KR20110078352A - Road, and, the related element for the emission factor experiment of the public transportation greenhouse gas and air pollution material and representative driving mode development system - Google Patents

Abstract

PURPOSE: A related factor and a representative driving mode development system for performing an emission factor of a public transportation greenhouse gas and an air pollution material test are provided to compute an emission factor equation due to a travelling speed by analyzing actual patterns of vehicles. CONSTITUTION: Data stored in a data logger of a CVB(Connected Vehicle Black Box) terminal device in which a GPS is attached and an OBD-II data is extracted. Driving cycles in which actual driving patterns and sorts of road are statistically generated using the extracted data. Spatio-temporal significance in the emission factor is very specifically secured through the representative driving mode by the sorts of road and sorts of vehicle.

Description

Development system for related factors and representative driving modes for experiments on emission factors of greenhouse gases and air pollutants by roads and means of transportation driving mode development system}

In order to calculate the total emissions of the road sector, operational data reflecting actual conditions such as fuel, vehicle / road operation, and other data, and technical data such as emission factors and unheated operation rates to be linked to these operational data are required. Do. Here, technical data such as emission factors are analyzed by the actual pattern of vehicle operation according to the type of road, and the emission coefficient for each pollutant according to the vehicle speed is statistically significant and the unheated state operation according to the temperature is calculated. The total quantity is calculated by combining the technical characteristic data linked to the data of the operation.

In order to develop driving mode to calculate emission factor in Korea, select representative vehicles by car type (car, bus, truck, etc.), and discharge the driving pattern for a certain period (monthly, annually) according to road type. A representative driving mode for calculating coefficients is being developed. Although this method has the advantage of being able to grasp the actual driving pattern, it is not easy to develop a new driving mode every time in the environment where rapid increase of vehicle and change of traffic environment are expected like in Korea, and development period and cost are enormous. Required. In addition, even if a new driving mode for calculating the emission factor is developed, the significance of the year is high, but in order to link with the actual operation activity data newly generated every year, the significance becomes lower as time passes, and maintains the same resolution as the actual operation activity data. New representative driving modes must be developed for this purpose.

The present invention requires the development of activity data and emission factors for estimating the amount of greenhouse gases and air pollutants emitted by roads and means of transportation. It is a system that analyzes and develops driving mode by road and transportation method (detailed vehicle type, displacement) from GPS location information.

The Greenhouse Gas and Air Pollutant Emission Inventory is the most basic and essential data in establishing the greenhouse gas and air pollutant reduction policy. It identifies each source and calculates greenhouse gas emissions from the source. It is a list of emissions. In order to calculate accurate emissions, activity information such as source status and fuel consumption is multiplied by each emission factor.

Emissions of other air pollutants, including greenhouse gases from anthropogenic combustion activities, can be classified into point, area and line sources, depending on their emission characteristics. Most road vehicles in the transportation sector are discharged on a line because of the nature of their operation.

Emissions of the road-moving source are mainly generated through the exhaust pipe in the combustion activity of the internal combustion engine, and evaporative emissions are generated in the fuel tanks and pipelines according to the influence of the outside air temperature. Emissions from particulates are also generated by wear due to operation. These emissions can be calculated using a combination of technical data of the internal combustion engine and activity data such as road type / type and vehicle speed.

In order to calculate the quantitative emissions of other pollutants, including greenhouse gases, generated by road transport means, it can theoretically be calculated using the following formula.

Where i is the pollutant discharged and k is the type of road transport means.

r: road type f _{k , v} (v): emission factor

In other words, the integration of time resolution related to the speed of individual transportation vehicles according to the type of road or road class (high speed national road, general national road, special city road, local road, national support local road, city and county road, other roads) for each pollutant discharged. To calculate the total amount. However, it is practically impossible to monitor the total amount of individual vehicles in time and space and to calculate the total amount. Therefore, most countries generate statistical data that reflect the realistic situation to the maximum and calculate the total amount.

<Figure 1> shows the correlation of relevant data for emission calculation. To calculate the total emissions of the road sector, operational data reflecting actual conditions such as fuel, vehicle / road operation, and other data, and technical data such as emission factors and unheated operation rates to be linked to these operational data need. Here, technical data such as emission factors are analyzed by the actual pattern of vehicle operation according to the type of road, and the emission coefficient for each pollutant according to the vehicle speed is statistically significant and the unheated state operation according to the temperature is calculated. The total quantity is calculated by combining the technical characteristic data linked to the data of the operation.

The fuel efficiency mode for domestic automobiles is controlled by institutions such as the National Institute of Environmental Research (CVS-75: Constant Sample Collector), which is a federal test procedure (FTP-75). The exhaust gas is measured by the Volume Sampler.

In the driving mode, it is not easy to reflect the actual driving pattern that always changes according to the road condition, the vehicle, and the traffic volume, so that the driving pattern of the actual vehicles is analyzed to make a statistically representative driving cycle. Driving modes are being developed to measure fuel economy and regulated emissions of manufactured vehicles, depending on the intended use.

The emission factor is representative of the emission rate according to vehicle activity, but is extended as a result of limited vehicles among all vehicles. This emission factor is determined under laboratory conditions by predetermined driving modes. The amount of air pollutants emitted from automobiles is determined by many variables. These variables include travel demand, traffic conditions of congestion and free flow, driving modes such as constant speed, idling, acceleration and deceleration, driving conditions such as cold / hot start, average speed, vehicle load, mileage, frequency of driving, etc. Vehicle model, age, maintenance status, engine size and shape, vehicle condition such as emission reduction device, fuel supply system, fuel characteristics such as fuel type, volatility, chemical additive composition, local climate conditions such as air temperature and humidity, road There is a wide variety of terrain conditions such as altitude. This emission factor is determined in the laboratory using an emission measuring device as an alternative to actual driving. This has the advantage of accurately reflecting specific local conditions of the target city. However, because the emission factor depends on a limited number of samples on a laboratory scale, it is not certain that it will accurately reflect the region or conditions at that time when applied to other regions. Data on vehicle emission factors are published by the Korea Institute for Environmental Pollution at the Korea Institute of Environmental Research, and are regularly published by the European Union EEA (1997). The California Air Resource Board is organically and systematically surveyed by the transportation authorities and managed through a computerized network.

Since the emission unit or emission factor is used as a basic measure of technical data to quantify and calculate the total emission amount, it is necessary to accurately calculate the emission amount of greenhouse gas and air pollutant per unit mileage for each vehicle. However, since actual vehicle emissions are greatly influenced by various factors such as vehicle type, fuel type, and operating conditions, it is impossible to accurately determine pollutant emissions of individual vehicles operating on roads. Therefore, by using the driving mode (test mode) that simulates the driving pattern when the vehicle actually runs on the road, the target vehicle is driven in the driving mode on the chassis dynamometer under laboratory conditions, and the unit driving measured at this time is performed. The method of calculating using the relationship between the amount of emission gas per distance and the average vehicle speed is generally applied.

In addition, the driving mode for calculating the emission coefficient is different depending on the type of road or grade of the road to which the vehicle is driven even at the same vehicle speed. For example, even if the target vehicle travels at an average vehicle speed of 70 km / hr, the average driving speed of the high speed national highway and the average driving speed of the general national highway have completely different driving patterns. This means that the high-speed national highway has no stop / release section due to signal waiting, but the longer the downtown section, the longer the waiting period. In addition, even if the same vehicle speed on the same road, driving patterns of cars, taxis, buses (especially in Seoul, town buses, trunk buses, branch buses, wide-area buses, intercity buses) and freight trucks may be different. . Figure 2 below is an example showing the change of vehicle speed according to the traffic volume in urban road section with vehicle speed limit of 50km / hr.

In section (a) of <Figure 2>, where traffic flow is good, the speed of the vehicle is faster than the signal waiting time (0km / hr), but the length of traffic is longer in the sections (b) to (d) where the traffic volume increases. Or slower. In terms of the total emissions of individual vehicles, even if the average vehicle speeds in the sections (a) to (d) are the same, the total emissions differ greatly because the driving patterns for stop / slowness and acceleration / deceleration are completely different.

In order to develop driving mode to calculate emission factor in Korea, select representative vehicles by car type (car, bus, truck, etc.), and discharge the driving pattern for a certain period (monthly, annually) according to road type. A representative driving mode for calculating coefficients is being developed. Although this method has the advantage of being able to grasp the actual driving pattern, it is not easy to develop a new driving mode every time in an environment where a sudden increase in vehicles and changes in traffic conditions are expected in Korea, and the development period and cost are enormous. Required. In addition, even if a new driving mode for calculating the emission factor is developed, the significance of the year is high, but in order to link with the actual operation activity data newly generated every year, the significance becomes lower as time passes, and maintains the same resolution as the actual operation activity data. New representative driving modes must be developed for this purpose.

The emission factors (g / km-s) according to the vehicle speed developed in the representative driving mode are calculated by multiplying the mileage (km / s-year) by vehicle type, which is the unit of activity data. Here, the emission coefficient basically means a hot-emission coefficient when the vehicle engine is heated above the normal temperature (70 ° C.), and the driving distance of each vehicle model is the driving distance in the engine heating section and the engine unheating section. It means sum.

In order to compare the emissions of individual vehicles during the hot emission and the cold emission, the expression of the cold emission is as follows.

Where β _j : driving ratio of the engine unheated state (%)

m _j : Mileage by car type (km)

           : Emission ratio of unheated state to engine heated state by car type.

For example, the values of Pre-Euro gasoline passenger cars presented in the EMEP / EEA emission inventory guidebook (2009) are shown in Table 1 below.

<Table 1> Value of Pre-Euro Gasoline Passenger Car

Pollutant e ^cold Of e ^hot CO 3.7-0.09t _a = 2.24 t _a = 14 ° C

(Temperature range: -10 ~ 30 ℃) NO _X 1.14-0.006t _a = 1.056 VOC 2.8-0.06t _a = 1.96 Fuel consumption 1.47-0.009t _a = 1.344

As shown in the table above, the ratio of represents a close relationship with the change in the outside air temperature. When the outside air temperature is 14 ° C, CO, NOx, VOC, and fuel consumption are 2.24 times and 1.056, respectively, in the unheated state of the engine compared to the engine heated state. It can be seen that pears, 1.96 times and 1.344 times more are discharged. Therefore, the 'mileage ratio in engine unheated' (β _j) of the mileage by vehicle type by emission pollutant is one of the most important activity data in calculating total emissions. Β _j value for the vehicle model is calculated as follows.

= β _j l 0.6474-0.02545 _trip - (l 0.00974-0.000385 _trip) t _a

Here, is a trip length, and is expressed as a one-time average travel distance as a travel distance from the start of the vehicle to the start of the vehicle once. β _j is becomes more outside temperature is low β _j becomes longer as a function of the average one-time help the movement distance and the outside temperature and the higher the opposing group outside temperature becomes shorter the time to reach the engine steady temperature β _j is reduced. For European countries, the average travel distance was between 8 and 15 km / time, with an average of 12.4 km / time. In Korea, the values surveyed from the 1997 Seoul Traffic Census and the 2002 Metropolitan Traffic Census DB were 14.26km / time and 12.35km / time, respectively. This one-time driving distance may vary according to the change of vehicles, traffic volume, transportation means, etc., like the change of the representative driving mode or the daily driving distance for each vehicle type, and may vary depending on the region (city area, suburban area, etc.) even in the same time zone. Can be.

The values of β _j , and the pollutant ratio of Pre-Euro gasoline passenger cars presented in the EMEP / EEA emission inventory guidebook (2009) in <Table 2> were 14.26 km / Calculated using the times and monthly average temperature of Seoul, Korea in 2008.

<Table 2> Ratio of β _j , and Pollutants in Pre-Euro Gasoline Passenger Vehicles of EMEP / EEA

month Temperature (℃)  β (%) Best Average lowest CO NOx VOC F.C One 1.9 -1.7 -5.0 29.2 3.853 1.150 1.485 1.485 2 3.2 -1.2 -4.9 29.0 3.808 1.147 1.481 1.481 3 11.9 7.3 3.7 25.3 3.043 1.096 1.404 1.404 4 19.5 14.1 9.3 22.5 2.431 1.055 1.343 1.343 5 22.7 17.7 13.1 20.9 2.107 1.034 1.311 1.311 6 26.1 21.5 17.6 19.3 1.765 1.011 1.277 1.277 7 28.4 25.1 22.6 17.8 1.441 0.989 1.244 1.244 8 29.5 25.3 21.8 17.7 1.423 0.988 1.242 1.242 9 26.9 22.0 18.0 19.1 1.720 1.008 1.272 1.272 10 21.0 16.1 12.1 21.6 2.251 1.043 1.325 1.325 11 11.7 7.6 3.8 25.2 3.016 1.094 1.402 1.402 12 5.0 1.1 -2.7 28.0 3.601 1.133 1.460 1.460

As shown in <Figure 3>, the change of emission pollutants and fuel consumption is large according to the change of monthly average temperature and daily average driving distance (the major factor of β value). Monthly average temperatures are easily obtained through the Meteorological Administration data, but daily average mileage is reported irregularly through the current census, which also requires considerable time and cost.

Recently produced cars in the automotive industry are equipped with sensors for various measurement and control. These devices are controlled by an ECU (Electronic Control Unit). The original development of the ECU was to precisely control the core functions of the engine such as ignition timing / fuel injection, variable valve timing, idling, limit value, air-fuel ratio control, etc. In addition to the advances in vehicle and computer performance, it also controls automatic transmission, as well as controlling all aspects of the vehicle, including driving, braking, steering systems, and safe operability. This electronic diagnostic system has evolved and recently became a standardized diagnostic system called On-Board Dignostic (ODB).

In 1988, the Society of Automative Engineers (SAE) established the standard plug connector for processing diagnostic test signals and OBD, an onboard diagnostic program standard, which was later supplemented to the standards OBD-1.5 and OBD-II. Developed. The OBD-I regulations provide for the standardization of diagnostics for fuel systems, oxygen sensors and exhaust gas recirculation (EGR) .The OBD-II regulations include catalytic efficiency, engine misfire and intake. It is mandatory to install 6 parts of engine control module I / O such as temperature sensor. Accordingly, all models exported to North America since 1996 should be equipped with the OBD-II system. In 2000, OBD-II was also mandated in Europe. In Korea, OBD-II system is mandatory for all passenger cars manufactured in 2005 (oil volatility passenger car in 2005, diesel diesel car in 2006), and OBD-II for all vehicles produced and imported domestically from 2005 to 2010. Mandatory installation.

The purpose of the OBD-II regulation was to introduce an electronic control system for the purpose of exhaust gas control in the 1980s, and to help diagnose the system to reduce emissions by electronically controlling the air-fuel ratio and ignition timing required for catalysts. On-board computer including fault diagnosis code to diagnose major parts related to emission control such as exhaust-related metering device and EGR system and to warn driver in case of a vehicle using three-way catalyst and feedback control system. Mandatory installation of the. Looking at the system configuration of OBD-II, as shown in <Figure 4>, various information as below can be extracted from monitoring items defined in OBD-II.

In addition, CVB (Connedted Vehicle Black Box) includes core functions such as communication function, vehicle diagnosis, and driving behavior analysis, and records the vehicle's driving information and driver's operation information in case of an accident and transfers to the vehicle operation information center. Says a telematics terminal. These CVBs are 'accident detection and driving information storage technology' that detects and stores vehicle operation information, driver operation information, vehicle behavior information, collision information, fault information, and driving information, as shown in Figure 5. It is divided into 'information analysis technology' for interpreting information, analyzing cause of accidents, and 'information technology' for use in various services such as automatic accident notification, vehicle location tracking, remote diagnosis and road traffic safety diagnosis based on the analyzed information. Looking at the information on each technology is as follows.

-Accident detection and driving information storage technology: Accident detection by CVB internal sensor and OBD information, detection by airbag deployment signal of separate airbag unit, technology of driving information and vehicle driving information, driver operation information, vehicle movement information, failure Technology that saves information, momentum (collision) information, GPS location information, image information, and extracts the corresponding information by using VAI to analyze accidents and cause analysis based on the stored information when an accident is detected

-Information analysis technology: Reconstruction of accidents from the measured and stored information through CVB, data processing process for identification of cause and behavior of vehicle, information list of various causes of accidents by accident analysis program based on driving information, and operation of vehicle components Information processing and analysis technology for analysis, simulation of accident situation

-Information technology: This technology uses CVB information for telematics. It refers to various services such as wireless communication and convenience, and it uses technology through processing and analysis of transmitted data in the vehicle operation information center. Data management and convenience providing technology with public institutions and accident handling related organizations such as automatic accident notification, vehicle location tracking, remote diagnosis and road traffic safety diagnosis

The CVB technology will be revised to the technical standard of the new black box that stores accident records and driving information at the same time.The Ministry of Land, Transport and Tourism is a new company that integrates the technical specifications of the vehicle black box (KSR 5076) and the driving recorder (KSR 5072). A collaboration with the Agency for Technical Standards was undertaken to complete the national standard. In addition, the government plans to gradually phase out black boxes for 750,000 commercial vehicles nationwide by 2011.In June 2009, the government introduced black boxes for 100,000 buses and corporate taxis in major cities. It is obliged to submit digital driving records to the government every quarter. Various information generated through CVB collects real-time information such as speed information, driving type information, driver behavior analysis degree in case of accident, (rapid) braking, (rapid) acceleration, (rapid) rotation information, and vehicle location information in real time. It can be used for various purposes such as dispatching, traffic accident analysis, insurance premium basic data.

The present invention has been made to solve the above problems, in order to calculate the total emissions of the road section of the present invention, the operation activity data reflecting the actual situation such as fuel, vehicle / road operation, other data and such operation Technical data such as emission factors and unheated operating rates to be linked to the activity data are needed. Here, technical data such as emission factors are analyzed by the actual pattern of vehicle operation according to the type of road, and the emission coefficient for each pollutant according to the vehicle speed is statistically significant and the unheated state operation according to the temperature is calculated. Calculate the total amount by combining the technical characteristic data linked to the data

According to the present invention, in order to calculate the total discharge amount of the road sector, operation activity data reflecting actual conditions such as fuel, vehicle / road operation, and other data, emission factors to be associated with such operation activity data, unheated operation ratio, and The same technical data is required. Here, technical data such as emission factors are analyzed by the actual pattern of vehicle operation according to the type of road, and the emission coefficient for each pollutant according to the vehicle speed is statistically significant and the unheated state operation according to the temperature is calculated. It is effective to calculate the total amount by combining the technical characteristic data linked to the operation data.

Hereinafter, preferred embodiments of the present invention will be described in more detail with reference to the accompanying drawings. The embodiments of the present invention may be modified in various forms, and the scope of the present invention should not be construed as being limited to the embodiments described below. These embodiments are provided to explain in detail the present invention to those skilled in the art. Accordingly, the shape of each element shown in the drawings may be exaggerated to emphasize a more clear description.

To develop a representative driving mode for calculating the emission factor in Korea, select a representative vehicle by car type (car, bus, truck, etc.), and run the driving pattern for a certain period of time depending on the type of road. I'm developing a mod. Although this method has the advantage of being able to grasp the actual driving pattern, it is not easy to develop a new driving mode every time in an environment where a rapid increase in vehicles and changes in traffic conditions are expected, as in Korea. Although significant demands have been made, and even if a representative driving mode for calculating a new emission factor has been developed, the significance of the year is high, but in order to link with the actual operational activity data newly generated each year, the significance may decrease with time.

Therefore, it is necessary to develop a representative driving mode in the necessity of the driving mode and related factors. In order to develop a representative driving mode for each vehicle type for various road conditions, detailed driving cycle data for each vehicle type are required.

The OBD-II data installed in the vehicle and the data stored in the data logger of the CVB terminal device equipped with GPS are extracted for each vehicle type linked to the emission factor classification system described above. The driving cycle can be generated, and the average driving distance, daily average starting frequency, and idling rate generated outside the driving cycle are also extracted in hourly / daily / weekly / monthly / yearly units. Emission factors developed at power levels can also ensure spatial and spatial significance in great detail.

In addition, in order to extract the representative driving mode, the representative driving mode can be extracted using the detailed characteristic data of the driving cycle for each vehicle type, which analyzes the speed change, acceleration change, location information, etc. according to the time flow among the CVB information. have.

In addition, in order to extract the one-time average driving distance, which is the main data of the beta value, as a related factor, the mileage by vehicle type from the engine temperature, the outside temperature, the engine temperature during the run, and the outside temperature data according to the passage of time among the information of the OBD-II. It is possible to extract the running ratio of the unheated state of the engine and the emission ratio of the unheated state to the engine heated state of each vehicle type.

In addition, in order to extract the daily mileage for each vehicle type, it is possible to extract the one-time average travel distance and the daily mileage as the travel distances when the one-time start of the target vehicle is turned on and off, from the information of the OBD-II.

In addition, the greenhouse gas emissions can be statistically analyzed using the concentration data of CO ₂ , N ₂ O, and CH ₄ , which are the greenhouse gas substances, and the amount of exhaust gas in the information of OBD-II. .

The present invention is not limited by the embodiments described above, and various changes and modifications can be made by those skilled in the art, which are included in the spirit and scope of the present invention as defined in the appended claims.

1 is an emission calculation procedure using activity, driving mode, emission coefficient.

2A and 2B are various driving modes according to the traffic volume of the road.

Figure 3 is a change in the emission of pollutants and fuel consumption according to the change in the monthly average temperature and daily average running distance (key factor of β value).

4 is a configuration of an OBD-II system.

5 is the CVB description range.

6 is a CVB storage information range.

7 is a CVB information utilization range.

8 is a configuration diagram of a driving mode analysis system.

9 is a detailed characteristic data of the driving cycle for each road type according to the vehicle type analyzed in the tachograph.

10 is a driving mode analyzed by the tachograph.

Claims (5)

In the system for developing driving mode analysis for development of emission factors for roads and transportation methods, OBD-II data installed inside the vehicle and data stored in the data logger of the CVB terminal device equipped with GPS are extracted statistically for the road. It extracts the driving cycle reflecting the actual driving pattern every year by type and vehicle type, and also generates the average driving distance, daily average starting frequency, and idling rate generated in other than the driving cycle by hour / day / weekly / monthly / yearly. A system that extracts one-time average driving distance, which is the main data of the beta value, as a related factor. The method of claim 1, wherein in the extraction of the representative driving mode, the representative driving by using the detailed characteristic data of the driving cycle for each vehicle type according to the vehicle type which analyzed the speed change, acceleration change, position information, etc. according to time flow among the information of the CVB. System to extract the mod. The method of claim 1, wherein in extracting the one-time average driving distance, which is the main data of the beta value as a related factor, the engine temperature at start, the outside air temperature and the engine temperature at running, and the outside air temperature according to the passage of time among the information of the OBD-II. The system extracts data of driving ratio of unheated engine and emission ratio of unheated engine to engine heating state of each vehicle type. The system of claim 1, wherein in extracting the daily driving distance for each vehicle type, the one-time average moving distance and one driving distance are extracted as the moving distance between when the one-time start of the target vehicle is turned on and off, among the information of the OBD-II. . According to claim 1, In calculating the daily greenhouse gas emissions by vehicle type, the greenhouse gas emissions statistics using the concentration data and the amount of gas emissions of the greenhouse gas substances CO ₂ , N ₂ O, CH ₄ among the information of OBD-II statistics System processing.

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