An in-vehicle IUPR result correction method, device, equipment and storage medium

Abstract

The application discloses a vehicle-mounted IUPR result correction method, device and equipment and a storage medium, wherein the method comprises the following steps: judging the working condition of the current vehicle based on the acquired vehicle surrounding environment data, running data and state data; performing self-adaptive adjustment on the fault diagnosis execution condition of the vehicle emission related monitoring component in the working condition according to the calibrated working condition-threshold mapping table; performing diagnosis monitoring on the adjusted fault diagnosis execution condition, if the identification diagnosis is not completed and is not a fault, introducing a hierarchical weighting correction coefficient based on the number of continuous incomplete times to reduce and correct the incomplete count data to obtain the corrected diagnosis result; and outputting the vehicle-mounted IUPR result through an adaptive dynamic compensation model based on the corrected diagnosis result. The application can accurately correct the IUPR value under extreme working conditions, effectively eliminate the interference of extreme working conditions on the IUPR accounting result, and improve the accuracy of the IUPR result.

Description

Technical Field

[0001] This invention relates to the field of vehicle monitoring technology, and in particular to a method, apparatus, device, and storage medium for correcting vehicle-mounted IUPR results. Background Technology

[0002] With increasingly stringent global automotive emission regulations (such as China VI and Euro VI), the monitoring requirements for vehicle emission-related components by on-board diagnostic (OBD) systems are constantly rising. Among these, IUPR (In-Use Performance Ratio) is a core indicator for measuring the actual operational effectiveness of the OBD system, requiring that the IUPR values ​​of each monitored component meet the regulatory limits (e.g., ≥0.90). The basic calculation of IUPR is the ratio of the number of diagnostic completions to the total number of diagnostic activations.

[0003] In actual vehicle operation, vehicles inevitably encounter various extreme or non-ideal operating conditions. For example, extremely cold temperatures in high-altitude and cold regions, low air pressure at extremely high altitudes, and typical short-distance, low-speed commuting conditions in large cities. In addition, the engine is often not fully warmed up after a cold start.

[0004] The core flaw of existing vehicle-mounted IUPR calculation solutions lies in the fact that they fail to distinguish between extreme operating conditions and real faults, and adopt a one-size-fits-all fixed threshold and counting rules. This results in non-fault diagnosis being incorrectly counted in scenarios such as low temperature, high altitude, short distance, and cold start, leading to falsely low IUPR values, non-compliant misjudgments, and the risk of missed faults.

[0005] Therefore, how to distinguish between extreme operating condition disturbances and real faults and dynamically correct the IUPR count accordingly to avoid numerical distortion and misjudgment is a technical problem that urgently needs to be solved. Summary of the Invention

[0006] The main objective of this invention is to provide an on-board IUPR result correction method, device, equipment, and storage medium that can accurately correct IUPR values ​​under extreme operating conditions, effectively eliminate the interference of extreme operating conditions on IUPR calculation results, improve the accuracy of IUPR results, and improve the diagnostic completion rate and false alarm rate without adding new hardware.

[0007] Firstly, this application provides a method for correcting vehicle-mounted IUPR results, wherein the method includes the following steps: Based on the acquired data on the vehicle's surrounding environment, operation, and status, the current operating condition of the vehicle is determined. Based on the calibrated operating condition-threshold mapping table, the fault diagnosis execution conditions of the vehicle emission-related monitoring components under the current operating condition are adaptively adjusted. The adjusted fault diagnosis execution conditions are monitored. If the diagnosis is not completed and is not due to a fault, a graded weighted correction coefficient is introduced based on the number of consecutive incompletes. The incomplete count data is deducted and corrected to obtain the corrected diagnosis result. Based on the corrected diagnostic results, the vehicle-mounted IUPR results are output through an adaptive dynamic compensation model.

[0008] In conjunction with the first aspect mentioned above, as an optional implementation method, the operating condition-threshold mapping calibration table pre-stored in the encrypted secure storage area of ​​the vehicle ECU is retrieved; Based on the identified current operating condition of the vehicle, the corresponding fault diagnosis threshold adjustment strategy is matched from the mapping calibration table; Based on the matched strategy, the diagnostic access threshold, operation threshold, and completion judgment threshold of emission-related monitoring components are adaptively adjusted to optimize the fault diagnosis execution conditions of vehicle emission-related monitoring components.

[0009] In conjunction with the first aspect mentioned above, as an optional implementation, if a low-temperature operating condition is identified, the minimum diagnostic runtime threshold is extended to a set threshold, and the minimum diagnostic engine load threshold is reduced to a set threshold. If the condition is identified as a high-altitude operating condition, the minimum intake flow threshold for diagnosis will be lowered to the set threshold, and the allowable fluctuation range of the diagnostic parameters will be expanded to the set threshold. If the condition is identified as a short-distance working condition, the diagnostic completion threshold will be lowered to the set threshold. If the condition is identified as a cold start, the diagnostic activation delay time will be shortened to the set threshold. If a condition is identified as a superimposed condition with multiple operating conditions, a weighted superposition method based on threshold adjustment will be adopted, and the adjustment range of parameters for a single type of operating condition will not exceed the set threshold.

[0010] In conjunction with the first aspect mentioned above, as an optional implementation method, a multi-dimensional analysis is performed on the reasons for incomplete diagnosis in each driving cycle to identify whether the incomplete diagnosis is due to non-fault incompleteness or fault incompleteness. The multi-dimensional analysis includes: whether the marking results of the comparison working conditions are extreme working conditions, whether the detection results of the sensor signals are valid, and whether the operating status of the emission components is normal.

[0011] In conjunction with the first aspect above, as an optional implementation method, if it is continuously determined to be a non-faulty incomplete task within a first set number of times, then the weighted correction coefficient is set as a first threshold, and the corresponding incomplete first count base is deducted according to the coefficient. Based on the incomplete first count base, the corrected number of first diagnosis completions and the total number of first diagnosis activations are calculated. If a non-faulty incomplete task is continuously determined within the second set number of times, the weighted correction coefficient is set to the second threshold, and the second count base for incomplete tasks is further deducted according to this coefficient. Based on the incomplete second count base, the corrected number of second diagnosis completions and the total number of second diagnosis activations are calculated. If the non-fault incomplete process is continuously determined within the third set number of attempts, it is determined that there is a hidden fault in the component or zero-point drift of the sensor, the weighted correction is stopped, and the process is automatically switched to regular fault diagnosis.

[0012] In conjunction with the first aspect mentioned above, as an optional implementation, if the identification and diagnosis is not completed, it is considered that the fault is not completed, then the weighted correction is not performed, and the fault is not completed is included in the fault count.

[0013] In conjunction with the first aspect mentioned above, as an optional implementation method, the vehicle's surrounding environmental parameters, operating parameters, and status parameters are synchronously collected at a set sampling frequency; Based on a preset quantization threshold, the sampled surrounding environmental parameters, operating parameters, and state parameters are identified and the vehicle is currently in a single extreme working condition or a superimposed working condition. The single extreme operating conditions include: low temperature operating conditions, high altitude operating conditions, short distance operating conditions, and cold start operating conditions. The multi-condition superposition operating conditions include: a combination of operating conditions that simultaneously satisfy two types of single operating conditions.

[0014] In conjunction with the first aspect mentioned above, as an optional implementation method, if the current ambient temperature is less than or equal to a set temperature threshold and the duration is greater than or equal to a set time threshold, it is determined to be a low-temperature operating condition. If the current altitude is greater than or equal to the set altitude threshold and the corresponding atmospheric pressure is less than or equal to the set pressure threshold, then it is judged as a high-altitude working condition. If the total mileage of the current single driving cycle is less than or equal to the set mileage threshold, and the driving time is less than or equal to the set threshold, it is judged as a short-distance working condition. The method includes: if the current engine coolant temperature is less than or equal to a set coolant temperature threshold, and the continuous running time after engine start is less than or equal to the set threshold, then it is determined to be a cold start condition.

[0015] In conjunction with the first aspect mentioned above, as an optional implementation method, the working condition marking result is bound to a unique identifier of the driving cycle to enable full traceability of the working condition.

[0016] In conjunction with the first aspect mentioned above, as an optional implementation method, an adaptive dynamic compensation model is established, which includes: a basic counting layer, a dynamic correction layer for operating conditions, a historical cyclic compensation layer, and a compliance constraint layer. Obtain the corrected number of diagnostic completions and the total number of diagnostic activations, and calculate the IUPR base count value using the base counting layer; Based on the IUPR base count value and the obtained operating condition dynamic coefficient, the operating condition dynamic adjustment value is calculated using the operating condition dynamic correction layer. Based on the dynamic adjustment value of the working condition and the obtained historical cyclic compensation coefficient, the historical cyclic compensation calculation value is calculated using the historical cyclic compensation layer; The historical cyclic compensation calculation value is constrained by the compliance clamping layer, and the constrained historical cyclic compensation calculation value is used as the final vehicle IUPR result. The constraint includes: constraining the historical cyclic compensation calculation value within a set numerical range.

[0017] In conjunction with the first aspect mentioned above, as an optional implementation method, the final vehicle-mounted IUPR result is verified to determine whether it meets the regulatory limits; The entire process of operating condition marking, fault diagnosis execution condition adjustment, and weighted correction is verified to determine whether the records are complete. If all verifications pass, compliance traceability data will be output, which includes: unique identifier of driving cycle, working condition marking information, threshold adjustment details, weighted correction coefficient, final IUPR result and verification result.

[0018] Secondly, this application provides an on-board IUPR result correction device, the device comprising: The judgment module is used to determine the current operating condition of the vehicle based on the acquired data on the vehicle's surrounding environment, operation data, and status data. The adjustment module is used to adaptively adjust the fault diagnosis execution conditions of vehicle emission-related monitoring components under the current operating conditions based on the calibrated operating condition-threshold mapping table. The processing module is used to monitor the adjusted fault diagnosis execution conditions. If the diagnosis is not completed and it is not a fault-related failure, a graded weighted correction coefficient is introduced based on the number of consecutive failures to deduct and correct the failure count data, and the corrected diagnosis result is obtained. The compensation module is used to output the vehicle IUPR results based on the corrected diagnostic results through an adaptive dynamic compensation model.

[0019] Thirdly, this application also provides an electronic device, the electronic device comprising: a processor; and a memory storing computer-readable instructions, which, when executed by the processor, implement the method described in any one of the first aspects.

[0020] Fourthly, this application also provides a computer-readable storage medium storing computer program instructions that, when executed by a computer, cause the computer to perform the method described in any of the first aspects.

[0021] This application provides a method, apparatus, device, and storage medium for correcting vehicle-mounted IUPR results. The method includes the following steps: determining the current operating condition of the vehicle based on acquired vehicle surrounding environment data, operational data, and status data; adaptively adjusting the fault diagnosis execution conditions of vehicle emission-related monitoring components under the current operating condition according to a calibrated operating condition-threshold mapping table; performing diagnostic monitoring on the adjusted fault diagnosis execution conditions; if a diagnosis is identified as incomplete and not due to a fault, a graded weighted correction coefficient is introduced based on the number of consecutive incomplete diagnoses to deduct and correct the incomplete count data, obtaining a corrected diagnostic result; and outputting the vehicle-mounted IUPR result based on the corrected diagnostic result through an adaptive dynamic compensation model. This application enables accurate correction of IUPR values ​​under extreme operating conditions, effectively eliminating the interference of extreme operating conditions on IUPR calculation results, improving the accuracy of IUPR results, and increasing the diagnostic completion rate and false alarm rate without adding new hardware.

[0022] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit the invention. Attached Figure Description

[0023] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0024] Figure 1 This is a flowchart of a vehicle-mounted IUPR result correction method provided in the embodiments of this application; Figure 2 This is a schematic diagram of an on-board IUPR result correction device provided in an embodiment of this application; Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of this application; Figure 4 This is a schematic diagram of a computer-readable program medium provided in an embodiment of this application. Detailed Implementation

[0025] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.

[0026] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. Some of the block diagrams shown in the drawings represent functional entities and do not necessarily correspond to physically or logically independent entities.

[0027] The embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0028] Reference Figure 1 , Figure 1 The diagram shown is a flowchart of a vehicle-mounted IUPR result correction method provided by the present invention. Figure 1 As shown, the method includes the following steps: Step S101: Based on the acquired vehicle surrounding environment data, operation data, and status data, determine the current operating condition of the vehicle.

[0029] Specifically, the vehicle's surrounding environmental parameters, operating parameters, and status parameters are collected synchronously at a set sampling frequency. Based on a preset quantization threshold, the sampled surrounding environmental parameters, operating parameters, and status parameters are identified and the vehicle is currently in a single extreme operating condition or a multi-condition superposition operating condition. The single extreme operating condition includes: low temperature operating condition, high altitude operating condition, short distance operating condition, and cold start operating condition. The multi-condition superposition operating condition includes: a combination of operating conditions that simultaneously satisfy two types of single operating conditions.

[0030] In one embodiment, the step of determining a single extreme operating condition in the current operating condition includes: if the current ambient temperature is less than or equal to a set temperature threshold and the duration is greater than or equal to a set time threshold, it is determined to be a low-temperature operating condition; if the current altitude is greater than or equal to a set altitude threshold and the corresponding atmospheric pressure is less than or equal to a set pressure threshold, it is determined to be a high-altitude operating condition; if the total mileage of the current single driving cycle is less than or equal to a set mileage threshold and the driving time is less than or equal to a set threshold, it is determined to be a short-distance operating condition; the step also includes: if the current engine coolant temperature is less than or equal to a set coolant temperature threshold and the continuous running time after engine start is less than or equal to a set threshold, it is determined to be a cold start operating condition.

[0031] In one embodiment, the working condition marking result is bound to a unique identifier of the driving cycle to enable full traceability of the working condition.

[0032] To illustrate this, a fixed sampling frequency of 50ms is used to synchronously collect three core vehicle operating signals (environmental parameters, operating parameters, and status parameters) in real time. This ensures signal timing synchronization and eliminates delays and deviations. Environmental parameters include ambient temperature, atmospheric pressure, and altitude; operating parameters include vehicle speed, single trip mileage, driving duration, and engine load rate; and status parameters include engine coolant temperature, continuous engine operation duration after startup, and intake airflow. Based on preset quantization thresholds, single extreme operating conditions and multiple overlapping operating conditions are identified and labeled in a tiered manner. The labeling results are bound to a unique identifier for each driving cycle, enabling full traceability. The specific operating condition identification thresholds are as follows: (1) Low temperature single working condition: ambient temperature ≤ -7℃, and the duration of continuous stability ≥ 60s, with no significant fluctuations or jumps in the signal; (2) High-altitude single working condition: altitude ≥ 2500m, corresponding atmospheric pressure ≤ 80kPa, both parameters are satisfied at the same time and the duration is ≥ 120s; (3) Short-distance single working condition: The total driving distance of a single driving cycle is ≤6km and the synchronous driving time is ≤900s, and the dual-parameter linkage judgment is used. (4) Cold start single operating condition: engine coolant temperature ≤45℃, and continuous running time after engine start ≤300s; (5) Multiple working conditions superimposed: If the threshold for judging two or more single working conditions is met at the same time, it will be automatically marked as the corresponding combination superimposed working condition, and the system will prioritize the execution of the superimposed working condition adaptation logic.

[0033] Step S102: Based on the calibrated operating condition-threshold mapping table, adaptively adjust the fault diagnosis execution conditions of the vehicle emission-related monitoring components under the current operating condition.

[0034] Specifically, the system retrieves the operating condition-threshold mapping calibration table pre-stored in the encrypted secure storage area of ​​the vehicle ECU; based on the identified current operating condition of the vehicle, it matches the corresponding fault diagnosis threshold adjustment strategy from the mapping calibration table; and based on the matched strategy, it adaptively adjusts the diagnostic access threshold, operating threshold, and completion judgment threshold of the emission-related monitoring components to optimize the fault diagnosis execution conditions of the vehicle emission-related monitoring components.

[0035] The adjustment strategy includes: If the condition is identified as a low-temperature operating condition, the minimum diagnostic runtime threshold will be increased to the set threshold, and the minimum diagnostic engine load threshold will be decreased to the set threshold. If the condition is identified as a high-altitude operating condition, the minimum intake flow threshold for diagnosis will be lowered to the set threshold, and the allowable fluctuation range of the diagnostic parameters will be expanded to the set threshold. If the condition is identified as a short-distance working condition, the diagnostic completion threshold will be lowered to the set threshold. If the condition is identified as a cold start, the diagnostic activation delay time will be shortened to the set threshold. If a condition is identified as a superimposed condition with multiple operating conditions, a weighted superposition method based on threshold adjustment will be adopted, and the adjustment range of parameters for a single type of operating condition will not exceed the set threshold.

[0036] To illustrate this, we retrieve the operating condition-threshold mapping calibration table pre-stored in the encrypted secure storage area of ​​the vehicle ECU. This mapping table is generated through joint calibration of bench extreme operating condition simulation experiments and real vehicle high-altitude / high-cold / urban road tests. It adapts differentiated calibration parameters for different displacement engines, different types of after-treatment systems, and different power forms of fuel / hybrid.

[0037] Based on the identified operating conditions, the three levels of parameters for the diagnostic access threshold, operating threshold, and completion judgment threshold of emission-related monitoring components are adaptively adjusted without altering the IUPR basic counting rules and core judgment logic. Only the preconditions for diagnostic execution are optimized to avoid non-faulty diagnostic failures under extreme operating conditions. The specific adjustment rules are as follows: (1) Low temperature single operating condition: The minimum operating time threshold for diagnosis is extended by 35%, the minimum engine load threshold for diagnosis is reduced by 15%, the diagnostic operating conditions are relaxed, and the engine operating characteristics are adapted to the low temperature environment. (2) High-altitude single operating condition: The minimum intake flow threshold for diagnosis is reduced by 20%, and the allowable fluctuation range of diagnostic parameters is expanded by 25% to adapt to the fluctuation of operating parameters caused by the thin air in high-altitude areas. (3) If the condition is identified as a short-distance working condition, the diagnostic completion threshold will be lowered to the set threshold. (4) If the condition is identified as a cold start, the diagnostic activation delay time will be shortened to the set threshold. (5) Short-distance + cold start superimposed working condition: shorten the diagnostic activation delay time by 20%, reduce the diagnostic completion judgment threshold by 18%, trigger the diagnostic process in advance, reduce the difficulty of short-distance loop diagnostic completion, and increase the probability of diagnostic completion. (6) Multiple complex superimposed working conditions: The threshold adjustment weighted superposition logic is adopted, and the adjustment range of a single parameter does not exceed 40% to avoid over-adjustment leading to missed detection of component failures; (7) Normal operating conditions: No threshold adjustment is made, and the default standard diagnostic parameters of the regulations are executed.

[0038] It is understandable that different operating conditions require corresponding adjustment strategies, including lowering the fault diagnosis criteria when encountering extreme operating conditions.

[0039] After performing diagnostic monitoring on the adjusted fault diagnosis execution conditions, the following steps are taken: a multi-dimensional analysis of the reasons for incomplete diagnosis in each driving cycle is performed to identify whether the incomplete diagnosis is due to non-fault incompleteness or fault incompleteness. The multi-dimensional analysis includes: whether the marking results of the comparison working conditions are extreme working conditions, whether the detection results of the sensor signals are valid, and whether the operating status of the emission components is normal.

[0040] To illustrate this, when all three dimensions are met simultaneously—that is, there is an extreme operating condition marker, the sensor signal is valid, and the emission components are operating normally—it is determined to be a non-fault-related incomplete task. If any of the above conditions are not met—that is, there is no extreme operating condition marker, or the sensor signal is invalid, or the emission components are in an abnormal state—it is determined to be a fault-related incomplete task.

[0041] Example of non-fault incomplete operation: The vehicle travels 3 kilometers in a short distance at -10℃. The system marks it as a low temperature + short-distance extreme condition. At the same time, the oxygen sensor signal is normal and there is no fault code. All three dimensions are met, so it is judged as a non-fault incomplete operation and a graded weighted correction is performed.

[0042] Example of an incomplete fault category: When the vehicle is driven in normal weather, the oxygen sensor displays a fault code and the signal is abnormal. Although there are no extreme operating conditions, the sensor signal is invalid. This is determined to be an incomplete fault category and is directly included in the regular fault count without weighted correction.

[0043] Step S103: Perform diagnostic monitoring on the adjusted fault diagnosis execution conditions. If the diagnosis is not completed and is not due to a fault, introduce a graded weighted correction coefficient based on the number of consecutive incompletes to deduct and correct the incomplete count data, and obtain the corrected diagnosis result.

[0044] Specifically, if a non-fault-related incomplete task is continuously determined within a first set number of attempts, the weighted correction coefficient is set to a first threshold, and the corresponding incomplete first count base is deducted according to this coefficient. Based on the incomplete first count base, the corrected number of first diagnostic completions and the total number of first diagnostic activations are calculated. If a non-fault-related incomplete task is continuously determined within a second set number of attempts, the weighted correction coefficient is set to a second threshold, and the incomplete second count base is further deducted according to this coefficient. Based on the incomplete second count base, the corrected number of second diagnostic completions and the total number of second diagnostic activations are calculated. If a non-fault-related incomplete task is continuously determined within a third set number of attempts, it is determined that the component has a latent fault or the sensor has zero-point drift, the weighted correction is stopped, and the process automatically switches to routine fault diagnosis.

[0045] In one embodiment, if the identification and diagnosis is not completed, it is considered a fault not completed. In this case, no weighted correction is performed, and the fault not completed is counted in the fault count.

[0046] To illustrate this more clearly, consider this scenario: A vehicle travels short distances (3 kilometers one way, ambient temperature -10℃) for 8 consecutive days in a frigid winter region. Each trip results in incomplete OBD diagnostics due to the combined effects of low temperature, short distance, and cold start.

[0047] Days 1-2: The system identifies extreme working conditions, but the number of consecutive incomplete attempts does not meet the correction trigger condition (requires 3 consecutive attempts). Weighted correction will not be performed for the time being, and each incomplete attempt will still be counted as the base count of 1.

[0048] Day 3: If the non-faulty operation fails for the third consecutive time, a graded weighted correction is triggered. The weighted correction coefficient is 0.85. The failure count base is reduced by 0.85 for this failure (i.e., 0.85 is actually counted, not 1), while the basic counting logic is retained.

[0049] Days 4-6: If the task is not completed for the 4th, 5th, or 6th consecutive non-faulty tasks, the weighted correction factor is 0.72. Each time the task is not completed, the base number of the incomplete task is reduced by 0.72 to gradually offset the counting deviation caused by extreme working conditions.

[0050] Days 7-8: If the non-faulty operation is not completed for the 7th and 8th consecutive time, the system determines that it is no longer a simple extreme operating condition interference, but may have a hidden fault in the component or zero drift of the sensor. The weighted correction is stopped immediately, and the system automatically switches to the regular fault investigation logic, triggering the fault pre-diagnosis process. Subsequent incomplete operations will no longer enjoy the discount treatment and will be directly counted as regular faults according to the fault category.

[0051] Final result: The first 6 non-fault-related failures were corrected through hierarchical weighting, and the actual total value included in the denominator was 1+1+0.85+0.72+0.72+0.72=5.01. Compared with the original 6 failures, the counting weight was reduced by about 16.5%, which effectively prevented the vehicle from being misjudged as non-compliant due to extreme operating conditions. At the same time, fault pre-diagnosis was triggered from the 7th failure onwards, preventing hidden faults from being covered up for a long time.

[0052] Step S104: Based on the corrected diagnostic results, output the vehicle IUPR results through the adaptive dynamic compensation model.

[0053] Specifically, an adaptive dynamic compensation model is established, comprising: a base counting layer, a dynamic operating condition correction layer, a historical cyclic compensation layer, and a compliance constraint layer. The model acquires the corrected number of diagnostic completions and the total number of diagnostic activations, and uses the base counting layer to calculate the IUPR base count value. Based on the IUPR base count value and the acquired dynamic operating condition coefficients, the dynamic operating condition correction layer calculates the dynamic operating condition adjustment value. Based on the dynamic operating condition adjustment value and the acquired historical cyclic compensation coefficients, the historical cyclic compensation layer calculates the historical cyclic compensation calculation value. The compliance constraint layer constrains the historical cyclic compensation calculation value, and the constrained historical cyclic compensation calculation value is used as the final on-board IUPR result, wherein the constraint includes: constraining the historical cyclic compensation calculation value within a set numerical range.

[0054] For ease of understanding and illustration, based on the corrected number of diagnostic completions and total number of diagnostic activations, a four-layer adaptive dynamic compensation model is adopted, which abandons the original fixed coefficients in regulations, couples dynamic adaptation under operating conditions with historical cyclic compensation, and calculates the final IUPR value level by level: The adaptive dynamic compensation module is divided into a basic counting layer, a working condition dynamic correction layer, a historical cyclic compensation layer, and a compliance constraint layer. The calculation formula for each level is as follows: 1. Basic counting layer: IUPR_Base = N_C / N_T; 2. Dynamic adjustment layer based on operating conditions: IUPR_Adj = IUPR_Base × K_F; 3. Historical Cycle Compensation Layer: IUPR_Cal = IUPR_Adj × (1 + W_C).

[0055] 4. Compliance Constraint Layer (Final Output): If IUPR_Cal > 1.00, then IUPR_Final = 1.00; If IUPR_Cal < 0.90 and there is no fault indicator, then IUPR_Final = 0.90. For other operating conditions, IUPR_Final = IUPR_Cal. The compliance constraint layer can be understood as being used to preset the output IUPR result, constraining it within a set range (0.9-1).

[0056] The parameters in the formula are defined as follows: IUPR_Base: base count value; N_C: number of diagnostics completed after weighted correction; N_T: total number of diagnostics activated after weighted correction; IUPR_Adj: Dynamic adjustment value for operating conditions; K_F: Dynamic coefficient for operating conditions, where 1.00 is taken for normal operating conditions, 0.95-0.98 for low temperature operating conditions, 0.96-0.99 for high altitude operating conditions, and 1.05-1.10 for short-distance + cold start operating conditions; IUPR_Cal: Historical cyclic compensation calculation value; W_C: Historical cyclic compensation coefficient, where +0.05 is taken for 3 consecutive non-fault failures, +0.08 to +0.12 is taken for 4-6 consecutive non-fault failures, and 0 is taken for 7 consecutive failures or failures. IUPR_Final: Final compliant output value.

[0057] Based on the corrected diagnostic results, after outputting the vehicle-mounted IUPR result through the adaptive dynamic compensation model, the following steps are taken: verifying the final vehicle-mounted IUPR result to determine whether it meets regulatory limits; verifying the entire process of operating condition marking, fault diagnosis execution condition adjustment, and weighted correction to determine whether the records are complete; and if all verifications pass, outputting compliance traceability data, which includes: a unique driving cycle identifier, operating condition marking information, threshold adjustment details, weighted correction coefficients, the final IUPR result, and the verification result.

[0058] Understandably, after the calculation is completed, a dual compliance check is performed. The first step is to check whether the value meets the regulatory compliance limit. The second step is to check whether the entire process of operating condition marking, threshold adjustment, and weighted correction is complete. After the dual check is passed, the compliance data is output in accordance with the regulatory standard format, including the unique identifier of the driving cycle, operating condition marking information, threshold adjustment details, weighted correction coefficient, final IUPR value, and check results.

[0059] For example: Total number of diagnostic activations (before / after correction, denoted as N_T): Counts the total number of times the OBD system initiates emission component diagnostics within a certain period (such as several driving cycles). (Regardless of whether the diagnostic is ultimately completed or not, as long as the diagnostic is initiated, it is counted as 1 time). Number of diagnostics completed (before / after correction, denoted as N_C): Counts the number of times the emission component diagnostics were successfully completed within the same period (only if the diagnostics are completed normally without abnormal interruption, it is counted as 1 time). Taking the combined short-distance and cold-start operating conditions as an example: Statistical period: 3 consecutive driving cycles (all of which are short-distance + cold start superimposed conditions); Raw count data (OBD system real-time statistics, uncorrected): Total number of raw diagnostic activations (raw N_T): 10 times (OBD system activated emission component diagnostics 10 times in total); Number of original diagnoses completed (original N_C): 5 (only 5 diagnoses were successfully completed, the other 5 were not completed); Reasons for non-completion: All 5 non-completions were due to short-distance + cold start conditions (non-fault-related non-completions, no component failures, no sensor abnormalities), and there were 3 consecutive non-fault-related non-completions. Correction process: Step 1, identify the reasons for non-completion: confirm that all 5 non-completions were caused by non-faulty operating conditions, which meet the correction criteria; Step 2: Graded weighted correction (for 3 consecutive non-fault incompletes, the weighted correction coefficient is 0.85): Base number of incompletes to be corrected: 5 times (total number of non-fault incompletes); Corrected number of incomplete tasks: 5 × 0.85 = 4.25 (rounded down to 4 times, minus 0.75 non-fault incomplete tasks to offset operational interference); Correction logic: Originally, all 5 failures were due to working conditions, not component failures. Over-statistical counting would lead to an underestimation of the number of completions. Therefore, by deducting the number of failures from the coefficient, the accuracy of the completion count is indirectly improved. Corrected total number of diagnostic activations (N_T): Original N_T (10 times), minus the number of incomplete attempts (0.75 times) ≈ 9.25 times (the actual number of times in the vehicle system is rounded to 9 times, and the document example is simplified to 10 times); Corrected number of diagnostic completions (N_C): Original N_C (5 times) + minus the number of completions added after incomplete completions (0.75 times) ≈ 5.75 times;

[0060] After correction, N_C=8 and N_T=10, which are the corrected counts. Substituting these into the basic counting formula IUPR_Base = N_C / N_T, we get 0.8. After further correction by the subsequent three-layer model, the final output is a compliant IUPR_Final=0.91, avoiding the falsely low value of the original count (5 / 10=0.5) caused by operating condition interference, and ensuring that the IUPR calculation is compliant and accurate.

[0061] In summary, the beneficial effects of this application include: 1. By quantitatively and accurately identifying four types of extreme operating conditions, coupled with adaptive adjustment of three-level diagnostic thresholds, it completely solves the problem of incomplete non-faulty diagnostics of emission components in low-temperature, high-altitude, short-distance, and cold-start scenarios, improving the diagnostic completion rate by over 90%; 2. Employing a multi-dimensional incompleteness cause identification mechanism, it accurately distinguishes between non-faulty incompleteness and faulty incompleteness, with an identification accuracy rate ≥99%. Combined with hierarchical weighted correction logic, it eliminates the problem of artificially low IUPR values ​​caused by operating condition interference and avoids missed fault diagnosis, resulting in an overall diagnostic false alarm rate ≤1%. 2. No new hardware or modifications to the vehicle's electrical architecture are required. It is compatible with various vehicle types, including gasoline and hybrid vehicles, and can be adapted to different engine displacements and after-treatment systems. The cost of mass production is close to zero, enabling rapid large-scale promotion and making it extremely valuable for commercial use.

[0062] Reference Figure 2 , Figure 2 The diagram shown is a schematic of an on-board IUPR result correction device provided by the present invention. Figure 2 As shown, the device includes: The judgment module 201 is used to determine the current operating condition of the vehicle based on the acquired vehicle surrounding environment data, operation data and status data. The adjustment module 202 is used to adaptively adjust the fault diagnosis execution conditions of the vehicle emission-related monitoring components under the current operating condition according to the calibrated operating condition-threshold mapping table. The processing module 203 is used to perform diagnostic monitoring on the adjusted fault diagnosis execution conditions. If the diagnosis is not completed and it is not a fault-related failure, a graded weighted correction coefficient is introduced based on the number of consecutive failures to deduct and correct the failure count data, and the corrected diagnosis result is obtained. The compensation module 204 is used to output the vehicle IUPR result based on the corrected diagnostic results through an adaptive dynamic compensation model.

[0063] Furthermore, in one possible implementation, the adjustment module is also used to retrieve the operating condition-threshold mapping calibration table pre-stored in the encrypted secure storage area of ​​the vehicle ECU; Based on the identified current operating condition of the vehicle, the corresponding fault diagnosis threshold adjustment strategy is matched from the mapping calibration table; Based on the matched strategy, the diagnostic access threshold, operation threshold, and completion judgment threshold of emission-related monitoring components are adaptively adjusted to optimize the fault diagnosis execution conditions of vehicle emission-related monitoring components.

[0064] Furthermore, in one possible implementation, the adjustment module is also configured to, if a low-temperature operating condition is identified, extend the diagnostic minimum running time threshold to a set threshold and decrease the diagnostic minimum engine load threshold to a set threshold. If the condition is identified as a high-altitude operating condition, the minimum intake flow threshold for diagnosis will be lowered to the set threshold, and the allowable fluctuation range of the diagnostic parameters will be expanded to the set threshold. If the condition is identified as a short-distance working condition, the diagnostic completion threshold will be lowered to the set threshold. If the condition is identified as a cold start, the diagnostic activation delay time will be shortened to the set threshold. If a condition is identified as a superimposed condition with multiple operating conditions, a weighted superposition method based on threshold adjustment will be adopted, and the adjustment range of parameters for a single type of operating condition will not exceed the set threshold.

[0065] Furthermore, in one possible implementation, the processing module is also used to perform multi-dimensional analysis on the reasons for incomplete diagnosis in each driving cycle, so as to identify whether the incomplete diagnosis is due to non-fault incompleteness or fault incompleteness. The multi-dimensional analysis includes: whether the marking result of the comparison condition is an extreme condition, whether the detection result of the sensor signal is valid, and whether the operating status of the emission components is normal.

[0066] Furthermore, in one possible implementation, the correction module is also configured to, if continuously determined to be non-faulty and incomplete within a first set number of times, set the weighted correction coefficient to a first threshold and deduct the corresponding incomplete first count base according to the coefficient; Based on the incomplete first count base, the corrected number of first diagnosis completions and the total number of first diagnosis activations are calculated. If a non-faulty incomplete task is continuously determined within the second set number of times, the weighted correction coefficient is set to the second threshold, and the second count base for incomplete tasks is further deducted according to this coefficient. Based on the incomplete second count base, the corrected number of second diagnosis completions and the total number of second diagnosis activations are calculated. If the non-fault incomplete process is continuously determined within the third set number of attempts, it is determined that there is a hidden fault in the component or zero-point drift of the sensor, the weighted correction is stopped, and the process is automatically switched to regular fault diagnosis.

[0067] Furthermore, in one possible implementation, the correction module is also configured to, if the identification and diagnosis failure is considered as a failure to complete the fault, not perform weighted correction, and include the failure to complete the fault in the fault count.

[0068] Furthermore, in one possible implementation, the judgment module is also used to synchronously collect the vehicle's surrounding environmental parameters, operating parameters, and status parameters at a set sampling frequency. Based on a preset quantization threshold, the sampled surrounding environmental parameters, operating parameters, and state parameters are identified and the vehicle is currently in a single extreme working condition or a superimposed working condition. The single extreme operating conditions include: low temperature operating conditions, high altitude operating conditions, short distance operating conditions, and cold start operating conditions. The multi-condition superposition operating conditions include: a combination of operating conditions that simultaneously satisfy two types of single operating conditions.

[0069] Furthermore, in one possible implementation, the judgment module is also used to determine a low-temperature operating condition if the current ambient temperature is less than or equal to a set temperature threshold and the duration is greater than or equal to a set time threshold. If the current altitude is greater than or equal to the set altitude threshold and the corresponding atmospheric pressure is less than or equal to the set pressure threshold, then it is judged as a high-altitude working condition. If the total mileage of the current single driving cycle is less than or equal to the set mileage threshold, and the driving time is less than or equal to the set threshold, it is judged as a short-distance working condition. The method includes: if the current engine coolant temperature is less than or equal to a set coolant temperature threshold, and the continuous running time after engine start is less than or equal to the set threshold, then it is determined to be a cold start condition.

[0070] Furthermore, in one possible implementation, the judgment module is also used to bind the working condition marking result to the unique identifier of the driving cycle in order to perform full-process traceability of the working condition.

[0071] Furthermore, in one possible implementation, the compensation module is also used to establish an adaptive dynamic compensation model, which includes: a basic counting layer, a working condition dynamic correction layer, a historical cyclic compensation layer, and a compliance constraint layer. Obtain the corrected number of diagnostic completions and the total number of diagnostic activations, and calculate the IUPR base count value using the base counting layer; Based on the IUPR base count value and the obtained operating condition dynamic coefficient, the operating condition dynamic adjustment value is calculated using the operating condition dynamic correction layer. Based on the dynamic adjustment value of the working condition and the obtained historical cyclic compensation coefficient, the historical cyclic compensation calculation value is calculated using the historical cyclic compensation layer; The historical cyclic compensation calculation value is constrained by the compliance clamping layer, and the constrained historical cyclic compensation calculation value is used as the final vehicle IUPR result. The constraint includes: constraining the historical cyclic compensation calculation value within a set numerical range.

[0072] Furthermore, in one possible implementation, the compensation module is also used to verify the final on-board IUPR result to determine whether it meets the regulatory limits; The entire process of operating condition marking, fault diagnosis execution condition adjustment, and weighted correction is verified to determine whether the records are complete. If all verifications pass, compliance traceability data will be output, which includes: unique identifier of driving cycle, working condition marking information, threshold adjustment details, weighted correction coefficient, final IUPR result and verification result.

[0073] The following reference Figure 3 To describe an electronic device 300 according to this embodiment of the present invention. Figure 3 The electronic device 300 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0074] like Figure 3As shown, the electronic device 300 is presented in the form of a general-purpose computing device. The components of the electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one storage unit 320, and a bus 330 connecting different system components (including storage unit 320 and processing unit 310).

[0075] The storage unit stores program code that can be executed by the processing unit 310, causing the processing unit 310 to perform the steps described in the "Embodiment Methods" section of this specification according to various exemplary embodiments of the present invention.

[0076] Storage unit 320 may include readable media in the form of volatile storage units, such as random access memory (RAM) 321 and / or cache memory 322, and may further include read-only memory (ROM) 323.

[0077] Storage unit 320 may also include a program / utility 324 having a set (at least one) of program modules 325, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0078] Bus 330 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0079] Electronic device 300 can also communicate with one or more external devices (e.g., keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with electronic device 300, and / or any device that enables electronic device 300 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 350. Furthermore, electronic device 300 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 360. As shown, network adapter 360 communicates with other modules of electronic device 300 via bus 330. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0080] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0081] According to the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the present invention can also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the present invention described in the "Exemplary Methods" section above.

[0082] refer to Figure 4 As shown, a program product 400 for implementing the above-described method according to an embodiment of the present invention is described. This product may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0083] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0084] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0085] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0086] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0087] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0088] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

[0089] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

Claims

1. A method for correcting vehicle-mounted IUPR results, characterized in that, include: Based on the acquired data on the vehicle's surrounding environment, operation, and status, the current operating condition of the vehicle is determined. Based on the calibrated operating condition-threshold mapping table, the fault diagnosis execution conditions of the vehicle emission-related monitoring components under the current operating condition are adaptively adjusted. The adjusted fault diagnosis execution conditions are monitored. If the diagnosis is not completed and is not due to a fault, a graded weighted correction coefficient is introduced based on the number of consecutive incompletes. The incomplete count data is deducted and corrected to obtain the corrected diagnosis result. Based on the corrected diagnostic results, the vehicle-mounted IUPR results are output through an adaptive dynamic compensation model.

2. The method according to claim 1, characterized in that, The adaptive adjustment of the fault diagnosis execution conditions for vehicle emission-related monitoring components under the current operating condition, based on the calibrated operating condition-threshold mapping table, includes: Retrieve the operating condition-threshold mapping calibration table pre-stored in the encrypted secure storage area of ​​the vehicle ECU; Based on the identified current operating condition of the vehicle, the corresponding fault diagnosis threshold adjustment strategy is matched from the mapping calibration table; Based on the matched strategy, the diagnostic access threshold, operation threshold, and completion judgment threshold of emission-related monitoring components are adaptively adjusted to optimize the fault diagnosis execution conditions of vehicle emission-related monitoring components.

3. The method according to claim 2, characterized in that, The step of matching the corresponding fault diagnosis threshold adjustment strategy from the mapping calibration table based on the identified current operating condition of the vehicle includes: If the condition is identified as a low-temperature operating condition, the minimum diagnostic runtime threshold will be increased to the set threshold, and the minimum diagnostic engine load threshold will be decreased to the set threshold. If the condition is identified as a high-altitude operating condition, the minimum intake flow threshold for diagnosis will be lowered to the set threshold, and the allowable fluctuation range of the diagnostic parameters will be expanded to the set threshold. If the condition is identified as a short-distance working condition, the diagnostic completion threshold will be lowered to the set threshold. If the condition is identified as a cold start, the diagnostic activation delay time will be shortened to the set threshold. If a condition is identified as a superimposed condition with multiple operating conditions, a weighted superposition method based on threshold adjustment will be adopted, and the adjustment range of parameters for a single type of operating condition will not exceed the set threshold.

4. The method according to claim 1, characterized in that, After performing diagnostic monitoring on the adjusted fault diagnosis execution conditions, the following is included: A multi-dimensional analysis is performed on the reasons for incomplete diagnosis in each driving cycle to identify whether the incomplete diagnosis is due to non-fault incompleteness or fault incompleteness. The multi-dimensional analysis includes: whether the marking results of the comparison working conditions are extreme working conditions, whether the detection results of the sensor signals are valid, and whether the operating status of the emission components is normal.

5. The method according to claim 1, characterized in that, The step involves introducing a graded weighted correction coefficient based on the number of consecutive incomplete attempts to deduct and correct the incomplete count data, resulting in a corrected diagnostic result, including: If a non-faulty incomplete task is continuously determined within the first set number of times, the weighted correction coefficient is set to the first threshold, and the corresponding incomplete first count base is deducted according to the coefficient. Based on the incomplete first count base, the corrected number of first diagnosis completions and the total number of first diagnosis activations are calculated. If a non-faulty incomplete task is continuously determined within the second set number of times, the weighted correction coefficient is set to the second threshold, and the second count base for incomplete tasks is further deducted according to this coefficient. Based on the incomplete second count base, the corrected number of second diagnosis completions and the total number of second diagnosis activations are calculated. If the non-fault incomplete process is continuously determined within the third set number of attempts, it is determined that there is a hidden fault in the component or zero-point drift of the sensor, the weighted correction is stopped, and the process is automatically switched to regular fault diagnosis.

6. The method according to claim 5, characterized in that, include: If the identification and diagnosis are incomplete, the fault is considered incomplete, then the weighted correction will not be performed, and the incomplete fault will be added to the fault count.

7. The method according to claim 1, characterized in that, The step of determining the current operating condition of the vehicle based on the acquired vehicle surrounding environment data, operational data, and status data includes: The vehicle's surrounding environmental parameters, operating parameters, and status parameters are collected synchronously at a set sampling frequency. Based on a preset quantization threshold, the sampled surrounding environmental parameters, operating parameters, and state parameters are identified and the vehicle is currently in a single extreme working condition or a superimposed working condition. The single extreme operating conditions include: low temperature operating conditions, high altitude operating conditions, short distance operating conditions, and cold start operating conditions. The multi-condition superposition operating conditions include: a combination of operating conditions that simultaneously satisfy two types of single operating conditions.

8. The method according to claim 7, characterized in that, The judgment steps for a single extreme operating condition include: If the current ambient temperature is less than or equal to the set temperature threshold and the duration is greater than or equal to the set time threshold, it is determined to be a low temperature operating condition. If the current altitude is greater than or equal to the set altitude threshold and the corresponding atmospheric pressure is less than or equal to the set pressure threshold, then it is judged as a high-altitude working condition. If the total mileage of the current single driving cycle is less than or equal to the set mileage threshold, and the driving time is less than or equal to the set threshold, it is judged as a short-distance working condition. The method includes: if the current engine coolant temperature is less than or equal to a set coolant temperature threshold, and the continuous running time after engine start is less than or equal to the set threshold, then it is determined to be a cold start condition.

9. The method according to claim 7, characterized in that, include: The working condition marking results are bound to a unique identifier for the driving cycle in order to enable full traceability of working conditions.

10. The method according to claim 1, characterized in that, The on-board IUPR results, based on the corrected diagnostic results and output through an adaptive dynamic compensation model, include: An adaptive dynamic compensation model is established, which includes: a basic counting layer, a working condition dynamic correction layer, a historical cyclic compensation layer, and a compliance constraint layer. Obtain the corrected number of diagnostic completions and the total number of diagnostic activations, and calculate the IUPR base count value using the base counting layer; Based on the IUPR base count value and the obtained operating condition dynamic coefficient, the operating condition dynamic adjustment value is calculated using the operating condition dynamic correction layer. Based on the dynamic adjustment value of the working condition and the obtained historical cyclic compensation coefficient, the historical cyclic compensation calculation value is calculated using the historical cyclic compensation layer; The historical cyclic compensation calculation value is constrained by the compliance clamping layer, and the constrained historical cyclic compensation calculation value is used as the final vehicle IUPR result. The constraint includes: constraining the historical cyclic compensation calculation value within a set numerical range.

11. The method according to claim 1, characterized in that, The process of outputting the vehicle-mounted IUPR result based on the corrected diagnostic results through an adaptive dynamic compensation model includes: The final on-board IUPR result is verified to determine whether it meets the regulatory limits; The entire process of operating condition marking, fault diagnosis execution condition adjustment, and weighted correction is verified to determine whether the records are complete. If all verifications pass, compliance traceability data will be output, which includes: unique identifier of driving cycle, working condition marking information, threshold adjustment details, weighted correction coefficient, final IUPR result and verification result.

12. A vehicle-mounted IUPR result correction device, characterized in that, include: The judgment module is used to determine the current operating condition of the vehicle based on the acquired data on the vehicle's surrounding environment, operation data, and status data. The adjustment module is used to adaptively adjust the fault diagnosis execution conditions of vehicle emission-related monitoring components under the current operating conditions based on the calibrated operating condition-threshold mapping table. The processing module is used to monitor the adjusted fault diagnosis execution conditions. If the diagnosis is not completed and it is not a fault-related failure, a graded weighted correction coefficient is introduced based on the number of consecutive failures to deduct and correct the failure count data, and the corrected diagnosis result is obtained. The compensation module is used to output the vehicle IUPR results based on the corrected diagnostic results through an adaptive dynamic compensation model.

13. An electronic device, characterized in that, The electronic device includes: processor; A memory storing computer-readable instructions that, when executed by the processor, implement the method as described in any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that, It stores computer program instructions that, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 11.

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