- Email: [email protected]
A new method to determine exhaust emission factors for heavy duty vehicles
The Scienceof the Total Environment 169(1995) 213-217
A new method to determine exhaust emission factors for heavy duty vehicles P. Jest, D. Hassel, K.S. Sonnborn* TiWRheinland
Safety and Environmental
Protection
GmbH,
D-51101
Cologne,
FRG
Received 16 March 1994;accepted12 November 1994
Abstract In contrast to the evaluation of exhaust gas and fuel consumption factors for passenger cars, heavy duty trucks and buses have not been tested on a chassis dynamometer. For reasons of practicability and costs, exhaust gas emissions and fuel consumption of 34 different diesel engines have been measured on dynamic engine test benches. Using these engines, the fleet of heavy duty trucks and buses in the Federal Rebublic of Germany for the reference years 1986 and 1990 can be represented. From the engines’ emission data sets, and data concerning the drive train and the driving resistance of representative vehicles, the exhaust emission behaviour of more than 300 different types of trucks and buses could be simulated on the basis of a newly developed method. It is therefore possible to calculate exhaust emission and fuel consumption factors for all categories of the entire fleet of heavy duty vehicles taking into account the road category, gradient, load factor and traffic flow conditions. This new method allows the determination of exhaust emission and fuel consumption factors for a broad range of different scales, from the emission simulation for a single vehicle up to global emission assessments. Exhaust emission factor; Heavy duty vehicle; Chassis dynamometer; Exhaust gas emission; Fuel
Keywords:
consumption
1. Introduction The purpose of this paper is to describe a new method for determination of emission factors. This method significantly complements and improves a method developed [l] about 10 years ago by TiiV Rheinland, for representing the emission behaviour of heavy commercial vehicles, based on
* Corresponding author. Elsevier ScienceBV. SSDZ
0048-9697(95)04650-C
steady-state engine maps, vehicle data and driving curves. 2. Description of the German and Swiss Emission Factor Program The Emission Factor Program was sponsored by the German Environmental Protection Agency CUBA) in Berlin and the Swiss Environmental Protection Agency (BUWAL) in Bern. The duration of the Project was 5 years.
P. Jest et al. /The Science of the Total Environment
214
The structure of the project is given in Fig. 1. The whole project was divided into three parts: . . l
collection of emission data, conducted by TiiV Rheinland, Kiiln; collection of driving behaviour data, conducted by FIGE GmbH, Herzogenrath; collection of vehicle mileage data, conducted by Heusch-Boesefeldt, Aachen.
At the beginning of the fundamental measurement program, the so called ‘Basis program’, an analysis of the fleet composition in Switzerland and Germany was conducted. As a result, about 300 different heavy duty vehicle types with 34 different diesel engine types could be identified and selected to represent the fleet in both countries. Examples of all the selected diesel engine types were measured on a transient engine test bench. For each engine, steady-state engine maps
hehaviour data
+
t
t
Fig. 1. Project termination.
structure
for heavy
duty
t
emission
together with transient emission data were collected for carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NO,), carbon dioxide (CO,), particulate matter (PM) and fuel consumption. These emission data sets were the basis for the development of emission functions and emission factors. In order to take into account emission relevant parameters such as cold start and altitude, an additional test program was carried out with the aim of determining correction factors. Driving behaviour data were collected for different vehicle categories. Speed curves were measured for 32 heavy duty vehicles under real world conditions. The analysis of the speed curves resulted in so-called driving patterns which are representative of the driving behaviour of heavy duty vehicles on different road categories. In the context of this project, vehicle mileage data are necessary to get mileage-weighted emission factors for different road and vehicle categories. 3. Determination of layer-specific emission factors
Collection of emission data
Calculation model for emission factors accordingr0 and driving patterns
169 (1995) 213-217
road types
factor
de-
The result of the fleet analysis was the definition of layers which cover the whole range of the heavy duty fleet in Germany and Switzerland. Fig. 2 shows the structure of the layers. Each vehicle category was divided into five to seven mass classes, and each mass class was classified into up to four body style classes. In addition, each body style class was divided into two model year groups. The total number of layers for the German fleet was 157 and for the Swiss fleet 72. As mentioned above, all these layers could be covered by 300 different heavy duty vehicle types. The principle idea for the emission model is the fact that the emissions of a vehicle are proportional to the engine power. The instantaneous power of an engine is divided into a steady-state and a non-steady-state part. The steady-state part L WR is the power for overcoming the wind, rolling, and gradient resistance. The non-steady-state part LB is the power for overcoming the inertia of the mass during acceleration. It seemed logical to use these two power parameters for the emission function.
of the
P. Jest et al. / The Science
Total Enuironment
natbed M3 M4 MS . . Ml M2 M3 M4 MS
boxbody talker . . . . . .
flatbed drop sided bOXbodY tanker
.
Ml M2
. .
Fig. 2. Structure
. .
.
Ml M2
Number of laycn of the heavy duty vchick
.
flectio Gcrmrny: inSwitzulrnd:
/
B 1986 > 1986
.L
+ 1986 > 1986
<
I1986 > 1986
Q. 157 a. 72
215
169 (199.5) 213-217
driving curves (test cycles) which cover the whole power range of the engines. These driving curves are converted into torque and engine speed/time sequences and the corresponding emissions are determined with these parameters in the steadystate engine maps. Parallel to this, the driving curves are converted into the power components and the values of the correction L, and L,, functions are determined on a second by second basis. The non-steady-state emissions are formed by summing up the steady-state emission values and the values of the correction function for each vehicle of the layer. These values are inserted in a grid with the coordinates L, and L,,. Forming the mean values cell by cell, the layer-specific emission functions are determined. Layer-specific emission factors are calculated by using the appropriate emission function and the L,, L,,- distribution functions of different driving patterns. These distribution functions are derived for all vehicles of a layer. With the equation of motion and the vehicle data sets, the
of the layers. condition
Using torque and speed of the engine as parameters for the emission function, the time derivation of the torque is necessary as an additional parameter to describe the non-steady-state emission behaviour. Such a three-parameter function needs a larger sample of experimental data for modelling purposes. To simulate the non-steady-state emissions of a vehicle, the steady-state engine maps are used on the one hand and, on the other hand, nonsteady-state correction functions are developed with the aid of the transient emission data. The non-steady-state correction function is based on the differences between the steady-state emission of the engine maps and the non-steady-state emissions given by measurements on transient motor test benches. The correction functions are developed for each of the 34 diesel engine types. As the correction functions for non-steady-state emissions are known, emission simulation is carried out for the individual vehicles of a layer. The input of the program package consists of real
-6% -3% 0% 3% 6%
1. Motorway --‘. 2 Nonmotamy
<
90%
hcavycqwion
dual carriageway
3. Extra urban roads 4. Main urban s@e.%
5. Urban statea with great distances berwccn Qmss roads
. .
’ . . . . . . . . . . ,
Number of layer specific emissionfactors in&many: inSwitzerland:
Fig. 3. Structure
10 %
. . . . .
. . . . -6% -3% 0%
. .
10%
of the heavy duty vehide cd. 5200 cd. 3400
of layer-specific
emission
fleet
factors.
P. Jost et al. /The Science of the Total Environment 169 (1995) 2I3-217
216
hy<7,5fload90% 350
-
50
--
&) -6%gradieni
. . . . . . . . . . . . . . . . . . . . . . -3%gradimt -
0 0
10
20
30
40
50
60
mean velocity of Driving
70
00
00
Patterns
Fig. 4. NO,-emissions for mean velocities of driving patterns and road gradient, layer: lorry < 7.5 ton, load 90 %.
driving patterns can be transformed into L,, functions. The emission factors J%vR- distribution of each single vehicle in a layer are put together unweighted to the emission factor of the layer. In Fig. 3 the structure of the layer-specific emission factors is presented. The factors are given for six road categories. Each is divided into four types of traffic flow condition, and each of those is split into five classes of gradient with two different load factors per gradient class. The set of layer-specific emission factors of the heavy 100
duty vehicle fleet consists per component of about 5200 data for Germany and 3300 data for Switzerland. Fig. 4 shows, as an example, the NO, emission factors for one layer (lorry < 7.5 tons, load 90%) as a function of the mean speed of the driving patterns and the road gradients. 4. Verification In order to assess the emission model, a verifi600
90
/
80
x z
70
3
60
;
z;
0” 0
30 20 10
OY
0 0
50
CO (g/h) measured
100
0
200
400
600
NOs (g/h) measured
Fig. 5. Comparison between calculated and measured CO and NO, emissions for the distribution vehicle.
P. Jost et al. /The
Science of the Total Environment
cation program was carried out, during the course of which three commercial vehicles, a distribution vehicle, an urban bus and a coach were examined. For this purpose, the three vehicles were run on the chassis dynamometer and the emissions measured at the Institute for Internal Combustion Engines and Thermodynamics at the Technical University of Graz, following driving cycles which had been measured in Switzerland during real runs on the road. The engines were then removed and mounted on the transient engine test bench, the transient emission data and the steady-state engine maps recorded. With these data sets it was possible to determine emission functions for each vehicle. So the emissions of the vehicles could be calculated for each cycle driven on the chassis dynamometer. In order to assess the quality of the emission modelling in Fig. 5, the calculated emissions are plotted as a function of the measured emissions. The distribution vehicle was selected as an example for this plot, since the measurement program for this vehicle was the most comprehensive. In total, 21 tests were conducted on the chassis dynamometer. As can be seen from Fig. 5, the agreement between calculation and measurement is satisfactory for CO and NO,. For CO, and fuel consumption it is even better, whereas the quality of agreement for HC and particulate matter is similar to that of CO. 5. Conclusions
The new method for developing
realistic emis-
169 (1995) 213-217
217
sion functions is independent of driving behaviour. It was made thus possible for the first time to separate the data of emission functions (steady-state engine test rigs and non-steady-state correction function) from the data of driving behaviour. The layer-specific emission factors are the basis for different stages of aggregation which are necessary for: global or regional emission assessment; emission inventories; 0 local emission assessments; e vehicle specific emission simulation for air pollution modelling.
l l
References
I11 D. Hassel, J. Brosthaus, F. Dursbeck, P. Jost and K.-S. Sonnborn, TiiV Rheinland: Das Abgas-Emissionsverhalten von Nutzfahrzeugen in der Bundesrepublik Deutschland im Bezugsjahr 1980. Berichte 11/83 des Umweltbundesamtes, Berlin. 132 Seiten, Erich Schmidt Verlag, Berlin, 1983. PI Th. Sams, J. Tieber and G. Pretterhofer, Verification of extrapolated dynamic commercial vehicle emissions. Conference, Exhaust gas emissions and immissions by road traffic. September 1992, Graz. 131 D. Hassel, P. Jost, F.-J. Weber, F. Dursbeck, K.-S. Sonnborn and D. Plettau, TiiV Rheinland Sicherheit und Umweltschutz GmbH: Abgas-Emissionsverhalten von Nutzfahrzeugen in der Bundesrepublik Deutschland fiir die Bezugsjahre 1986 und 1990. Abschluss /J bericht eines Forschungsvorhabens des Umweltbundesamtes, Berlin. 303 Seiten. Kijln, September 1994.
A new method to determine exhaust emission factors for heavy duty vehicles P. Jest, D. Hassel, K.S. Sonnborn* TiWRheinland
Safety and Environmental
Protection
GmbH,
D-51101
Cologne,
FRG
Received 16 March 1994;accepted12 November 1994
Abstract In contrast to the evaluation of exhaust gas and fuel consumption factors for passenger cars, heavy duty trucks and buses have not been tested on a chassis dynamometer. For reasons of practicability and costs, exhaust gas emissions and fuel consumption of 34 different diesel engines have been measured on dynamic engine test benches. Using these engines, the fleet of heavy duty trucks and buses in the Federal Rebublic of Germany for the reference years 1986 and 1990 can be represented. From the engines’ emission data sets, and data concerning the drive train and the driving resistance of representative vehicles, the exhaust emission behaviour of more than 300 different types of trucks and buses could be simulated on the basis of a newly developed method. It is therefore possible to calculate exhaust emission and fuel consumption factors for all categories of the entire fleet of heavy duty vehicles taking into account the road category, gradient, load factor and traffic flow conditions. This new method allows the determination of exhaust emission and fuel consumption factors for a broad range of different scales, from the emission simulation for a single vehicle up to global emission assessments. Exhaust emission factor; Heavy duty vehicle; Chassis dynamometer; Exhaust gas emission; Fuel
Keywords:
consumption
1. Introduction The purpose of this paper is to describe a new method for determination of emission factors. This method significantly complements and improves a method developed [l] about 10 years ago by TiiV Rheinland, for representing the emission behaviour of heavy commercial vehicles, based on
* Corresponding author. Elsevier ScienceBV. SSDZ
0048-9697(95)04650-C
steady-state engine maps, vehicle data and driving curves. 2. Description of the German and Swiss Emission Factor Program The Emission Factor Program was sponsored by the German Environmental Protection Agency CUBA) in Berlin and the Swiss Environmental Protection Agency (BUWAL) in Bern. The duration of the Project was 5 years.
P. Jest et al. /The Science of the Total Environment
214
The structure of the project is given in Fig. 1. The whole project was divided into three parts: . . l
collection of emission data, conducted by TiiV Rheinland, Kiiln; collection of driving behaviour data, conducted by FIGE GmbH, Herzogenrath; collection of vehicle mileage data, conducted by Heusch-Boesefeldt, Aachen.
At the beginning of the fundamental measurement program, the so called ‘Basis program’, an analysis of the fleet composition in Switzerland and Germany was conducted. As a result, about 300 different heavy duty vehicle types with 34 different diesel engine types could be identified and selected to represent the fleet in both countries. Examples of all the selected diesel engine types were measured on a transient engine test bench. For each engine, steady-state engine maps
hehaviour data
+
t
t
Fig. 1. Project termination.
structure
for heavy
duty
t
emission
together with transient emission data were collected for carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NO,), carbon dioxide (CO,), particulate matter (PM) and fuel consumption. These emission data sets were the basis for the development of emission functions and emission factors. In order to take into account emission relevant parameters such as cold start and altitude, an additional test program was carried out with the aim of determining correction factors. Driving behaviour data were collected for different vehicle categories. Speed curves were measured for 32 heavy duty vehicles under real world conditions. The analysis of the speed curves resulted in so-called driving patterns which are representative of the driving behaviour of heavy duty vehicles on different road categories. In the context of this project, vehicle mileage data are necessary to get mileage-weighted emission factors for different road and vehicle categories. 3. Determination of layer-specific emission factors
Collection of emission data
Calculation model for emission factors accordingr0 and driving patterns
169 (1995) 213-217
road types
factor
de-
The result of the fleet analysis was the definition of layers which cover the whole range of the heavy duty fleet in Germany and Switzerland. Fig. 2 shows the structure of the layers. Each vehicle category was divided into five to seven mass classes, and each mass class was classified into up to four body style classes. In addition, each body style class was divided into two model year groups. The total number of layers for the German fleet was 157 and for the Swiss fleet 72. As mentioned above, all these layers could be covered by 300 different heavy duty vehicle types. The principle idea for the emission model is the fact that the emissions of a vehicle are proportional to the engine power. The instantaneous power of an engine is divided into a steady-state and a non-steady-state part. The steady-state part L WR is the power for overcoming the wind, rolling, and gradient resistance. The non-steady-state part LB is the power for overcoming the inertia of the mass during acceleration. It seemed logical to use these two power parameters for the emission function.
of the
P. Jest et al. / The Science
Total Enuironment
natbed M3 M4 MS . . Ml M2 M3 M4 MS
boxbody talker . . . . . .
flatbed drop sided bOXbodY tanker
.
Ml M2
. .
Fig. 2. Structure
. .
.
Ml M2
Number of laycn of the heavy duty vchick
.
flectio Gcrmrny: inSwitzulrnd:
/
B 1986 > 1986
.L
+ 1986 > 1986
<
I1986 > 1986
Q. 157 a. 72
215
169 (199.5) 213-217
driving curves (test cycles) which cover the whole power range of the engines. These driving curves are converted into torque and engine speed/time sequences and the corresponding emissions are determined with these parameters in the steadystate engine maps. Parallel to this, the driving curves are converted into the power components and the values of the correction L, and L,, functions are determined on a second by second basis. The non-steady-state emissions are formed by summing up the steady-state emission values and the values of the correction function for each vehicle of the layer. These values are inserted in a grid with the coordinates L, and L,,. Forming the mean values cell by cell, the layer-specific emission functions are determined. Layer-specific emission factors are calculated by using the appropriate emission function and the L,, L,,- distribution functions of different driving patterns. These distribution functions are derived for all vehicles of a layer. With the equation of motion and the vehicle data sets, the
of the layers. condition
Using torque and speed of the engine as parameters for the emission function, the time derivation of the torque is necessary as an additional parameter to describe the non-steady-state emission behaviour. Such a three-parameter function needs a larger sample of experimental data for modelling purposes. To simulate the non-steady-state emissions of a vehicle, the steady-state engine maps are used on the one hand and, on the other hand, nonsteady-state correction functions are developed with the aid of the transient emission data. The non-steady-state correction function is based on the differences between the steady-state emission of the engine maps and the non-steady-state emissions given by measurements on transient motor test benches. The correction functions are developed for each of the 34 diesel engine types. As the correction functions for non-steady-state emissions are known, emission simulation is carried out for the individual vehicles of a layer. The input of the program package consists of real
-6% -3% 0% 3% 6%
1. Motorway --‘. 2 Nonmotamy
<
90%
hcavycqwion
dual carriageway
3. Extra urban roads 4. Main urban s@e.%
5. Urban statea with great distances berwccn Qmss roads
. .
’ . . . . . . . . . . ,
Number of layer specific emissionfactors in&many: inSwitzerland:
Fig. 3. Structure
10 %
. . . . .
. . . . -6% -3% 0%
. .
10%
of the heavy duty vehide cd. 5200 cd. 3400
of layer-specific
emission
fleet
factors.
P. Jost et al. /The Science of the Total Environment 169 (1995) 2I3-217
216
hy<7,5fload90% 350
-
50
--
&) -6%gradieni
. . . . . . . . . . . . . . . . . . . . . . -3%gradimt -
0 0
10
20
30
40
50
60
mean velocity of Driving
70
00
00
Patterns
Fig. 4. NO,-emissions for mean velocities of driving patterns and road gradient, layer: lorry < 7.5 ton, load 90 %.
driving patterns can be transformed into L,, functions. The emission factors J%vR- distribution of each single vehicle in a layer are put together unweighted to the emission factor of the layer. In Fig. 3 the structure of the layer-specific emission factors is presented. The factors are given for six road categories. Each is divided into four types of traffic flow condition, and each of those is split into five classes of gradient with two different load factors per gradient class. The set of layer-specific emission factors of the heavy 100
duty vehicle fleet consists per component of about 5200 data for Germany and 3300 data for Switzerland. Fig. 4 shows, as an example, the NO, emission factors for one layer (lorry < 7.5 tons, load 90%) as a function of the mean speed of the driving patterns and the road gradients. 4. Verification In order to assess the emission model, a verifi600
90
/
80
x z
70
3
60
;
z;
0” 0
30 20 10
OY
0 0
50
CO (g/h) measured
100
0
200
400
600
NOs (g/h) measured
Fig. 5. Comparison between calculated and measured CO and NO, emissions for the distribution vehicle.
P. Jost et al. /The
Science of the Total Environment
cation program was carried out, during the course of which three commercial vehicles, a distribution vehicle, an urban bus and a coach were examined. For this purpose, the three vehicles were run on the chassis dynamometer and the emissions measured at the Institute for Internal Combustion Engines and Thermodynamics at the Technical University of Graz, following driving cycles which had been measured in Switzerland during real runs on the road. The engines were then removed and mounted on the transient engine test bench, the transient emission data and the steady-state engine maps recorded. With these data sets it was possible to determine emission functions for each vehicle. So the emissions of the vehicles could be calculated for each cycle driven on the chassis dynamometer. In order to assess the quality of the emission modelling in Fig. 5, the calculated emissions are plotted as a function of the measured emissions. The distribution vehicle was selected as an example for this plot, since the measurement program for this vehicle was the most comprehensive. In total, 21 tests were conducted on the chassis dynamometer. As can be seen from Fig. 5, the agreement between calculation and measurement is satisfactory for CO and NO,. For CO, and fuel consumption it is even better, whereas the quality of agreement for HC and particulate matter is similar to that of CO. 5. Conclusions
The new method for developing
realistic emis-
169 (1995) 213-217
217
sion functions is independent of driving behaviour. It was made thus possible for the first time to separate the data of emission functions (steady-state engine test rigs and non-steady-state correction function) from the data of driving behaviour. The layer-specific emission factors are the basis for different stages of aggregation which are necessary for: global or regional emission assessment; emission inventories; 0 local emission assessments; e vehicle specific emission simulation for air pollution modelling.
l l
References
I11 D. Hassel, J. Brosthaus, F. Dursbeck, P. Jost and K.-S. Sonnborn, TiiV Rheinland: Das Abgas-Emissionsverhalten von Nutzfahrzeugen in der Bundesrepublik Deutschland im Bezugsjahr 1980. Berichte 11/83 des Umweltbundesamtes, Berlin. 132 Seiten, Erich Schmidt Verlag, Berlin, 1983. PI Th. Sams, J. Tieber and G. Pretterhofer, Verification of extrapolated dynamic commercial vehicle emissions. Conference, Exhaust gas emissions and immissions by road traffic. September 1992, Graz. 131 D. Hassel, P. Jost, F.-J. Weber, F. Dursbeck, K.-S. Sonnborn and D. Plettau, TiiV Rheinland Sicherheit und Umweltschutz GmbH: Abgas-Emissionsverhalten von Nutzfahrzeugen in der Bundesrepublik Deutschland fiir die Bezugsjahre 1986 und 1990. Abschluss /J bericht eines Forschungsvorhabens des Umweltbundesamtes, Berlin. 303 Seiten. Kijln, September 1994.