CN115600397A

CN115600397A - DPF original exhaust carbon-loaded model calibration method and device, computer equipment and storage medium

Info

Publication number: CN115600397A
Application number: CN202211233113.7A
Authority: CN
Inventors: 王远东; 袁忠庄; 鞠妍; 刘学文
Original assignee: FAW Jiefang Automotive Co Ltd
Current assignee: FAW Jiefang Automotive Co Ltd
Priority date: 2022-10-10
Filing date: 2022-10-10
Publication date: 2023-01-13

Abstract

The application relates to a DPF original exhaust carbon-loaded model calibration method, a DPF original exhaust carbon-loaded model calibration device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring road test operation parameters generated by the operation of a vehicle under different working conditions and actual road test results of the carbon loading amount of the DPF; respectively processing road test operation parameters under various working conditions by adopting a DPF simulation carbon-loaded model corresponding to the original carbon-loaded model of the DPF to obtain a corresponding DPF carbon loading capacity simulation result; performing data analysis on each road of trial operation parameters to obtain a working condition characteristic image of each road of trial operation parameters; correcting the DPF simulated carbon loading model according to the DPF carbon loading capacity simulation result, the DPF carbon loading capacity actual road test result and the working condition characteristic portrait; and finally updating the original carbon-loaded model of the DPF based on the corrected calibration parameters of the DPF simulation carbon-loaded model. By adopting the method, the calibration efficiency of the original carbon-loaded model of the DPF can be improved.

Description

DPF original exhaust carbon-loaded model calibration method and device, computer equipment and storage medium

Technical Field

The application relates to the technical field of finished automobile system integration calibration, in particular to a DPF original exhaust carbon-loaded model calibration method, device, computer equipment and storage medium.

Background

With the development of the automobile industry and the national requirements on environmental protection, the emission standard of particulate matters in automobile exhaust is more and more strict. Arranging a DPF (Diesel Particulate Filter) in the exhaust aftertreatment system can effectively reduce Particulate matter in the exhaust gas of the automobile. After the particulates in the DPF are accumulated to a certain extent, regeneration is required to empty the particulates, and the regeneration interval of the DPF needs to be judged by the DPF carbon loading amount calculated by the DPF raw exhaust model.

In the traditional technology, the DPF original exhaust model is calibrated only based on the weighing result of the DPF, so that in order to guarantee the calibration effect, a road test is frequently required to be repeatedly carried out and the DPF is frequently weighed, and the method needs to consume a long period and has the problem of low calibration efficiency.

Disclosure of Invention

In view of the above, it is necessary to provide a DPF raw exhaust carbon-loaded model calibration method, device, computer device and computer readable storage medium capable of efficiently calibrating a DPF raw exhaust carbon-loaded model.

In a first aspect, the application provides a calibration method for a DPF original exhaust carbon-loaded model. The method comprises the following steps:

acquiring road test operation parameters generated by the operation of a vehicle under different working conditions and actual road test results of the carbon loading amount of the DPF;

building a DPF simulation carbon-loaded model corresponding to the DPF original exhaust carbon-loaded model;

respectively processing road test operation parameters under each working condition by adopting the DPF simulation carbon-loaded model to obtain DPF carbon-loaded quantity simulation results respectively corresponding to each working condition;

performing data analysis on each road of trial operation parameters to obtain a working condition characteristic image of each road of trial operation parameters;

correcting the DPF carbon loading simulation model according to the DPF carbon loading simulation result, the DPF carbon loading actual road test result and the working condition characteristic portrait to obtain a corrected DPF carbon loading simulation model;

and updating the original carbon-loaded model of the DPF based on the corrected calibration parameters of the DPF simulation carbon-loaded model.

In one embodiment, the analyzing the data of each trial-run parameter to obtain the operating condition characteristic image of each trial-run parameter includes:

and respectively analyzing at least one of frequency analysis, centralized trend analysis and discrete degree analysis on each road test operation parameter to obtain a working condition characteristic image of each road test operation parameter.

In one embodiment, the correcting the DPF simulated carbon-loaded model according to the DPF carbon-loaded amount simulation result, the DPF carbon-loaded amount actual road test result, and the operating condition characteristic image to obtain a corrected DPF simulated carbon-loaded model includes:

selecting a current working condition to be processed from a plurality of working conditions;

correcting the DPF simulated carbon-loaded model based on the DPF carbon-loaded capacity simulation result corresponding to the current working condition, the DPF carbon-loaded capacity actual road test result and the working condition characteristic portrait;

selecting the next working condition to be processed from a plurality of working conditions as the next current working condition, returning the DPF carbon loading capacity simulation result, the DPF carbon loading capacity actual road test result and the working condition characteristic portrait which correspond to the current working condition, and correcting the DPF simulated carbon loading model;

and finishing the iterative correction process when the correction of the DPF simulation carbon-loaded model is finished under the last working condition to obtain the corrected DPF simulation carbon-loaded model.

In one embodiment, the road test operation parameters under each working condition comprise road test operation sub-parameters respectively corresponding to a plurality of driving miles, and one road test operation sub-parameter corresponds to one DPF carbon loading amount simulation sub-result; the actual road test result of the DPF carbon loading capacity under each working condition comprises actual road test sub-results of the DPF carbon loading capacity corresponding to a plurality of driving miles respectively;

based on the DPF carbon loading capacity simulation result that current operating mode corresponds, DPF carbon loading capacity actual road test result and operating mode characteristic portrait, revise DPF emulation carbon loading model, include:

determining a DPF carbon loading capacity simulation sub-result and a DPF carbon loading capacity actual road test sub-result corresponding to the same driving mileage under the current working condition;

calculating a difference value between a DPF carbon loading capacity simulation sub-result and a DPF carbon loading capacity actual road test sub-result of the same driving mileage;

comparing the difference value with the preset difference value;

and if the difference is larger than a preset difference, correcting the DPF simulation carbon-supported model based on the working condition characteristic image of the road test operation sub-parameter.

In one embodiment, the modifying the DPF simulation carbon-supported model based on the condition characteristic image of the road test operation sub-parameter includes:

determining a pulse spectrum correction area of the DPF simulation carbon-loaded model according to the working condition characteristic portrait of the road test operation sub-parameters;

and adjusting the data in the pulse spectrum correction region according to the magnitude of the difference value.

In one embodiment, the road test operation parameters include engine speed, fuel injection amount, coolant temperature, atmospheric pressure, excess air factor, nitrogen and oxygen flow rate, exhaust temperature, oxygen flow rate, and exhaust flow rate.

In a second aspect, the application further provides a calibration device for the original carbon-loaded DPF model. The device comprises:

the acquisition module is used for acquiring road test operation parameters generated by the operation of the vehicle under different working conditions and actual road test results of the carbon loading of the DPF;

the building module is used for building a DPF simulation carbon-loaded model corresponding to the DPF original exhaust carbon-loaded model;

the processing module is used for processing the road test operation parameters under each working condition by adopting the DPF simulation carbon-loaded model to obtain DPF carbon-loaded quantity simulation results corresponding to each working condition;

the analysis module is used for carrying out data analysis on the test operation parameters of each path to obtain working condition characteristic images of the test operation parameters of each path;

the correction module is used for correcting the DPF carbon loading simulation model according to the DPF carbon loading simulation result, the actual road test result of the DPF carbon loading and the working condition characteristic portrait to obtain a corrected DPF carbon loading simulation model;

and the updating module is used for updating the original DPF carbon-loaded model based on the corrected calibration parameters of the DPF simulation carbon-loaded model.

In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:

In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:

acquiring road test operation parameters generated by the operation of a vehicle under different working conditions and DPF carbon loading capacity actual road test results;

In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:

According to the calibration method, the calibration device, the calibration computer equipment, the calibration medium and the calibration computer program product of the DPF original carbon-loaded model, road test operation parameters generated by operation under different working conditions are used as simulation input, the actual road test result of the DPF carbon loading capacity is used as a simulation target, the DPF simulated carbon-loaded model built based on the DPF original carbon-loaded model is corrected according to the working condition characteristic portrait of the whole vehicle operation, and finally the DPF original carbon-loaded model is updated based on the calibration parameters of the corrected DPF simulated carbon-loaded model. Therefore, the working condition characteristic portrait is introduced to assist in adjusting the parameters of the DPF simulation carbon-loaded model, so that the original carbon-loaded model of the DPF of the engine can be finally completed, the road test can not be repeatedly carried out, the DPF can be frequently weighed, the effective calibration of the original carbon-loaded model of the DPF of the engine can be realized, and the calibration efficiency is greatly improved. In addition, the off-line calibration of the DPF original exhaust carbon-loaded model is completed according to the working condition characteristic image of the whole vehicle operation under the condition that an engine system entity is not needed, and the efficiency of calibrating the DPF original exhaust carbon-loaded model is improved.

Drawings

FIG. 1 is a diagram of an environment in which a DPF original exhaust carbon-supported model calibration method is applied in some embodiments;

FIG. 2 is a schematic flow chart of a DPF original exhaust carbon loading model calibration method in some embodiments;

FIG. 3 is a schematic flow chart of a process for modifying a DPF simulated carbon-supported model based on operating condition signature profiles in some embodiments;

FIG. 4 is a schematic flow chart of a DPF original exhaust carbon loading model calibration method in other embodiments;

FIG. 5 is a block diagram of a DPF original exhaust carbon loading model calibration device in some embodiments;

FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

It is noted that, as used herein, the terms "comprises," "comprising," "includes," "including," "has," "having" and any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of steps or means is not necessarily limited to those steps explicitly listed, but may include other steps or means not expressly listed or inherent to such process, method, article, or apparatus. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

The method for calibrating the original exhaust carbon-loaded DPF model provided by the embodiment of the application can be applied to the application environment shown in FIG. 1. In which in-vehicle terminal 102 may communicate with computer device 104 through a network. The data storage system may store data that computer device 104 needs to process. The data storage system may be integrated on the computer device 104, or may be located on the cloud or other network server. The in-vehicle terminal 102 may also access a CAN network of the vehicle through a CAN bus, and may communicate with the computer device 104 through a limited network, a wireless network, or a mobile network (e.g., a 4G or 5G network).

After acquiring the road test operation parameters generated by the vehicle operating under different working conditions, the vehicle-mounted terminal 102 transmits the acquired road test operation parameters to the computer device 104 through the network. The computer device 104 obtains road test operation parameters generated by the operation of the vehicle under different working conditions and DPF carbon loading capacity actual road test results, then builds a DPF simulation carbon loading model corresponding to the original carbon loading model based on the DPF, and respectively processes the road test operation parameters under each working condition by adopting the built DPF simulation carbon loading model to obtain DPF carbon loading capacity simulation results corresponding to each working condition. The computer device 104 further needs to perform data analysis on each pilot run parameter to obtain a working condition characteristic image of each pilot run parameter, correct the DPF carbon-loaded simulation model according to the DPF carbon loading amount simulation result, the DPF carbon loading amount actual road test result, and the working condition characteristic image, further obtain a corrected DPF carbon-loaded simulation model, and finally update the DPF original exhaust carbon-loaded model based on the calibration parameters of the corrected DPF carbon-loaded simulation model.

The road test operation parameters generated by the running of the vehicle under different working conditions and the actual road test result of the DPF carbon loading acquired by the computer device 104 can be stored locally or on a data storage system, the computer device 104 can be a terminal or a server, the terminal can be but not limited to various personal computers, notebook computers, smart phones, tablet computers, internet of things devices and portable wearable devices, and the internet of things devices can be smart sound boxes, smart televisions, smart air conditioners, smart vehicle-mounted devices and the like. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, and the like. The server is implemented by an independent server or a server cluster consisting of a plurality of servers.

In one embodiment, as shown in fig. 2, a method for calibrating a raw exhaust carbon loading model of a DPF, which is illustrated by applying the method to the computer device in fig. 1, includes the following steps:

step 202, obtaining road test operation parameters generated by the vehicle running under different working conditions and actual road test results of DPF carbon loading capacity.

The working condition is the working condition of the vehicle under a certain condition. Road tests are driving tests performed in different environments and roads to detect vehicle performance. The road test operation parameters are operation parameters of an engine when the vehicle is subjected to a road test. The actual road test result of the carbon loading of the DPF is the actual carbon loading of the DPF measured when the vehicle is in road test. It can be understood that the road test of the vehicle under different working conditions can obtain the road test operation parameters generated by the vehicle running under different working conditions and the actual road test result of the carbon loading of the DPF.

Specifically, install vehicle terminal on the vehicle, when the vehicle carried out the way examination under different operating modes, vehicle terminal can gather the way examination operating parameter under the corresponding operating mode. The computer equipment can acquire the acquired road test operation parameters generated by the operation of the vehicle under different working conditions and the actual carbon loading of the DPF through measurement through a network.

In one embodiment, the road test operation parameters collected by the vehicle-mounted terminal under the corresponding working conditions include engine speed, fuel injection quantity, coolant temperature, atmospheric pressure, excess air coefficient, nitrogen and oxygen flow, exhaust temperature, exhaust flow and oxygen flow.

Wherein the engine speed is the number of revolutions per minute of the engine crankshaft; the fuel injection quantity is the fuel injection quantity sprayed by the fuel injector after receiving the fuel injection signal; the coolant temperature is the temperature of coolant that circulates in the engine cooling system for removing excess heat generated during engine operation; the excess air ratio is the ratio of the amount of air actually supplied to the fuel for combustion to the theoretical amount of air, and is an important parameter reflecting the fuel-to-air mixing ratio; the flow rate of nitrogen and oxygen is the flow rate of nitrogen and oxygen compounds in the tail gas discharged in the running process of the vehicle; the exhaust temperature is the temperature of exhaust gas emitted during vehicle operation; the exhaust flow rate is the exhaust flow rate discharged during vehicle operation; the oxygen flow rate is the flow rate of oxygen in exhaust gas discharged during the operation of the vehicle.

And step 204, building a DPF simulation carbon-loaded model corresponding to the DPF original exhaust carbon-loaded model.

The DPF raw exhaust carbon load model is a calculation model that is mounted in a vehicle electronic control unit (engine integrated control device) and estimates the amount of carbon loaded in the DPF. The DPF simulation carbon-loaded model is a calculation model which is built on the basis of the principle of a DPF original exhaust carbon-loaded model and is used for estimating the carbon loading in the DPF in an off-line mode.

Specifically, the principle of the original carbon-loaded DPF exhaust model is as follows: the carbon loading capacity in the DPF is equal to the carbon loading capacity in exhaust gas at the outlet of the engine minus the carbon loading capacity consumed in the active regeneration and passive regeneration reactions, and the real-time carbon loading in the DPF can be obtained through integral calculation. The original value of the carbon loading amount can be obtained by looking up a table according to the rotating speed of the engine and the circulating fuel injection amount, and the original value is finally obtained by correcting the temperature of the cooling liquid, the environmental condition and the excess air coefficient. The carbon load consumed by active regeneration can be determined by parameters such as oxygen flow, excess air coefficient, exhaust temperature, exhaust flow and the like. The carbon load consumed by the passive regeneration reaction may be determined by the nitrogen oxygen flow, the exhaust temperature, and the current carbon load of the DPF.

And step 206, respectively processing the road test operation parameters under each working condition by adopting a DPF simulation carbon loading model to obtain DPF carbon loading capacity simulation results respectively corresponding to each working condition.

And the DPF carbon loading simulation result is the DPF carbon loading calculated by a DPF simulation carbon loading model.

Specifically, the carbon loading of the DPF is increased differently under different working conditions. Under each working condition, the carbon loading of the DPF under the working condition can be estimated through the corresponding road test operation parameters. After the computer equipment acquires road test running parameters generated by running of the vehicle under different working conditions, the road test running parameters under all the working conditions are processed by adopting a DPF simulation carbon-loaded model built based on a DPF original-exhaust carbon-loaded model, and DPF carbon loading capacity simulation results corresponding to all the working conditions respectively can be obtained.

And step 208, performing data analysis on each path of test operation parameter to obtain a working condition characteristic image of each path of test operation parameter.

The data analysis is to analyze a large amount of collected data by using a proper statistical analysis method, and to summarize, understand and digest the data so as to maximally develop the function of the data and play the role of the data. The purpose of the data analysis is to extract useful information. The working condition characteristic portrait is a figure capable of visually representing the working condition characteristics. The working condition characteristics under the working condition can be read visually through the working condition characteristic image.

Specifically, under each working condition, each road test operation parameter is processed by a corresponding data analysis method to obtain a corresponding working condition characteristic image. And for the same road test operation parameter under different working conditions, obtaining corresponding working condition characteristic images of the same road test operation parameter under different working conditions by adopting the same data analysis method. After the computer equipment acquires road test operation parameters generated by the operation of the vehicle under different working conditions, data analysis is carried out on the road test operation parameters by adopting a corresponding data analysis method, and further working condition characteristic images corresponding to the road test operation parameters are obtained.

In one embodiment, the data analysis of the test operation parameters of each path to obtain the working condition characteristic image of the test operation parameters of each path includes: and respectively analyzing at least one of frequency analysis, centralized trend analysis and discrete degree analysis on each road test operation parameter to obtain a working condition characteristic image of each road test operation parameter.

The frequency analysis is a mode of counting the frequency of different values of a group of data or the frequency of the data falling into a specified area to know the data distribution condition. The central tendency analysis is a data analysis mode for reflecting the variable value towards the central position by various representative measures. The dispersion degree analysis is a way to measure the dispersion degree of a set of data. The degree of scatter reflects the degree to which a set of data is far from its central value, and is therefore also referred to as the tendency to decentralize. The change trend of a set of data can be completely illustrated from the aspects of both the concentration trend and the dispersion degree.

In one embodiment, at least one of frequency analysis, central tendency analysis, or discrete degree analysis may be performed on two or more road test operation parameters simultaneously.

Optionally, frequency analysis is performed on the engine speed acquired by way test under a specific working condition and corresponding fuel injection quantity, coolant temperature, atmospheric pressure, excess air coefficient, nitrogen oxygen flow, exhaust temperature, exhaust flow and oxygen flow, so as to obtain a working condition characteristic image corresponding to the engine speed and corresponding fuel injection quantity, coolant temperature, atmospheric pressure, excess air coefficient, nitrogen oxygen flow, exhaust temperature, exhaust flow and oxygen flow under the working condition. Optionally, the centralized trend analysis and the dispersion degree analysis are performed on the engine speed, the fuel injection quantity, the exhaust temperature, the exhaust flow quantity and the air excess coefficient acquired by road test acquisition under a specific working condition, so as to obtain a working condition characteristic image corresponding to the engine speed, the fuel injection quantity, the exhaust temperature, the exhaust flow quantity and the air excess coefficient under the working condition.

In the above embodiment, the operating condition characteristic image of each trial operation parameter is obtained by performing at least one of frequency analysis, concentration trend analysis, or discrete degree analysis on each trial operation parameter. The obtained working condition characteristic image can visually reflect the working condition characteristics, and further provides a basis for subsequently correcting the DPF simulation carbon-supported model.

And step 210, correcting the DPF carbon loading simulation model according to the DPF carbon loading simulation result, the DPF carbon loading actual road test result and the working condition characteristic portrait to obtain the corrected DPF carbon loading simulation model.

Specifically, after the computer device adopts the built DPF simulation carbon-loaded model to process road test operation parameters under each working condition, DPF carbon-loaded quantity simulation results respectively corresponding to each working condition can be obtained. For a specific working condition, the DPF carbon loading capacity simulation result under the working condition is compared with the DPF carbon loading capacity actual road test result obtained by measuring in the road test under the working condition, and the accuracy of the DPF carbon loading simulation model processing result can be known. If the difference between the DPF carbon loading capacity simulation result and the actual road test result of the DPF carbon loading capacity under the working condition is large (for example, exceeds a preset difference value), the accuracy of the processing result of the DPF simulated carbon-loaded model is low, and at the moment, the DPF simulated carbon-loaded model needs to be corrected according to the working condition characteristic image of each road test operation parameter under the working condition.

For each working condition, comparing the simulation result of the carbon loading capacity of the DPF under the working condition with the actual road test result of the carbon loading capacity of the DPF measured during road test under the working condition, and before the DPF simulation carbon-loaded model is not corrected completely, correcting the model parameters of the DPF simulation carbon-loaded model according to the working condition characteristic image of each road test operation parameter under the working condition until the corrected condition is reached, so as to obtain the corrected DPF simulation carbon-loaded model. The corrected condition may specifically be that a difference between the DPF carbon loading amount simulation result and the DPF carbon loading amount actual road test result reaches a preset difference.

And step 212, updating the original DPF exhaust carbon-loaded model based on the corrected calibration parameters of the DPF simulation carbon-loaded model.

The calibration parameters refer to model parameters in a DPF simulation carbon-supported model.

The model parameters needing to be corrected in the DPF simulation carbon-supported model correspond to the model parameters needing to be corrected in the DPF original exhaust carbon-supported model one by one. And when the DPF simulation carbon-loaded model is corrected, determining model parameters needing to be corrected in the DPF simulation carbon-loaded model, and updating the model parameters needing to be corrected in the DPF original exhaust carbon-loaded model according to the determined model parameters in the DPF simulation carbon-loaded model, namely completing the calibration of the DPF original exhaust carbon-loaded model.

According to the calibration method of the DPF original carbon-loaded model, road test operation parameters generated by operation under different working conditions are used as simulation input, the actual road test result of the DPF carbon-loaded quantity is used as a simulation target, the DPF simulated carbon-loaded model built based on the DPF original carbon-loaded model is corrected according to the working condition characteristic portrait of the whole vehicle operation, and finally the DPF original carbon-loaded model is updated based on the corrected calibration parameters of the DPF simulated carbon-loaded model. Therefore, the working condition characteristic portrait is introduced to assist in adjusting the parameter of the DPF simulation carbon-loaded model, so that the original DPF carbon-loaded model of the engine can be finally completed, the road test cannot be repeatedly carried out, the DPF can be frequently weighed, the effective calibration of the original DPF carbon-loaded model of the engine can be realized, and the calibration efficiency is greatly improved. In addition, the off-line calibration of the DPF original carbon-loaded model is completed according to the working condition characteristic image of the whole vehicle operation under the condition that an engine system entity is not needed, and the efficiency of calibrating the DPF original carbon-loaded model is improved.

In one embodiment, the method for correcting the DPF carbon-loaded simulation model according to the DPF carbon loading simulation result, the DPF carbon loading actual road test result, and the operating condition characteristic image to obtain the corrected DPF carbon-loaded simulation model includes: selecting a current working condition to be processed from a plurality of working conditions; correcting the DPF carbon loading simulation model based on a DPF carbon loading simulation result, a DPF carbon loading actual road test result and a working condition characteristic portrait which correspond to the current working condition; selecting the next working condition to be processed from the plurality of working conditions as the next current working condition, returning the DPF carbon loading capacity simulation result corresponding to the current working condition, the DPF carbon loading capacity actual road test result and the working condition characteristic portrait, and continuously executing the step of correcting the DPF simulated carbon loading model; and finishing the iterative correction process when the correction of the DPF simulation carbon-loaded model is finished under the last working condition to obtain the corrected DPF simulation carbon-loaded model.

It should be noted that when the DPF raw exhaust carbon loading model is calibrated, the calibration result needs to be corrected under a plurality of different working conditions respectively, so that the calibration result can cover different working conditions. Therefore, the DPF simulation carbon-supported model also needs to be corrected under a plurality of different working conditions.

And when the DPF simulation carbon-loaded model is corrected under one working condition, the working condition is the current working condition. After the DPF simulation carbon-loaded model is corrected under the current working condition, the next working condition needs to be selected to correct the DPF simulation carbon-loaded model. And correcting the DPF simulation carbon loading model under each working condition, wherein the working condition can be called as the current working condition.

In one embodiment, the computer device may randomly select one of the plurality of operating conditions as the current operating condition, or may select one of the plurality of operating conditions as the current operating condition according to a preset sequence. The present embodiment does not limit the manner of selecting the current operating condition.

It can be understood that different working conditions correspond to different DPF carbon loading simulation results, DPF carbon loading actual road test results, and working condition characteristic images. For the current working condition, the computer equipment needs to correct the DPF carbon loading simulation model based on the DPF carbon loading simulation result, the DPF carbon loading actual road test result and the working condition characteristic portrait corresponding to the current working condition.

Specifically, after the computer equipment obtains the DPF carbon loading capacity simulation result and the actual road test result of the DPF carbon loading capacity under the current working condition, the DPF carbon loading capacity simulation result and the actual road test result of the DPF carbon loading capacity under the current working condition are compared, if the difference between the DPF carbon loading capacity simulation result and the actual road test result of the DPF carbon loading capacity under the current working condition is large, the accuracy of the processing result of the DPF simulation carbon-loaded model under the current working condition is low, and at the moment, the DPF simulation carbon-loaded model needs to be corrected according to the working condition characteristic image of each road test operation parameter under the current working condition. And after the current working condition is corrected, repeating the steps on the next current working condition, and performing iterative correction on the DPF simulated carbon-loaded model until the DPF simulated carbon-loaded model is corrected under the last working condition and then meets the iterative correction finishing condition to obtain the corrected DPF simulated carbon-loaded model.

In the above embodiment, the obtained corrected DPF simulated carbon-loaded model can be ensured to meet the use scenes of different working conditions by iteratively correcting the DPF simulated carbon-loaded model under different working conditions.

In one embodiment, the road test operation parameters under each working condition comprise road test operation sub-parameters respectively corresponding to a plurality of driving miles, and one road test operation sub-parameter corresponds to one DPF carbon loading amount simulation sub-result; the actual road test result of the DPF carbon loading capacity under each working condition comprises actual road test sub-results of the DPF carbon loading capacity corresponding to a plurality of driving mileage. Based on DPF carbon loading capacity simulation result, the actual road test result of DPF carbon loading capacity that current operating mode corresponds and operating mode characteristic portrait, revise DPF emulation carbon-loaded model, include: determining a DPF carbon loading capacity simulation sub-result and a DPF carbon loading capacity actual road test sub-result corresponding to the same driving mileage under the current working condition; calculating a difference value between a DPF carbon loading capacity simulation sub-result and a DPF carbon loading capacity actual road test sub-result of the same driving mileage; comparing the difference value with a preset difference value; and if the difference is larger than the preset difference, correcting the DPF simulation carbon-loaded model based on the working condition characteristic image of the road test operation sub-parameters.

When the vehicle performs the road test under the specific working condition, the road test operation parameters acquired by the vehicle-mounted terminal comprise a plurality of groups of road test operation parameters acquired under the plurality of sections of driving mileage. The road test operation parameters corresponding to each section of the traveled mileage can be called as road test operation sub-parameters under the working condition. For example, the vehicle runs a first driving mileage, and the vehicle-mounted terminal acquires a road test operation parameter corresponding to the first driving mileage; and the vehicle continues to run to reach a second running mileage, and the vehicle-mounted terminal acquires the road test operation parameters corresponding to the second running mileage. At this time, the road test operation parameter corresponding to the first driving mileage and the road test operation parameter corresponding to the second driving mileage may be referred to as the road test operation sub-parameters under the working condition. And for each road test operation sub-parameter, the computer equipment adopts a DPF (diesel particulate filter) simulation carbon-loaded model to process the road test operation sub-parameter, so that a corresponding DPF carbon-loaded simulation sub-result can be obtained.

In one embodiment, the multiple sections of the mileage are distributed in an arithmetic progression, that is, the interval between every two adjacent sections of the mileage is the same. In other embodiments, the distance between the mileage of each two adjacent segments may also be different, and this is not limited in this application.

It can be understood that, when the vehicle performs a road test under a specific working condition, the DPF carbon loading amount actual road test result corresponding to each driving mileage may be referred to as a DPF carbon loading amount actual road test sub-result under the working condition. The actual road test result of the DPF carbon loading capacity under each working condition comprises actual road test sub-results of the DPF carbon loading capacity respectively corresponding to a plurality of driving miles.

The preset difference is a preset numerical value used for measuring the prediction accuracy of the DPF simulation carbon-supported model, and is usually expressed by percentage. In one embodiment, the preset difference may be 5% or 10%, which is not limited in this application. Correspondingly, the difference between the DPF carbon loading simulation result and the DPF carbon loading actual road test result is also expressed by percentage. The prediction accuracy of the DPF simulation carbon loading model can be determined by comparing the difference value between the DPF carbon loading capacity simulation result and the actual road test result of the DPF carbon loading capacity with a preset difference value.

In one embodiment, the process of correcting the DPF carbon loading simulation model based on the DPF carbon loading simulation result corresponding to the current working condition, the DPF carbon loading actual road test result, and the working condition characteristic portrait includes: and iteratively correcting the DPF carbon loading simulation model based on DPF carbon loading simulation sub-results, DPF carbon loading actual road test sub-results and working condition characteristic images corresponding to a plurality of driving miles under the current working condition.

Specifically, for each specific driving mileage under the current working condition, when the difference between the DPF carbon loading amount simulation sub-result and the DPF carbon loading amount actual road test sub-result is greater than the preset difference, it may be determined that the prediction accuracy of the DPF carbon loading simulation model is low, and at this time, the DPF carbon loading simulation model needs to be corrected according to the working condition characteristic image of the road test driving sub-parameter corresponding to the driving mileage. After the correction is completed, the next correction process is started based on the next driving mileage under the current working condition. And continuously iterating until the correction process corresponding to each driving mileage under the current working condition is completed.

In the above embodiment, the DPF carbon-loaded simulation model is iteratively corrected based on the road test operation sub-parameters, the DPF carbon loading amount simulation sub-results, and the DPF carbon loading amount actual road test sub-results corresponding to the multiple driving miles under the current working condition, so that the correction of the DPF carbon-loaded simulation model under the current working condition can be completed.

In one embodiment, as shown in fig. 3, the step of modifying the DPF simulated carbon-supported model based on the condition feature image of the road test operation sub-parameters includes:

and 302, determining a pulse spectrum correction area of the DPF simulation carbon-loaded model according to the working condition characteristic image of the road test operation sub-parameters.

The pulse spectrum correction region is a parameter range in which the pulse spectrum in the DPF simulation carbon-supported model needs to be corrected. Different road test operation parameters correspond to a pulse spectrum. Usually, one working condition corresponds to one pulse spectrum correction area, and the pulse spectrum corresponding to each pilot operation parameter in the DPF simulation carbon-loaded model covers most of the working conditions.

Specifically, the computer device performs at least one of frequency analysis, concentration trend analysis and dispersion degree analysis on the road test operation sub-parameters to obtain a working condition characteristic image corresponding to the road test operation sub-parameters. And determining a pulse spectrum correction area of the DPF simulation carbon-supported model according to the working condition characteristic image.

For example, the road test operation sub-parameters corresponding to the specific driving mileage under the specific working condition include the engine speed and the fuel injection amount corresponding to the engine speed, and the engine speed and the fuel injection amount corresponding to the specific driving mileage under the specific working condition are subjected to frequency analysis to obtain a working condition characteristic image corresponding to the engine speed and the fuel injection amount under the working condition. The engine speed and the corresponding distribution range of the fuel injection amount under the specific driving mileage of the specific working condition can be determined through the working condition characteristic image, and then the engine speed and the pulse spectrum correction area corresponding to the fuel injection amount in the DPF simulation carbon-supported model can be determined.

And step 304, adjusting the data in the pulse spectrum correction area according to the difference value.

Specifically, when the difference between the DPF carbon loading amount simulation sub-result and the DPF carbon loading amount actual road test sub-result is greater than a preset difference, it may be determined that the prediction accuracy of the DPF carbon loading simulation model is low, and at this time, data in the determined pulse spectrum correction region needs to be adjusted.

In this embodiment, the pulse spectrum correction region of the DPF simulation carbon-supported model is determined according to the operating condition characteristic image of the road test operation sub-parameter, and then data in the pulse spectrum correction region is adjusted according to the difference value, so that accurate correction of the DPF simulation carbon-supported model can be realized.

Referring to fig. 4, the calibration method of the DPF raw exhaust carbon loading model according to the present application is further described in detail with a specific embodiment:

the calibration method of the DPF original exhaust carbon-loaded model comprises the steps of working condition data acquisition, DPF weighing, data processing, model calculation, comparison with an actual road test result and model correction based on a working condition characteristic portrait.

The following detailed description is made: a vehicle-mounted remote terminal processing system (vehicle-mounted terminal) is installed on a road test vehicle, and the vehicle-mounted terminal is debugged, so that the vehicle-mounted terminal can accurately and completely record vehicle road test operation parameters. The vehicle-mounted terminal has data acquisition and storage functions. And adding engine operation parameters (such as fuel injection quantity, rotating speed, atmospheric temperature, NO2 content, aftertreatment temperature and the like) related to DPF original exhaust carbon-loaded model calibration on the vehicle-mounted terminal, and setting sampling frequency. Before the road test, the DPF of the road test vehicle needs to be weighed after being sufficiently worn out as the DPF reference mass.

And the vehicle-mounted terminal automatically acquires and records the added engine operation parameters related to the calibration of the DPF original exhaust carbon-loaded model when the road test vehicle runs under the set working condition. And the engine operation parameters collected by each section of fixed mileage after the vehicle runs under the set working condition are road test operation sub-parameters. And weighing and measuring the mass of the DPF after the running distance is fixed, and subtracting the reference mass of the DPF from the weighing result to obtain the actual road test result of the carbon loading amount of the DPF. And when the actual road test sub-result of the DPF carbon loading reaches the driving regeneration threshold, ending the data acquisition process, and stopping driving the road test vehicle.

After the data acquisition process under multiple working conditions is finished, the computer equipment can acquire road test operation parameters generated by the acquired road test vehicles operating under different working conditions and the actual carbon loading of the DPF through the network.

On one hand, the computer equipment writes a data processing program based on Python (a computer programming language), the obtained road test operation parameters are loaded by using a Pandas library (an extended program library of the Python language), the data processing program can automatically integrate a plurality of groups of road test operation parameters acquired under different working conditions into one, missing value processing and abnormal value processing are automatically completed, the influence of invalid and error data is eliminated, normalized processing is carried out on the data, and finally, a standard EXCEL file is generated from the processed file and is automatically named according to the requirements of vehicle information and the like. Completely new files can be used directly for analysis and calculation.

It should be noted that the data processing program written based on Python not only can perform data processing on the obtained road test operation parameters, but also can process the road test operation parameters to generate a working condition characteristic image of each road test operation parameter. For example, frequency analysis, centralized trend analysis and discrete degree analysis are performed on various parameters such as fuel injection quantity, engine speed, atmospheric temperature, NO2 content and aftertreatment temperature of the road test vehicle in the road test process to generate a working condition characteristic image. According to the working condition characteristic image, each road test operation parameter can be subjected to relevant analysis, so that the degree of correlation between the change of each parameter and the carbon loading capacity of the DPF in the DPF simulation carbon-loaded model can be determined, and basis and guidance are provided for correcting the calibration quantity and the calibration pulse spectrum of the DPF simulation carbon-loaded model.

On the other hand, the computer equipment builds a DPF simulation carbon-loaded model corresponding to the DPF original exhaust carbon-loaded model based on MATLAB/Simulink software (a simulation tool). The DPF carbon loading simulation result can be obtained by processing the road test operation parameters subjected to the data processing by adopting the built DPF simulation carbon loading model.

For each specific driving mileage of a specific working condition, the computer device processes the road test operation sub-parameters corresponding to the specific driving mileage of the specific working condition by adopting the built DPF simulation carbon-loaded model to obtain a DPF carbon loading capacity simulation sub-result corresponding to the specific driving mileage of the specific working condition, calculates the difference value between the DPF carbon loading capacity simulation sub-result corresponding to the specific driving mileage of the specific working condition and the DPF carbon loading capacity actual road test sub-result corresponding to the specific driving mileage of the specific working condition, compares the obtained difference value with a preset difference value, and if the calculated difference value is greater than the preset difference value, the DPF simulation carbon-loaded model needs to be corrected according to the working condition characteristic drawing of each road test operation parameter under the working condition. The preset difference may be set to 5%, or may be set to another percentage.

The DPF carbon loading capacity simulation sub-results corresponding to the multiple driving miles can be obtained based on the road test operation sub-parameters corresponding to the multiple driving miles under the specific working condition, and the DPF carbon loading capacity simulation sub-results, the DPF carbon loading capacity actual road test sub-results and the working condition feature images corresponding to the multiple driving miles are used for carrying out iterative correction on the DPF simulated carbon loading model, so that the DPF simulated carbon loading model can be corrected under the specific working condition. When the DPF carbon loading amount simulation sub-result, the DPF carbon loading amount actual road test sub-result and the working condition characteristic image corresponding to the last driving mileage are used for correcting the DPF carbon loading simulation model, the preset difference value can be 10%.

And under each working condition, carrying out iterative correction on the DPF carbon loading capacity simulation sub-result, the DPF carbon loading capacity actual road test sub-result and the working condition characteristic image corresponding to a plurality of driving miles on the DPF carbon loading capacity simulation sub-result, until the DPF carbon loading capacity simulation model is corrected, and finally updating the DPF original exhaust carbon loading model on the basis of the corrected calibration parameters of the DPF carbon loading capacity simulation model.

And finally, the updated DPF original exhaust carbon-loaded model is written to an electronic control unit of the road test vehicle for road test verification.

According to the calibration method of the DPF original carbon-loaded model, road test operation parameters generated by operation under different working conditions are used as simulation input, the actual road test result of the DPF carbon-loaded quantity is used as a simulation target, the DPF simulated carbon-loaded model built based on the DPF original carbon-loaded model is corrected according to the working condition characteristic portrait of the whole vehicle operation, and finally the DPF original carbon-loaded model is updated based on the corrected calibration parameters of the DPF simulated carbon-loaded model. Therefore, the working condition characteristic portrait is introduced to assist in adjusting the parameters of the DPF simulation carbon-loaded model, so that the original carbon-loaded model of the DPF of the engine can be finally completed, the road test can not be repeatedly carried out, the DPF can be frequently weighed, the effective calibration of the original carbon-loaded model of the DPF of the engine can be realized, and the calibration efficiency is greatly improved. In addition, the off-line calibration of the DPF original carbon-loaded model is completed according to the working condition characteristic image of the whole vehicle operation under the condition that an engine system entity is not needed, and the efficiency of calibrating the DPF original carbon-loaded model is improved.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not limited to being performed in the exact order illustrated and, unless explicitly stated herein, may be performed in other orders. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, as shown in fig. 5, the present application further provides a DPF raw exhaust carbon-loaded model calibration apparatus 500 for implementing the DPF raw exhaust carbon-loaded model calibration method, including: the system comprises an acquisition module 501, a building module 501, a processing module 503, an analysis module 504, a correction module 505 and an updating module 506, wherein:

the obtaining module 501 is configured to obtain road test operation parameters generated by the vehicle operating under different working conditions and actual road test results of the DPF carbon loading.

The building module 502 is used for building a DPF simulation carbon-loaded model corresponding to the DPF original exhaust carbon-loaded model;

the processing module 503 is configured to process the road test operation parameters under each working condition by using a DPF simulation carbon loading model, so as to obtain DPF carbon loading simulation results corresponding to each working condition;

an analysis module 504, configured to perform data analysis on each path of test operation parameters to obtain a working condition characteristic image of each path of test operation parameters;

the correction module 505 is used for correcting the DPF carbon loading simulation model according to the DPF carbon loading simulation result, the DPF carbon loading actual road test result and the working condition characteristic portrait to obtain a corrected DPF carbon loading simulation model;

and an updating module 506, configured to update the DPF original exhaust carbon loading model based on the corrected calibration parameters of the DPF simulated carbon loading model.

In one embodiment, the analysis module is further configured to perform at least one of frequency analysis, centralized trend analysis, or discrete degree analysis on each road test operation parameter, to obtain a working condition characteristic image of each road test operation parameter.

In one embodiment, the correction module is further configured to select a current operating condition to be processed from a plurality of operating conditions; correcting the DPF carbon loading simulation model based on a DPF carbon loading simulation result, a DPF carbon loading actual road test result and a working condition characteristic portrait which correspond to the current working condition; selecting the next working condition to be processed from the plurality of working conditions as the next current working condition, returning the DPF carbon loading capacity simulation result, the DPF carbon loading capacity actual road test result and the working condition characteristic portrait which correspond to the current working condition, and continuously executing the step of correcting the DPF simulated carbon loading model; and finishing the iterative correction process when the correction of the DPF simulation carbon-loaded model is finished under the last working condition to obtain the corrected DPF simulation carbon-loaded model.

In one embodiment, the correction module is further configured to determine a DPF carbon loading amount simulation sub-result and a DPF carbon loading amount actual road test sub-result corresponding to the same driving mileage under the current working condition; calculating the difference value between the DPF carbon loading capacity simulation sub-result and the DPF carbon loading capacity actual road test sub-result of the same driving mileage; comparing the difference value with a preset difference value; and if the difference is larger than the preset difference, correcting the DPF simulation carbon-loaded model based on the working condition characteristic image of the road test operation sub-parameters.

In one embodiment, the correction module is further configured to determine a pulse spectrum correction region of the DPF simulation carbon-supported model according to the operating condition characteristic image of the road test operation sub-parameter; and adjusting the data in the pulse spectrum correction area according to the difference value.

In one embodiment, the obtaining module is further configured to obtain an engine speed, an oil injection amount, a coolant temperature, an atmospheric pressure, an excess air coefficient, a nitrogen oxygen flow rate, an exhaust temperature, an oxygen flow rate, and an exhaust flow rate.

All or part of each module in the DPF original exhaust carbon loading model calibration device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a terminal or a server, and its internal structure diagram may be as shown in fig. 6. The computer device comprises a processor, a memory, and a communication interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The communication interface of the computer device is used for communicating with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to realize the calibration method of the DPF original exhaust carbon-loaded model.

Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory having a computer program stored therein and a processor that when executing the computer program performs the steps of:

In one embodiment, the processor, when executing the computer program, further performs the steps of: carrying out data analysis on each path of trial operation parameters to obtain a working condition characteristic image of each path of trial operation parameters, and the method comprises the following steps: and respectively analyzing at least one of frequency analysis, centralized trend analysis and discrete degree analysis on each road test operation parameter to obtain a working condition characteristic image of each road test operation parameter.

In one embodiment, the processor, when executing the computer program, further performs the steps of: according to DPF carbon loading capacity simulation result, the actual road test result of DPF carbon loading capacity and working condition characteristic portrait, revise DPF emulation carbon carries the model, obtains the DPF emulation carbon that finishes that revises and carries the model, include: selecting a current working condition to be processed from a plurality of working conditions; correcting the DPF simulated carbon-loaded model based on a DPF carbon loading capacity simulation result, a DPF carbon loading capacity actual road test result and a working condition characteristic portrait corresponding to the current working condition; selecting the next working condition to be processed from the plurality of working conditions as the next current working condition, returning the DPF carbon loading capacity simulation result, the DPF carbon loading capacity actual road test result and the working condition characteristic portrait which correspond to the current working condition, and correcting the DPF carbon loading simulation model to continue to execute the step; and finishing the iterative correction process when the correction of the DPF simulation carbon-loaded model is finished under the last working condition to obtain the corrected DPF simulation carbon-loaded model.

In one embodiment, the processor, when executing the computer program, further performs the steps of: based on DPF carbon loading capacity simulation result, the actual way of DPF carbon loading capacity result that current operating mode corresponds and operating mode characteristic portrait, revise DPF emulation carbon-loaded model, include: determining a DPF carbon loading capacity simulation sub-result and a DPF carbon loading capacity actual road test sub-result corresponding to the same driving mileage under the current working condition; calculating the difference value between the DPF carbon loading capacity simulation sub-result and the DPF carbon loading capacity actual road test sub-result of the same driving mileage; comparing the difference value with a preset difference value; and if the difference value is greater than the preset difference value, correcting the DPF simulation carbon-loaded model based on the working condition characteristic image of the road test operation sub-parameters.

In one embodiment, the processor, when executing the computer program, further performs the steps of: correcting a DPF simulation carbon-loaded model based on a working condition characteristic image of a road test operation sub-parameter, comprising the following steps of: determining a pulse spectrum correction area of the DPF simulation carbon-loaded model according to the working condition characteristic portrait of the road test operation sub-parameters; and adjusting the data in the pulse spectrum correction area according to the size of the difference value.

In one embodiment, the processor, when executing the computer program, further performs the steps of: the acquired road test operation parameters comprise engine speed, fuel injection quantity, coolant temperature, atmospheric pressure, excess air coefficient, nitrogen and oxygen flow, exhaust temperature, oxygen flow and exhaust flow.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, performs the steps of:

In one embodiment, the computer program when executed by the processor further performs the steps of: carrying out data analysis on each way of trial operation parameters to obtain a working condition characteristic image of each way of trial operation parameters, wherein the working condition characteristic image comprises the following steps: and respectively carrying out at least one analysis of frequency analysis, centralized trend analysis or discrete degree analysis on each road test operation parameter to obtain a working condition characteristic image of each road test operation parameter.

In one embodiment, the computer program when executed by the processor further performs the steps of: according to DPF carbon loading capacity simulation result, the actual road test result of DPF carbon loading capacity and working condition characteristic portrait, revise DPF emulation carbon carries the model, obtains the DPF emulation carbon that finishes that revises and carries the model, include: selecting a current working condition to be processed from a plurality of working conditions; correcting the DPF carbon loading simulation model based on a DPF carbon loading simulation result, a DPF carbon loading actual road test result and a working condition characteristic portrait which correspond to the current working condition; selecting the next working condition to be processed from the plurality of working conditions as the next current working condition, returning the DPF carbon loading capacity simulation result, the DPF carbon loading capacity actual road test result and the working condition characteristic portrait which correspond to the current working condition, and correcting the DPF carbon loading simulation model to continue to execute the step; and finishing the iterative correction process when the correction of the DPF simulation carbon-loaded model is finished under the last working condition to obtain the corrected DPF simulation carbon-loaded model.

In one embodiment, the computer program when executed by the processor further performs the steps of: based on DPF carbon loading capacity simulation result, the actual road test result of DPF carbon loading capacity that current operating mode corresponds and operating mode characteristic portrait, revise DPF emulation carbon-loaded model, include: determining a DPF carbon loading capacity simulation sub-result and a DPF carbon loading capacity actual road test sub-result corresponding to the same driving mileage under the current working condition; calculating the difference value between the DPF carbon loading capacity simulation sub-result and the DPF carbon loading capacity actual road test sub-result of the same driving mileage; comparing the difference value with a preset difference value; and if the difference is larger than the preset difference, correcting the DPF simulation carbon-loaded model based on the working condition characteristic image of the road test operation sub-parameters.

In one embodiment, the computer program when executed by the processor further performs the steps of: correcting a DPF simulation carbon-loaded model based on a working condition characteristic image of a road test operation sub-parameter, comprising the following steps of: determining a pulse spectrum correction area of the DPF simulation carbon-loaded model according to the working condition characteristic portrait of the road test operation sub-parameters; and adjusting the data in the pulse spectrum correction area according to the difference value.

In one embodiment, the computer program when executed by the processor further performs the steps of: the acquired road test operation parameters comprise engine speed, fuel injection quantity, coolant temperature, atmospheric pressure, excess air coefficient, nitrogen and oxygen flow, exhaust temperature, oxygen flow and exhaust flow.

In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the steps of:

performing data analysis on each path of trial operation parameters to obtain a working condition characteristic image of each path of trial operation parameters;

In one embodiment, the computer program when executed by the processor further performs the steps of: carrying out data analysis on each path of trial operation parameters to obtain a working condition characteristic image of each path of trial operation parameters, and the method comprises the following steps: and respectively carrying out at least one analysis of frequency analysis, centralized trend analysis or discrete degree analysis on each road test operation parameter to obtain a working condition characteristic image of each road test operation parameter.

In one embodiment, the computer program when executed by the processor further performs the steps of: according to DPF carbon loading capacity simulation result, the actual road test result of DPF carbon loading capacity and operating mode characteristic portrait, revise DPF emulation carbon carries the model, obtains the DPF emulation carbon that finishes of revising and carries the model, include: selecting a current working condition to be processed from a plurality of working conditions; correcting the DPF carbon loading simulation model based on a DPF carbon loading simulation result, a DPF carbon loading actual road test result and a working condition characteristic portrait which correspond to the current working condition; selecting the next working condition to be processed from the plurality of working conditions as the next current working condition, returning the DPF carbon loading capacity simulation result, the DPF carbon loading capacity actual road test result and the working condition characteristic portrait which correspond to the current working condition, and correcting the DPF carbon loading simulation model to continue to execute the step; and finishing the iterative correction process when the correction of the DPF simulation carbon loading model is finished under the last working condition to obtain the corrected DPF simulation carbon loading model.

In one embodiment, the computer program when executed by the processor further performs the steps of: the obtained road test operation parameters comprise engine speed, fuel injection quantity, coolant temperature, atmospheric pressure, excess air coefficient, nitrogen and oxygen flow, exhaust temperature, oxygen flow and exhaust flow.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, databases, or other media used in the embodiments provided herein can include at least one of non-volatile and volatile memory. The nonvolatile Memory may include a Read-Only Memory (ROM), a magnetic tape, a floppy disk, a flash Memory, an optical Memory, a high-density embedded nonvolatile Memory, a resistive Random Access Memory (ReRAM), a Magnetic Random Access Memory (MRAM), a Ferroelectric Random Access Memory (FRAM), a Phase Change Memory (PCM), a graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases involved in the embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.

All possible combinations of the technical features in the above embodiments may not be described for the sake of brevity, but should be considered as being within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A DPF original exhaust carbon loading model calibration method is characterized by comprising the following steps:

respectively processing road test operation parameters under each working condition by adopting the DPF simulation carbon loading model to obtain DPF carbon loading capacity simulation results respectively corresponding to each working condition;

and updating the DPF original exhaust carbon loading model based on the corrected calibration parameters of the DPF simulation carbon loading model.

2. The method of claim 1, wherein the analyzing the data of each trial-run parameter to obtain the working condition characteristic image of each trial-run parameter comprises:

and respectively carrying out at least one analysis of frequency analysis, centralized trend analysis or discrete degree analysis on each road test operation parameter to obtain a working condition characteristic image of each road test operation parameter.

3. The method of claim 1, wherein the step of correcting the DPF carbon loading simulation model according to the DPF carbon loading simulation result, the DPF carbon loading actual road test result and the operating condition characteristic image to obtain a corrected DPF carbon loading simulation model comprises the steps of:

and finishing the iterative correction process when the correction of the DPF simulation carbon loading model is finished under the last working condition to obtain the corrected DPF simulation carbon loading model.

4. The method of claim 3, wherein the road test operation parameters under each working condition comprise road test operation sub-parameters corresponding to a plurality of driving mileage respectively, and one road test operation sub-parameter corresponds to one DPF carbon loading simulation sub-result; the actual road test result of the DPF carbon loading capacity under each working condition comprises actual road test sub-results of the DPF carbon loading capacity corresponding to a plurality of driving miles respectively;

based on the DPF carbon loading capacity simulation result that current operating mode corresponds, the actual way of DPF carbon loading capacity is tried on results and operating mode characteristic is portrait, revises DPF emulation carbon-loaded model, include:

calculating the difference value between the DPF carbon loading capacity simulation sub-result and the DPF carbon loading capacity actual road test sub-result of the same driving mileage;

comparing the difference value with the preset difference value;

5. The method according to claim 4, wherein the correcting the DPF simulation carbon-loaded model based on the working condition characteristic image of the road test operation sub-parameters comprises:

6. The method of any of claims 1-5, wherein the road test operating parameters include engine speed, fuel injection, coolant temperature, atmospheric temperature, barometric pressure, excess air factor, flow of nitrogen and oxygen, exhaust temperature, flow of oxygen, flow of exhaust.

7. The calibration device for the original carbon-loaded DPF model is characterized by comprising the following components:

the acquisition module is used for acquiring road test operation parameters generated by the operation of the vehicle under different working conditions and DPF carbon loading capacity actual road test results;

the analysis module is used for carrying out data analysis on each path of test operation parameter to obtain a working condition characteristic image of each path of test operation parameter;

and the updating module is used for updating the DPF original exhaust carbon loading model based on the corrected calibration parameters of the DPF simulation carbon loading model.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.

9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 6 when executed by a processor.