Offline simulation method, device, equipment and medium for gaseous emissions of vehicles

Abstract

This invention discloses an offline simulation method, apparatus, device, and medium for vehicle gaseous emissions. Its features include: loading offline test data of a target vehicle and offline model parameters of a pre-built offline post-processing model; running a preset simulation test program based on the offline test data and the offline model parameters to obtain the offline simulated exhaust emission results of the target vehicle; obtaining the actual exhaust emission results of the target vehicle; determining the simulation error of the target vehicle based on the offline simulated exhaust emission results and the actual exhaust emission results; and completing the offline simulation of the target vehicle if the simulation error meets a preset error condition. This invention achieves rapid and efficient simulation of vehicle gaseous emissions using a pre-built offline post-processing model, improving the efficiency and accuracy of vehicle gaseous emission simulation.

Description

Technical Field

[0001] This invention relates to the field of vehicle testing, and more particularly to an offline simulation method, apparatus, equipment, and medium for vehicle gaseous emissions. Background Technology

[0002] When a vehicle is running, the engine burns fuel, producing various types of gaseous emissions, which are released into the air. During the development of automotive control technology, it is necessary to determine the indicators for each gaseous emission from fuel combustion to regulate the vehicle's development plan. In existing technologies, due to the highly complex chemical reactions involved in gasoline engine combustion, actual test vehicles are typically used on test benches to collect gaseous emissions data. However, because each test uses real combustion, the data collection process requires a considerable amount of time for detection and analysis on the test platform, and there is also a waiting period for the test vehicle to prepare for the next test. Therefore, existing technologies result in long single-test simulation times for vehicle gaseous emissions, a limited number of effective tests, and low simulation testing efficiency. Summary of the Invention

[0003] This invention provides an offline simulation method, apparatus, equipment, and medium for vehicle gaseous emissions, enabling efficient and accurate testing of vehicle gaseous emissions.

[0004] According to one aspect of the present invention, an offline simulation method for vehicle gaseous emissions is provided, comprising:

[0005] Load the offline test data of the target vehicle and the offline model parameters of the pre-built offline post-processing model;

[0006] Run a preset simulation test program based on the offline test data and the offline model parameters to obtain the offline simulation exhaust results of the target vehicle;

[0007] Obtain the actual exhaust emission results of the target vehicle, and determine the simulation error of the target vehicle based on the offline simulation exhaust emission results and the actual exhaust emission results;

[0008] If the simulation error meets the preset error condition, the offline simulation of the target vehicle is completed.

[0009] According to another aspect of the present invention, an offline simulation apparatus for vehicle gaseous emissions is provided, comprising:

[0010] The data loading module is used to load the offline test data of the target vehicle and the offline model parameters of the pre-built offline post-processing model;

[0011] The post-processing model execution module is used to run a preset simulation test program based on the offline test data and the offline model parameters to obtain the offline simulation exhaust results of the target vehicle.

[0012] The error calculation module is used to obtain the actual exhaust results of the target vehicle and determine the simulation error of the target vehicle based on the offline simulation exhaust results and the actual exhaust results.

[0013] The result verification module is used to complete the offline simulation of the target vehicle if the simulation error meets the preset error conditions.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the offline simulation method for vehicle gaseous emissions according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the offline simulation method for vehicle gaseous emissions according to any embodiment of the present invention.

[0019] The technical solution of this invention loads offline test data of the target vehicle and offline model parameters of a pre-built offline post-processing model. It loads the corresponding model data and test data into the testing platform, enabling rapid testing through the offline post-processing model, thus improving the simulation efficiency of vehicle gaseous emissions. Based on the offline test data and offline model parameters, a preset simulation test program is run to obtain the offline simulated exhaust emission results of the target vehicle. The vehicle is then simulated on the testing platform to determine the corresponding simulation test results. This allows for repeated testing, reducing the test interval between each offline simulation test and further improving the efficiency of offline simulation testing. Finally, the actual exhaust emission results of the target vehicle are obtained, and based on the offline simulation... The simulation error of the target vehicle is determined by comparing the actual exhaust emission results with those of the real vehicle. This simulation error helps determine the simulation error of the offline post-processing model, reducing the error between the simulation and the actual test, and improving the accuracy of the simulation. If the simulation error meets a preset error condition, the offline simulation of the target vehicle is completed. When the preset error condition is met, the iteration of the offline post-processing model is stopped, and the offline simulation of the target vehicle is completed. This achieves rapid and efficient simulation of vehicle gaseous emissions using a pre-built offline post-processing model, solving the technical problem of low efficiency in simulating vehicle gaseous emissions in existing technologies, and improving the efficiency and accuracy of vehicle gaseous emission simulation.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of an offline simulation method for vehicle gaseous emissions provided in Embodiment 1 of the present invention;

[0023] Figure 2 This is a flowchart of another offline simulation method for vehicle gaseous emissions provided in Embodiment 2 of the present invention;

[0024] Figure 3 A flowchart illustrating another offline simulation method for vehicle gaseous emissions provided in this embodiment of the invention;

[0025] Figure 4This is a schematic diagram of the structure of an offline simulation device for vehicle gaseous emissions provided in Embodiment 3 of the present invention;

[0026] Figure 5 This is a schematic diagram of the structure of an electronic device for implementing the offline simulation method for vehicle gaseous emissions according to embodiments of the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0028] Example 1

[0029] Figure 1 This is a flowchart of an offline simulation method for vehicle gaseous emissions provided in Embodiment 1 of the present invention. This embodiment is applicable to simulating vehicle gaseous emissions during the vehicle development stage. The method can be executed by an offline simulation device for vehicle gaseous emissions, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0030] S110, Load the offline test data of the target vehicle and the offline model parameters of the pre-built offline post-processing model.

[0031] Offline test data can be data simulating fuel combustion emissions from the target vehicle.

[0032] The offline post-processing model can be a pre-built simulation model used to simulate the gaseous emissions from the target vehicle.

[0033] The offline model parameters can be the model parameters of the offline post-processing model.

[0034] Optionally, after obtaining the offline test data and offline model parameters, the offline test data and offline model parameters are loaded into the test platform, and the target vehicle is simulated and tested using the test platform based on the offline test data and offline model parameters. The test platform can use Matlab (Matrix Laboratory), where the simulation model is built using the Simulink simulation tool.

[0035] Specifically, offline test data and offline model parameters for simulation experiments of gaseous emissions from the target vehicle are loaded into the test platform.

[0036] S120. Run a preset simulation test program based on the offline test data and the offline model parameters to obtain the offline simulation exhaust results of the target vehicle.

[0037] The simulation test program can be a pre-written program for simulation.

[0038] Among them, the offline simulation tail emission results can be obtained by the test platform running a simulation test program based on offline test data and offline model parameters to obtain simulated gaseous emissions.

[0039] Specifically, in the testing platform, a pre-written simulation test program is run to calculate and output simulated gaseous emissions based on offline test data and offline model parameters.

[0040] S130. Obtain the actual exhaust emission results of the target vehicle, and determine the simulation error of the target vehicle based on the offline simulation exhaust emission results and the actual exhaust emission results.

[0041] Among them, the actual vehicle exhaust results can be the gaseous emissions emitted by the test vehicle at the test speed during the simulation test on the test bench.

[0042] The simulation error can be the difference between the exhaust emission results of the actual vehicle and the exhaust emission results of the offline simulation.

[0043] Specifically, after obtaining the offline simulation exhaust results, the actual vehicle exhaust results are obtained from the test bench of the test vehicle to determine the simulation error between the offline simulation exhaust results and the actual vehicle exhaust results.

[0044] S140. If the simulation error meets the preset error condition, the offline simulation of the target vehicle is completed.

[0045] The preset error conditions can be pre-set conditions used to judge the accuracy of offline simulation. It should be noted that the preset error conditions can be used to confirm the accuracy of the simulation error. If the accuracy of the simulation error meets the standard, it is considered that the simulation error meets the preset error conditions; if the accuracy of the simulation error does not meet the standard, it is considered that the simulation error does not meet the preset error conditions.

[0046] Specifically, the simulation error is obtained, the preset error conditions corresponding to the simulation error are determined, and it is judged whether the simulation error meets the preset error conditions. If the simulation error meets the preset error conditions, the offline simulation of the target vehicle is considered to be completed.

[0047] Optionally, in another alternative embodiment of the present invention, after the offline simulation of the target vehicle is completed, the following steps are included:

[0048] The offline model parameters are calibrated and uploaded.

[0049] Optionally, after the offline simulation of the target vehicle is completed on the test platform, the offline model parameters of the offline post-processing model at this time meet the simulation of vehicle gaseous emissions, and then the offline model parameters are calibrated and uploaded and delivered.

[0050] The technical solution of this invention loads offline test data of the target vehicle and offline model parameters of a pre-built offline post-processing model. It loads the corresponding model data and test data into the testing platform, enabling rapid testing through the offline post-processing model, thus improving the simulation efficiency of vehicle gaseous emissions. Based on the offline test data and offline model parameters, a preset simulation test program is run to obtain the offline simulated exhaust emission results of the target vehicle. The vehicle is then simulated on the testing platform to determine the corresponding simulation test results. This allows for repeated testing, reducing the test interval between each offline simulation test and further improving the efficiency of offline simulation testing. Finally, the actual exhaust emission results of the target vehicle are obtained, and based on the offline simulation... The simulation error of the target vehicle is determined by comparing the actual exhaust emission results with those of the real vehicle. This simulation error helps determine the simulation error of the offline post-processing model, reducing the error between the simulation and the actual test, and improving the accuracy of the simulation. If the simulation error meets a preset error condition, the offline simulation of the target vehicle is completed. When the preset error condition is met, the iteration of the offline post-processing model is stopped, and the offline simulation of the target vehicle is completed. This achieves rapid and efficient simulation of vehicle gaseous emissions using a pre-built offline post-processing model, solving the technical problem of low efficiency in simulating vehicle gaseous emissions in existing technologies, and improving the efficiency and accuracy of vehicle gaseous emission simulation.

[0051] Example 2

[0052] Figure 2 This is a flowchart of another offline simulation method for vehicle gaseous emissions provided in Embodiment 2 of the present invention. The relationship between this embodiment and the above embodiments is that, after the simulation error does not meet the preset error conditions, a specific method is used to continue simulation testing through a testing platform. Figure 2 As shown, the offline simulation method for the vehicle's gaseous emissions includes:

[0053] S210, Load the offline test data of the target vehicle and the offline model parameters of the pre-built offline post-processing model.

[0054] Optionally, in another optional embodiment of the present invention, before loading the offline test data of the target vehicle and the offline model parameters of the offline post-processing model, the method further includes:

[0055] Based on the emission results of the target vehicle, determine the raw measurement data of the target vehicle; based on the raw measurement data, determine the offline test data of the target vehicle.

[0056] The emission results of the target vehicle can be obtained from the engine emissions of the target vehicle through an emission analyzer.

[0057] The raw measurement data can be obtained by communicating the emission results of the target vehicle to the engine test platform.

[0058] Specifically, in the engine test platform, the target vehicle is used to conduct actual engine fuel combustion tests. The emission results of the target vehicle are collected by an emission analyzer and uploaded to the engine test platform for data acquisition. The original measurement data of the target vehicle is determined, and the offline test data of the target vehicle is determined based on the original measurement data.

[0059] Optionally, in another optional embodiment of the present invention, determining the original measurement data of the target vehicle based on the emission results of the target vehicle includes:

[0060] Load the raw emission results and after-treatment emission results of the target vehicle; perform data standardization and format conversion on the raw emission results and after-treatment emission results to obtain the raw measurement data of the target vehicle.

[0061] The raw emissions results can be the engine emissions results collected by the analyzer at the target vehicle;

[0062] Among them, the after-treatment emission results can be the emission results after processing the engine emission results.

[0063] Among them, standardized data collection can be a collection method that collects emission results according to a pre-set standardized data format.

[0064] Format conversion can be a pre-set method for converting the storage format of data.

[0065] Specifically, in the test platform, the raw emission results and after-treatment emission results of the target vehicle are loaded. The raw emission results and after-treatment emission results are collected through a preset data standardization acquisition method, and the collected data are converted to obtain the raw measurement data of the target vehicle.

[0066] Optionally, in another optional embodiment of the present invention, determining the offline test data of the target vehicle based on the original measurement data includes:

[0067] Acquire test operation data of the target vehicle; perform data validity screening on the test operation data and the raw measurement data to determine valid operation data and valid measurement data; process the valid operation data and valid measurement data according to a preset data processing method to determine offline test data.

[0068] Among them, the test operation data can be the test data of the target vehicle obtained through the engine electronic control system of the target vehicle.

[0069] Among them, data validity screening can be used to screen valid data from experimental run data and raw measurement data.

[0070] Valid run data can be experimental run data that has passed data validity screening. Valid measurement data can be raw measurement data that has passed data validity screening.

[0071] The data processing method can be a pre-set method for data processing on the test platform. Optionally, when performing simulation tests on the test platform using an offline post-processing model, data processing needs to be performed according to the requirements of the offline post-processing model for the input data. Variable names that the offline post-processing model can recognize are defined, and data settings are set into the corresponding variable names. These variable names can include at least one of the following: engine speed, vehicle speed, air-fuel ratio signal, exhaust temperature, exhaust flow rate, exhaust pressure, and various gaseous emissions from the engine's original emissions.

[0072] Specifically, the test operation data of the target vehicle is obtained through the engine electronic control system of the target vehicle. The test operation data and the original test call are screened for data validity to obtain valid operation data and valid measurement data. The valid operation data and valid test data are processed by the preset data processing method to obtain offline test data.

[0073] Optionally, in another optional embodiment of the present invention, the step of screening the experimental run data and the original measurement data for data validity to determine valid run data and valid measurement data includes:

[0074] Obtain the engine running time of the target vehicle; align the test running data and the original measurement data along the time axis; based on the engine running time, extract the valid running data and the valid measurement data corresponding to the engine running time from the time-aligned test running data and the original measurement data.

[0075] The engine running time can be the start and end time of the target vehicle's operation on the test platform.

[0076] Time axis alignment involves arranging the time of experimental data acquisition and the time of original measurement data in a one-to-one correspondence. It should be noted that during simulation testing, because the acquisition methods for experimental data and original measurement data are different, the acquisition times for the acquired experimental data and original measurement data are also different. Therefore, it is necessary to align the experimental data and original measurement data on the same time axis, ensuring a one-to-one correspondence between experimental data and original measurement data at the same time point.

[0077] Specifically, the engine running time of the target vehicle in the test platform is obtained, and the test running data and the original measurement data are aligned one by one on the same time axis. The start time and end time of the engine running of the target vehicle in the test platform are determined based on the engine running time. Data is extracted from the test running data and the original measurement data on the same time axis according to the start time and end time to determine the valid running data and valid measurement data corresponding to the engine running time.

[0078] S220. Run a preset simulation test program based on the offline test data and the offline model parameters to obtain the offline simulation exhaust results of the target vehicle.

[0079] S230. Obtain the actual exhaust emission results of the target vehicle, and determine the simulation error of the target vehicle based on the offline simulation exhaust emission results and the actual exhaust emission results.

[0080] S240. If the simulation error meets or does not meet the preset error condition, adjust the offline model parameters according to the simulation error until the simulation error of the target vehicle meets the preset error condition.

[0081] Specifically, the simulation error is obtained, the preset error condition corresponding to the simulation error is determined, and it is determined whether the simulation error meets the preset error condition. If the simulation error does not meet the preset error condition, the offline model parameters are adjusted according to the simulation error, and the preset simulation test program is run again according to the adjusted offline model parameters and the number of offline test data until the simulation error of the target vehicle meets the preset error condition, and then the offline simulation of the target vehicle is completed.

[0082] The technical solution of this invention loads offline test data of the target vehicle and offline model parameters of a pre-built offline post-processing model. It loads the corresponding model data and test data into a testing platform, enabling rapid testing through the offline post-processing model, thus improving the simulation efficiency of vehicle gaseous emissions. Based on the offline test data and offline model parameters, a preset simulation test program is run to obtain the offline simulated exhaust emission results of the target vehicle. The vehicle is then simulated on the testing platform to determine the corresponding simulation test results. This allows for repeated testing, reducing the test interval between each offline simulation test and further improving the efficiency of offline simulation testing. Finally, the actual exhaust emission results of the target vehicle are obtained, and based on the offline simulated exhaust emission results and the actual exhaust emission results, the target vehicle's emissions are determined. The simulation error of the vehicle can be used to determine the simulation error of the offline post-processing model, reduce the error between the simulation and the actual test, and improve the accuracy of the simulation. If the simulation error meets or does not meet the preset error condition, the offline model parameters are adjusted according to the simulation error until the simulation error of the target vehicle meets the preset error condition. If the preset error condition is not met, the offline post-processing model continues to iterate until the offline simulation of the target vehicle is completed. This realizes the rapid and efficient simulation of vehicle gaseous emissions through a pre-built offline post-processing model, solves the technical problem of low efficiency in the simulation of vehicle gaseous emissions in the prior art, and improves the efficiency and accuracy of vehicle gaseous emission simulation.

[0083] Optional, Figure 3 A flowchart illustrating another offline simulation method for vehicle gaseous emissions provided in an embodiment of the present invention.

[0084] S310, offline post-processing model integration. The post-processing model framework is integrated into Matlab, and then the pre-created offline model parameters are integrated into SimLink.

[0085] S320, offline simulation program development. The simulation test program is written in Matlab.

[0086] S330, Data Acquisition and Processing of the Real Vehicle Test Platform. When testing the emissions results of the target vehicle, the raw emissions results and post-processed emissions results collected by the emissions analyzer need to be communicated to the real vehicle test platform. A format conversion program is edited using Python software to convert the DAT format emissions test files collected by the real vehicle test platform into a MAT format file that can be recognized by MATLAB.

[0087] Furthermore, a data processing program was edited in MATLAB to align the raw measurement data and test run data along the time axis. Based on the engine running time, valid running data and valid measurement data corresponding to the engine running time were extracted from the time-aligned test run data and raw measurement data. The valid running data and valid measurement data were then processed according to the preset data processing method to determine the offline test data.

[0088] S340, Load the offline test data and offline model parameters of the target vehicle.

[0089] S350. Output offline simulation tailrace results. In MATLAB, based on offline test data and offline model parameters, run the offline post-processing model for 10 seconds to output the offline simulation tailrace results, and save the offline simulation tailrace results as a new simulation result file.

[0090] S360. Model Accuracy Judgment. Obtain the actual exhaust emission results of the target vehicle. Based on the offline simulation exhaust emission results and the actual vehicle exhaust emission results, determine the simulation error of the target vehicle and judge whether the simulation error meets the preset error conditions. If the simulation error meets the preset error conditions, proceed to S380. If the simulation error does not meet the preset error conditions, proceed to S370.

[0091] S370. For the output offline simulation tail row results, identify the areas with out-of-tolerance results in the offline simulation tail row results, adjust and optimize the offline model parameters, and then execute S350.

[0092] S380, virtual calibration offline model parameters delivered for use.

[0093] The technical solution of this invention enables rapid and efficient simulation of vehicle gaseous emissions through a pre-built offline post-processing model, solving the technical problem of low efficiency in simulating vehicle gaseous emissions in the prior art, and improving the efficiency and accuracy of vehicle gaseous emission simulation.

[0094] Example 3

[0095] Figure 4 This is a schematic diagram of the structure of an offline simulation device for vehicle gaseous emissions provided in Embodiment 3 of the present invention. Figure 4 As shown, the device includes: a data loading module 410, a post-processing model running module 420, an error calculation module 430, and a result verification module 440, wherein,

[0096] The data loading module 410 is used to load the offline test data of the target vehicle and the offline model parameters of the pre-built offline post-processing model;

[0097] The post-processing model running module 420 is used to run a preset simulation test program based on the offline test data and the offline model parameters to obtain the offline simulation exhaust results of the target vehicle.

[0098] Error calculation module 430: Obtain the actual exhaust results of the target vehicle, and determine the simulation error of the target vehicle based on the offline simulation exhaust results and the actual exhaust results;

[0099] The result verification module 440 is used to complete the offline simulation of the target vehicle if the simulation error meets the preset error conditions.

[0100] The technical solution of this invention loads offline test data of the target vehicle and offline model parameters of a pre-built offline post-processing model. It loads the corresponding model data and test data into the testing platform, enabling rapid testing through the offline post-processing model, thus improving the simulation efficiency of vehicle gaseous emissions. Based on the offline test data and offline model parameters, a preset simulation test program is run to obtain the offline simulated exhaust emission results of the target vehicle. The vehicle is then simulated on the testing platform to determine the corresponding simulation test results. This allows for repeated testing, reducing the test interval between each offline simulation test and further improving the efficiency of offline simulation testing. Finally, the actual exhaust emission results of the target vehicle are obtained, and based on the offline simulation... The simulation error of the target vehicle is determined by comparing the actual exhaust emission results with those of the real vehicle. This simulation error helps determine the simulation error of the offline post-processing model, reducing the error between the simulation and the actual test, and improving the accuracy of the simulation. If the simulation error meets a preset error condition, the offline simulation of the target vehicle is completed. When the preset error condition is met, the iteration of the offline post-processing model is stopped, and the offline simulation of the target vehicle is completed. This achieves rapid and efficient simulation of vehicle gaseous emissions using a pre-built offline post-processing model, solving the technical problem of low efficiency in simulating vehicle gaseous emissions in existing technologies, and improving the efficiency and accuracy of vehicle gaseous emission simulation.

[0101] Optionally, the device further includes a backpropagation module, wherein:

[0102] The backpropagation module is used to adjust the offline model parameters according to the simulation error if the simulation error meets or does not meet the preset error condition, until the simulation error of the target vehicle meets the preset error condition.

[0103] Optionally, the device further includes a data measurement module and a data processing module, wherein:

[0104] The data measurement module is used to determine the raw measurement data of the target vehicle based on the emission results of the target vehicle;

[0105] The data processing module is used to determine the offline test data of the target vehicle based on the original measurement data.

[0106] Optionally, the data measurement module is specifically used for:

[0107] Load the raw emissions and after-treatment emissions of the target vehicle;

[0108] The raw emission results and post-treatment emission results are collected and format-converted in a standardized manner to obtain the raw measurement data of the target vehicle.

[0109] Optionally, the data processing module is specifically used for:

[0110] Obtain test operation data of the target vehicle;

[0111] The experimental data and the raw measurement data are screened for validity to determine the valid experimental data and valid measurement data;

[0112] The effective operating data and effective measurement data are processed according to a preset data processing method to determine the offline test data.

[0113] Optionally, the data measurement module is further used for:

[0114] Obtain the engine running time of the target vehicle;

[0115] Align the test run data and the original measurement data along the time axis;

[0116] Based on the engine running time, the effective running data and the effective measurement data corresponding to the engine running time are extracted from the test running data and the original measurement data aligned with the time axis.

[0117] Optionally, the device further includes a parameter uploading module, wherein:

[0118] The parameter upload module is used to calibrate and upload the offline model parameters.

[0119] The offline simulation device for vehicle gaseous emissions provided in this embodiment of the invention can execute the offline simulation method for vehicle gaseous emissions provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0120] Example 4

[0121] Figure 5A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0122] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0123] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0124] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as offline simulation methods for vehicle gaseous emissions.

[0125] In some embodiments, the offline simulation method for vehicle gaseous emissions can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the offline simulation method for vehicle gaseous emissions described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the offline simulation method for vehicle gaseous emissions by any other suitable means (e.g., by means of firmware).

[0126] Various embodiments of the methods and techniques described above herein can be implemented in digital electronic circuit methods, integrated circuit methods, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), methods-on-a-chip (SOCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable method including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage method, at least one input device, and at least one output device, and transmitting data and instructions to the storage method, the at least one input device, and the at least one output device.

[0127] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0128] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution method, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor methods, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0129] To provide interaction with a user, the methods and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0130] The methods and techniques described herein can be implemented in computing methods that include backend components (e.g., as a data server), or computing methods that include middleware components (e.g., an application server), or computing methods that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the methods and techniques described herein), or any combination of such backend, middleware, or frontend components. The components of the methods can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0131] Computational methods can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0132] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0133] Example 5

[0134] This embodiment provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the program implements the steps of the offline simulation method for vehicle gaseous emissions as provided in any embodiment of the present invention. The method includes:

[0135] Load the offline test data of the target vehicle and the offline model parameters of the pre-built offline post-processing model;

[0136] Run a preset simulation test program based on the offline test data and the offline model parameters to obtain the offline simulation exhaust results of the target vehicle;

[0137] Obtain the actual exhaust emission results of the target vehicle, and determine the simulation error of the target vehicle based on the offline simulation exhaust emission results and the actual exhaust emission results;

[0138] If the simulation error meets the preset error condition, the offline simulation of the target vehicle is completed.

[0139] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor method, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution method, apparatus, or device.

[0140] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in conjunction with instruction execution methods, apparatuses, or devices.

[0141] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0142] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0143] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computing device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0144] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0145] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An offline simulation method for vehicle gaseous emissions, characterized in that, include: Load the offline test data of the target vehicle and the offline model parameters of the pre-built offline post-processing model; Run a preset simulation test program based on the offline test data and the offline model parameters to obtain the offline simulation exhaust results of the target vehicle; Obtain the actual exhaust emission results of the target vehicle, and determine the simulation error of the target vehicle based on the offline simulation exhaust emission results and the actual exhaust emission results; If the simulation error meets the preset error condition, the offline simulation of the target vehicle is completed. After determining the simulation error of the target vehicle based on the offline simulation exhaust results and the actual vehicle exhaust results, the method further includes: If the simulation error does not meet the preset error condition, the offline model parameters are adjusted according to the simulation error until the simulation error of the target vehicle meets the preset error condition. Before loading the offline test data of the target vehicle and the offline model parameters of the pre-built offline post-processing model, the following is also included: The raw measurement data of the target vehicle are determined based on the emission results of the target vehicle; The offline test data of the target vehicle is determined based on the original measurement data; The determination of the raw measurement data for the target vehicle based on its emission results includes: Load the raw emissions and after-treatment emissions of the target vehicle; The raw emission results and post-treatment emission results are collected and format-converted in a standardized manner to obtain the raw measurement data of the target vehicle; The process of determining the offline test data of the target vehicle based on the original measurement data includes: Obtain test operation data of the target vehicle; The experimental data and the raw measurement data are screened for validity to determine the valid experimental data and valid measurement data; The effective operational data and effective measurement data are processed according to a preset data processing method to determine the offline test data; The process of screening the experimental data and the raw measurement data for data validity to determine valid experimental data and valid measurement data includes: Obtain the engine running time of the target vehicle; Align the test run data and the original measurement data along the time axis; Based on the engine running time, the effective running data and the effective measurement data corresponding to the engine running time are extracted from the test running data and the original measurement data aligned with the time axis.

2. The method according to claim 1, characterized in that, After completing the offline simulation of the target vehicle, the following is included: The offline model parameters are calibrated and uploaded.

3. An offline simulation device for vehicle gaseous emissions, characterized in that, include: The data loading module is used to load the offline test data of the target vehicle and the offline model parameters of the offline post-processing model; The post-processing model running module is used to run a preset simulation test program based on the offline test data and the offline model parameters to obtain the offline simulation exhaust results of the target vehicle. The error calculation module is used to obtain the actual exhaust results of the target vehicle and determine the simulation error of the target vehicle based on the offline simulation exhaust results and the actual exhaust results. The result verification module is used to complete the offline simulation of the target vehicle if the simulation error meets the preset error conditions. The device further includes a backpropagation module, wherein: The backpropagation module is used to adjust the offline model parameters according to the simulation error if the simulation error meets or does not meet the preset error condition, until the simulation error of the target vehicle meets the preset error condition. The device further includes a data measurement module and a data processing module, wherein: The data measurement module is used to determine the raw measurement data of the target vehicle based on the emission results of the target vehicle; The data processing module is used to determine the offline test data of the target vehicle based on the original measurement data; The data measurement module is specifically used for: Load the raw emissions and after-treatment emissions of the target vehicle; The raw emission results and post-treatment emission results are collected and format-converted in a standardized manner to obtain the raw measurement data of the target vehicle; The data processing module is specifically used for: Obtain test operation data of the target vehicle; The experimental data and the raw measurement data are screened for validity to determine the valid experimental data and valid measurement data; The effective operational data and effective measurement data are processed according to a preset data processing method to determine the offline test data; The data measurement module is also specifically used for: Obtain the engine running time of the target vehicle; Align the test run data and the original measurement data along the time axis; Based on the engine running time, the effective running data and the effective measurement data corresponding to the engine running time are extracted from the test running data and the original measurement data aligned with the time axis.

4. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the offline simulation method for vehicle gaseous emissions as described in any one of claims 1-2.

5. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the offline simulation method for vehicle gaseous emissions as described in any one of claims 1-2.

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