work of the engine from the start to t j,i time, with the unit of kW·h; W ref is the WHTC cycle work, with the unit of kW·h; Δt is the data sampling period, taking 1 s.

[0096] According to the work-based windows divided above, calculate the average power percentage of all work-based windows. Mark the windows with the average power percentage greater than the power percentage threshold as valid windows. The initial value of the power percentage threshold is 20%. The proportion of valid windows should be no less than 50%. If the proportion is lower than 50%, then gradually decrease the power percentage threshold in steps of 1% until the proportion of valid windows reaches 50%. In any case, the power percentage threshold is decreased to 10% at most.

[0097] Statistically analyze the specific emission values of nitrogen oxides for all valid windows. Determine that vehicles with the 90th percentile value greater than 0.69 g / kWh belong to high-emission vehicles. Among them, the specific emission values of nitrogen oxides are calculated based on the engine operation data and the data of the post-nitrogen oxide emission sensor. The specific calculation method is as follows:

[0098] First, calculate the engine instantaneous torque T according to the engine maximum reference torque, the engine actual torque percentage, and the engine instantaneous torque percentage. If the calculation result is negative, record the engine instantaneous torque T as 0. If the calculation result is positive, keep it unchanged. The calculation formula for the engine instantaneous torque T is shown in Equation (3) below:

[0099]

[0100] According to the engine instantaneous torque T and the engine speed, calculate the engine instantaneous work W t , and the calculation formula for the engine instantaneous work W t is shown in Equation (4) below:

[0101]

[0102] According to the engine instantaneous work Wt Calculate the instantaneous power P of the engine. The calculation formula for the instantaneous power P of the engine is shown in the following formula (5):

[0103]

[0104] Calculate the cumulative cycle work W within the effective window of the engine according to the instantaneous power P of the engine i , and the calculation formula for the cumulative cycle work of the engine is shown in the following formula (6), where i is the PEMS working condition test time, n is the above engine speed, and T is the above engine instantaneous torque.

[0105]

[0106] Calculate the transient NOx emission mass M according to the output value of the NOx sensor downstream of the SCR, the engine fuel consumption rate, and the engine intake air flow t , and the transient NOx emission mass M t The calculation formula is shown in the following formula (7):

[0107]

[0108] According to the transient NOx emission mass M t Calculate the total mass M of nitrogen oxide emissions within the effective window i , according to the total mass M of nitrogen oxide emissions within the effective window i And the cumulative cycle work W of the engine within the effective window i , calculate the window specific emission L of each effective window i , and the window specific emission L of the effective window i The calculation formula is shown in the following formula (8):

[0109]

[0110] In addition, in this embodiment, the data platform center can also obtain the vehicle information for the PEMS working condition test and the start and end times of the above vehicle for the PEMS test. When it is necessary to obtain the detection results of the vehicle for the PEMS working condition test, the data platform center will calculate the effective window nitrogen oxide specific emission value according to the engine operation data and the post-nitrogen oxide emission sensor data, and screen out the vehicles with the 90th percentile value greater than 0.69 g / kWh. Specifically, it can display "The PEMS working condition remote test emission exceeds the standard! Conduct in-depth detection" in the detection result column of high-emission vehicles.

[0111] In this embodiment, the data platform center utilizes the engine operation data and the post-nitrogen oxide emission sensor data uploaded by the vehicle terminal, and quickly screens out the vehicles with excessive nitrogen oxide emissions under this test condition in the platform according to the calculation method defined under the PEMS working condition test, realizing efficient detection of vehicle nitrogen oxide emissions.

[0112] In one of the embodiments, the working condition test further includes the C-WTVC working condition test under laboratory conditions;

[0113] According to the working condition test data, identifying the highly-emitting vehicles that are secondarily identified among the non-preferred highly-emitting vehicles further includes:

[0114] Obtaining the weighting coefficient corresponding to the vehicle model of the non-preferred highly-emitting vehicle;

[0115] Based on the average value method, statistically calculate the average specific nitrogen oxide emission value within the C-WTVC test road condition interval;

[0116] According to the average specific nitrogen oxide emission value and the weighting coefficient corresponding to the vehicle model of the non-preferred highly-emitting vehicle, obtain the final average specific nitrogen oxide emission value;

[0117] According to the final average specific nitrogen oxide emission value, identify the highly-emitting vehicles that are secondarily identified among the non-preferred highly-emitting vehicles.

[0118] The C-WTVC working condition test under laboratory conditions refers to measuring the engine operation data and the post-nitrogen oxide emission sensor data of the vehicle under the C-WTVC working condition on a laboratory roller. The standard C-WTVC cycle includes an urban cycle (duration 900s), a highway cycle (duration 468s), and a highway cycle (duration 432s). During actual testing, based on the average value method, statistically calculate the average specific nitrogen oxide emission values within the three road condition intervals of urban, highway, and highway in the C-WTVC test, and then calculate the final average specific nitrogen oxide emission value according to the weighting coefficients corresponding to different vehicle models. Determine that the vehicle with a final average specific nitrogen oxide emission value greater than 0.69 g / kWh is a highly-emitting vehicle.

[0119] In addition, in this embodiment, the data platform center can also obtain the vehicle information of the vehicle undergoing the C-WTVC working condition test under laboratory conditions and the start and end times of the above vehicle undergoing the C-WTVC working condition test. When it is necessary to obtain the detection results of the vehicle undergoing the C-WTVC working condition test, the data platform center will calculate the average specific nitrogen oxide emission value according to the engine operation data and the post-nitrogen oxide emission sensor data, and determine that the vehicle with an average specific nitrogen oxide emission value greater than 0.69 g / kWh is a highly-emitting vehicle. Specifically, it can display "Remote test emission exceeded for C-WTVC working condition! Conduct in-depth detection" in the detection result column of the highly-emitting vehicle.

[0120] In this embodiment, the data platform center utilizes the engine operation data and the post-nitrogen oxide emission sensor data uploaded by the vehicle-mounted terminal, and quickly screens out the vehicles with excessive nitrogen oxide emissions under this test condition within the platform according to the calculation method defined under the C-WTVC working condition test, realizing efficient detection of vehicle nitrogen oxide emissions.

[0121] In one of the embodiments, after obtaining the engine operation data and the post-nitrogen oxide emission sensor data of different vehicles, it further includes:

[0122] Obtain the control system data of different vehicles; according to the engine operation data, control system data, and post-nitrogen oxide emission sensor data of different vehicles, monitor the fault status of the vehicles in real time.

[0123] The control system data of the vehicle includes the fault codes generated by the vehicle control system when the vehicle has a fault. The data platform center judges whether the vehicle has a fault that affects the normal emission function according to the obtained fault codes, and counts the fault types according to the fault codes. For example, when the vehicle's emission function is affected due to carbon deposition inside the engine, the data platform center obtains the fault code of the control system and generates a fault prompt message, which can be "Serious carbon deposition inside the engine, please clean it in time". If there is no fault, the data platform center generates a message that can be normally evaluated, such as "The emission function is normal".

[0124] In this embodiment, the data platform center monitors the fault status of the vehicle in real time according to the fault codes generated by the vehicle control system and gives timely feedback. By performing vehicle fault detection before evaluating the nitrogen oxide emissions of the vehicle, the accuracy and credibility of the detection results are ensured.

[0125] In one of the embodiments, before identifying high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data, it further includes:

[0126] Eliminate the engine operation data and the post-nitrogen oxide emission sensor data corresponding to the abnormal moments of the post-nitrogen oxide emission sensor data.

[0127] When the output value of the SCR downstream NOx sensor of the data volume is abnormal data such as "FF", "FFFF", etc., the data platform center directly eliminates the engine operation data and the post-nitrogen oxide emission sensor data corresponding to this abnormal data moment.

[0128] In this embodiment, the data platform center further preprocesses the data uploaded by the vehicle-mounted terminal, eliminates the engine operation data and the post-nitrogen oxide emission sensor data corresponding to the moments when abnormal values appear in the post-nitrogen oxide emission sensor data, so as to make the evaluation results of the data platform more accurate and the screening of high-emission vehicles more effective.

[0129] To illustrate the technical solution of the electric power steering control method of the present application in detail, the following will adopt specific application examples and combine with Figure 4 describe the entire processing process in detail, which specifically includes the following steps:

[0130] 1. The data platform center 401 obtains the engine operation data 406, the post-nitrogen oxide emission sensor data 407, and the control system data 408 of the vehicle 405 through the vehicle-mounted terminal 409; the data obtained by the data platform center includes at least the content of Table 1:

[0131] Table 1 Data Information

[0132] Data serial number Data information name 1 Engine speed 2 Engine maximum reference torque 3 Engine actual torque percentage 4 Engine friction torque percentage 5 Engine coolant temperature 6 Engine fuel consumption rate 7 Engine intake air flow 8 Engine WHTC cycle work 9 Engine rated power 10 SCR downstream NOx sensor output value 11 Ambient temperature 12 Vehicle speed

[0133] 2. The data platform center 401 cleans and filters the engine operation data 406, the post-nitrogen oxide emission sensor data 407, and the control system data 408 of the vehicle 405, and the following specific processing needs to be carried out:

[0134] a). The vehicle information module 402 filters the engine operation data, the post-nitrogen oxide emission sensor data, and the control system data within the test time range according to the start and end times of the vehicle test.

[0135] b). The fault monitoring module 403 monitors the fault status of the vehicle in real time according to the fault codes generated by the vehicle control system. If there is a fault, a fault prompt message is generated. If there is no fault, the next step is carried out.

[0136] c). The emission monitoring module 404 eliminates all the detection data corresponding to the abnormal output value of the SCR downstream NOx sensor.

[0137] d). The emission monitoring module 404 eliminates the engine operation data and the post-nitrogen oxide emission sensor data corresponding to the cold start stage of the vehicle for the vehicles undergoing transient nitrogen oxide emission exceedance tests and PEMS working condition tests.

[0138] 3. The emission monitoring module 404 identifies high-emission vehicles according to the defined algorithm based on the cleaned and filtered valid data. The identification process is as follows:

[0139] a). Conduct a transient nitrogen oxide emission exceedance test on the vehicle according to the engine operation data 406 and the post-nitrogen oxide emission sensor data 407. According to the results of the transient nitrogen oxide emission exceedance test, identify the preferred high-emission vehicles and non-preferred high-emission vehicles among different vehicles. The vehicles with transient nitrogen oxide emissions exceeding the standard are the preferred high-emission vehicles; the vehicles with transient nitrogen oxide emissions not exceeding the standard, that is, the non-preferred high-emission vehicles, need to be processed in the next step.

[0140] b). The emission monitoring module 404 performs PEMS working condition tests on non-preferred high-emission vehicles, or data from C-WTVC working condition tests under laboratory conditions. Based on the data from the above working condition tests, secondary identification of high-emission vehicles is carried out on non-preferred high-emission vehicles. Under the PEMS working condition test conditions, vehicles with the 90th percentile value of the specific emission value of nitrogen oxides in the effective window greater than 0.69 g / kWh are high-emission vehicles; under the C-WTVC working condition test conditions, vehicles with an average specific emission value of nitrogen oxides greater than 0.69 g / kWh are high-emission vehicles.

[0141] 4. The data platform center 401 generates a deep detection prompt message for the high-emission vehicles screened out in step 3, prompting the use of the dedicated on-vehicle emission device 410 for deep detection; classification and evaluation analysis are carried out on the vehicles 405 that are not screened out.

[0142] It should be understood that although the various steps in the flowcharts involved in the above embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least some of the steps or stages in other steps or other steps.

[0143] Based on the same inventive concept, as Figure 5 shown, an embodiment of the present application further provides a vehicle nitrogen oxide emission detection device for implementing the vehicle nitrogen oxide emission detection method involved above. The device includes:

[0144] A data acquisition module 502, configured to acquire engine operation data and post-nitrogen oxide emission sensor data of different vehicles;

[0145] An identification module 504, configured to identify high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data;

[0146] A message generation module 506, configured to generate a deep detection prompt message for performing nitrogen oxide deep detection on high-emission vehicles;

[0147] A message push module 508, configured to push the deep detection prompt message, and the deep detection prompt message is used to prompt the use of a dedicated on-vehicle emission device to perform nitrogen oxide emission detection on high-emission vehicles.

[0148] The above vehicle nitrogen oxide emission detection device obtains the engine operation data and the post-nitrogen oxide emission sensor data of different vehicles; identifies high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data; generates a deep detection prompt message for detecting nitrogen oxides in high-emission vehicles; and pushes the deep detection prompt message, which is used to prompt the use of a dedicated on-vehicle emission device to detect the nitrogen oxide emissions of high-emission vehicles. In the entire vehicle nitrogen oxide emission detection process, high-emission vehicles are quickly identified based on the vehicle nitrogen oxide emission detection data; a deep detection prompt message is pushed for the identified high-emission vehicles to prompt the use of a dedicated on-vehicle emission device for emission detection, enabling efficient vehicle nitrogen oxide emission detection.

[0149] In one embodiment, the identification module is further configured to identify high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data, including: performing a transient nitrogen oxide emission exceedance test on the vehicle according to the engine operation data and the post-nitrogen oxide emission sensor data to obtain a transient nitrogen oxide emission exceedance test result; identifying the preferred high-emission vehicles and non-preferred high-emission vehicles among different vehicles according to the transient nitrogen oxide emission exceedance test result; obtaining the working condition test data of the non-preferred high-emission vehicles, and the working condition test includes PEMS working condition test or C-WTVC working condition test under laboratory conditions; and identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the working condition test data.

[0150] In one embodiment, the working condition test includes a PEMS working condition test; the identification module is further configured to identify the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the working condition test data, including: obtaining the engine WHTC cycle work of the non-preferred high-emission vehicle; dividing the work-based window based on the work-based window method and the engine WHTC cycle work and counting the average power percentage of all work-based windows; obtaining the power percentage threshold of the non-preferred high-emission vehicle; obtaining the effective window according to the average power percentage of the work-based window and the power percentage threshold; counting the nitrogen oxide specific emission value of the effective window; and identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the nitrogen oxide specific emission value of the effective window.

[0151] In one embodiment, the working condition test further includes a C-WTVC working condition test under laboratory conditions; the identification module is further configured to identify the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the working condition test data, further including: obtaining the weighting coefficient corresponding to the model of the non-preferred high-emission vehicle; statistically calculating the average nitrogen oxide specific emission value within the C-WTVC test road condition range based on the average value method; obtaining the final average nitrogen oxide specific emission value according to the average nitrogen oxide specific emission value and the weighting coefficient corresponding to the model of the non-preferred high-emission vehicle; and identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the final average nitrogen oxide specific emission value.

[0152] In one embodiment, after the data acquisition module acquires the engine operation data and the post nitrogen oxide emission sensor data of different vehicles, it further includes: acquiring the control system data of different vehicles; and monitoring the fault status of the vehicles in real time according to the engine operation data, the control system data, and the post nitrogen oxide emission sensor data of different vehicles.

[0153] In one embodiment, before the identification module identifies high-emission vehicles based on the engine operation data and the post nitrogen oxide emission sensor data, it further includes: eliminating the engine operation data and the post nitrogen oxide emission sensor data corresponding to the abnormal moments of the post nitrogen oxide emission sensor data.

[0154] Each module in the above vehicle nitrogen oxide emission detection device can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0155] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 6 shown. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a vehicle nitrogen oxide emission detection method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0156] Those skilled in the art can understand that Figure 6 the structure shown in

[0157] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0158] Obtain the engine operation data and the post-nitrogen oxide emission sensor data of different vehicles;

[0159] Identify high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data;

[0160] Generate a depth detection prompt message for performing in-depth nitrogen oxide detection on high-emission vehicles;

[0161] Push the depth detection prompt message, which is used to prompt to perform nitrogen oxide emission detection on high-emission vehicles using dedicated on-vehicle emission equipment.

[0162] In one embodiment, when the processor executes the computer program, the following steps are further implemented: perform a transient nitrogen oxide emission exceedance test on the vehicle according to the engine operation data and the post-nitrogen oxide emission sensor data to obtain a transient nitrogen oxide emission exceedance test result; identify the preferred high-emission vehicles and non-preferred high-emission vehicles among different vehicles according to the transient nitrogen oxide emission exceedance test result; obtain the working condition test data of the non-preferred high-emission vehicles, and the working condition test includes PEMS working condition test or C-WTVC working condition test under laboratory conditions; identify the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the working condition test data.

[0163] In one embodiment, when the processor executes the computer program, the following steps are further implemented: obtain the engine WHTC cycle work of the non-preferred high-emission vehicle; divide the work-based window based on the work-based window method and the engine WHTC cycle work and count the average power percentage of all work-based windows; obtain the power percentage threshold of the non-preferred high-emission vehicle; obtain the effective window according to the average power percentage of the work-based window and the power percentage threshold; count the specific emission value of nitrogen oxide in the effective window; identify the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the specific emission value of nitrogen oxide in the effective window.

[0164] In one embodiment, when the processor executes the computer program, the following steps are further implemented: obtain the weighting coefficient corresponding to the non-preferred high-emission vehicle model; statistically obtain the average specific emission value of nitrogen oxide in the C-WTVC test road condition interval based on the average value method; obtain the final average specific emission value of nitrogen oxide according to the average specific emission value of nitrogen oxide and the weighting coefficient corresponding to the non-preferred high-emission vehicle model; identify the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the final average specific emission value of nitrogen oxide.

[0165] In one embodiment, when the processor executes the computer program, the following steps are further implemented: obtaining control system data of different vehicles; and monitoring the fault status of the vehicles in real time according to the engine operation data, control system data, and post-nitrogen oxide emission sensor data of different vehicles.

[0166] In one embodiment, when the processor executes the computer program, the following steps are further implemented: eliminating the engine operation data and post-nitrogen oxide emission sensor data corresponding to the abnormal moments of the post-nitrogen oxide emission sensor data.

[0167] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, the following steps are implemented:

[0168] Obtaining the engine operation data and post-nitrogen oxide emission sensor data of different vehicles;

[0169] Identifying high-emission vehicles according to the engine operation data and post-nitrogen oxide emission sensor data;

[0170] Generating a depth detection prompt message for performing in-depth nitrogen oxide detection on high-emission vehicles;

[0171] Pushing the depth detection prompt message, where the depth detection prompt message is used to prompt to perform nitrogen oxide emission detection on high-emission vehicles using dedicated on-vehicle emission equipment.

[0172] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: performing a transient nitrogen oxide emission exceedance test on the vehicle according to the engine operation data and post-nitrogen oxide emission sensor data to obtain a transient nitrogen oxide emission exceedance test result; identifying the preferred high-emission vehicles and non-preferred high-emission vehicles among different vehicles according to the transient nitrogen oxide emission exceedance test result; obtaining the operating condition test data of the non-preferred high-emission vehicles, and the operating condition test includes PEMS operating condition test or C-WTVC operating condition test under laboratory conditions; and identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the operating condition test data.

[0173] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: obtaining the engine WHTC cycle work of the non-preferred high-emission vehicle; dividing the work-based window based on the work-based window method and the engine WHTC cycle work and statistically calculating the average power percentage of all work-based windows; obtaining the power percentage threshold of the non-preferred high-emission vehicle; obtaining the effective window according to the average power percentage of the work-based window and the power percentage threshold; statistically calculating the specific nitrogen oxide emission value of the effective window; and identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the specific nitrogen oxide emission value of the effective window.

[0174] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining a weighted coefficient corresponding to a non-preferred high-emission vehicle model; statistically calculating an average nitrogen oxide specific emission value within the C-WTVC test road condition range based on the average value method; obtaining a final average nitrogen oxide specific emission value according to the average nitrogen oxide specific emission value and the weighted coefficient corresponding to the non-preferred high-emission vehicle model; and identifying, according to the final average nitrogen oxide specific emission value, the high-emission vehicles that are secondarily identified among the non-preferred high-emission vehicles.

[0175] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining control system data of different vehicles; and real-time monitoring the fault status of the vehicles according to the engine operation data, the control system data, and the post-nitrogen oxide emission sensor data of different vehicles.

[0176] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: eliminating the engine operation data and the post-nitrogen oxide emission sensor data corresponding to the abnormal moments of the post-nitrogen oxide emission sensor data.

[0177] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0178] Obtaining the engine operation data and the post-nitrogen oxide emission sensor data of different vehicles;

[0179] Identifying high-emission vehicles according to the engine operation data and the post-nitrogen oxide emission sensor data;

[0180] Generating a depth detection prompt message for performing in-depth nitrogen oxide detection on high-emission vehicles;

[0181] Pushing the depth detection prompt message, where the depth detection prompt message is used to prompt to perform nitrogen oxide emission detection on high-emission vehicles by using dedicated on-vehicle emission equipment.

[0182] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: performing a transient nitrogen oxide emission exceedance test on the vehicle according to the engine operation data and the post-nitrogen oxide emission sensor data to obtain a transient nitrogen oxide emission exceedance test result; identifying preferred high-emission vehicles and non-preferred high-emission vehicles among different vehicles according to the transient nitrogen oxide emission exceedance test result; obtaining the condition test data of the non-preferred high-emission vehicles, where the condition test includes a PEMS condition test or a C-WTVC condition test under laboratory conditions; and identifying, according to the condition test data, the high-emission vehicles that are secondarily identified among the non-preferred high-emission vehicles.

[0183] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining the engine WHTC cycle work of non-preferred high-emission vehicles; dividing work-based windows based on the work-based window method and the engine WHTC cycle work, and statistically calculating the average power percentage of all work-based windows; obtaining the power percentage threshold of non-preferred high-emission vehicles; obtaining valid windows based on the average power percentage of the work-based windows and the power percentage threshold; statistically calculating the specific NOx emissions value of the valid windows; and identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the specific NOx emissions value of the valid windows.

[0184] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining the weighting coefficient corresponding to the model of non-preferred high-emission vehicles; statistically calculating the average specific NOx emissions value within the C-WTVC test road condition range based on the average value method; obtaining the final average specific NOx emissions value according to the average specific NOx emissions value and the weighting coefficient corresponding to the model of non-preferred high-emission vehicles; and identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the final average specific NOx emissions value.

[0185] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining the control system data of different vehicles; and monitoring the fault status of the vehicles in real time according to the engine operation data, control system data, and post-NOx emission sensor data of different vehicles.

[0186] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: removing the engine operation data and post-NOx emission sensor data corresponding to the abnormal moments of the post-NOx emission sensor data.

[0187] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0188] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0189] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0190] The above-described embodiments merely represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the patent of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for detecting nitrogen oxide emissions of a vehicle, characterized in that, The method includes: Obtaining the engine operation data and the post-NOx emission sensor data of different vehicles, where the post-NOx emission sensor data refers to the output value of the NOx sensor downstream of the SCR; Identifying high-emission vehicles based on the engine operation data and the post-NOx emission sensor data; Generating a depth detection prompt message for performing in-depth NOx detection on the high-emission vehicles; Pushing the depth detection prompt message, which is used to prompt the use of dedicated on-vehicle emission equipment to detect the NOx emissions of the high-emission vehicles; The identifying high-emission vehicles based on the engine operation data and the post-NOx emission sensor data includes: Performing a transient NOx emission exceedance test on the vehicles based on the engine operation data and the post-NOx emission sensor data to obtain a transient NOx emission exceedance test result; Identifying the preferred high-emission vehicles and non-preferred high-emission vehicles among the different vehicles according to the transient NOx emission exceedance test result; Obtaining the operating condition test data of the non-preferred high-emission vehicles, where the operating condition test includes PEMS operating condition test or C-WTVC operating condition test under laboratory conditions; Identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the operating condition test data.

2. The method according to claim 1, characterized in that, The operating condition test includes PEMS operating condition test; The identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the operating condition test data includes: Obtaining the engine WHTC cycle work of the non-preferred high-emission vehicles; Dividing work-based windows based on the work-based window method and the engine WHTC cycle work, and statistically calculating the average power percentage of all work-based windows; Obtaining the power percentage threshold of the non-preferred high-emission vehicles; Obtaining effective windows according to the average power percentage of the work-based windows and the power percentage threshold; Statistically calculating the NOx specific emission values of the effective windows; Identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the NOx specific emission values of the effective windows.

3. The method according to claim 1, characterized in that The operating condition test also includes C-WTVC operating condition test under laboratory conditions; The identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the operating condition test data further includes: Obtaining the weighting coefficient corresponding to the vehicle model of the non-preferred high-emission vehicles; Statistically calculating the average NOx specific emission value within the C-WTVC test road condition interval based on the average value method; Obtaining the final average NOx specific emission value according to the average NOx specific emission value and the weighting coefficient corresponding to the vehicle model of the non-preferred high-emission vehicles; Identifying the secondarily identified high-emission vehicles among the non-preferred high-emission vehicles according to the final average NOx specific emission value.

4. The method according to claim 1, characterized in that, After obtaining the engine operation data and the post-NOx emission sensor data of different vehicles, it further includes: Obtaining the control system data of different vehicles; Real-time monitoring the fault status of the vehicles based on the engine operation data, control system data, and post-NOx emission sensor data of different vehicles.

5. The method according to claim 1, wherein Before identifying high-emission vehicles based on the engine operation data and the post-NOx emission sensor data, it further includes: Exclude the engine operation data and the post-NOx emission sensor data corresponding to the abnormal moment of the post-NOx emission sensor data.

6. A vehicle nitrogen oxide emission detection device, characterized in that, The device includes: A data acquisition module, configured to acquire engine operation data and post-NOx emission sensor data of different vehicles; An identification module, configured to identify high-emission vehicles according to the engine operation data and the post-NOx emission sensor data; A message generation module, configured to generate a depth detection prompt message for performing in-depth NOx detection on the high-emission vehicles; A message push module, configured to push the depth detection prompt message, where the depth detection prompt message is used to prompt to perform NOx emission detection on the high-emission vehicles by using a dedicated on-vehicle emission device; The identification module is specifically configured to perform a transient NOx emission exceedance test on a vehicle according to the engine operation data and the post-NOx emission sensor data to obtain a transient NOx emission exceedance test result; identify a preferred high-emission vehicle and a non-preferred high-emission vehicle among the different vehicles according to the transient NOx emission exceedance test result; acquire the working condition test data of the non-preferred high-emission vehicle, and the working condition test includes a PEMS working condition test or a C-WTVC working condition test under laboratory conditions; identify the high-emission vehicles identified for the second time among the non-preferred high-emission vehicles according to the working condition test data.

7. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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