Vehicle diesel engine bench simulation emission test method, system, device and medium

Abstract

The invention provides a vehicle diesel engine bench simulation emission test method, system, device and medium, and belongs to the bench test technology field, a test bench and a test device are configured, a flowmeter and an analyzer are calibrated through a linear regression equation, and a mapping relation between a measured value and an output quantity is established; an engine transient working condition model is constructed based on real vehicle data, and mapping of the rack control process and the real vehicle operation working condition is achieved; configuring the rotating speed, the torque, the air inlet temperature and the air inlet humidity controlled by the rack as boundary conditions, evaluating the control following performance through a correlation coefficient calculation mode, and verifying the environmental parameter consistency based on a mean value deviation; calculating the exhaust flow, and configuring measurement data based on the intake flow and the fuel consumption; executing a transient test, and obtaining real-time data of an engine running state and discharged pollutants; and under the condition that the double boundary condition constraints are met, carrying out equivalence analysis on a rack and a real vehicle emission result.

Description

Technical Field

[0001] This invention belongs to the field of bench testing technology, specifically relating to a bench simulation emission test method, system, equipment, and medium for automotive diesel engines. Background Technology

[0002] Currently, vehicle exhaust emissions have become a consideration in environmental governance. Real-world vehicle emissions assessment primarily relies on Portable Emissions Measurement Systems (PEMS) to test vehicle pollutant emissions in real-world conditions. PEMS consists of a series of testing devices and offers advantages such as high precision and accuracy, making it suitable for scientific research on the characteristics of vehicle emissions in real-world driving.

[0003] However, the key to PEMS road testing lies in its test conditions being entirely based on real-world driving environments. These conditions are influenced by traffic conditions, driver behavior, and environmental factors, exhibiting significant randomness and non-reproducibility compared to fixed laboratory cycles. Furthermore, existing testing equipment contains measurement errors, affecting the accuracy of emissions tests. Traditional bench testing struggles to accurately simulate the complex and variable operating conditions of real vehicles, leading to significant deviations between test results and actual vehicle emissions. During transient engine operation, the combustion phase angle may deviate from the calibration range, and sudden changes in parameters such as intake air temperature and humidity can cause fluctuations in pollutant concentrations, impacting the stability of the testing process and the accuracy of the data. Summary of the Invention

[0004] This invention provides a bench simulation emission test method for automotive diesel engines. The method can accurately reproduce the dynamic operating conditions in PEMS road tests in a laboratory environment, thereby overcoming the randomness and non-reproducibility problems of actual road tests.

[0005] The methods include: S101: Configure the test bench and test equipment, calibrate the flow meter and analyzer through linear regression equation, and establish the mapping relationship between the measured value and the output; S102: Construct an engine transient operating condition model based on real vehicle data to realize the mapping between the bench control process and the real vehicle operating conditions; S103: Configure the speed, torque, intake air temperature, and humidity of the test bench as boundary conditions, evaluate the control tracking performance by calculating the correlation coefficient, and verify the consistency of environmental parameters based on the mean deviation. S104: Calculate exhaust flow rate and configure measurement data based on intake flow rate and fuel consumption; S105: Perform transient tests to obtain real-time data on engine operating status and pollutant emissions; S106: Under the constraint of dual boundary conditions, conduct an equivalence analysis of bench and real vehicle emission results.

[0006] Preferably, step S101 specifically includes: performing linearization checks on the air flow meter and the fuel consumption meter; performing correlation checks between the air flow and the output analog quantity on the air flow meter; performing correlation checks between the fuel consumption and the output analog quantity on the fuel consumption meter; and performing linearization and leakage checks on the direct sampling analyzer. The formula for calculating the linearization check is: y=a1x+a0 In the formula: y is the actual value, a1 is the slope of the regression line, x is the baseline value, and a0 is the intercept of the regression line.

[0007] Preferably, step S102 specifically includes: By collecting transient data on engine speed, torque, intake air temperature, intake air humidity, exhaust air temperature and fuel consumption during real vehicle road tests, a multi-dimensional dynamic operating condition database containing time series characteristics is established. The dynamic operating condition database is used to extract features using machine learning algorithms to generate transient operating condition curves that highly match the actual vehicle operating patterns. By comparing the test bench operating parameters with the actual vehicle operating condition curves in real time, the load and intake conditions of the dynamometer are adjusted to ensure that the time-domain distribution deviation of the speed and torque of the test bench control process from that of the actual vehicle operating condition is less than the preset time-domain deviation threshold.

[0008] Preferably, step S103 specifically includes: Based on real vehicle PEMS data, speed and torque environmental parameter operating condition curves are constructed, and bench control parameters are corrected in real time. Define the first type of boundary conditions and the first type of boundary conditions. The first type of boundary conditions includes: speed and torque boundary conditions; The second type of boundary conditions includes: intake air temperature, intake air humidity, exhaust air temperature, and exhaust flow rate boundary conditions; Configure the first type of boundary conditions so that the speed correlation is greater than the preset speed threshold coefficient and the torque correlation is greater than the preset torque threshold coefficient; In configuring the second type of boundary conditions, the deviation of the average parameter value is less than the preset mean deviation threshold.

[0009] Preferably, the formula for calculating the exhaust flow rate in step S104 is:

[0010] In the formula: q exh q represents exhaust flow rate; oil Fuel consumption; q air This refers to the intake airflow rate; When the deviation between the measured exhaust flow rate and the preset exhaust flow rate exceeds the preset exhaust flow rate deviation threshold, the intake flow meter and fuel consumption meter are corrected so that the corrected deviation is within the preset exhaust flow rate deviation threshold range. An environmental parameter-combustion efficiency coupled model is constructed. By real-time monitoring of cylinder pressure and combustion phase angle, the compensation coefficient in the exhaust flow calculation is adjusted so that the correlation coefficient between the bench exhaust flow and the exhaust flow of the actual vehicle PEMS data is within the preset exhaust flow threshold range.

[0011] Preferably, step S105 specifically includes: Engine cylinder pressure, intake airflow rate, exhaust back pressure, NOx concentration, and CO2 concentration are obtained at a preset frequency. The combustion phase angle is calculated based on the cylinder pressure crankshaft angle diagram. When combustion is detected to deviate from the calibration range, the test loading rate is adjusted to maintain steady-state conditions. When the intake air temperature or humidity changes abruptly beyond the preset fluctuation threshold, the intake disc valve is adjusted to reduce the fluctuation range of the emitted pollutant concentration to within the preset fluctuation threshold.

[0012] Preferably, step S106 specifically includes: Feature matching is performed between the emission data from the test bench and the emission data from the actual vehicle. By constructing a mapping relationship and adjusting the weight allocation of the equivalence analysis, the error rate of the equivalence matching degree is made lower than the preset matching degree threshold. The environmental boundary condition threshold range is adjusted based on real-time monitored environmental parameters, and boundary condition correction coefficients are generated to ensure that the deviation rate between bench test conditions and actual vehicle operation conditions is less than the preset deviation threshold. By comparing the emissions data of the test bench and the actual vehicle, the equivalence analysis parameters are corrected, and an iteratively optimized equivalence analysis report is generated.

[0013] This application also provides a vehicle diesel engine bench emission simulation testing system, the system comprising: The parameter mapping module is used to configure the test bench and test equipment, calibrate the flow meter and analyzer through linear regression equations, and establish the mapping relationship between the measured value and the output. The operating condition mapping module is used to build an engine transient operating condition model using real vehicle data, so as to realize the mapping between the bench control process and the real vehicle operating conditions. The parameter matching and processing module is used to configure the speed, torque, intake air temperature, and humidity of the bench control as boundary conditions, evaluate the control follow-up performance by calculating the correlation coefficient, and verify the consistency of environmental parameters based on the mean deviation. The data configuration module is used to calculate exhaust flow and configure measurement data based on intake flow and fuel consumption. The real-time data acquisition module is used to perform transient tests and acquire real-time data on engine operating status and pollutant emissions; The analysis and processing module is used to perform equivalence analysis of bench and real vehicle emission results under dual boundary condition constraints.

[0014] According to another embodiment of this application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the vehicle diesel engine bench simulation emission test method.

[0015] According to another embodiment of this application, a storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the vehicle diesel engine bench simulation emission test method.

[0016] As can be seen from the above technical solutions, the present invention has the following advantages: The present invention provides a bench simulation emission testing method for automotive diesel engines. This method calibrates flow meters and analyzers using linear regression equations, performs linearization checks on air flow meters and fuel consumption meters, and establishes a precise mapping relationship between measured values ​​and output quantities. This solves the problem of insufficient measurement accuracy and improves the reliability of measurement data. Based on transient data collected from real vehicle road tests, a transient operating condition model of the engine is constructed. Features are extracted to generate transient operating condition curves, and bench control process parameters are adjusted in real time. This ensures that parameters such as bench speed and torque highly match the time-domain distribution of real vehicle operating conditions, with deviations less than a preset threshold. This effectively solves the problem of inaccurate bench operating condition simulation and makes the test conditions closer to the actual operating conditions of real vehicles.

[0017] This invention calculates the combustion phase angle by real-time monitoring of parameters such as engine cylinder pressure. When combustion deviates, the test loading rate is adjusted to maintain steady-state conditions. When the intake air temperature or humidity changes abruptly and exceeds a preset fluctuation threshold, the intake disc valve is adjusted to reduce the fluctuation range of emission pollutant concentration, thereby solving the problem of instability in the test process and ensuring the stability and reliability of the test data.

[0018] Under the constraint of dual boundary conditions, feature matching is performed on the emission data of the test bench and the actual vehicle. The weight allocation is adjusted by constructing a mapping relationship. The boundary condition threshold is adjusted according to real-time environmental parameters and a correction coefficient is generated. The equivalence analysis parameters are corrected by comparing the differences in emission data. Finally, an iteratively optimized equivalence analysis report is generated, which solves the problem of the difficulty in accurately assessing the equivalence of test bench and actual vehicle emissions. Attached Figure Description

[0019] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description 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.

[0020] Figure 1 A schematic diagram of a PEMS emissions testing system for automotive diesel engine bench testing; Figure 2 Flowchart of the bench simulation emission test method for automotive diesel engines; Figure 3 A flowchart illustrating an embodiment of a bench-simulated emissions test method for automotive diesel engines; Figure 4 This is a schematic diagram of the torque test trajectory; Figure 5 This is a schematic diagram of torque correlation analysis; Figure 6 This is a schematic diagram of the rotational speed test trajectory; Figure 7 This is a schematic diagram of the speed correlation analysis; Figure 8 This is a schematic diagram of the intake air temperature test trajectory; Figure 9 This is a schematic diagram of the air intake humidity test trajectory; Figure 10 This is a schematic diagram of the exhaust temperature test trajectory; Figure 11 This is a schematic diagram of the exhaust flow test trajectory; Figure 12 This is a schematic diagram of the CO2 test trajectory; Figure 13 NO x Test trajectory diagram; Figure 14 This is a schematic diagram of an electronic device. Detailed Implementation

[0021] like Figure 1 As shown, a schematic diagram of a PEMS emission testing system for simulating emissions from a vehicle diesel engine bench test is provided to realize a bench test method for simulating emissions from a vehicle diesel engine.

[0022] This application Figure 1The process involves connecting the fuel system control terminal of engine 1 to the test bench control device 9 via fuel valve 5 and fuel consumption meter 7. The cold end of engine 1 is connected to the test bench control device 9 via intercooler 8. The air end of engine 1 is connected to the test bench control device 9 sequentially via intake disc valve 2, intake flow meter 3, and intake air conditioning 4. The output end of engine 1 is connected to the test bench control device 9 via flexible coupling 15 and dynamometer 6. Engine 1 is also connected to the test bench control device 9 via engine operation data acquisition module 11 and dilution channel 17. Dilution channel 17 is connected to emission test control device 10 via CVS intake fan 18, particulate matter sampling system 13, dilution analyzer 14, and CVS negative pressure fan 12. An exhaust temperature sensor 16 is installed between engine 1 and dilution channel 17, and the exhaust temperature sensor 16 is connected to engine operation data acquisition module 11.

[0023] In the above embodiments, PEMS emission testing is simulated by measuring and controlling engine operating parameters and emissions during bench testing of automotive diesel engines. By utilizing the coordinated operation of various sensors, actuators, and measurement and control devices, operating data and emission data of the engine under different operating conditions are collected to evaluate the engine's emission performance.

[0024] Specifically, by controlling parameters such as the oil circuit, air circuit, and engine load, various operating conditions during actual vehicle operation are simulated, and emissions are diluted, sampled, and analyzed to obtain accurate emission data.

[0025] The specific work process involves inspecting and calibrating all components of the system to ensure that the intake disc valve 2, intake flow meter 3, intake air conditioning 4, oil valve 5, fuel consumption meter 7, intercooler 8, bench control device 9, engine operation data acquisition module 11, exhaust temperature sensor 16, and other equipment are functioning properly and measuring accurately. According to the test requirements, relevant parameters, such as target values ​​for engine speed, torque, intake air temperature, and humidity, are preset in the bench control device 9.

[0026] In the process of simulating engine operating conditions, the air flow rate is regulated by the intake disc valve 2, measured by the intake flow meter 3, and then regulated by the intake air conditioning system 4 to adjust the temperature and humidity to meet the preset intake conditions before entering the air end of engine 1. The intake flow meter 3 and the intake air conditioning system 4 feed the measurement data back to the bench control device 9. Based on the difference between the actual and preset intake parameters, the bench control device 9 controls the intake disc valve 2 and the intake air conditioning system 4 to achieve precise adjustment of the intake volume, temperature, and humidity, simulating the intake state under different operating conditions of a real vehicle.

[0027] In terms of the fuel circuit control method, fuel enters the fuel consumption meter 7 from the fuel tank via fuel valve 5, and then supplies fuel to the fuel circuit control terminal of engine 1. The fuel consumption meter 7 measures the fuel consumption in real time and transmits the data to the bench test and control device 9. The bench test and control device 9 adjusts the fuel supply by controlling the opening of fuel valve 5, simulating the fuel consumption under different operating conditions of the real vehicle.

[0028] The output of engine 1 is connected to dynamometer 6 via flexible coupling 15. Dynamometer 6 simulates vehicle driving resistance and provides load to engine 1. The bench control device 9 controls the load of dynamometer 6 according to the preset speed-torque operating condition curve, so that engine 1 operates at the same speed and torque state as the actual vehicle PEMS operating condition, realizing the mapping between the bench control process and the actual vehicle operating condition.

[0029] In terms of cooling control, the coolant at the cold end of engine 1 returns to the engine after heat exchange through intercooler 8. The working state of intercooler 8 is monitored and adjusted by bench testing and control device 9 to ensure stable engine operating temperature and simulate the working state of the cooling system of a real vehicle.

[0030] This application also relates to operational data acquisition. During engine operation, the engine operational data acquisition module 11 collects the engine's speed, torque, cylinder pressure and other operating parameters in real time, as well as the exhaust temperature data measured by the exhaust temperature sensor 16, and transmits these data to the bench measurement and control device 9 for processing and storage.

[0031] The emission treatment and analysis method involves the exhaust gas from engine 1 entering a dilution channel 17, where it is mixed and diluted with clean air introduced by the CVS intake fan 18. A portion of the diluted exhaust gas enters the particulate matter sampling system 13 to collect particulate matter; another portion enters the dilution analyzer 14 to measure the concentrations of substances such as NOx, CO, and CO2. The CVS negative pressure fan 12 maintains negative pressure within the dilution channel 17 to ensure normal exhaust gas flow. The emission test control device 10 receives data from the particulate matter sampling system 13 and the dilution analyzer 14, analyzes and processes it, and ultimately obtains the engine's emission pollutant data. After the test, engine 1 is stopped, and the power to all equipment is turned off. The bench test control device 9 and the emission test control device 10 store and export the collected and processed data for subsequent analysis. Through comprehensive analysis of engine operating parameters and emission pollutant data, the engine's emission performance is evaluated, and the bench emission results are compared with the PEMS test results to achieve the goal of reproducing the PEMS test conditions.

[0032] The following details the specific steps of the bench simulation emission testing method for automotive diesel engines involved in this application. Specific details, such as particular system structures and technologies, are presented for illustrative purposes rather than limiting, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details.

[0033] It should be understood that, when used in this specification, the term "comprising" indicates the presence of the described feature, integral, step, operation, element, and / or component, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or collections thereof. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0034] The terms "one embodiment" or "some embodiments" used in this application mean that one or more embodiments of this application include the specific features, structures, or characteristics described in that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this application do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized.

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0036] Please see Figure 2 The diagram shows a flowchart of a bench-simulated emissions test method for a vehicle diesel engine in a specific embodiment. The method includes: S101: Configure the test bench and test equipment, calibrate the flow meter and analyzer through linear regression equation, and establish the mapping relationship between the measured value and the output.

[0037] In some embodiments, the test bench and various equipment required for the experiment are determined, such as air flow meters, fuel consumption meters, and direct sampling analyzers. For the air flow meters, the actual air flow values ​​are measured under different flow settings, and the output analog signals are recorded.

[0038] The linearization check calculation formula in this embodiment is: y = a1x + a0. Where: y is the actual value, a1 is the slope of the regression line, x is the baseline value, and a0 is the intercept of the regression line.

[0039] This embodiment uses data from multiple measurement points and the linear regression equation y=a1x+a0 to calculate calibration parameters, establishing an accurate mapping relationship between airflow and the output analog quantity. A similar method is used for the fuel consumption meter, measuring actual fuel consumption and the output analog quantity under different fuel consumption levels to complete linearization checks and correlation calibration.

[0040] In this embodiment, in addition to linearization checks, the direct sampling analyzer also needs to undergo leak checks to ensure that the instrument is well-sealed and that no gas leaks affect the measurement results.

[0041] As can be seen, this embodiment utilizes linear regression, fitting data points using the least squares method to find the linear equation that best represents the relationship between the measured value and the output quantity. In flowmeter and analyzer calibration, this equation can be used to accurately convert the analog signal output by the instrument into the actual physical quantity, eliminating the instrument's own nonlinear errors and systematic errors, and ensuring measurement accuracy.

[0042] S102: Construct an engine transient operating condition model based on real vehicle data to realize the mapping between the bench control process and the real vehicle operating conditions.

[0043] In some embodiments, a PEMS device installed on a real vehicle collects transient data such as engine speed, torque, intake air temperature, intake air humidity, exhaust air temperature, and fuel consumption under urban road conditions, highway conditions, mountain road conditions, and different driving styles. The massive amounts of collected data are preprocessed to remove outliers and noise, and a multidimensional dynamic operating condition database containing time-series characteristics is established.

[0044] In some specific embodiments, by collecting transient data of engine speed, torque, intake air temperature, intake air humidity, exhaust air temperature, and fuel consumption during real vehicle road tests, a multi-dimensional dynamic operating condition database containing time series features is established; machine learning algorithms are used to extract features from the dynamic operating condition database to generate transient operating condition curves that highly match the operating patterns of the real vehicle; by comparing the bench operating parameters with the real vehicle operating condition curves in real time, the load and intake conditions of the dynamometer are adjusted so that the time-domain distribution deviation of the speed and torque of the bench control process from the real vehicle operating conditions is less than a preset time-domain deviation threshold.

[0045] Optionally, this embodiment can utilize an RNN (Recurrent Neural Network) or an LSTM (Long Short-Term Memory Network) to extract features from the database, extracting changes in engine operating parameters under different operating conditions, and generating transient operating condition curves that highly match the actual vehicle operating patterns. During bench testing, the engine speed, torque, and other parameters on the bench are compared in real-time with the actual vehicle operating condition curves. By adjusting the load of the dynamometer and equipment such as the intake air conditioning system, the time-domain distribution deviation of the speed, torque, and other parameters in the bench control process from the actual vehicle operating conditions is made less than a preset time-domain deviation threshold.

[0046] As one implementation method of this embodiment, based on big data and machine learning technologies, the operating modes and characteristics of the engine under different operating conditions are learned from a large amount of real vehicle operating data. Through the established transient operating condition model, the changing trends of the engine's operating parameters under various actual operating conditions can be predicted. During bench testing, the bench control parameters are adjusted in real time according to the model, making the bench simulation conditions more consistent with the actual vehicle operating conditions, facilitating the identification and improvement of potential emission problems of the engine under actual operating conditions.

[0047] This embodiment can also be based on feedback control principles, comparing the actual operating parameters of the test bench with the ideal real-vehicle operating condition curve to obtain a deviation signal. Based on the deviation signal, the engine load and intake conditions are adjusted using a dynamometer and intake air conditioning equipment, forming a closed-loop control process. This allows the test bench operating parameters to continuously approach the real-vehicle operating condition parameters, achieving accurate simulation of the real-vehicle operating conditions. This avoids large deviations between the test bench conditions and actual operating conditions, ensuring that the engine emission data obtained from the test bench more accurately reflects its emissions during actual road driving.

[0048] S103: Configure the speed, torque, intake air temperature, and humidity of the test bench as boundary conditions, evaluate the control tracking performance by calculating the correlation coefficient, and verify the consistency of environmental parameters based on the mean deviation.

[0049] In some embodiments, based on the distribution range and variation patterns of parameters such as engine speed, torque, intake air temperature, and intake air humidity in the actual vehicle PEMS data, the corresponding boundary condition settings for bench testing are determined. During the bench test, engine speed and torque data are collected in real time, and the correlation coefficients between the bench-measured speed and torque and the corresponding parameters of the actual vehicle are calculated using a correlation coefficient calculation formula (such as the Pearson correlation coefficient formula). The speed correlation is required to be greater than a preset speed threshold coefficient (such as 0.97), and the torque correlation is required to be greater than a preset torque threshold coefficient (such as 0.85), thereby evaluating the bench's ability to follow the actual vehicle's speed and torque control.

[0050] The correlation coefficient can be calculated using the Pearson correlation coefficient method. The preset speed threshold coefficient can be 0.97, and the torque correlation coefficient, which is greater than the preset torque threshold coefficient, can be 0.85.

[0051] Optionally, this embodiment can collect intake air temperature and humidity data in real time, calculate the deviation between these data and the average values ​​of the corresponding parameters on the actual vehicle, and require that the deviation of the average value of each parameter be less than a preset average deviation threshold, such as 10% to 15%, to verify the consistency of the test bench and the environmental parameters of the actual vehicle. If the requirements are not met, the parameters of the dynamometer load, intake air conditioning, and other equipment can be adjusted in a timely manner through the test bench control system.

[0052] As can be seen, the correlation coefficient in this embodiment is used to measure the degree of linear correlation between two variables. By calculating the correlation coefficients between the test bench and the actual vehicle's speed and torque, the closeness of the test bench control parameters to the actual vehicle's operating conditions can be assessed. The mean deviation is used to measure the average difference between the test bench and the actual vehicle's environmental parameters. By controlling the mean deviation, the similarity between the test bench environment and the actual vehicle environment can be ensured. By accurately configuring and evaluating boundary conditions, it is ensured that the test bench operating conditions are highly consistent with the actual vehicle's operating conditions in terms of speed, torque, and intake air temperature and humidity. This improves the comparability and reliability of the test bench results and the actual vehicle emissions.

[0053] S104: Calculate exhaust flow rate and configure measurement data based on intake flow rate and fuel consumption.

[0054] In some embodiments, exhaust flow can be calculated by combining intake flow and fuel consumption. Specifically, the calculation method is: exhaust flow = intake flow + fuel consumption × fuel-air ratio (the fuel-air ratio is dynamically determined based on engine combustion characteristics and test conditions).

[0055] This embodiment uses a calibrated intake flow meter to measure intake air flow and a fuel consumption meter to measure fuel consumption. The measurement data are transmitted to a benchtop monitoring and control system or a relevant calculation module to calculate the exhaust flow. Simultaneously, the measurement data, including intake air flow, fuel consumption, and the calculated exhaust flow, are integrated, stored, and preprocessed.

[0056] In this way, based on the fact that air and fuel in the engine are converted into exhaust after combustion, the exhaust flow rate can be accurately calculated using known intake air flow rate and fuel consumption, as well as a reasonably determined fuel-air ratio.

[0057] S105: Perform transient tests to obtain real-time data on engine operating status and pollutant emissions.

[0058] In some embodiments, an engine bench test is initiated according to a preset transient operating condition program to acquire real-time data on engine cylinder pressure, intake airflow velocity, exhaust back pressure, NOx concentration, and CO2 concentration multiple times per second, as well as data on engine operating status and emissions. Engine cylinder pressure is measured using a cylinder pressure sensor, and the combustion phase angle is calculated using a specific algorithm in conjunction with the crankshaft angle signal.

[0059] When a deviation of the combustion phase angle from the calibration range is detected, possible causes are analyzed, and the test loading rate is adjusted using a dynamometer to maintain engine operation under stable conditions. Simultaneously, intake air temperature and humidity are monitored in real time. When sudden changes in intake air temperature or humidity exceed preset fluctuation thresholds, the fluctuation range of emission pollutant concentrations is reduced to within the preset fluctuation thresholds by adjusting the intake disc valve opening, etc. All collected data is transmitted in real time to the data acquisition system for storage and preliminary processing.

[0060] As can be seen, this embodiment uses multiple sensors to monitor engine operation and emission-related parameters in real time. Utilizing the correlations between these parameters—such as cylinder pressure and combustion phase angle, intake parameters and emission pollutant concentrations—the engine operating conditions are evaluated and adjusted in real time. Furthermore, based on the differences between the monitored parameter changes and preset standards, the test conditions are adjusted promptly to ensure a stable test process and obtain accurate and reliable real-time data.

[0061] S106: Under the constraint of dual boundary conditions, conduct an equivalence analysis of bench and real vehicle emission results.

[0062] In some embodiments, it can be determined whether the bench test meets the set first type of boundary conditions, such as the speed and torque correlation coefficient requirements, and the second type of boundary conditions, such as the mean deviation requirements of environmental parameters such as intake air temperature and humidity.

[0063] If the conditions are met, feature matching is performed on the concentrations and total emissions of pollutants such as NOx, CO, and CO2 obtained from bench tests and the PEMS emission data from actual vehicles. By constructing mapping relationships, such as based on the composition of emitted pollutants and their concentration trends, similarities and differences are analyzed.

[0064] Based on the feature matching results, the weight allocation of the equivalence analysis is adjusted to ensure that the equivalence matching error rate is lower than a preset matching threshold, which can be between 5% and 8%. Simultaneously, the environmental boundary condition threshold range is adjusted based on real-time monitoring of intake air temperature, humidity, and atmospheric pressure, and boundary condition correction coefficients are generated to ensure that the deviation rate between the bench test conditions and the actual vehicle operating conditions is less than a preset deviation threshold, which can be between 8% and 10%. By continuously comparing the differences between bench and actual vehicle emission data, the equivalence analysis parameters are continuously corrected, ultimately generating an iteratively optimized equivalence analysis report.

[0065] In some specific embodiments, step S106 further performs feature matching between the emission data from the test bench and the emission data from the actual vehicle. By constructing a mapping relationship, the weight allocation of the equivalence analysis is adjusted so that the equivalence matching error rate is lower than a preset matching threshold. The environmental boundary condition threshold range is adjusted according to the real-time monitored environmental parameters, and boundary condition correction coefficients are generated to ensure that the deviation rate between the test bench conditions and the actual vehicle operating conditions is less than a preset deviation threshold. By comparing the differences between the emission data from the test bench and the actual vehicle, the equivalence analysis parameters are corrected, and an iteratively optimized equivalence analysis report is generated.

[0066] It should be noted that during bench testing, sensors placed in the intake and exhaust systems monitor environmental parameters such as intake air temperature, intake air humidity, exhaust air temperature, and atmospheric pressure in real time. These sensors undergo rigorous calibration to ensure measurement accuracy. The real-time monitored environmental parameter values ​​are compared with initially set environmental boundary condition thresholds. If environmental parameters change, such as the intake air temperature rising beyond a certain range, the environmental boundary condition threshold range is recalculated and adjusted according to a pre-established mathematical model, bringing the intake air temperature threshold range back to a reasonable range.

[0067] This embodiment also identifies shortcomings in current equivalence analysis methods and parameters by comparing and analyzing the differences between bench and real vehicle emission data. An optimization algorithm is used to iteratively optimize the equivalence analysis parameters, continuously searching for the optimal solution in the parameter space. This allows the equivalence analysis model to better fit the relationship between bench and real vehicle emission data, improving the accuracy of the equivalence analysis.

[0068] As can be seen, based on statistical and data analysis methods, the equivalence between bench and real-vehicle emission results is quantified through feature matching and weight adjustment. Considering the impact of environmental parameter changes on emissions, boundary conditions and analysis parameters are dynamically adjusted to make the equivalence analysis more consistent with reality. Iterative optimization is employed to continuously improve the analysis model and parameters, thereby enhancing the accuracy of the equivalence analysis.

[0069] Based on the above embodiments, in order to further improve the reliability of the vehicle diesel engine bench simulation emission test method provided in the above embodiments, the following is an implementable method, such as... Figures 3 to 13 As shown, the specific steps include the following: S101: Before the test, prepare the air flow meter, fuel consumption meter, data acquisition module, direct sampling analyzer, and dilution device. During equipment preparation, perform linearization checks on the air flow meter and fuel consumption meter, check the correlation between air flow and output analog quantity on the air flow meter, and check the correlation between fuel consumption and output analog quantity on the fuel consumption meter. In this embodiment, a direct sampling analyzer is used for linearization and leakage checks.

[0070] S102: Based on the test data from the vehicle's PEMS (Power, Equipment, and Systems) system, obtain the corresponding engine speed-torque curve. Based on this curve, write a matching transient test condition program in the engine bench control system to ensure that the engine operating point during bench testing is consistent with the actual vehicle PEMS conditions.

[0071] This embodiment reproduces the same transient operating conditions on an engine test bench and evaluates whether the first type of boundary conditions (test bench control following performance) and the second type of boundary conditions meet the requirements.

[0072] The first type of boundary conditions, namely bench control tracking, include: speed and torque.

[0073] The second type of boundary conditions includes: intake air temperature, intake air humidity, exhaust air temperature, and exhaust flow rate.

[0074] The first type of boundary condition requires that the speed correlation be greater than 0.9 and the torque correlation be greater than 0.85. The second type of boundary condition requires that the average deviation of each parameter be less than 10%.

[0075] Among them, the speed and torque are provided by the dynamometer, the intake air temperature and humidity are provided by the intake air conditioner, the exhaust temperature is provided by the exhaust temperature sensor, the intake air flow is provided by the intake air flow meter, and the fuel consumption is provided by the fuel consumption meter.

[0076] It should be noted that before bench testing, the engine's speed-torque operating curve during actual operation is obtained based on the test data from the vehicle's PEMS (Portable Emissions Measurement System). Then, in the engine bench control system, this operating curve is converted into an executable transient test program. After the program is set, the bench test is started. The engine load is adjusted using a dynamometer to simulate the resistance changes during vehicle operation, thereby controlling the engine speed and torque. The intake air conditioning system precisely regulates the temperature and humidity of the air entering the engine. Simultaneously, various sensors, such as the intake flow meter, fuel consumption meter, and exhaust temperature sensor, collect corresponding parameter data in real time and transmit the data to the bench measurement and control system.

[0077] To assess whether the first type of boundary condition (bench control tracking performance) meets the requirements, real-time data of engine speed and torque are collected on the engine bench during the reproduction of transient operating conditions. Simultaneously, corresponding speed and torque data from the actual vehicle's PEMS test data are obtained. The correlation coefficient calculation method is used to calculate the speed correlation value for the bench and actual vehicle speed data; similarly, the torque correlation value is calculated for the torque data. Table 1 presents the speed-torque correlation analysis table.

[0078] Table 1

[0079] The calculated speed correlation values ​​are compared with a preset threshold of 0.9, and the torque correlation values ​​are compared with a preset threshold of 0.85. If the speed correlation is greater than 0.9 and the torque correlation is greater than 0.85, the first type of boundary condition is considered to meet the requirements. If not, the reasons are analyzed, which may include insufficient dynamometer control accuracy or response delay of the bench control system. Adjustments are made to the dynamometer parameters and bench control program based on the specific reasons, and then the transient operating conditions are reproduced and the correlation calculation and evaluation are repeated until the requirements are met. Only when the bench control follow-up meets the requirements are the engine performance and emission data obtained from bench testing more valuable, truly reflecting the engine's power performance in actual vehicle operation, and providing a reliable basis for engine power system optimization and performance evaluation.

[0080] The assessment of whether the second type of boundary conditions meets the requirements involves real-time acquisition of intake temperature, intake humidity, and exhaust temperature data using intake air temperature sensors, intake air humidity sensors, and exhaust temperature sensors during bench testing. Intake flow rate and fuel consumption are measured using an intake flow meter and a fuel consumption meter, and exhaust flow rate is calculated using the exhaust flow rate calculation formula. Simultaneously, the corresponding intake temperature, intake humidity, exhaust temperature, and exhaust flow rate data from the actual vehicle PEMS test data are acquired. The average values ​​of the bench-measured intake temperature, intake humidity, exhaust temperature, and exhaust flow rate are calculated compared to the corresponding data from the actual vehicle. Then, the deviation of the average value for each parameter is calculated as (bench parameter average value - actual vehicle parameter average value) / actual vehicle parameter average value × 100%. The calculated deviation of the average value for each parameter is compared to a preset 10% threshold. If the deviation of the average value for all parameters is less than 10%, the second type of boundary conditions are considered to meet the requirements. If one or more parameter deviations do not meet the requirements, the cause is analyzed, which may be insufficient intake air conditioning adjustment precision, sensor measurement errors, etc. The relevant equipment is calibrated, adjusted, or repaired to address the problem, and then data acquisition and calculation are repeated until the requirements are met.

[0081] The formula for calculating the exhaust flow rate in this embodiment is: .

[0082] In the formula: qexh is the exhaust flow rate; qoil is the fuel consumption; qair is the intake flow rate.

[0083] In this embodiment, when the deviation between the measured exhaust flow rate and the preset exhaust flow rate exceeds the preset exhaust flow rate deviation threshold, the intake flow meter and fuel consumption meter are corrected so that the corrected deviation is within the preset exhaust flow rate deviation threshold range; an environmental parameter-combustion efficiency coupling model is constructed, and the compensation coefficient in the exhaust flow rate calculation is adjusted by real-time monitoring of cylinder pressure and combustion phase angle so that the correlation coefficient between the bench exhaust flow rate and the exhaust flow rate of the actual vehicle PEMS data is within the preset exhaust flow rate threshold range.

[0084] It should be noted that exhaust flow rate is closely related to intake flow rate and fuel consumption. When there is a significant deviation in the exhaust flow rate measurement, the exhaust flow rate measurement value can be indirectly corrected by investigating and correcting the measurement errors of the intake flow meter and fuel consumption meter, which are related to the exhaust flow rate calculation. The principle is similar to that in a system based on measurement data, when the final calculation result deviates, the error in the input data is traced and corrected to ensure the accuracy of the calculation result.

[0085] This embodiment also utilizes an environmental parameter-combustion efficiency coupling model to link environmental parameters and combustion state with exhaust flow calculation. Based on real-time changes in combustion state and environmental parameters, the compensation coefficient in the exhaust flow calculation is dynamically adjusted to correct the calculated exhaust flow value, making it closer to the actual vehicle exhaust flow. The principle is that environmental parameters and combustion state affect exhaust flow during actual engine operation. By establishing a model and real-time monitoring and adjustment, the influence of these factors on exhaust flow is compensated, achieving a better match between bench exhaust flow and actual vehicle exhaust flow, thus improving the engine's environmental performance.

[0086] In this embodiment, a first type of boundary condition and a second type of boundary condition are defined. The first type of boundary condition (bench control tracking performance) requires: a speed correlation coefficient greater than 0.97 and a torque correlation coefficient greater than 0.85. The second type of boundary condition requires: the average deviation of each parameter is less than 10%.

[0087] The formula for calculating the correlation coefficient is: .

[0088] In the formula: x and y are the measurements used to check the correlation. The intercept of the regression line represents the value of the dependent variable y when the independent variable x=0. In the regression line y=a1x+a0, it is the y-intercept of the line. The slope of the regression line reflects the average change in the dependent variable y when the independent variable x changes by one unit, indicating the steepness of the linear relationship between x and y. It is the actual measured value of the i-th dependent variable y. Let y be the sample mean of the dependent variable, which is the sum of all... The arithmetic mean of the values ​​reflects the overall average level of the y-values. n is the sample size, representing the total number of data points used in the correlation analysis. i is the index value, used to number the sample data points sequentially, from 1 to n, representing the i-th sample data point.

[0089] S103: Conduct transient tests and collect bench test data of the engine required for emissions calculations. Engine bench test data includes: speed, torque, intake air temperature, intake air humidity, exhaust air temperature, fuel consumption, intake air flow, NOx concentration, and CO2 concentration, and is exported through the bench measurement and control system or a rarefaction analyzer.

[0090] In some embodiments, various sensors are used to convert engine speed, torque, temperature, flow rate, and pollutant concentration during operation into electrical or digital signals. These signals are then transmitted via data transmission lines to a test bench or related measuring equipment for processing and storage. Analysis of this data provides insight into the engine's performance and emission characteristics under transient operating conditions, and identifies potential problems that may exist during actual engine operation.

[0091] S104: Based on satisfying the first and second type boundary conditions, compare the bench emission results with the PEMS test results to reproduce the PEMS test conditions.

[0092] In this embodiment, it is confirmed that the bench test has met both Type I and Type II boundary conditions. If not, the bench test conditions need to be readjusted until the conditions are met. Once the boundary conditions are met, the emission data collected and exported from the bench test is compared with the emission data obtained from the actual vehicle PEMS test.

[0093] During the comparison, the data is first preprocessed, such as removing outliers and normalizing the data, to make the two sets of data comparable. Then, analysis is conducted from multiple aspects, such as comparing the time-varying curves of different pollutant concentrations to observe whether the timing of emission peaks and the range of emission concentration fluctuations are consistent; the errors between bench emission data and PEMS emission data for different pollutants are calculated, such as mean absolute error and mean square error. Through these comparative analyses, the similarity between the bench emission results and the PEMS test results is assessed. If the results are similar, it indicates that the PEMS test conditions have been successfully reproduced on the bench; if there are significant differences, the reasons are further analyzed, which may be due to the accuracy of the test equipment, subtle deviations in the simulation of the operating conditions, etc. Improvements and optimizations are made to address the causes, and the test and comparison are repeated until the goal of reproducing the PEMS test conditions is achieved. By comparing the bench emission results and the PEMS test results, the degree of reproducibility of the bench test with the real vehicle emission conditions can be accurately assessed. If the PEMS test conditions are successfully reproduced, the emission data obtained from the bench test can serve as a reliable reference for the engine's emission performance in actual operation, and can be used for the evaluation and certification of engine emission performance, as well as the research and development and improvement of emission control technologies.

[0094] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0095] The following are embodiments of the vehicle diesel engine bench emission simulation test system provided in this disclosure. This system and the vehicle diesel engine bench emission simulation test methods in the above embodiments belong to the same inventive concept. For details not described in detail in the embodiments of the vehicle diesel engine bench emission simulation test system, please refer to the embodiments of the above vehicle diesel engine bench emission simulation test methods.

[0096] The system includes a parameter mapping module, which is used to configure the test bench and test equipment, calibrate the flow meter and analyzer through a linear regression equation, and establish a mapping relationship between the measured value and the output.

[0097] The operating condition mapping module is used to build an engine transient operating condition model using real vehicle data, thereby mapping the bench control process with the actual vehicle operating conditions.

[0098] The parameter matching processing module is used to configure the speed, torque, intake air temperature, and humidity of the bench control as boundary conditions, evaluate the control tracking performance by calculating the correlation coefficient, and verify the consistency of environmental parameters based on the mean deviation.

[0099] The data configuration module is used to calculate exhaust flow and configure measurement data based on intake flow and fuel consumption.

[0100] The real-time data acquisition module is used to perform transient tests and acquire real-time data on engine operating status and pollutant emissions.

[0101] The analysis and processing module is used to perform equivalence analysis of bench and real vehicle emission results under dual boundary condition constraints.

[0102] like Figure 14 As shown, this application also provides an electronic device, including a display module 103, a memory 102, a processor 101, and a computer program stored in the memory and executable on the processor 101. When the processor 101 executes the program, it implements the steps of a bench simulation emission test method for a vehicle diesel engine.

[0103] In embodiments of the present invention, electronic devices include, but are not limited to, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments described and / or claimed herein.

[0104] In this embodiment, processor 101 may be implemented using at least one of an application-specific integrated circuit, a programmable logic device, a field-programmable gate array, a processor, a controller, a microcontroller, a microprocessor, or an electronic unit designed to perform the functions described herein. In some cases, such an implementation may be implemented within a controller. For software implementation, implementations such as processes or functions may be implemented with separate software modules that allow the performance of at least one function or operation. Software code may be implemented by a software application (or program) written in any suitable programming language, and the software code may be stored in memory and executed by the controller.

[0105] The display module 103 is used to display information input by the user or information provided to the user. The display module 103 may include a display panel, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like.

[0106] The memory 102 can be used to store software programs and various data. The memory 102 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0107] This application also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the vehicle diesel engine bench simulation emission test method.

[0108] The storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example,, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0109] In a storage medium, a readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying readable program code. This propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0110] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A bench-simulated emission test method for automotive diesel engines, characterized in that, The methods include: S101: Configure the test bench and test equipment, calibrate the flow meter and analyzer through linear regression equation, and establish the mapping relationship between the measured value and the output; S102: Construct an engine transient operating condition model based on real vehicle data to realize the mapping between the bench control process and the real vehicle operating conditions; S103: Configure the speed, torque, intake air temperature, and humidity of the test bench as boundary conditions, evaluate the control tracking performance by calculating the correlation coefficient, and verify the consistency of environmental parameters based on the mean deviation. S104: Calculate exhaust flow rate and configure measurement data based on intake flow rate and fuel consumption; S105: Perform transient tests to obtain real-time data on engine operating status and pollutant emissions; S106: Under the constraint of dual boundary conditions, conduct an equivalence analysis of bench and real vehicle emission results.

2. The bench simulation emission test method for automotive diesel engines according to claim 1, characterized in that, Step S101 specifically includes: performing linearization checks on the air flow meter and fuel consumption meter; performing correlation checks between air flow and output analog quantity on the air flow meter; performing correlation checks between fuel consumption and output analog quantity on the fuel consumption meter; and performing linearization and leakage checks on the direct sampling analyzer. The formula for calculating the linearization check is: y=a1x+a0 In the formula: y is the actual value, a1 is the slope of the regression line, x is the baseline value, and a0 is the intercept of the regression line.

3. The bench simulation emission test method for automotive diesel engines according to claim 1, characterized in that, Step S102 specifically includes: By collecting transient data on engine speed, torque, intake air temperature, intake air humidity, exhaust air temperature and fuel consumption during real vehicle road tests, a multi-dimensional dynamic operating condition database containing time series characteristics is established. The dynamic operating condition database is used to extract features using machine learning algorithms to generate transient operating condition curves that highly match the actual vehicle operating patterns. By comparing the test bench operating parameters with the actual vehicle operating condition curves in real time, the load and intake conditions of the dynamometer are adjusted to ensure that the time-domain distribution deviation of the speed and torque of the test bench control process from that of the actual vehicle operating condition is less than the preset time-domain deviation threshold.

4. The bench simulation emission test method for automotive diesel engines according to claim 1, characterized in that, Step S103 specifically includes: Based on real vehicle PEMS data, speed and torque environmental parameter operating condition curves are constructed, and bench control parameters are corrected in real time. Define the first type of boundary conditions and the first type of boundary conditions. The first type of boundary conditions includes: speed and torque boundary conditions; The second type of boundary conditions includes: intake air temperature, intake air humidity, exhaust air temperature, and exhaust flow rate boundary conditions; Configure the first type of boundary conditions so that the speed correlation is greater than the preset speed threshold coefficient and the torque correlation is greater than the preset torque threshold coefficient; In configuring the second type of boundary conditions, the deviation of the average parameter value is less than the preset mean deviation threshold.

5. The bench simulation emission test method for automotive diesel engines according to claim 1, characterized in that, The formula for calculating exhaust flow rate in step S104 is: In the formula: q exh q represents exhaust flow rate; oil Fuel consumption; q air This refers to the intake airflow rate; When the deviation between the measured exhaust flow rate and the preset exhaust flow rate exceeds the preset exhaust flow rate deviation threshold, the intake flow meter and fuel consumption meter are corrected so that the corrected deviation is within the preset exhaust flow rate deviation threshold range. An environmental parameter-combustion efficiency coupled model is constructed. By real-time monitoring of cylinder pressure and combustion phase angle, the compensation coefficient in the exhaust flow calculation is adjusted so that the correlation coefficient between the bench exhaust flow and the exhaust flow of the actual vehicle PEMS data is within the preset exhaust flow threshold range.

6. The bench simulation emission test method for automotive diesel engines according to claim 1, characterized in that, Step S105 specifically includes: Engine cylinder pressure, intake airflow rate, exhaust back pressure, NOx concentration, and CO2 concentration are obtained at a preset frequency. The combustion phase angle is calculated based on the cylinder pressure crankshaft angle diagram. When combustion is detected to deviate from the calibration range, the test loading rate is adjusted to maintain steady-state conditions. When the intake air temperature or humidity changes abruptly beyond the preset fluctuation threshold, the intake disc valve is adjusted to reduce the fluctuation range of the emitted pollutant concentration to within the preset fluctuation threshold.

7. The bench simulation emission test method for automotive diesel engines according to claim 1, characterized in that, Step S106 specifically includes: Feature matching is performed between the emission data from the test bench and the emission data from the actual vehicle. By constructing a mapping relationship and adjusting the weight allocation of the equivalence analysis, the error rate of the equivalence matching degree is made lower than the preset matching degree threshold. The environmental boundary condition threshold range is adjusted based on real-time monitored environmental parameters, and a boundary condition correction coefficient is generated to ensure that the deviation rate between bench test conditions and actual vehicle operation conditions is less than the preset deviation threshold. By comparing the emission data of the test bench and the actual vehicle, the equivalence analysis parameters are corrected, and an iteratively optimized equivalence analysis report is generated.

8. A bench-based emission simulation system for automotive diesel engines, characterized in that, The system is used to drive into the simulated emission test method for a vehicle diesel engine bench as described in any one of claims 1 to 7; The system includes: The parameter mapping module is used to configure the test bench and test equipment, calibrate the flow meter and analyzer through linear regression equations, and establish the mapping relationship between the measured value and the output. The operating condition mapping module is used to build an engine transient operating condition model using real vehicle data, so as to realize the mapping between the bench control process and the real vehicle operating conditions. The parameter matching and processing module is used to configure the speed, torque, intake air temperature, and humidity of the bench control as boundary conditions, evaluate the control follow-up performance by calculating the correlation coefficient, and verify the consistency of environmental parameters based on the mean deviation. The data configuration module is used to calculate exhaust flow and configure measurement data based on intake flow and fuel consumption. The real-time data acquisition module is used to perform transient tests and acquire real-time data on engine operating status and pollutant emissions; The analysis and processing module is used to perform equivalence analysis of bench and real vehicle emission results under dual boundary condition constraints.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the bench simulation emission test method for automotive diesel engines as described in any one of claims 1 to 7.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the bench simulation emission test method for automotive diesel engines as described in any one of claims 1 to 7.

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