EMISSIONS OF A LIGHT DUTY
MULTIFUEL VEHICLE UNDER URBAN
DRIVING CONDITIONS
Provenza Alessio,
Bonnel Pierre, Carriero Massimo, Perujo Adolfo, Weiss Martin
European Commission, Directorate General Joint Research Centre (JRC), Institute for Energy and
Transport, Sustainable Transport Unit
Via Enrico Fermi, 2749 - 21027 Ispra (VA) - Italy
In collaboration with
Dondi Davide, De Santoli Livio, Fraticelli Fabio
CITERA Research Center, Rome, Italy
http://www.jrc.ec.europa.eu/
CRC Real-World Emissions Workshop – San Diego – March 25-28 2012
General background: legislation
•
Directive 2009/30/EC, (fuel quality) target: reduce GHG
emissions per unit of energy at least by 6% until 2020.
•
Regulation 79/2009 target: ensure the proper functioning
of hydrogen-powered motor vehicles by specifying
harmonized safety requirements.
•
No existing specific methods to type-approve vehicles
fueled by H2-CNG blends.
General background
Assessment of transport technologies using real-world
emissions measurements
CO2 regulations of light (EC/443/2009) and heavy-duty
vehicles (on-going development of EU HDV CO2 testing
procedures: Model based, real-world PEMS measurements
could be used as validation test methods)
Objective of the present research: development of data
evaluation methods for real-world CO2 emissions, to
establish links with vehicle/engine characteristics and/or
operating conditions (speed, road grade, etc...)
In-use emissions testing
Recent Legislative Developments:
Publication of the PEMS based In-Service Conformity (ISC)
provisions for the future EURO VI standards, (also
applicable to EURO V engines)
European PEMS Pilot Program for Non Road Mobile
Machinery (NRMM) engines
PEMS candidate method to check and to limit the Real
Driving Emissions (RDE) of Light Duty Vehicles from Euro 6
standards onwards (2014)
Objectives of the study
To develop methods to make use of the in-use emissions
data collected with PEMS.
To study the exhaust emissions as function of the CNG-
hydrogen in real-world driving conditions.
To relate on-road data with test cell data
To asses the greenhouse gasses emission reduction
obtained by means of hydrogen blends.
Data used for the study
Real-world measurements from a EURO 4 light-duty vehicle
5 different fuels used: Gasoline, CNG, CNG+10%H2,
CNG+20%H2, CNG+30%H2.
Vehicle tested on an urban route 17Km long (two tests for
each fuel)
Vehicle specifications
BRAND
FIAT
MODEL
Panda
YEAR
2007
DISPLACEMENT
1242 cm3
Gasoline
FUEL
CNG
Hydrogen-CNG Blends
Max Power
44/38 kW
(gasoline/CNG)
After treatment
3-way catalyst
PEMS installation
PEMS installation
Results: Trip averaged emissions
300
0.25
250
0.20
200
) 0.15
)
Gasoline
Gasoline
m
m
K
K
/
CNG
CNG
150
/
(g
CN(g
CNG+10%H2
x G+10%H2
2
CO
CNNOG+20%H2
0.10
CNG+20%H2
CNG+30%H2
CNG+30%H2
100
0.05
50
0
0.00
Test 1
Test 2
Test 1
Test 2
Trip averaged emissions
Trip averaged emissions strongly influenced by traffic conditions
Difficult to have direct comparison with standard test cycle due to:
Road grade, idling, different average vehicle speed.
30
1800
1600
25
1400
)
1200
h 20
/
)
Ga(ssoline
Gasoline
(Km
1000
d
e
CNG
CNG
15
CNidlingG+10%H2
CNG+10%H2
spe
l
e
a 800
g
CNtG+20%H2
CNG+20%H2
a
r
To
e
CNG+30%H2
CNG+20%H2
Av 10
600
400
5
200
0
0
Test 1
Test 2
Test 1
Test 2
Averaging window approach
Moving averaging window – Distance based (4 and 11 km,
using a time increment equal to the data sampling frequency)
Data binning according to the parameters governing the vehicle
dynamics and therefore the fuel consumption and the
emissions
Average speed
Average road grade
Average relative positive acceleration (RPA)
Exception: Aerodynamic effects assumed to remain constant within a speed
range (effect of front wind had to be neglected)
Statistics conducted in the different bins
Comparison with ECE (urban part of NEDC)
Results
•
Averaging reference distance = NEDC length, 11.007 km.
•
Average road grade between -0.25% and 0.25%.
•
Distribution of CO2 emissions (g/km) as function of the average
window speed.
Test 1
Test 2
Results
•
Averaging reference distance = ECE 15 length, 4.052 km.
•
Average road grade between -0.25% and 0.25%.
•
Distribution of CO2 emissions (g/km) as function of the average
window speed.
300
300
250
250
200
)
200
)
m
Ga
m soline
Gasoline
/K
/K
(g
CNG
(g
CNG
2
2
CNG+10%H2
CNG+10%H2
CO
CO
150
CNG+2
1500%H2
CNG+20%H2
CNG+30%H2
CNG+30%H2
100
100
Test 1
Test 2
50
50
0
10
20
30
40
50
0
10
20
30
40
50
60
70
Average Window Speed (Km/h)
Window average speed (Km/h)
Results
•
Averaging reference distance = ECE 15 length, 4.052 km.
•
Average road grade between -0.25% and 0.25%, max idle 33%.
•
Distribution of CO2 emissions (g/km) as function of the window
relative positive acceleration in the speed bin 15-25 Km/h.
300
R² = 0.7872
250
R² = 0.8745
R² = 0.9746
200
)
m
R² = 0.9782
Gasoline
/K
(g
CNG
2
R² = 0.781
CNG+10%H2
CO 150
CNG+20%H2
CNG+30%H2
100
50
0
5
10
15
20
25
Window Relative Positive Acceleration (m/s2)
Results
•
Averaging reference distance = ECE 15 length, 4.052 km.
•
Average road grade between -0.25% and 0.25%.
•
Speed bin 15-25 Km/h.
•
Comparison between dyno emissions and on-road emissions
300
250
200
)
/Km
ECE
150
(g 2
TEST 1
CO
TEST 2
100
50
0
Gasoline
CNG
CNG+10%H2
CNG+20%H2
CNG+30%H2
Results
•
Averaging reference distance = ECE 15 length, 4.052 km.
•
Average road grade between -0.25% and 0.25%.
•
Speed bin 15-25 Km/h.
•
Comparison between dyno emissions and on-road emissions
0.3
0.25
0.2
)
m
/K
ECE
0.15
(g x
TEST 1
NO
TEST 2
0.1
0.05
0
Gasoline
CNG
CNG+10%H2
CNG+20%H2
CNG+30%H2
Conclusions: methodology
Indicators proposed for a systematic data binning method
RPA was found to be a good indicator to explain the
variability in the CO2 emissions at constant road grade and
speed
The averaging window method provides an efficient way to
link emissions and average operating characteristics
Conclusions: results
Use of hydrogen blends effectively reduce on-road CO2
emissions
NOx emission generally increase as the hydrogen content in
the blend increases
Largest spread of CO2 results in bins corresponding to the
largest RPA spread.
Special thanks to:
S. Alessandrini and F. Forni,
PEMS technicians
A. Ceci, Driver