A vehicle emissions system using a car simulator and a geographical information system: Part 1--system description and testing.

ABSTRACT

A methodology for estimating vehicular emissions comprising a car simulator, a basic traffic model, and a geographical information system is capable of estimating vehicle emissions with high time and space resolution. Because of the extent of the work conducted, this article comprises two sections: In Part 1 of this work, we describe the system and its components and use examples for testing it. In Part 2 we will study in more detail the emissions of the sample fleet using the system and will make comparisons with another emission model. The experimental data for the car simulator is obtained using on-board measuring equipment and laboratory Fourier transform IR (FTIR) measurements with a dynamometer following typical driving cycles. The car simulator uses this data to generate emission factors every second. These emission factors, together with information on car activity and velocity profiles of highways and residential and arterial roads in Mexico City in conjunction with a basic traffic model, provide emissions per second of a sample fleet. A geographical information system is used to localize these road emissions.

INTRODUCTION

Vehicle emissions are one of the main uncertainty sources in urban air quality studies. Among the reasons for this situation is that emission models often use broad assumptions. Most models (refs 1 and 2), with a few exceptions such as ref 3, do not consider the variations in power demand for typical urban traffic (such as stop-and-go driving), and do not explicitly predict emissions during idling. Also, because speed averages are used, neither time nor high spatial resolution is possible.

The purpose of this research is to reduce these uncertainties. In this first part, the basic components of the proposed emission system are presented. Also, to test the system we provide comparison with measurements. In the second part that will appear later, we will study the emissions of the sample car fleet, their implications in the context of the proposed system, and we will make comparisons with another emission model that will be studied.

At the core of the system introduced here is the use of real physics governing the operation of a car, incorporating on-board field and laboratory emission measurements under realistic traffic conditions, to allow for high time and spatial resolution.

To this end, we use the ADvanced VehIcle SimulatOR (ADVISOR), developed by the National Renewable Energy Laboratory (NREL), (4) capable of predicting the engine emissions of hydrocarbons (HCs), oxides of nitrogen (N[O.sub.x]), carbon monoxide (CO), and carbon dioxide (C[O.sub.2]) and engine fuel consumption by using second-by-second engine torque and vehicle speed. Several researchers have used and developed this software to study its functionality and have obtained satisfactory results with regard to the experimental measurements. This provides a solid background for ADVISOR simulations. (5-12)

As part of this research, ADVISOR incorporates on-road emission data obtained from two sources; onboard equipment and Fourier Transform IR (FTIR) spectroscopy used in conjunction with a dynamometer. (13) At this stage of our research, 17 vehicles were used to represent the age distribution and technologies of the car fleet of Mexico City. Additions to ADVISOR to obtain ammonia (N[H.sub.3]), sulfur dioxide (S[O.sub.2]), C[O.sub.2], and evaporative volatile organic compounds (VOCs), have been implemented. Benzene ([C.sub.6][H.sub.6]), formaldehyde ([H.sub.2]CO), and a host of other emissions compounds can be easily incorporated into the proposed system using C[O.sub.2] ratios such as the ones found in ref 14.

[FIGURE 1 OMITTED]

Vehicle activity, residential, arterial, and highway velocity profiles as well as field emission using on-board equipment were obtained from data generated in the Mexico City Vehicle Activity Study conducted by the International Sustainable Systems Research Center (IS-SRC). (15) This information was used to build road cycles for the emissions simulations and to design a basic traffic model providing information of vehicle speed profiles for a given road in Mexico City.

The emission information resulting from ADVISOR and the traffic model is displayed and incorporated for analysis in a geographical information system (GIS) allowing the generation of geographical maps of emission under different vehicle population scenarios, thus obtaining a flexible and more accurate vehicular emission system.

Methodology

In the following subsections, we present the main features of ADVISOR, the description of the experimental work, the added schemes to estimate N[H.sub.3], S[O.sub.2], and VOC's evaporative emissions, and the basic traffic model that will be in charge of calculating the total emissions on a given road.

The Vehicle Simulator: ADVISOR

The vehicle simulator ADVISOR, developed by the NREL is a widely used software tool to simulate conventional and hybrid vehicles. It operates in the MATLAB/SIMU-LINK visual block diagram-programming environment.

ADVISOR is an analytical tool that uses basic physics and measured component performance to model vehicles that can utilize a variety of custom and standard driving cycles; it can predict the fuel economy, acceleration, grade sustainability and emissions of a given vehicle and plot or data log any number of intermediate and final values.

ADVISOR is based on Newton's Second Law, the basic equation of solid-body motion that includes the specific forces acting on vehicles (4) that can be arranged into the form

F = [m.sub.v]g[C.sub.u] + 1/2[rho][C.sub.d][A.sub.VEH][v.sup.2] + [m.sub.v]a + [m.sub.v]g sin([theta]) (1)

where:

F is the tractive force required at the wheels of the vehicle, N

[m.sub.v] is the mass of the vehicle, kg

g is the local gravity acceleration, m x [sec.sup.-2]

[C.sub.u] is the coefficient of rolling resistance between the wheels and the road surface

[rho] is the density of the ambient air, kg x [m.sup.-3]

[C.sub.d] is the coefficient of aerodynamic drag of the vehicle in the direction of travel, m x [sec.sup.-1]

[A.sub.VEH] is the frontal cross-sectional area of the vehicle, [m.sup.2]

v is the magnitude of the speed of the vehicle in the direction of travel, m x [sec.sup.-1]

a is the acceleration of the vehicle, m x [sec.sup.-2], and

[theta] is the angle of inclination of the road surface upon which the vehicle is traveling.

At each discrete time step of 1 sec, ADVISOR calculates at the wheels the energy of the vehicle required to follow a pre-determined vehicle velocity profile. It then determines the amount of input energy required by each component, such as the motor and transmission, to meet the energy requirement at the wheels.

The structure used for a conventional vehicle is shown in block diagram form in Figure 1.

Field Measurements and Torque-RPM-Emission Maps

ADVISOR calculates engine emissions of HCs, N[O.sub.x], CO, C[O.sub.2], and engine fuel consumption by means of steady-state maps that correlate the emissions and fuel consumption with torque and speed requested at the engine. Such maps, which we call here Torque-RPM-Emission (TRE) maps, were formed by linear interpolation of emissions data using on-board SEMTECH generating station equipment and a tachometer implemented for 17 different cars. Torque was estimated by using eq 1 with measured velocities obtained with a Global Positioning System (GPS) and the estimated characteristics of each vehicle. The onboard equipment is shown in Figure 2.

A typical condition of urban driving requires a variety of conditions of revolutions per minute (RPM) and torque. To measure data in a portion typically used of the TRE map, the field trips were designed to contain low velocities, stop-and-go driving, idling periods, and slow and rapid accelerations after a stop. The 17 vehicles that were selected to obtain a representative sample of private car technologies used in Mexico City (15) are described in Table 1. Their emissions are weighted by a coefficient to accommodate the age distribution of the sample according to ref 15, as will be shown in Part 2 of this paper. Private cars are responsible for more than 70% of the total travel in Mexico City.

[FIGURE 2 OMITTED]

Measurements on a Dynamometer using FTIR

FTIR spectroscopy was used to measure exhaust emissions of a fleet of cars subjected to similar driving cycles as the ones used to obtain the TRE maps. A chassis dynamometer equipped with inertial masses was used. The methodology for the FTIR measurements is described in ref 13.

Among the measured gases using FTIR was N[H.sub.3], a toxic gas emitted by a few brand new cars equipped with catalytic converters. Tailpipe N[H.sub.3] emission in g x [sec.sup.-1] are calculated using the following formula obtained by placing a trend line on the experimental data with a RMS error of 0.99,

[N[H.sub.3]] = 0.032 + 0.023[NO] (2)

where [NO] is the emission in g x [sec.sup.-1] simulated by ADVISOR. This formula is activated by the exhaust flux temperature of 52 [degrees]C. Equation 2 was incorporated in the SIMULINK block corresponding to the exhaust system.

Other important toxic gas emissions such as methane (C[H.sub.4]), ethylene ([C.sub.2][H.sub.4]), nitrous oxide ([N.sub.2]O), and [C.sub.2][H.sub.6] were also obtained. Their relationships with other emission gases such as C[O.sub.2] are currently obtained and will be incorporated as part of the emission system.

[FIGURE 3 OMITTED]

Simulated and Measured Emissions Comparisons