Expressway vehicle brake and tire wear particulate matter emission calculation method

Abstract

The invention discloses an expressway vehicle brake and tire wear particulate matter emission calculation method. The method comprises the steps of obtaining basic information data of a to-be-researched expressway and expressway motor vehicle trajectory data; the MOVES model is subjected to localization processing, and a VSP-Bin distribution table of motor vehicle brake and tire wear particulate matter emission and emission factors and emission rates under Bin distribution are obtained through the localized MOVES model; calculating expressway motor vehicle brake and tire wear particulate matter discharge under the second-by-second track; and calculating the expressway motor vehicle brake and tire wear particulate matter discharge amount under the spatial latitude. According to the invention, the MOVES model brake and tire wear emission calculation module is used to calculate a highway motor vehicle brake and tire wear particulate matter emission list under a second-by-second track, and the emission conditions of different regions of a highway can be analyzed.

Description

Technical Field

[0001] The invention belongs to the technical field of traffic engineering, and in particular relates to a method for calculating emission of particulate matter from braking and tire wear of vehicles on highways. Background Art

[0002] The main methods for evaluating non-exhaust emissions from motor vehicles, especially brake and tire wear particulate matter, currently include model-based estimation and experimental testing. Model-based estimation methods usually involve the use of emission models in a specific operating environment. The model depends on parameters such as geographical location, climate conditions and road characteristics for local adjustment. Commonly used models include MOVES, MOBILE, COPERT and EMFAC. However, there is a lack of methods to apply the MOVES model to calculate the brake and tire particulate matter emissions of motor vehicles under second-by-second trajectories and calculate their spatiotemporal emission characteristics. Experimental testing methods mainly rely on bench tests in laboratories or portable monitoring equipment on actual roads to measure the emission factors of tires and brakes. This method can more accurately reflect the emissions under real road conditions, but its disadvantages are high cost and difficulty in fully covering different road and traffic conditions. Therefore, it is of great significance to establish a highly portable model for non-exhaust emissions from transportation in different regions. Summary of the invention

[0003] Based on the problem that the prior art lacks a method for calculating the second-by-second trajectory of motor vehicle brake and tire wear particle emissions, and it is difficult to analyze the spatiotemporal distribution characteristics of motor vehicle brake and tire wear particle emissions, the present invention provides a method for calculating highway vehicle brake and tire wear particle emissions. The method can perform localized correction on high-speed traffic data based on the MOVES model, and calculate the motor vehicle brake and tire particle emissions and spatiotemporal distribution characteristics under the second-by-second trajectory.

[0004] The technical solution of the present invention is as follows: A method for calculating the emission of particulate matter from braking and tire wear of vehicles on highways comprises the following steps: Step 1, obtaining basic information data of the highway to be studied and vehicle trajectory data of the highway; Step 2: localize the MOVES model, and obtain the VSP-Bin distribution table of motor vehicle brake and tire wear particulate matter emissions, as well as the emission factor and emission rate under the Bin distribution through the localized MOVES model; Step 3, calculating the highway motor vehicle braking and tire wear particulate matter emissions under the second-by-second trajectory; Step 4: Calculate the emission of particulate matter from braking and tire wear of motor vehicles on highways at spatial latitudes.

[0005] Specifically, the basic information of the expressway in step 1 includes geographical and meteorological information, including: road type, mileage, geographical location, temperature along the section, humidity along the section, section slope and location information of data collection points on the section.

[0006] Specifically, in step 1, the data of the motor vehicle trajectory data on the highway is cleaned, and then the motor vehicle specific power of the motor vehicle at different times is calculated according to the formula. The motor vehicle specific power calculation formula is:

[0007] In the formula, VSP n for n The specific power of the motor vehicle in seconds, v n For motor vehicles n The instantaneous speed in seconds, a n For motor vehicles n The instantaneous acceleration at the second.

[0008] Furthermore, step 3 specifically includes: extracting the displacement trajectory of a single motor vehicle from the motor vehicle trajectory data, obtaining the second-by-second operating conditions of the motor vehicle through the VSP formula and comparing the VSP-Bin distribution table of motor vehicle brake and tire wear particulate matter emissions in step 2, and then obtaining the second-by-second particulate matter emissions of the motor vehicle trajectory based on the emission factor and its emission rate under the Bin distribution.

[0009] Specifically, the calculation formula for particulate matter emissions from motor vehicle trajectories second by second includes:

[0010] in, i For the model, j is the vehicle number, n is the nth second of the vehicle's travel, v n Indicates the motor vehicle n Speed ​​per second, in m / s; d n Indicates the motor vehicle n Displacement per second, in m; d n-1 It represents the displacement of the motor vehicle at the n-1th second, in meters; D ij Indicates the model i、 Number j A second-by-second displacement trajectory dataset of motor vehicles; VSP n represents the specific power of the motor vehicle at the nth second; E ijIndicates the model i , numbered j A second-by-second dataset of particulate matter emissions from motor vehicles; E ijn Indicates the model i , numbered j The particulate matter emission of the motor vehicle at the nth second, Δ t = 1 second; e ijn Indicates the model i , numbered j The emission rate of the motor vehicle at the nth second, in g / s; e Bin represents the distribution of brake and tire emission factors under Bin distribution; VSP Bin Represents the VSP-Bin distribution table; E ij Indicates the model i , numbered j The total brake and tire emissions of motor vehicles on the highway section, in grams.

[0011] Furthermore, step 4 specifically includes the following steps: First, establish the spatial grid of the highway section and determine the interval between two adjacent spatial grids. L， According to the maximum displacement of all motor vehicles maxd n , calculate the number of spatial grids required num_grids , the calculation formula is:

[0012] Secondly, calculate the motor vehicle brake and tire emissions for each spatial grid using the following formula:

[0013] in, E(x) Representing a spatial grid x Total cumulative brake and tire wear particulate matter emissions; E ijn Indicates the model i , numbered j The particulate matter emission of motor vehicles at the nth second; x n Indicates the trajectory of the vehicle n The number of the grid corresponding to the second; δ ( xx n ) represents the Kronecker function, when x=x n The value is 1 when the condition is true, otherwise it is 0.

[0014] The beneficial effects of the present invention are: The present invention uses the brake and tire wear particulate matter emission calculation module of the MOVES model to obtain the VSP-Bin distribution table of motor vehicle brake and tire wear particulate matter emissions and the emission factor and emission rate under the Bin distribution, calculates the highway motor vehicle brake and tire wear particulate matter emission inventory under the second-by-second trajectory, and then analyzes the wear particulate matter emissions in different areas of the highway; this method simplifies the measurement process of motor vehicle brake and tire particulate matter emissions at the micro level to the greatest extent, and has high portability, and is suitable for calculating the highway motor vehicle brake and tire particulate matter emission inventory under different operating environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flow chart of the method of the present invention; Figure 2 This is a case diagram of a road section studied in the present invention; Figure 3 It is the motor vehicle brake wear particulate emission factor under different Bin distributions calculated by the present invention according to the localized MOVES model; Figure 4 It is the motor vehicle tire wear particulate emission factor under different Bin distributions calculated by the present invention according to the localized MOVES model; Figure 5 This is a graph showing the annual changes in PM10 emission factors generated by braking of a large truck in an embodiment of the present invention; Figure 6 It is the spatiotemporal emission distribution map of vehicle brake and tire wear particulate matter. DETAILED DESCRIPTION

[0016] The calculation method proposed by the present invention is explained in full and detail below in conjunction with the accompanying drawings and embodiments of the specification.

[0017] Embodiment 1:

[0018] like Figure 1 The flowchart of the method of the present invention is a method for calculating the emission of particulate matter from braking and tire wear of vehicles on highways, which specifically includes: Step 1: Obtain basic information data of the highway to be studied and the vehicle trajectory data of the highway.

[0019] In this step, the main basic information obtained is the geographical meteorological information of the highway, including: the road type of the highway section, the mileage of the section, the geographical location of the section, the temperature of the area along the section, the humidity of the area along the section, the slope of the section and the location information of the data collection points of the section.

[0020] like Figure 2This embodiment takes a section of a city highway as an example. The highway section is about 678.75 meters long and is located in a plain area. The road type is a city expressway. The climate along the line is a subtropical monsoon climate. The motor vehicle trajectory data was collected in April. The average daytime temperature was 20°C. According to historical meteorological data, the humidity was 50%, and the slope of the section was 0°.

[0021] The motor vehicle trajectory data obtained in this step mainly include: highway flow data, highway motor vehicle category information, second-by-second motor vehicle travel spatiotemporal trajectory data, average motor vehicle speed on highway sections, and motor vehicle mileage information.

[0022] The methods for collecting motor vehicle trajectory data on highways include: shooting videos at fixed points on highways, vehicle trajectory data based on GPS, active vehicle trajectory collection based on mobile phone APP or vehicle-mounted software, etc. The data is characterized by continuous, second-by-second spatiotemporal trajectory data of motor vehicles, and includes the model information of each motor vehicle.

[0023] The second-by-second spatiotemporal trajectory data of motor vehicles on the research section of this embodiment are shown in Table 1, where the vehicle ID is 1 and the vehicle type is 20, indicating the displacement, speed and acceleration of a vehicle of type household light vehicle between 1 and 24 seconds.

[0024] Table 1. Spatiotemporal trajectory data of motor vehicles

[0025] Perform data cleaning on the trajectory data to remove erroneous trajectory data such as missing, duplicated, and abnormal data, and retain the correct trajectory data.

[0026] Based on this data, the motor vehicle specific power at different times is calculated according to the formula to provide data input for calculating the emission inventory. The motor vehicle specific power calculation formula is:

[0027] In the formula, VSP n for n The specific power of the motor vehicle in seconds, v n For motor vehicles n The instantaneous speed in seconds, a n For motor vehicles n The instantaneous acceleration at the second.

[0028] Step 2: localize the MOVES model and calculate the VSP-Bin distribution table of motor vehicle brake and tire wear particulate matter emissions and the emission factor rate under the Bin distribution through the localized MOVES model.

[0029] During the localization process of the MOVES model, the fuel type parameters, climate information parameters, geographic information parameters, road type parameters, air conditioning parameters and the average age of motor vehicles in the localization module of the MOVES model are localized and corrected to ensure that the model can accurately reflect the actual operating environment of the highway. The localization process is an existing technology and will not be repeated here.

[0030] When calculating the average age of motor vehicles, the annual statistical yearbooks of the surrounding areas of the expressway are used; the formula , calculate the distribution ratio of motor vehicles in different years, and thus calculate the average age of motor vehicles on the highway, so as to complete the localization processing of the MOVES model.

[0031] In the above formula, m is the model year; k For the measurement year; S m is the number of motor vehicles registered in the year, estimated as the number of new vehicles in the year; P k The total number of motor vehicles in the measurement year; V m is the proportion of vehicles in the stated year.

[0032] By running the localized MOVES model, the VSP-Bin distribution tables of brake wear particles and tire wear particles during the driving of the motor vehicle are obtained, as shown in Tables 2 and 3 respectively. Table 2 shows the definition of motor vehicle brake emissions under different working conditions, and Table 3 shows the definition of motor vehicle tire emissions under different working conditions.

[0033] Table 2 Different working conditions of motor vehicle brake emissions

[0034] Table 3 Different operating conditions of motor vehicle tire emissions

[0035] Bin=0 is the braking state, and Bin=1 is the idling state of the vehicle.

[0036] According to the emission inventory generated by the localized MOVES model, the emission factors and emission rates of brake and tire wear particulate matter emissions under Bin distribution are obtained respectively. According to the vehicle types on this highway section, which mainly include motorcycles, light vehicles, small trucks, long-distance buses, urban buses, cargo trucks and trailers, the corresponding vehicle types are found in the MOVES model, and the emission factors and rates under Bin distribution are obtained.

[0037] like Figure 3 and Figure 4 As shown, Figure 3 The emission factors of PM2.5 emissions from tire wear of different types of motor vehicles under Bin distribution are shown. Figure 4 The emission factors of PM2.5 emissions from brakes of different models of motor vehicles under Bin distribution are shown. It can be seen that the emission size of brake and tire wear particles of different models of motor vehicles is positively correlated with the average tonnage of their models.

[0038] In order to further demonstrate the differences in emission rates of vehicles of different ages, the present invention selects 2020 as the base year, and analyzes in detail the changing trends of motor vehicle brake emission factors from 1990 to 2020. In view of the fact that tire wear emissions are mainly affected by material properties and have a low correlation with the age of the vehicle, the present invention does not include tire wear emissions in the scope of investigation, but conducts an in-depth discussion on the changes in brake emissions under different vehicle age conditions. Taking heavy trucks as an example, the present invention selects brake emission factors under four operating conditions: idle (Bin 1), low speed (Bin 11), medium speed (Bin 21) and high speed (Bin 33) for analysis. All data are presented in grams per second (g / s). Figure 5 The research results show that for heavy trucks, the change in brake emission factor with vehicle age is relatively small at idle and high speeds; while at low and medium speeds, more obvious fluctuations are observed.

[0039] Step 3, calculate the highway motor vehicle braking and tire wear particulate matter emissions based on the second-by-second trajectory.

[0040] By using the VSP formula and comparing the VSP-Bin distribution table of motor vehicle brake and tire wear particulate matter emissions in step 2, the second-by-second operating conditions of the motor vehicle are obtained, and then based on the emission factor and its emission rate under the Bin distribution, the second-by-second particulate matter emissions of the motor vehicle trajectory are obtained.

[0041] Extract the displacement trajectory of a single motor vehicle from the motor vehicle trajectory data:

[0042] in, i For the model, j is the vehicle number,n is the nth second of the vehicle's travel, v n It indicates the speed of the motor vehicle at the nth second, in m / s; d n It represents the displacement of the motor vehicle at the nth second, in m; d n-1 It represents the displacement of the motor vehicle at the n-1th second, in meters; D ij Indicates the model i、 Number j A second-by-second displacement trajectory dataset of motor vehicles; VSP n represents the specific power of the motor vehicle at the nth second; E ij Indicates the model i , numbered j A second-by-second dataset of particulate matter emissions from motor vehicles; E ijn Indicates the model i , numbered j The particulate matter emission of the motor vehicle at the nth second, Δ t = 1 second; e ijn Indicates the model i , numbered j The emission rate of the motor vehicle at the nth second, in g / s; e Bin represents the distribution of brake and tire emission factors under Bin distribution; VSP Bin Represents the VSP-Bin distribution table; E ij Indicates the model i , numbered j The total brake and tire emissions of motor vehicles on the highway section, in grams.

[0043] Step 4, calculate the highway motor vehicle brake and tire wear particulate matter emissions at spatial latitude, specifically including: First, establish the spatial grid of the highway section and determine the interval between two adjacent spatial grids. L， For dividing the spatial area of ​​the highway, this embodiment takes 5m interval as the spatial grid division scale, and then finds the maximum displacement of all motor vehicles maxd n , that is, the farthest position in the trajectory data is taken as the total length of the research section. maxd nThe displacement of the light vehicle with vehicle ID 1432 in the vehicle trajectory data is 678.75m. Next, calculate the number of required spatial grids num_grids , and its calculation formula is:

[0044] In this embodiment, it is calculated through a formula that the highway is divided into 136 spatial grids with a length of 5 meters.

[0045] Next, calculate the motor vehicle brake and tire emissions for each spatial grid and create a one-dimensional array E(x), where x represents the spatial grid number, initially 0, and the length of the array is num_grids. The emission of each spatial grid is calculated using the following formula:

[0046] in E(x) Representing a spatial grid x Total amount of brake and tire wear particulate matter emissions; E ijn Indicates the model i , numbered j The particulate matter emission of motor vehicles at the nth second; x n Indicates the trajectory of the vehicle n The number of the grid corresponding to the second; δ ( xx n ) represents the Kronecker function, when x=x n The value is 1 when the condition is true, otherwise it is 0.

[0047] Through the above steps, the cumulative motor vehicle brake and tire wear particulate matter emissions of all spatial grids can be calculated, so as to analyze the emission conditions in different areas of the highway, so that decision makers can formulate traffic management strategies based on the pollutant concentrations in different areas.

[0048] According to this calculation, the spatial emission characteristics of this highway section are obtained, such as Figure 6 As shown in the figure, it can be analyzed that the PM2.5 particle emissions from motor vehicles at the entrance and exit ramps are much greater than those at other sections, while the emissions from tire wear particles are relatively less variable. It can be inferred that the braking conditions of motor vehicles at the entrance and exit areas of highways are more frequent than those at ordinary sections, and the particle concentration in this area is higher. Therefore, decision makers can take traffic management measures for motor vehicles in this area to make the acceleration and deceleration of motor vehicles at the entrance and exit areas of highways smoother, thereby reducing the concentration of brake wear particle emissions.

[0049] Through the above content, relevant staff can make various changes and modifications within the framework of this calculation method to measure the brake and tire pollutant emissions of motor vehicles under different environmental roads. The technical scope of this invention is not limited to the content described in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A method for calculating the emission of particulate matter from braking and tire wear of vehicles on highways, characterized in that: The following steps are involved: Step 1, obtaining basic information data of the highway to be studied and vehicle trajectory data of the highway; Step 2: localize the MOVES model, and obtain the VSP-Bin distribution table of motor vehicle brake and tire wear particulate matter emissions, as well as the emission factor and emission rate under the Bin distribution through the localized MOVES model; Step 3, calculating the highway motor vehicle braking and tire wear particulate matter emissions under the second-by-second trajectory; Step 4: Calculate the emission of particulate matter from braking and tire wear of motor vehicles on highways at spatial latitudes.

2. A method for calculating highway vehicle brake and tire wear particulate matter emissions according to claim 1, characterized in that: The basic information of the expressway in step 1 includes geographical and meteorological information, specifically including: road type, mileage, geographical location, temperature along the section, humidity along the section, section slope and location information of data collection points on the section.

3. The method for calculating highway vehicle brake and tire wear particulate matter emissions according to claim 1, characterized in that: In step 1, the data of the motor vehicle trajectory on the highway is cleaned, and then the motor vehicle specific power of the motor vehicle at different times is calculated according to the formula. The motor vehicle specific power calculation formula is: ; In the formula, VSP n for n The specific power of the motor vehicle in seconds, v n For motor vehicles n The instantaneous speed in seconds, a n For motor vehicles n The instantaneous acceleration at the second.

4. The method for calculating highway vehicle brake and tire wear particulate matter emissions according to claim 1, characterized in that: Step 3 specifically includes: extracting the displacement trajectory of a single motor vehicle from the motor vehicle trajectory data, obtaining the second-by-second operating conditions of the motor vehicle through the VSP formula and comparing the VSP-Bin distribution table of motor vehicle brake and tire wear particulate matter emissions in step 2, and then obtaining the second-by-second particulate matter emissions of the motor vehicle trajectory based on the emission factor and its emission rate under the Bin distribution.

5. A method for calculating highway vehicle brake and tire wear particulate matter emissions according to claim 4, characterized in that: The calculation formula for particulate matter emissions from motor vehicle trajectories second by second includes: ; in, i For the model, j is the vehicle number, n is the nth second of the vehicle's travel, v n Indicates the motor vehicle n Speed ​​per second, in m / s; d n Indicates the motor vehicle n Displacement per second, in m; d n-1 It represents the displacement of the motor vehicle at the n-1th second, in meters; D ij Indicates the model i、 Number j A second-by-second displacement trajectory dataset of motor vehicles; VSP n represents the specific power of the motor vehicle at the nth second; E ij Indicates the model i , numbered j A second-by-second dataset of particulate matter emissions from motor vehicles; E ijn Indicates the model i , numbered j The particulate matter emission of the motor vehicle at the nth second, Δ t = 1 second; e ijn Indicates the model i , numbered j The emission rate of the motor vehicle at the nth second, in g / s; e Bin represents the distribution of brake and tire emission factors under Bin distribution; VSP Bin Represents the VSP-Bin distribution table; E ij Indicates the model i , numbered j The total brake and tire emissions of motor vehicles on the highway section, in grams.

6. A method for calculating highway vehicle brake and tire wear particulate matter emissions according to claim 1, characterized in that: Step 4 specifically includes the following steps: First, establish the spatial grid of the highway section and determine the interval between two adjacent spatial grids. L， According to the maximum displacement of all motor vehicles maxd n , calculate the number of spatial grids required num_grids , the calculation formula is: ; Secondly, calculate the motor vehicle brake and tire emissions for each spatial grid using the following formula: ； in, E(x) Representing a spatial grid x Total amount of brake and tire wear particulate matter emissions; E ijn Indicates the model i , numbered j The particulate matter emission of motor vehicles at the nth second; x n Indicates the trajectory of the vehicle n The number of the grid corresponding to the second; δ ( xx n ) represents the Kronecker function, when x=x n The value is 1 when the condition is true, otherwise it is 0.

Images