Heavy-duty vehicle brake emission test cycle construction method, device, equipment and medium

Abstract

The invention relates to the technical field of automobile emission testing, in particular to a test cycle construction method, device and equipment for brake emission of a heavy duty vehicle and a medium, and the method comprises the steps: obtaining a target vehicle type of a to-be-tested heavy duty vehicle; determining an initial deceleration threshold curve of the to-be-tested heavy duty vehicle based on the target vehicle model; acquiring actual operation data of the heavy duty vehicle of the target vehicle model under actual road operation conditions, and calculating probability distribution of braking characteristic parameters of the heavy duty vehicle to be tested according to the initial deceleration threshold curve and the actual operation data of the target vehicle model; and according to the probability distribution, determining a plurality of target travel intervals from the sample operation data of the heavy vehicle of the target vehicle type, and according to the plurality of target travel intervals, generating a test cycle of brake emission of the to-be-tested heavy vehicle. Therefore, the problems that the brake emission test cycle of the heavy-duty vehicle cannot reflect the actual brake emission of the vehicle, the test accuracy is low and the like in the related technology are solved.

Description

Technical Field

[0001] The present application relates to the technical field of automobile emission testing, and in particular to a test cycle construction method, device, equipment and medium for brake emission of heavy vehicles. Background Art

[0002] Non-exhaust particulate matter from automobiles mainly comes from brake wear, tire wear, road wear and road resuspended dust (non-direct source). As automobile emission regulations continue to tighten, while automobile exhaust particulate matter emissions have been reduced, the emission of non-exhaust particulate matter has also become increasingly prominent. The contribution of automobile exhaust sources and non-exhaust sources to the total amount of traffic-related PM10 emissions is almost equal, and with the increasingly stringent control of exhaust emissions, the relative contribution of non-exhaust sources to traffic-related emissions will become greater and greater. Therefore, brake wear particulate matter emissions have become the regulatory direction of the next stage of emission standards at home and abroad.

[0003] The number of heavy-duty vehicles in my country only accounts for about 5% of the total number of vehicles, but their non-exhaust particulate matter emissions per vehicle are more than three times that of light-duty vehicles, and their average annual mileage is about four times that of light-duty vehicles. It is estimated that the total amount of non-exhaust particulate matter emitted by heavy-duty vehicles in my country is about 60% of that of light-duty vehicles. Therefore, it is very necessary to regulate the emission of non-exhaust particulate matter from heavy-duty vehicles, especially brake particulate matter.

[0004] Heavy-duty vehicles are of various types and complex systems, and there are significant differences in the operating characteristics of different types of heavy-duty vehicles, such as braking strength, operating conditions, and actual load. The existing brake emission test cycles for heavy-duty vehicles include simulation tests on brake benches, or brake emission test cycles based on standard cycles, but they do not take into account the large differences in braking characteristics between the brake emission test cycle and the actual driving process of the vehicle, resulting in the brake emission data obtained from the test being unable to reflect the actual brake emission conditions of the vehicle, which will further affect the research and development and supervision of low-emission brakes, resulting in the ineffective control of the brake emissions of vehicles. Summary of the invention

[0005] The present application provides a method, device, equipment and medium for constructing a heavy-duty vehicle brake emission test cycle to solve the problems in the related art that the heavy-duty vehicle brake emission test cycle cannot reflect the actual brake emission of the vehicle and the test accuracy is low.

[0006] A first aspect of the present application provides a method for constructing a test cycle for brake emissions of heavy-duty vehicles, comprising the following steps: obtaining a target vehicle model of the heavy-duty vehicle to be tested; determining an initial deceleration threshold curve of the heavy-duty vehicle to be tested based on the target vehicle model; collecting actual operating data of the target vehicle model under actual road operating conditions, and calculating the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested based on the initial deceleration threshold curve and the actual operating data of the target vehicle model; determining multiple target travel intervals from the sample operating data of the target vehicle model according to the probability distribution, and generating a test cycle for brake emissions of the heavy-duty vehicle to be tested according to the multiple target travel intervals.

[0007] Optionally, the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested is calculated based on the initial deceleration threshold curve and the actual operating data of the target vehicle model, including: correcting the initial deceleration threshold curve based on the actual operating data to obtain a target deceleration threshold curve; analyzing the sample operating data of the target vehicle model heavy-duty vehicle based on the target deceleration curve to obtain the braking characteristic parameters of the heavy-duty vehicle to be tested that conform to the actual operating data, and calculating the probability distribution of the braking characteristic parameters.

[0008] Optionally, before determining multiple target travel intervals from the sample operation data of the target model heavy-duty vehicle according to the probability distribution, it also includes: obtaining sample operation data of heavy-duty vehicles of multiple models in the heavy-duty vehicle emission remote supervision platform; determining target sample operation data from the sample operation data according to the target model of the heavy-duty vehicle to be tested, and constructing a sample operation database of the target model heavy-duty vehicle based on the target sample operation data; determining multiple target travel intervals from the sample operation database of the target model heavy-duty vehicle according to the probability distribution.

[0009] Optionally, before determining multiple target travel intervals from a sample operation database of a target vehicle model heavy-duty vehicle according to the probability distribution, the method further includes: segmenting the operation travel in the sample operation database of the target vehicle model heavy-duty vehicle to obtain multiple travel intervals; filtering the multiple travel intervals based on a screening rule of the travel interval to obtain multiple travel intervals that meet the screening rule, and classifying the multiple travel intervals that meet the screening rule, wherein different categories of travel intervals correspond to different speed intervals, deceleration intervals and parking durations of the cycle; constructing a target travel library based on the multiple travel intervals that meet the screening rule; and screening multiple target travel intervals that are consistent with the probability distribution in the target travel library.

[0010] Optionally, the initial deceleration threshold curve is corrected according to the actual operation data, including: obtaining braking data information of the target vehicle type heavy-duty vehicle in the actual operation data; and correcting the initial deceleration threshold curve according to the braking data information.

[0011] Optionally, after generating a test cycle of the brake emission of the heavy-duty vehicle to be tested according to multiple target travel intervals, it also includes: performing a chi-square test on the braking characteristic parameters of the test cycle based on the probability distribution; adjusting the multiple target travel intervals based on the results of the chi-square test until the braking characteristic parameters of the test cycle conform to the probability distribution.

[0012] A second aspect of the present application provides a device for constructing a test cycle for braking emissions of heavy-duty vehicles, including: an acquisition module for acquiring a target vehicle model of a heavy-duty vehicle to be tested; a determination module for determining an initial deceleration threshold curve of the heavy-duty vehicle to be tested based on the target vehicle model; a calculation module for collecting actual operating data of the target vehicle model under actual road operating conditions, and calculating the probability distribution of braking characteristic parameters of the heavy-duty vehicle to be tested based on the initial deceleration threshold curve and the actual operating data of the target vehicle model; a generation module for determining multiple target travel intervals from sample operating data of the target vehicle model according to the probability distribution, and generating a test cycle for braking emissions of the heavy-duty vehicle to be tested according to the multiple target travel intervals.

[0013] Optionally, the calculation module is further used to: correct the initial deceleration threshold curve according to actual operating data to obtain a target deceleration threshold curve; analyze the sample operating data of the target vehicle model heavy-duty vehicle according to the target deceleration curve to obtain the braking characteristic parameters of the heavy-duty vehicle to be tested that are consistent with the actual operating data, and calculate the probability distribution of the braking characteristic parameters.

[0014] Optionally, it also includes: a construction module, which is used to obtain sample operation data of heavy-duty vehicles of multiple models in the heavy-duty vehicle emission remote supervision platform before determining multiple target travel intervals from the sample operation data of the target model heavy-duty vehicle according to the probability distribution; determine target sample operation data from the sample operation data according to the target model of the heavy-duty vehicle to be tested, and construct a sample operation database of the target model heavy-duty vehicle based on the target sample operation data; determine multiple target travel intervals from the sample operation database of the target model heavy-duty vehicle according to the probability distribution.

[0015] Optionally, it also includes: a screening module, which is used to divide the running travel in the sample running database of the target vehicle model heavy-duty vehicle to obtain multiple travel intervals before determining multiple target travel intervals from the sample running database of the target vehicle model heavy-duty vehicle according to the probability distribution; based on the screening rules of the travel intervals, the multiple travel intervals are screened to obtain multiple travel intervals that meet the screening rules, and the multiple travel intervals that meet the screening rules are classified, wherein different categories of travel intervals correspond to different speed intervals, deceleration intervals and parking durations of the cycle; a target travel library is constructed based on the multiple travel intervals that meet the screening rules; and multiple target travel intervals that are consistent with the probability distribution are screened in the target travel library.

[0016] Optionally, the calculation module is further used to: obtain braking data information of the target vehicle type heavy-duty vehicle in the actual operation data; and correct the initial deceleration threshold curve according to the braking data information.

[0017] Optionally, it also includes: an adjustment module, which is used to perform a chi-square test on the braking characteristic parameters of the test cycle based on the probability distribution after generating a test cycle of the brake emission of the heavy-duty vehicle to be tested according to multiple target travel intervals; and adjust the multiple target travel intervals based on the results of the chi-square test until the braking characteristic parameters of the test cycle conform to the probability distribution.

[0018] The third aspect of the present application provides an electronic device, 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 execute a test cycle construction method for heavy-duty vehicle brake emissions as described in the above embodiment.

[0019] The fourth aspect of the present application provides a computer-readable storage medium having a computer program or instructions stored thereon, and the computer program or instructions are executed by a processor to perform a test cycle construction method for heavy-duty vehicle brake emissions as described in the above-mentioned embodiment.

[0020] The fifth aspect of the present application provides a computer program product, including a computer program or instructions. When the computer program or instructions are executed, a test cycle construction method for heavy-duty vehicle brake emissions is implemented as in the above-mentioned embodiment.

[0021] Therefore, this application has at least the following beneficial effects:

[0022] The embodiment of the present application can determine the initial deceleration threshold curve of the heavy-duty vehicle to be tested according to the target model of the heavy-duty vehicle to be tested, and collect the actual operation data of the target model heavy-duty vehicle under actual road operating conditions, and then determine the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested that meet the actual operation, and determine multiple target travel intervals from the sample operation data of the target model heavy-duty vehicle according to the probability distribution, and generate a test cycle of the braking emission of the heavy-duty vehicle to be tested according to the multiple target travel intervals, so as to ensure that the generated test cycle can meet the braking characteristics of the actual road operation of the target model, so that the subsequent heavy-duty vehicle to be tested can perform a braking emission test according to the test cycle, reflecting the actual braking emission of the vehicle, and the test accuracy is high, which can provide a basis for formulating reasonable emission standards for heavy-duty vehicles and reduce the non-exhaust particulate matter emissions of heavy-duty vehicles. As a result, the technical problems that the heavy-duty vehicle braking emission test cycle in the related art cannot reflect the actual braking emission of the vehicle and the test accuracy is low are solved.

[0023] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0025] Figure 1 A flowchart of a method for constructing a test cycle for brake emissions of a heavy-duty vehicle provided in accordance with an embodiment of the present application;

[0026] Figure 2 A specific flow chart of a method for constructing a test cycle for brake emissions of a vehicle provided in an embodiment of the present application;

[0027] Figure 3 A schematic diagram of a system for constructing a test cycle for brake emissions of a vehicle provided in accordance with an embodiment of the present application;

[0028] Figure 4 An exemplary diagram of a device for constructing a test cycle for brake emissions of a heavy-duty vehicle provided in accordance with an embodiment of the present application;

[0029] Figure 5 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0031] The following describes the test cycle construction method, device, equipment and medium for heavy-duty vehicle brake emissions in accordance with an embodiment of the present application with reference to the accompanying drawings. The brake emission test cycle mentioned in the above background technology is the basis for establishing the brake emission test method and determining the brake emission limit. If the brake emission test cycle is significantly different from the braking characteristics of the vehicle during actual driving, the brake emission data obtained by this test cannot reflect the actual brake emission of the vehicle, which will further affect the research and development and supervision of low-emission brakes, thereby leading to the problem that the brake emission of the vehicle cannot be effectively controlled. The present application provides a test cycle construction method for brake emission of heavy vehicles. In this method, the initial deceleration threshold curve of the heavy-duty vehicle to be tested can be determined according to the target model of the heavy-duty vehicle to be tested, and the actual operation data of the target model heavy-duty vehicle under actual road operating conditions can be collected, so as to determine the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested that meet the actual operation. According to the probability distribution, multiple target travel intervals are determined from the sample operation data of the target model heavy-duty vehicle, and a test cycle for brake emission of the heavy-duty vehicle to be tested is generated according to the multiple target travel intervals, ensuring that the generated test cycle can meet the braking characteristics of the actual road operation of the target model, so that the subsequent heavy-duty vehicle to be tested can be tested for brake emissions according to the test cycle to reflect the actual brake emission of the vehicle, and the test accuracy is high. This solves the problems in the related art that the brake emission test cycle of heavy vehicles cannot reflect the actual brake emissions of the vehicle and the test accuracy is low.

[0032] Specifically, Figure 1 A flowchart of a method for constructing a test cycle for brake emissions of a heavy-duty vehicle provided in an embodiment of the present application.

[0033] like Figure 1 As shown, the test cycle construction method for heavy-duty vehicle brake emissions includes the following steps:

[0034] In step S101, a target model of a heavy-duty vehicle to be tested is obtained.

[0035] Among them, the heavy-duty vehicles to be tested are vehicles that require the construction of a test cycle for brake emission testing.

[0036] It can be understood that the embodiment of the present application can obtain the target model of the heavy-duty vehicle to be tested, so as to subsequently construct a test cycle that meets the brake emissions of the heavy-duty vehicle to be tested.

[0037] In step S102, an initial deceleration threshold curve of the heavy-duty vehicle to be tested is determined based on the target vehicle type.

[0038] It is understandable that the embodiment of the present application can determine the initial deceleration threshold curve of the heavy-duty vehicle to be tested based on the target vehicle model.

[0039] Specifically, through the remote monitoring platform for heavy-duty vehicle emissions, a large sample of data under actual operating conditions of the target model of the heavy-duty vehicle to be tested (called sample operating data) can be obtained, including time, vehicle speed, engine speed and other information. Through the analysis of these operating data, a preliminary deceleration threshold curve related to the vehicle speed of the heavy-duty vehicle to be tested can be established, which can achieve a large sample of actual operating data without increasing the cost of additional data acquisition, further expanding the basic database for the construction of subsequent brake emission test cycles, and greatly reducing the cost of constructing brake emission test cycles.

[0040] In step S103, actual operating data of the target heavy-duty vehicle under actual road operating conditions is collected, and the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested is calculated according to the initial deceleration threshold curve and the actual operating data of the target vehicle.

[0041] Among them, the braking characteristic parameters include average deceleration, initial braking speed, braking interval time, braking duration, braking distance, number of brakes per kilometer, etc.

[0042] It can be understood that the embodiments of the present application can collect the actual operating data of the target heavy-duty vehicle under actual road operating conditions, and then calculate the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested based on the initial deceleration threshold curve and the actual operating data of the target vehicle, so as to subsequently construct a braking emission test cycle that conforms to the actual operating state of the heavy-duty vehicle to be tested.

[0043] In an embodiment of the present application, the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested is calculated based on the initial deceleration threshold curve and the actual operating data of the target vehicle model, including: correcting the initial deceleration threshold curve based on the actual operating data to obtain the target deceleration threshold curve; analyzing the sample operating data of the target vehicle model heavy-duty vehicle based on the target deceleration curve to obtain the braking characteristic parameters of the heavy-duty vehicle to be tested that are consistent with the actual operating data, and calculating the probability distribution of the braking characteristic parameters.

[0044] The target deceleration threshold curve may be understood as a best-fit deceleration threshold curve.

[0045] Since the initial deceleration threshold curve is initially established based on a large sample of actual operating data, it may include some deceleration events caused by non-brake friction (such as lifting the throttle, driving resistance, etc.). These factors will cause the initial curve to not fully reflect the actual situation, so further correction is required. Therefore, the embodiment of the present application can correct the initial deceleration threshold curve according to the actual operating data to obtain the target deceleration threshold curve, and analyze the sample operating data of the target model heavy-duty vehicle according to the target deceleration curve to obtain the braking characteristic parameters of the heavy-duty vehicle to be tested that conform to the actual operating data, and calculate the probability distribution of the braking characteristic parameters to ensure the subsequent construction of a brake emission test cycle that can truthfully reflect the actual operating conditions of the vehicle.

[0046] Specifically, the embodiment of the present application analyzes the actual operation data of heavy-duty vehicles of the heavy-duty vehicle emission remote supervision platform through the best fitting deceleration threshold curve related to the speed of the heavy-duty vehicle of the target model, and obtains the probability distribution of the braking characteristic parameters of the actual road operation of the heavy-duty vehicle of the target model, including the average deceleration, initial braking speed, braking interval time, braking duration, braking distance, number of brakes per kilometer, etc.

[0047] In an embodiment of the present application, the initial deceleration threshold curve is corrected according to the actual operating data, including: obtaining braking data information of the target vehicle type heavy-duty vehicle in the actual operating data; and correcting the initial deceleration threshold curve according to the braking data information.

[0048] Since the data of the heavy-duty vehicle emission remote monitoring platform does not include braking torque or braking pressure information, it is impossible to determine whether a deceleration event is caused by brake action or by the driver lifting the accelerator or the vehicle's driving resistance. Therefore, the embodiment of the present application can obtain the braking data information of the target vehicle heavy-duty vehicle in the actual operation data to screen out vehicle deceleration caused by non-brake friction (such as lifting the accelerator, driving resistance, etc.), and use the actual braking condition data in the collected actual operation data to correct and fit the deceleration threshold curve related to the vehicle speed of the target vehicle heavy-duty vehicle, so as to obtain the best fitting deceleration threshold curve related to the vehicle speed of the target vehicle heavy-duty vehicle.

[0049] Specifically, the embodiment of the present application can use target model heavy-duty vehicles (more than 10 vehicles) to collect vehicle time, speed, engine speed, braking torque / brake pressure, brake engagement and other information under actual road operating conditions, and can obtain the braking condition of the target model heavy-duty vehicles under actual road operating conditions. The actual braking condition data is used to correct and fit the deceleration threshold curve related to the speed of the target model heavy-duty vehicles, and the best fitting deceleration threshold curve related to the speed of the target model heavy-duty vehicles can be obtained.

[0050] In step S104, a plurality of target travel intervals are determined from sample operation data of the target heavy-duty vehicle according to probability distribution, and a test cycle of brake emission of the heavy-duty vehicle to be tested is generated according to the plurality of target travel intervals.

[0051] Among them, the target travel range is a short travel range that conforms to the probability distribution of the braking characteristic parameters, which can reflect the operating scenarios of the target heavy-duty vehicle under different road conditions.

[0052] It can be understood that the embodiments of the present application can determine multiple target travel intervals from the sample operation data of the target vehicle type heavy-duty vehicle according to the probability distribution, and generate a test cycle for the braking emissions of the heavy-duty vehicle to be tested according to the multiple target travel intervals. The generated test cycle can meet the braking characteristics of the actual road operation of the target vehicle type, so that the subsequent heavy-duty vehicle to be tested can perform braking emissions tests based on the test cycle to reflect the actual braking emissions of the vehicle, which can provide a basis for formulating reasonable emission standards for heavy-duty vehicles and reduce non-exhaust particulate matter emissions from heavy-duty vehicles.

[0053] In an embodiment of the present application, before determining multiple target travel intervals from the sample operation data of the target model heavy-duty vehicle according to the probability distribution, it also includes: obtaining sample operation data of heavy-duty vehicles of multiple models in the heavy-duty vehicle emission remote supervision platform; determining target sample operation data from the sample operation data according to the target model of the heavy-duty vehicle to be tested, and constructing a sample operation database of the target model heavy-duty vehicle based on the target sample operation data; determining multiple target travel intervals from the sample operation database of the target model heavy-duty vehicle according to the probability distribution.

[0054] It can be understood that the embodiments of the present application can obtain sample operation data of heavy-duty vehicles of various models in the remote monitoring platform for heavy-duty vehicle emissions, and determine the target sample operation data of the target model heavy-duty vehicle from the sample operation data according to the target model of the heavy-duty vehicle to be tested, and construct a sample operation database of the target model heavy-duty vehicle based on the target sample operation data, and then determine multiple target travel intervals from the sample operation database of the target model heavy-duty vehicle according to the probability distribution.

[0055] In an embodiment of the present application, before determining multiple target travel intervals from a sample operation database of a target vehicle type heavy-duty vehicle according to a probability distribution, it also includes: segmenting the operation travel in the sample operation database of the target vehicle type heavy-duty vehicle to obtain multiple travel intervals; filtering multiple travel intervals based on travel interval screening rules to obtain multiple travel intervals that meet the screening rules, and classifying the multiple travel intervals that meet the screening rules, wherein different categories of travel intervals correspond to different speed intervals, deceleration intervals and parking durations of the cycle; constructing a target travel library based on multiple travel intervals that meet the screening rules; and screening multiple target travel intervals that are consistent with the probability distribution in the target travel library.

[0056] Among them, the filtering rules are pre-set by the user based on needs, including filtering rules including maximum speed, maximum deceleration, maximum acceleration, etc.

[0057] It can be understood that the embodiment of the present application can divide the running trip in the sample running database of the target vehicle model into multiple short trip intervals, and filter the multiple formed intervals according to the screening rules to obtain multiple trip intervals (valid trip intervals) that meet the screening rules, and classify the multiple trip intervals that meet the screening rules, wherein different categories of trip intervals correspond to different speed intervals, deceleration intervals and parking durations of the cycle, and then construct a target trip library based on the multiple trip intervals that meet the screening rules; and filter multiple target trip intervals that are consistent with the probability distribution in the target trip library.

[0058] Specifically, the construction process of the test cycle includes: according to the operation data of the heavy-duty vehicle emission remote supervision platform, an independent vehicle operation database is established for the target heavy-duty vehicle, and the vehicle operation data is cut to generate the short-stroke library of the target heavy-duty vehicle; the screening rules including the maximum speed, maximum deceleration, maximum acceleration, etc. are formulated to screen out the effective short-stroke library; the short-stroke library is divided and defined by principal component analysis and cluster analysis. The short strokes in different short-stroke libraries respectively reflect the operation scenarios of the target heavy-duty vehicle under different road conditions, corresponding to different speed intervals, acceleration intervals and parking duration intervals of the cycle. From the established short-stroke library, a short stroke that is consistent with the probability distribution of the actual road operation braking characteristic parameters (average deceleration, braking duration and initial braking speed) of the target heavy-duty vehicle is selected to construct the preliminary braking emission test cycle of the target heavy-duty vehicle to be tested.

[0059] In an embodiment of the present application, after generating a test cycle for the brake emission of the heavy-duty vehicle to be tested according to multiple target travel intervals, it also includes: performing a chi-square test on the braking characteristic parameters of the test cycle based on the probability distribution; adjusting the multiple target travel intervals based on the results of the chi-square test until the braking characteristic parameters of the test cycle conform to the probability distribution.

[0060] It can be understood that after generating a test cycle for the brake emissions of the heavy-duty vehicle to be tested, the embodiment of the present application can perform a chi-square test on the braking characteristic parameters of the test cycle based on the probability distribution, and adjust multiple target travel intervals according to the test results until the braking characteristic parameters of the test cycle conform to the probability distribution, thereby improving the accuracy of the test cycle, ensuring that the generated test cycle can truly reflect the actual operating characteristics of the heavy-duty vehicle under various working conditions, and improving the credibility of the test results.

[0061] Specifically, the specific process of the test cycle construction method for heavy-duty vehicle brake emissions in the embodiment of the present application is as follows: Figure 2As shown, the following steps are included:

[0062] 1. Determine the vehicle type classification for heavy-duty vehicle brake emission test cycle construction, such as city buses, passenger cars, trucks, dump trucks and semi-trailer tractors.

[0063] 2. Establish a preliminary deceleration threshold curve related to vehicle speed for a specific type (target vehicle type) of heavy-duty vehicle. Through the heavy-duty vehicle emission remote monitoring platform, a large sample of actual operating data of a specific type of heavy-duty vehicle can be obtained, including information such as time, vehicle speed, and engine speed. By applying the experience of the minimum deceleration threshold of the braking event caused by the brake action, a preliminary deceleration threshold curve related to vehicle speed for a specific type of heavy-duty vehicle can be established.

[0064] 3. Establish the best-fit deceleration threshold curve related to the vehicle speed for a specific type of heavy-duty vehicle. The data of the remote monitoring platform for heavy-duty vehicle emissions does not contain information on braking torque or braking pressure, so it is impossible to determine whether a deceleration event is caused by brake action or by the driver lifting the accelerator or the vehicle's driving resistance. In order to screen out vehicle deceleration caused by non-brake friction (such as lifting the accelerator, driving resistance, etc.), this application uses a specific type of heavy-duty vehicle (more than 10 vehicles) to collect vehicle time, speed, engine speed, braking torque / brake pressure, brake engagement and other information under actual road operating conditions, and can obtain the braking conditions of the brakes of a specific type of heavy-duty vehicle under actual road operating conditions. Using actual braking condition data, for a specific type of heavy-duty vehicle, first perform linear interpolation processing on the missing values, outliers, etc. of the deceleration threshold curve related to the vehicle speed to correct the data, and perform logarithmic fitting on the corrected data, and the best-fit deceleration threshold curve related to the vehicle speed for a specific type of heavy-duty vehicle can be obtained:

[0065] a_threshold=b1*ln(v)+c1; (1)

[0066] Where a is the deceleration, m / s 2 ; v is the vehicle speed, km / h; b1 is the logarithmic term coefficient; c1 is the constant term.

[0067] 4. Analyze the probability distribution of braking characteristic parameters that are consistent with the actual road operation of heavy-duty vehicles. Obtain the actual operation data of heavy-duty vehicles of a specific type of heavy-duty vehicle emission remote monitoring platform, and screen out the deceleration segments caused by brake action through the best-fit deceleration threshold curve related to the vehicle speed of the vehicle model. Each deceleration segment is called a braking event. Calculate the average deceleration, initial braking speed, braking interval time, braking duration, braking distance, and number of brakes per kilometer for each braking event, and perform probability distribution analysis on the braking characteristic parameters of all deceleration events obtained to obtain the probability distribution of braking characteristic parameters of the actual road operation of a specific type of heavy-duty vehicle.

[0068] 5. Construct a preliminary brake emission test cycle for a specific type of heavy-duty vehicle. Based on the operating data of the heavy-duty vehicle emission remote supervision platform, an independent vehicle operation database is established for a specific type of heavy-duty vehicle, and the vehicle operation data is cut to generate a short-stroke library for a specific type of heavy-duty vehicle; formulate screening rules including maximum speed, maximum deceleration, maximum acceleration, etc., to screen out an effective short-stroke library; use principal component analysis and cluster analysis to divide and define the short-stroke library. The short strokes in different short-stroke libraries reflect the operating scenarios of a specific type of heavy-duty vehicle under different road conditions, corresponding to different speed ranges, acceleration ranges, and parking duration ranges of the cycle. Select a short stroke that matches the probability distribution of the braking characteristic parameters (average deceleration, braking duration, and initial braking speed) of the actual road operation of a specific type of heavy-duty vehicle from the established short-stroke library to construct a preliminary brake emission test cycle for a specific type of heavy-duty vehicle.

[0069] 6. Based on the probability distribution of the braking characteristic parameters of a specific type of heavy-duty vehicle, a chi-square test is performed on the braking characteristic parameters of the preliminary braking emission test cycle of the constructed specific type of heavy-duty vehicle, and a braking emission test cycle curve that conforms to the actual road operation braking characteristics of the specific type of heavy-duty vehicle can be obtained.

[0070] In summary, the present application can construct a brake emission test cycle based on the actual road operation data of the vehicle of the heavy-duty vehicle emission remote supervision platform, and can obtain a large sample of actual operation data without increasing the cost of additional data acquisition, further expanding the basic database for the construction of the brake emission test cycle, and greatly reducing the cost of constructing the brake emission test cycle; through the test data analysis results of the braking characteristics such as braking torque / brake pressure of heavy-duty vehicles traveling on actual roads, the preliminary deceleration threshold curve related to the vehicle speed of the established specific type of heavy-duty vehicle can be fitted and corrected to screen out deceleration events caused by brake action, so as to ensure the accuracy of the probability distribution analysis of the braking characteristic parameters of the actual road operation of the heavy-duty vehicle; by performing a chi-square test on the constructed preliminary brake emission test cycle of the specific type of heavy-duty vehicle and the probability distribution of the braking characteristic parameters of the actual road operation of the heavy-duty vehicle, it can be ensured that the constructed brake emission test cycle meets the braking characteristics of the actual road operation of the specific heavy-duty vehicle.

[0071] According to the test cycle construction method for heavy-duty vehicle braking emissions proposed in the embodiment of the present application, the initial deceleration threshold curve of the heavy-duty vehicle to be tested can be determined according to the target model of the heavy-duty vehicle to be tested, and the actual operation data of the target model heavy-duty vehicle under actual road operating conditions can be collected, so as to determine the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested that meet the actual operation, and determine multiple target travel intervals from the sample operation data of the target model heavy-duty vehicle according to the probability distribution, and generate a test cycle for the braking emissions of the heavy-duty vehicle to be tested according to the multiple target travel intervals, so as to ensure that the generated test cycle can meet the braking characteristics of the actual road operation of the target model, so that the subsequent heavy-duty vehicle to be tested can perform braking emissions tests according to the test cycle, reflecting the actual braking emissions of the vehicle, and the test accuracy is high, so as to provide a basis for formulating reasonable emission standards for heavy-duty vehicles and reduce non-exhaust particulate matter emissions of heavy-duty vehicles.

[0072] The following describes the test cycle construction method for heavy-duty vehicle brake emissions in the embodiment of the present application through a specific embodiment, taking a truck as an example, including the following steps:

[0073] 1. Select a specific type of heavy-duty vehicle. This embodiment takes a truck as an example, that is, construct a brake emission test cycle for the truck.

[0074] 2. Establish a preliminary deceleration threshold curve related to truck speed. Through the heavy-duty vehicle emission remote monitoring platform, we can obtain a large sample of actual operation data of my country's trucks, including time, speed, engine speed and other information. Through the analysis of these operation data, we can establish a preliminary deceleration threshold curve related to truck speed.

[0075] 3. Obtain the braking data of my country's trucks under actual road conditions through actual testing. Select more than 10 trucks in good operating condition and collect vehicle time, speed, engine speed, brake torque / brake pressure, brake engagement and other data information under actual road conditions.

[0076] 4. Use actual braking data to correct and fit the deceleration threshold curve related to truck speed, and you can get the best fitting deceleration threshold curve related to truck speed. This step is mainly to screen out vehicle deceleration caused by non-brake friction (such as lifting the accelerator, driving resistance, etc.) in the preliminary deceleration threshold curve, so that the deceleration events analyzed by the best fitting deceleration threshold curve are all caused by brake friction, so as to indirectly analyze the braking characteristics of my country's trucks through the speed-time data obtained by the heavy-duty vehicle emission remote supervision platform. Through analysis, the best fitting deceleration threshold curve for a certain type of vehicle can be obtained as follows:

[0077] a_threshold=-0.097065*ln(v)-0.3185; (2)

[0078] Where a is the deceleration, m / s 2 ; v is vehicle speed, km / h.

[0079] 5. Analyze the probability distribution of braking characteristic parameters that are consistent with the actual road operation of trucks. By analyzing the actual operation data of trucks on the heavy-duty vehicle emission remote supervision platform through the best fitting deceleration threshold curve related to the truck speed, the probability distribution of braking characteristic parameters of the actual road operation of trucks can be obtained, including average deceleration, initial braking speed, braking interval time, braking duration, braking distance, number of brakes per kilometer, etc.

[0080] 6. Construct a preliminary braking emission test cycle for trucks. According to the operating data of the heavy-duty vehicle emission remote supervision platform, an independent vehicle operation database is established for trucks, and the vehicle operation data is cut to generate a short-trip library for trucks; formulate screening rules including maximum speed, maximum deceleration, maximum acceleration, etc., to screen out an effective short-trip library; use principal component analysis and cluster analysis to divide and define the short-trip library. The short trips in different short-trip libraries reflect the operating scenarios of trucks under different road conditions, corresponding to different speed ranges, acceleration ranges and parking duration ranges of the cycle. From the established short-trip library, select a short trip that is consistent with the probability distribution of the actual road operation braking characteristic parameters (average deceleration, braking duration and initial braking speed) of the truck, and the preliminary braking emission test cycle for the truck.

[0081] 7. Based on the probability distribution of the braking characteristic parameters of the actual road operation of trucks, a chi-square test is performed on the braking characteristic parameters of the preliminary braking emission test cycle of the constructed trucks, and a braking emission test cycle curve that conforms to the braking characteristics of the actual road operation of trucks can be obtained.

[0082] In addition, the present application embodiment also provides a heavy-duty vehicle brake emission test cycle construction system, such as Figure 3 As shown, including:

[0083] 1. Obtain actual operation data of a large sample of trucks through the heavy-duty vehicle emission remote monitoring platform 21, including time, vehicle speed, engine speed and other information.

[0084] 2. The deceleration threshold curve calculation module 22 is used to analyze the actual operation data of a large sample of trucks obtained by the heavy-duty vehicle emission remote monitoring platform 21, and the braking information obtained by the braking characteristic parameter acquisition module 23 under actual road operating conditions, to complete the establishment of a preliminary deceleration threshold curve related to the truck speed and the best fitting deceleration threshold curve.

[0085] 3. The braking characteristic parameter acquisition module 23 under actual road operating conditions is used to collect the braking information of the truck's brakes under actual road operating conditions (the collected information includes the vehicle's time, speed, engine speed, braking torque / brake pressure, brake engagement status, etc.). In this embodiment, the braking characteristic parameter acquisition module 23 under actual road operating conditions can be further configured as follows: a braking torque sensor or a braking pressure sensor is installed on the brake of the test vehicle to obtain the braking torque or braking pressure data of the test vehicle, and the test vehicle is connected to the OBD interface of the test vehicle through the computer's Inka software on the test vehicle to obtain the test vehicle's time, speed, engine speed and other information.

[0086] 4. The heavy-duty vehicle braking characteristic parameter probability distribution calculation module 24 under actual road operating conditions is used to analyze the actual operating data of a large sample of trucks obtained by the heavy-duty vehicle emission remote monitoring platform 21 to obtain the braking characteristic parameter probability distribution of the trucks.

[0087] 5. Use the heavy-duty vehicle short-trip library to establish a calculation module 25 to establish a vehicle operation database for the truck operation data acquired by the heavy-duty vehicle emission remote monitoring platform 21, and cut the vehicle operation data to generate a short-trip library for the truck.

[0088] 6. Use the heavy-duty vehicle brake emission test cycle establishment / adjustment calculation module 26 to screen, divide and define the short-stroke library, and select short strokes that are consistent with the probability distribution of the truck's actual road operation braking characteristic parameters (average deceleration, braking duration and braking initial speed) to construct the truck's preliminary brake emission test cycle. Then use this module to perform a chi-square test on the braking characteristic parameters of the constructed preliminary brake emission test cycle of the truck based on the probability distribution of the truck's braking characteristic parameters, and you can get a brake emission test cycle curve that meets the truck's actual road operation braking characteristics.

[0089] In general, the heavy-duty vehicle brake emission test cycle construction method of the embodiment of the present application can (1) ensure that the constructed brake emission test cycle of a specific type of heavy-duty vehicle meets the actual road operation braking characteristics of the heavy-duty vehicle of this type. By analyzing the test data results of brake characteristic parameters such as brake torque / brake pressure of heavy-duty vehicles on actual roads, the preliminary deceleration threshold curve related to the vehicle speed of the established specific type of heavy-duty vehicle can be fitted and corrected to screen out deceleration events caused by brake action, thereby ensuring the accuracy of the probability distribution analysis of the brake characteristic parameters of the actual road operation of the heavy-duty vehicle; by performing a chi-square test on the constructed preliminary brake emission test cycle of the specific type of heavy-duty vehicle and the probability distribution of the brake characteristic parameters of the actual road operation of the heavy-duty vehicle, it can be ensured that the constructed brake emission test cycle meets the braking characteristics of the actual road operation of the specific heavy-duty vehicle. (2) It can significantly reduce the development cost of brake emission test cycle construction. Based on the actual road operation data of the vehicle of the heavy-duty vehicle emission remote supervision platform, the brake emission test cycle is constructed, and a large sample of actual operation data can be obtained without increasing the cost of additional data acquisition, further expanding the basic database for brake emission test cycle construction, and significantly reducing the cost of brake emission test cycle construction. (3) It can solve the problem that there is no method for constructing a brake emission test cycle for heavy-duty vehicles. Currently, only the UN GTR standard stipulates a brake emission test cycle for light-duty vehicles, and other domestic and foreign standards or research papers have not reported a brake emission test cycle for heavy-duty vehicles. The present invention provides a method for constructing a brake emission test cycle for heavy-duty vehicles.

[0090] Next, a test cycle construction device for heavy-duty vehicle brake emissions proposed in an embodiment of the present application will be described with reference to the accompanying drawings.

[0091] Figure 4 It is a block diagram of a test cycle construction device for heavy-duty vehicle brake emissions according to an embodiment of the present application.

[0092] like Figure 4 As shown, the heavy-duty vehicle brake emission test cycle construction device 10 includes: an acquisition module 100 , a determination module 200 , a calculation module 300 and a generation module 400 .

[0093] Among them, the acquisition module 100 is used to obtain the target model of the heavy-duty vehicle to be tested; the determination module 200 is used to determine the initial deceleration threshold curve of the heavy-duty vehicle to be tested based on the target model; the calculation module 300 is used to collect the actual operation data of the target model heavy-duty vehicle under actual road operating conditions, and calculate the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested according to the initial deceleration threshold curve and the actual operation data of the target model; the generation module 400 is used to determine multiple target travel intervals from the sample operation data of the target model heavy-duty vehicle according to the probability distribution, and generate a test cycle of the braking emission of the heavy-duty vehicle to be tested according to the multiple target travel intervals.

[0094] In an embodiment of the present application, the calculation module 300 is further used to: correct the initial deceleration threshold curve according to the actual operating data to obtain the target deceleration threshold curve; analyze the sample operating data of the target vehicle model heavy-duty vehicle according to the target deceleration curve to obtain the braking characteristic parameters of the heavy-duty vehicle to be tested that conform to the actual operating data, and calculate the probability distribution of the braking characteristic parameters.

[0095] In the embodiment of the present application, the device 10 of the embodiment of the present application further includes: a construction module.

[0096] Among them, the construction module is used to obtain sample operation data of heavy-duty vehicles of various models in the heavy-duty vehicle emission remote supervision platform before determining multiple target travel intervals from the sample operation data of the target model heavy-duty vehicle according to the probability distribution; determine the target sample operation data from the sample operation data according to the target model of the heavy-duty vehicle to be tested, and construct the sample operation database of the target model heavy-duty vehicle based on the target sample operation data; determine multiple target travel intervals from the sample operation database of the target model heavy-duty vehicle according to the probability distribution.

[0097] In the embodiment of the present application, the device 10 of the embodiment of the present application further includes: a screening module.

[0098] Among them, the screening module is used to divide the running travel in the sample running database of the target vehicle model heavy-duty vehicle to obtain multiple travel intervals before determining multiple target travel intervals from the sample running database of the target vehicle model heavy-duty vehicle according to the probability distribution; screen the multiple travel intervals based on the screening rules of the travel intervals to obtain multiple travel intervals that meet the screening rules, and classify the multiple travel intervals that meet the screening rules, wherein different categories of travel intervals correspond to different speed intervals, deceleration intervals and parking durations of the cycle; construct a target travel library based on the multiple travel intervals that meet the screening rules; and screen multiple target travel intervals that are consistent with the probability distribution in the target travel library.

[0099] In the embodiment of the present application, the calculation module 300 is further used to: obtain the braking data information of the target vehicle type heavy-duty vehicle in the actual operation data; and correct the initial deceleration threshold curve according to the braking data information.

[0100] In the embodiment of the present application, the device 10 of the embodiment of the present application further includes: an adjustment module.

[0101] Among them, the adjustment module is used to perform a chi-square test on the braking characteristic parameters of the test cycle based on the probability distribution after generating a test cycle of the brake emission of the heavy-duty vehicle to be tested according to multiple target travel intervals; and adjust the multiple target travel intervals based on the results of the chi-square test until the braking characteristic parameters of the test cycle meet the probability distribution.

[0102] It should be noted that the aforementioned explanation of the embodiment of the method for constructing a test cycle for brake emissions of heavy vehicles is also applicable to the device for constructing a test cycle for brake emissions of heavy vehicles of this embodiment, and will not be repeated here.

[0103] According to the test cycle construction device for heavy-duty vehicle braking emissions proposed in the embodiment of the present application, the initial deceleration threshold curve of the heavy-duty vehicle to be tested can be determined according to the target model of the heavy-duty vehicle to be tested, and the actual operation data of the target model heavy-duty vehicle under actual road operating conditions can be collected, so as to determine the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested that meet the actual operation, and determine multiple target travel intervals from the sample operation data of the target model heavy-duty vehicle according to the probability distribution, and generate a test cycle for the braking emissions of the heavy-duty vehicle to be tested according to the multiple target travel intervals, so as to ensure that the generated test cycle can meet the braking characteristics of the actual road operation of the target model, so that the subsequent heavy-duty vehicle to be tested can perform braking emission tests according to the test cycle, reflecting the actual braking emissions of the vehicle, and the test accuracy is high, so as to provide a basis for formulating reasonable emission standards for heavy-duty vehicles and reduce non-exhaust particulate matter emissions of heavy-duty vehicles.

[0104] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0105] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0106] When the processor 502 executes the program, the test cycle construction method for heavy-duty vehicle brake emissions provided in the above embodiment is implemented.

[0107] Furthermore, the electronic device further comprises:

[0108] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0109] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0110] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0111] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0112] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0113] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0114] An embodiment of the present application also provides a computer-readable storage medium having a computer program or instruction stored thereon. When the computer program or instruction is executed by a processor, the test cycle construction method for heavy-duty vehicle brake emissions as described above is implemented.

[0115] The embodiment of the present application also provides a computer program product, including a computer program or instructions, which, when executed, implements the above-mentioned test cycle construction method for heavy-duty vehicle brake emissions.

[0116] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0117] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0118] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0119] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of multiple of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0120] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

Claims

1. A method for constructing a test cycle for heavy-duty vehicle brake emissions, characterized in that: The following steps are involved: Obtain the target model of the heavy-duty vehicle to be tested; Determining an initial deceleration threshold curve of the heavy-duty vehicle to be tested based on the target vehicle type; Collecting actual operating data of a target heavy-duty vehicle under actual road operating conditions, and calculating a probability distribution of a braking characteristic parameter of the heavy-duty vehicle to be tested according to the initial deceleration threshold curve and the actual operating data of the target vehicle; A plurality of target travel intervals are determined from sample operation data of the target heavy-duty vehicle according to the probability distribution, and a test cycle of brake emission of the heavy-duty vehicle to be tested is generated according to the plurality of target travel intervals.

2. The test cycle construction method for heavy vehicle brake emissions according to claim 1, characterized in that: The calculating the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested according to the initial deceleration threshold curve and the actual operating data of the target vehicle type includes: Correcting the initial deceleration threshold curve according to the actual operation data to obtain a target deceleration threshold curve; The sample operation data of the target heavy-duty vehicle is analyzed according to the target deceleration curve to obtain the braking characteristic parameters of the heavy-duty vehicle to be tested that conform to the actual operation data, and the probability distribution of the braking characteristic parameters is calculated.

3. The test cycle construction method for heavy vehicle brake emissions according to claim 1, characterized in that: Before determining a plurality of target travel intervals from the sample running data of the target heavy-duty vehicle according to the probability distribution, the method further includes: Obtain sample operation data of various heavy-duty vehicles in the heavy-duty vehicle emission remote monitoring platform; Determining target sample operation data from the sample operation data according to the target model of the heavy-duty vehicle to be tested, and constructing a sample operation database of the target model of the heavy-duty vehicle based on the target sample operation data; A plurality of target travel intervals are determined from a sample operation database of the target vehicle type heavy-duty vehicle according to the probability distribution.

4. The test cycle construction method for heavy vehicle brake emissions according to claim 3 is characterized in that: Before determining a plurality of target travel intervals from a sample operation database of the target heavy-duty vehicle according to the probability distribution, the method further includes: Segmenting the running trips in the sample running database of the target heavy-duty vehicle to obtain a plurality of running intervals; Based on the screening rule of the travel interval, the multiple travel intervals are screened to obtain multiple travel intervals that meet the screening rule, and the multiple travel intervals that meet the screening rule are classified, wherein different categories of travel intervals correspond to different speed intervals, deceleration intervals and parking durations of the cycle; Building a target trip library based on multiple trip intervals that meet the screening rules; A plurality of target travel intervals that are consistent with the probability distribution are selected from the target travel library.

5. The test cycle construction method for heavy vehicle brake emissions according to claim 2, characterized in that: The step of correcting the initial deceleration threshold curve according to the actual operation data includes: Obtaining braking data information of the target heavy-duty vehicle in the actual operation data; The initial deceleration threshold curve is modified according to the braking data information.

6. The test cycle construction method for heavy vehicle brake emissions according to claim 1, characterized in that: After generating the test cycle of the brake emission of the heavy vehicle to be tested according to the multiple target travel intervals, the method further includes: Performing a chi-square test on the braking characteristic parameters of the test cycle based on the probability distribution; The plurality of target travel intervals are adjusted based on the result of the chi-square test until the braking characteristic parameters of the test cycle conform to the probability distribution.

7. A test cycle construction device for heavy vehicle brake emissions, characterized in that: include: An acquisition module is used to acquire the target model of the heavy-duty vehicle to be tested; A determination module, configured to determine an initial deceleration threshold curve of the heavy-duty vehicle to be tested based on the target vehicle type; A calculation module, used to collect actual operating data of a target heavy-duty vehicle under actual road operating conditions, and calculate the probability distribution of the braking characteristic parameters of the heavy-duty vehicle to be tested according to the initial deceleration threshold curve and the actual operating data of the target vehicle; A generation module is used to determine multiple target travel intervals from the sample operation data of the target heavy-duty vehicle according to the probability distribution, and generate a test cycle of the brake emission of the heavy-duty vehicle to be tested according to the multiple target travel intervals.

8. An electronic device, characterized in that: include: 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 test cycle construction method for heavy vehicle brake emissions as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: The computer program or instructions are executed by a processor to implement the test cycle construction method for heavy-duty vehicle brake emissions as described in any one of claims 1-6.

10. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed, the test cycle construction method for heavy vehicle brake emissions as described in any one of claims 1-6 is implemented.

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