Vehicle DPF fault processing method and system

Abstract

The invention discloses a vehicle DPF fault processing method and system.The method comprises the steps that when an Internet of Vehicles platform detects a vehicle DPF blockage fault, fuel oil data in vehicle data received in real time are analyzed through the Internet of Vehicles platform to determine whether the vehicle DPF blockage fault is caused by user behaviors or not; if a non-user behavior causes a vehicle DPF blockage fault, analyzing driving data in the vehicle data, and determining whether the vehicle DPF blockage fault is caused by an operation scene or not; and the service platform receives the fault judgment result sent by the Internet of Vehicles platform, and carries out corresponding processing flows according to different fault reasons. According to the invention, the method can achieve the quick and effective processing of faults, reduces the occurrence of problems, improves the user experience, can improve the working efficiency, and reduces the cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of engine emissions, in particular to a vehicle DPF fault processing method and system. BACKGROUND

[0002] The diesel particulate filter (DPF) is an important part of the modern diesel engine vehicle emission control system, which is used to reduce particulate matter (PM) in diesel engine emissions. During vehicle operation, due to operating cost oil products and urea quality, DPF clogging limits torque. Short distance driving, long time low speed (1000 revolutions or so) work causes DPF parking regeneration frequent failure, and users complain.

[0003] Therefore, how to accurately classify when DPF fault occurs, and perform corresponding fault processing according to different fault categories, to realize rapid and effective processing of faults and improve user experience. SUMMARY

[0004] The main purpose of the present application is to provide a vehicle DPF fault processing method and system, which can realize rapid and effective processing of faults, reduce problems, improve user experience, and also improve work efficiency and reduce cost.

[0005] In a first aspect, the present application provides a vehicle DPF fault processing method, wherein the method comprises the following steps: when the vehicle internet platform detects a vehicle DPF clogging fault, analyzing fuel data in real-time received vehicle data through the vehicle internet platform to determine whether the vehicle DPF clogging fault is caused by user behavior; If the vehicle DPF clogging fault is not caused by user behavior, analyze the driving data in the vehicle data to determine whether the vehicle DPF clogging fault is caused by the running scene; The service platform receives the fault judgment result sent by the vehicle internet platform, and performs corresponding processing process according to different fault reasons.

[0006] In combination with the above first aspect, as an optional implementation manner, the refueling change value, urea liquid level change value, urea to fuel consumption ratio and fuel water data in the vehicle data are analyzed based on the received vehicle data to determine whether unqualified oil products, urea or parking regeneration is not performed according to the prompt; If so, it is determined that the vehicle DPF clogging fault is caused by user behavior.

[0007] In conjunction with the first aspect above, as an optional implementation, the retrieved vehicle driving data from the vehicle data is analyzed to determine whether the vehicle is in a set speed range and / or less than a set driving distance, wherein the driving data includes: idling time, mileage, urea to fuel consumption ratio, number of driving regenerations, DPF failure frequency, regeneration interval, original exhaust, common speed range, common speed range, and operating route; If so, it is determined that the vehicle DPF is blocked due to the operating scenario.

[0008] In combination with the first aspect above, as an optional implementation, if it is determined that the vehicle DPF blockage fault is caused by the user's walking, the user is reminded through different reminder methods; If it is determined that the vehicle DPF blockage fault is caused by the operating scenario, the engine operating speed is increased to the target speed and the parking regeneration time is extended to the target time.

[0009] In conjunction with the first aspect above, as an optional implementation method, the accuracy of the vehicle exhaust temperature thermal management system and the carbon load model is optimized to achieve successful on-the-road regeneration; The exhaust temperature thermal management system optimization includes: controlling the engine exhaust temperature to be greater than or equal to a first set temperature, controlling the driving regeneration temperature to be greater than or equal to a second set temperature, and controlling the regeneration efficiency to be greater than or equal to a set threshold; The accuracy optimization of the carbon load model includes: performing actual data calibration by controlling the engine speed, throttle opening and fuel injection amount during driving regeneration, so that the carbon model error is within a set range to achieve successful vehicle regeneration.

[0010] In combination with the first aspect above, as an optional implementation method, remote upgrade is performed through the OTA system based on the data after the optimization is completed.

[0011] In combination with the first aspect above, as an optional implementation method, it is determined whether the carbon load of this parking regeneration reaches the limit according to the DPF regeneration carbon load limit table; If the limit is reached, the vehicle DPF is determined to be blocked and the user is notified to perform a parking regeneration operation.

[0012] In a second aspect, the present application provides a vehicle DPF fault handling system, the system comprising: The vehicle networking platform is used to analyze fuel data in real-time vehicle data when a vehicle DPF blockage fault is detected to determine whether the vehicle DPF blockage fault is caused by user behavior; If the vehicle DPF clogging fault is not caused by user behavior, the driving data in the vehicle data is analyzed to determine whether the vehicle DPF clogging fault is caused by the operating scenario; a service platform configured to receive the fault judgment result sent by the vehicle networking platform and perform a corresponding processing procedure according to different fault causes.

[0013] With reference to the second aspect above, as an optional implementation manner, the service platform is further configured to, if the vehicle DPF clogging fault is determined to be caused by user behavior, remind the user through different reminding manners. If the vehicle DPF clogging fault is determined to be caused by a running scenario, the engine working speed is increased to a target speed, and the parking regeneration time is prolonged to a target time length.

[0014] With reference to the second aspect above, as an optional implementation manner, the vehicle networking platform is further configured to determine whether the carbon load of this parking regeneration reaches a limit value according to a DPF regeneration carbon load limit value table. If the limit value is reached, the vehicle DPF clogging fault is determined, and the user is notified to perform a parking regeneration operation.

[0015] The vehicle DPF fault processing method and system provided in the application, wherein the method comprises the following steps: when the vehicle networking platform detects a vehicle DPF clogging fault, the vehicle networking platform analyzes fuel data in real-time received vehicle data to determine whether the vehicle DPF clogging fault is caused by user behavior; if the vehicle DPF clogging fault is not caused by user behavior, driving data in the vehicle data is analyzed to determine whether the vehicle DPF clogging fault is caused by a running scenario; a service platform receives the fault judgment result sent by the vehicle networking platform and performs a corresponding processing procedure according to different fault causes. The application can realize rapid and effective processing of faults, reduce problems, improve user experience, and also improve work efficiency and reduce costs.

[0016] It should be understood that the foregoing general description and the following detailed description are only exemplary and do not limit the application. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the application and, together with the description, serve to explain the principles of the application.

[0018] Figure 1 A vehicle DPF fault processing method flowchart provided in the embodiments of the application; Figure 2 A vehicle DPF fault processing system schematic diagram provided in the embodiments of the application. DETAILED DESCRIPTION

[0019] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0020] Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Some of the blocks shown in the drawings are functional entities that do not necessarily correspond to physically or logically separate entities.

[0021] The embodiments of the present application are further described in detail below with reference to the accompanying drawings.

[0022] Reference Figure 1 , Figure 1 The figure shows a flow chart of a vehicle DPF fault processing method provided by the present invention, as shown in FIG. Figure 1 As shown, the method includes the steps of: Step S101: When the vehicle networking platform detects a vehicle DPF blockage fault, the vehicle networking platform analyzes the fuel data in the real-time vehicle data received to determine whether the vehicle DPF blockage fault is caused by user behavior.

[0023] Specifically, the DPF regeneration carbon load limit table determines whether the carbon load for this parking regeneration has reached the limit. If so, the vehicle's DPF is deemed to be blocked, and the user is notified to perform a parking regeneration. It should be noted that if the carbon load reaches the limit, and the parking regeneration cycle is not greater than or equal to 200 hours or 1200 kilometers—for example, if the parking regeneration cycle is 70-150 hours or less than 800 kilometers—a blocking fault is considered present. At this point, it is necessary to determine whether the fault is caused by user behavior (such as filling with substandard fuel or urea, or failing to perform parking regeneration as prompted) or the operating scenario (low speed, short distance). In one embodiment, the parking regeneration cycle is greater than or equal to 200 hours or 1200 kilometers. This serves as the criterion for determining whether manual intervention is necessary. If the limit is exceeded, manual intervention is not required; if it is not, intervention is required.

[0024] In one embodiment, when the parking regeneration cycle is 70-150 hours or less than 800 kilometers, the vehicle's refueling point and the urea to fuel consumption ratio are determined to be between 7% and 10%. If the conditions are met, the vehicle's low idle operation duration, operation trajectory, and idle mileage are determined.

[0025] That is to say, when the limit value is detected and the regeneration cycle is less than 200h or 1200km, the refueling change value, urea liquid level change value, urea to fuel consumption ratio and fuel water inflow data retrieved from the vehicle data are analyzed based on the received vehicle data to determine whether unqualified oil or urea is added or parking regeneration is not performed as prompted; if so, it is determined that the vehicle DPF blockage fault is caused by user behavior. Specifically, when the IoV system receives a report of a DPF blockage failure from a vehicle, it retrieves and analyzes the regeneration data for the past year after the vehicle's sale to determine whether the time interval between driving and parked regenerations and whether the parking interval is greater than or equal to 200 hours or 1200 kilometers. If the ratio of the vehicle's driving regeneration times to the number of parked regenerations is greater than 1.5 and the parked regeneration time interval is between 150-190 hours or 800-1000 kilometers, the system determines whether the carbon load of this parked regeneration has reached the limit based on the DPF regeneration carbon load limit table. If so, the user is notified to perform a parked regeneration operation (if the carbon load has reached the limit, regeneration is required to burn off the carbon deposits so that the engine can return to normal speed. Ensure that the user's vehicle is used first to buy time for data analysis or on-site operation). The system also retrieves the vehicle's one-year refueling change values, urea level change values, urea to fuel consumption ratio, fuel water ingress failures, and uses a data model to calculate whether substandard oil or urea was added, or whether parked regeneration was not performed as prompted. The results are output to the service system for user reminders and care.

[0026] Optionally, the connected vehicle platform detects DPF fault torque limits and conducts regeneration fault inquiries, time period analysis, driving regeneration time and interval analysis, parked regeneration frequency and interval analysis, and fuel water ingress fault and refueling point analysis within a time period to determine whether frequent DPF failures are caused by substandard fuel. This information is then fed back to the service system, which then conducts a user revisit and informs the user of the failure, refueling, and regeneration frequency, verifying the customer's intentions: 1. User willingness to receive usage reminders; 2. Promote fuel product care activities and refueling point recommendations. It is understood that the retrieved data is analyzed to determine whether DPF failures are caused by user behavior.

[0027] In one embodiment, when the parking regeneration cycle is 70-150 hours or less than 800 kilometers, the vehicle's refueling point and the urea to fuel consumption ratio are determined to be between 7% and 10%. If the conditions are met, the vehicle's low idle operation duration, operation trajectory, and idle mileage are determined.

[0028] When the parking regeneration cycle 150-190h or 800-1000Km, the priority is to determine whether the vehicle refueling point and the urea and fuel consumption ratio are in 7%-10% whether to meet (query this vehicle 3 months urea concentration change and urea amount and fuel consumption ratio, this is the consumption ratio is whether the engine is normal exhaust treatment. Urea concentration is normal, fuel ratio is normal, no fault of engine high sulfur content, task is not user reason), not meet guide user regeneration operation (including teach user see DPF fault, etc., tell the user to need to carry out parking regeneration, away from gas station, flammable and explosive goods, start the engine on the spot press the parking regeneration switch and wait for the DPF lamp to go out).

[0029] It should be noted that the DPF fault blockage fault directly affects whether the vehicle emission meets the regulatory requirements, the DPF blockage fault trigger reason 1, the DPF pressure difference sensor gas pipeline blockage. 2, DPF carbon load is too large without regeneration (DPF regeneration is divided into passive regeneration, driving active regeneration and parking active regeneration, service regeneration, to ensure the effective operation of the entire exhaust aftertreatment system) 3, DPF blockage. It can be understood that the reason of DPF is comprehensive, the user adds inferior oil and urea, or does not add urea, or the low speed and short distance operation caused by working condition, we realize it through improving the engine driving regeneration strategy.

[0030] The system determines whether the user needs to perform regeneration operation according to the data and DPF regeneration carbon load, and reminds the user to perform vehicle parking regeneration operation through the service system 400 or the mobile phone APP.

[0031] Step S102: If the vehicle DPF blockage fault is caused by non-user behavior, analyze the driving data in the vehicle data to determine whether the vehicle DPF blockage fault is caused by the running scene.

[0032] In an embodiment, if it is determined that the fault is not caused by user behavior, the vehicle data is analyzed to determine whether the vehicle is in a set speed interval and / or less than a set driving distance, wherein the driving data includes: idle running time, mileage, urea and fuel consumption ratio, driving regeneration frequency, DPF fault frequency, regeneration interval time, original exhaust, commonly used speed interval, commonly used speed interval, operation route; if so, it is determined that the vehicle DPF clogging fault is caused by the operation scenario. Specifically, when the vehicle network system receives the DPF clogging fault reported by the vehicle, the regeneration data of the vehicle sold in the past year is analyzed to determine the time interval of driving regeneration and parking regeneration and whether the parking is in 70-150h or less than 800Km, and then the user reason process is judged to check the user reason. After checking the user reason, the idle running time, single section mileage, total mileage, urea and fuel consumption ratio, driving regeneration frequency, user regeneration interval time, original exhaust, commonly used speed interval, commonly used speed interval, operation route and other data of the vehicle sold in the past year are analyzed to determine whether the vehicle is in a fixed road section and a low-speed operation scenario. When it is determined that the fault is caused by the scenario, the commonly used road section data of the vehicle is analyzed to complete the optimization of the regeneration model and improve the success rate of driving regeneration.

[0033] Optionally, the vehicle network platform detects the DPF fault limit torque, performs regeneration fault query, time period analysis, driving regeneration frequency and interval time analysis, parking regeneration frequency and interval time analysis, parking regeneration frequency and interval time analysis, fuel water fault and refueling point analysis in the time period, processing query record, vehicle running mileage, running time, load, route, engine data analysis, scene reproduction real vehicle verification program optimization verification, vehicle type and scene data storage, basic program database, to determine whether the fault is caused by the operation scenario. If so, the engine operating speed is increased to the target speed, and the parking regeneration time is extended to the target time length. That is, the data analysis is indeed for the scenario, the engine data is upgraded, the working idle speed is increased, the aftertreatment exhaust temperature is increased, and the vehicle is burned to remove part of the carbon deposit during operation, to extend the parking regeneration time.

[0034] Specifically, the accuracy of the vehicle exhaust temperature thermal management system and the carbon load model is optimized to realize the success of driving regeneration; wherein the exhaust temperature thermal management system optimization includes: controlling the engine exhaust temperature to be greater than or equal to a first set temperature, controlling the driving regeneration temperature to be greater than or equal to a second set temperature, and controlling the regeneration efficiency to be greater than or equal to a set threshold; the accuracy optimization of the carbon load model includes: by controlling the engine speed, throttle opening and fuel injection amount during driving regeneration, the actual data is calibrated to make the carbon model error within a set range, to realize the success of vehicle regeneration. Based on the data after optimization, the OTA system is used for remote upgrade.

[0035] In one embodiment, 1. Exhaust temperature thermal management is improved: the engine exhaust temperature is raised to ≥300°C, the regeneration temperature during driving is ≥550°C, and regeneration efficiency is increased by ≥80%. 2. The carbon model accuracy is calibrated, with the model error controlled within ±15. This is achieved by calibrating actual data to ensure successful regeneration during driving, primarily by increasing engine speed, throttle opening, and fuel injection during driving. This achieves the target regeneration interval of 200 hours or 1200 kilometers.

[0036] After optimization is complete, data is remotely updated via the OTA system, and vehicle DPF data is continuously monitored to ensure the model optimization goals are met. Customers are then contacted via the service system to confirm the results. This data accumulation allows for continuous optimization of the connected car DPF travel regeneration strategy model.

[0037] In one embodiment, after a vehicle's passive regeneration, the DPF collects carbon particles, triggering a driving regeneration. A determination is made as to whether the driving regeneration was successful. If so, the DPF is confirmed to have recovered. If not, the parked regeneration indicator immediately illuminates. A determination is made again as to whether the parking regeneration was successful. If so, the DPF is confirmed to have recovered. If not, the DPF overload indicator immediately illuminates. The parking regeneration is then determined to be successful again. If so, the DPF is confirmed to have recovered. If not, the DPF overload indicator illuminates, the parking regeneration stops, and manual intervention is performed to determine whether the regeneration was successful. If still unsuccessful, the DPF has failed. Otherwise, the DPF is restored. This approach can reduce the frequency of parking regeneration and ensure successful driving regeneration. It should be noted that passive regeneration conditions include: exhaust temperature greater than or equal to 200°C (higher temperatures increase regeneration efficiency); greater exhaust flow rate increases regeneration efficiency; and greater nitrogen dioxide concentration increases regeneration efficiency. Driving regeneration conditions include: carbon load or mileage reaching a limit; vehicle speed or throttle not reaching zero; and coolant temperature reaching a limit. The parking regeneration triggering conditions include: the carbon model reaches the calibration value; the vehicle speed is 0; the accelerator pedal is not pressed; the brake pedal is not pressed; the gear is in neutral.

[0038] Step S103: The service platform receives the fault judgment result sent by the Internet of Vehicles platform and performs corresponding processing according to different fault causes.

[0039] Specifically, if it is determined that the vehicle DPF blockage failure is caused by the user's behavior, the user will be reminded through different reminder methods; if it is determined that the vehicle DPF blockage failure is caused by the operating scenario, the engine operating speed will be increased to the target speed, and the parking regeneration time will be extended to the target time.

[0040] To sum up, this application can reduce vehicle failures and reasonably handle problems with minimal manpower costs, reduce a large number of on-site services, analyze failures through data from the Internet of Vehicles, and provide service action guidance in different scenarios, greatly improving service efficiency and reducing enterprise costs.

[0041] Reference Figure 2 , Figure 2 The figure shows a schematic diagram of a vehicle DPF fault processing system provided by the present invention, as shown in FIG. Figure 2 As shown, the system includes: Internet of Vehicles Platform 201: When a vehicle DPF clogging fault is detected, it analyzes the fuel data in the real-time vehicle data received to determine whether the vehicle DPF clogging fault is caused by user behavior; If the vehicle DPF blockage failure is not caused by user behavior, the driving data in the vehicle data is analyzed to determine whether the vehicle DPF blockage failure is caused by the operating scenario.

[0042] Service platform 202: It is used to receive the fault judgment results sent by the Internet of Vehicles platform and perform corresponding processing procedures according to different fault causes.

[0043] As shown in the figure, the connected vehicle system primarily functions as follows: vehicle location information, real-time vehicle fault collection, vehicle driving trajectory analysis, DPF regeneration time, engine runtime, start data version, fault count, fuel level changes, refueling point marking, DPF optimization data model, and other functions and vehicle data analysis. Real-time vehicle data reporting relies on the in-cab T-BOX, primarily used for the transmission and exchange of vehicle data (longitude and latitude, fault information, fuel level, mileage, engine data, software version number, and other real-time vehicle data). The OTA system is primarily used for remote data upgrades for vehicles requiring data optimization, enabling remote vehicle upgrades. The service system is used for troubleshooting when a fault occurs, implementing different troubleshooting processes based on the cause to achieve a fast and effective fault handling mechanism.

[0044] Furthermore, in one possible embodiment, the vehicle networking platform is further configured to analyze, based on the received vehicle data, refueling change values, urea level change values, urea-to-fuel consumption ratio, and fuel-water influx data retrieved from the vehicle data to determine whether unqualified fuel or urea was refilled or parking regeneration was not performed as prompted; If so, it is determined that the vehicle DPF blockage fault is caused by user behavior.

[0045] Furthermore, in a possible embodiment, the vehicle networking platform is further configured to analyze the retrieved vehicle driving data from the vehicle data to determine whether the vehicle is in a set speed range and / or less than a set driving distance, wherein the driving data includes: idling time, mileage, urea to fuel consumption ratio, number of driving regenerations, DPF failure frequency, regeneration interval, original exhaust, common speed range, common speed range, and operating route; If so, it is determined that the vehicle DPF is blocked due to the operating scenario.

[0046] Furthermore, in a possible implementation, the service platform is further configured to remind the user through different reminder methods if it is determined that the vehicle DPF blockage fault is caused by the user's behavior; If it is determined that the vehicle DPF blockage fault is caused by the operating scenario, the engine operating speed is increased to the target speed and the parking regeneration time is extended to the target time.

[0047] Furthermore, in a possible implementation, the service platform is also used to optimize the accuracy of the vehicle exhaust thermal management system and carbon load model to achieve successful on-the-go regeneration; The exhaust temperature thermal management system optimization includes: controlling the engine exhaust temperature to be greater than or equal to a first set temperature, controlling the driving regeneration temperature to be greater than or equal to a second set temperature, and controlling the regeneration efficiency to be greater than or equal to a set threshold; The accuracy optimization of the carbon load model includes: performing actual data calibration by controlling the engine speed, throttle opening and fuel injection amount during driving regeneration, so that the carbon model error is within a set range to achieve successful vehicle regeneration.

[0048] Furthermore, in a possible implementation, the service platform is also used to perform remote upgrades through an OTA system based on the data after the optimization is completed.

[0049] Furthermore, in a possible implementation, the vehicle networking platform is further configured to determine whether the carbon load of the current parking regeneration reaches the limit value according to the DPF regeneration carbon load limit value table; If the limit is reached, the vehicle DPF is determined to be blocked and the user is notified to perform a parking regeneration operation.

[0050] The foregoing is merely a list of specific embodiments of the present application, intended to enable those skilled in the art to understand or implement the present 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 the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the broadest scope consistent with the principles and novel features of the present application.

Claims

1. A vehicle DPF fault handling method, characterized in that: include: When the IoV platform detects a DPF blockage fault, it analyzes the fuel data in the real-time vehicle data received to determine whether the DPF blockage fault is caused by user behavior. If the vehicle DPF clogging fault is not caused by user behavior, the driving data in the vehicle data is analyzed to determine whether the vehicle DPF clogging fault is caused by the operating scenario; The service platform receives the fault judgment result sent by the Internet of Vehicles platform and performs corresponding processing procedures according to different fault causes.

2. The method according to claim 1, characterized in that The vehicle networking platform analyzes fuel data in real-time vehicle data to determine whether the vehicle DPF blockage fault is caused by user behavior, including: Based on the received vehicle data, analyzing the refueling change value, urea level change value, urea to fuel consumption ratio, and fuel water inflow data retrieved from the vehicle data to determine whether unqualified fuel or urea was refueled or whether parking regeneration was not performed as prompted; If so, it is determined that the vehicle DPF blockage fault is caused by user behavior.

3. The method according to claim 1, characterized in that The analyzing the operating data and engine data in the vehicle data to determine whether the vehicle DPF blockage fault is caused by the operating scenario includes: Analyzing the retrieved vehicle driving data from the vehicle data to determine whether the vehicle is in a set speed range and / or less than a set driving distance, wherein the driving data includes: idling time, mileage, urea to fuel consumption ratio, number of driving regenerations, DPF failure frequency, regeneration interval, original exhaust, common speed range, common speed range, and operating route; If so, it is determined that the vehicle DPF is blocked due to the operating scenario.

4. The method according to claim 1, wherein The corresponding processing flow is carried out according to different fault causes, including: If it is determined that the vehicle DPF blockage fault is caused by the user's behavior, the user will be reminded through different reminder methods; If it is determined that the vehicle DPF blockage fault is caused by the operating scenario, the engine operating speed is increased to the target speed and the parking regeneration time is extended to the target time.

5. The method according to claim 4, characterized in that Also includes: Optimize the accuracy of the vehicle's exhaust thermal management system and carbon load model to achieve successful on-the-go regeneration; The exhaust temperature thermal management system optimization includes: controlling the engine exhaust temperature to be greater than or equal to a first set temperature, controlling the driving regeneration temperature to be greater than or equal to a second set temperature, and controlling the regeneration efficiency to be greater than or equal to a set threshold; The accuracy optimization of the carbon load model includes: performing actual data calibration by controlling the engine speed, throttle opening and fuel injection amount during vehicle regeneration, so that the carbon model error is within a set range to achieve successful vehicle regeneration.

6. The method according to claim 5, characterized in that Also includes: Based on the data after optimization, remote upgrade is performed through the OTA system.

7. The method according to claim 1, characterized in that include: Determine whether the carbon load of this parking regeneration reaches the limit according to the DPF regeneration carbon load limit table; If the limit is reached, the vehicle DPF is determined to be blocked and the user is notified to perform a parking regeneration operation.

8. A vehicle DPF fault handling system, characterized in that: include: The vehicle networking platform is used to analyze fuel data in real-time vehicle data when a vehicle DPF blockage fault is detected to determine whether the vehicle DPF blockage fault is caused by user behavior; If the vehicle DPF clogging fault is not caused by user behavior, the driving data in the vehicle data is analyzed to determine whether the vehicle DPF clogging fault is caused by the operating scenario; The service platform is used to receive the fault judgment results sent by the Internet of Vehicles platform and perform corresponding processing procedures according to different fault causes.

9. The system according to claim 8, characterized in that: The service platform is further configured to remind the user through different reminder methods if it is determined that the vehicle DPF blockage fault is caused by the user's behavior; If it is determined that the vehicle DPF blockage fault is caused by the operating scenario, the engine operating speed is increased to the target speed and the parking regeneration time is extended to the target time.

10. The system according to claim 8, characterized in that: The vehicle networking platform is further configured to determine whether the carbon load of the current parking regeneration has reached the limit according to the DPF regeneration carbon load limit table; If the limit is reached, the vehicle DPF is determined to be blocked and the user is notified to perform a parking regeneration operation.

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