pm sensor development and simulation for diesel
TRANSCRIPT
Renewable energies | Eco-friendly production | Innovative transport | Eco-efficient processes | Sustainable resources
PM Sensor Development and Simulation for Diesel Particulate Filter
On Board Diagnostic CLEERS Workshop 2013Dearborn, April 10-12th, 2013
J. Lavy, C.N. Millet, Y. Creff (IFP Energies nouvelles)
F. Duault, S. Raquin (EFI Automotive)
Ph. Breuil, J.P. Viricelle (Ecole des Mines de St Etienne)
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Outline
Context and objectives PM sensor basic approaches PM sensor design optimization PM sensor response characterization and analysis Vehicle evaluation on chassis dyno PM sensor response modeling Conclusion and outlook
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Outline
Context and objectives PM sensor basic approaches PM sensor design optimization PM sensor response characterization and analysis Vehicle evaluation on chassis dyno PM sensor response modeling Conclusion and outlook
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Context and objectives
DPF now generalized to cope DPF now generalized to cope DPF now generalized to cope DPF now generalized to cope with more and more stringent with more and more stringent with more and more stringent with more and more stringent emission standards, especially emission standards, especially emission standards, especially emission standards, especially for onfor onfor onfor on----road vehicle applicationsroad vehicle applicationsroad vehicle applicationsroad vehicle applications
PM10 annual mean daily value (µg/m 3) - 2012
WHO guidelines : 20 µg/m3EU regulation limits : 40 µg/m 3
Air quality standards in many Air quality standards in many Air quality standards in many Air quality standards in many countries aim at reducing countries aim at reducing countries aim at reducing countries aim at reducing population exposure to air population exposure to air population exposure to air population exposure to air pollutantspollutantspollutantspollutants PMPMPMPM10101010, PM, PM, PM, PM25252525, SO, SO, SO, SO2222, NO, NO, NO, NO2222, CO, O, CO, O, CO, O, CO, O3333
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Context and objectivesEurope LDV
PM mass certification and EOBD threshold limits (mg/km)
020406080
100120140160180200
Euro
3Eur
o 4
Euro
5 a
(200
9)
Euro
5 b
(201
1)
Euro
6.1
(201
4)
Euro
6.2
(201
7)
EOBD
Certification
US LDV
PM OTL/Certification limitratio
0
1
2
3
4
5
6
2004
-200
9
2010
-201
2
2013
+
Similar trend for HDVNeed for accurate DPF filtration efficiency diagnostic
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Context and objectives Today, detection of DPF failure is based on differential Today, detection of DPF failure is based on differential Today, detection of DPF failure is based on differential Today, detection of DPF failure is based on differential
pressure sensor technologypressure sensor technologypressure sensor technologypressure sensor technology Limited sensitivity: only severe DPF failures can be detectedLimited sensitivity: only severe DPF failures can be detectedLimited sensitivity: only severe DPF failures can be detectedLimited sensitivity: only severe DPF failures can be detected Technology not able to meet future stringent EOBD threshold limiTechnology not able to meet future stringent EOBD threshold limiTechnology not able to meet future stringent EOBD threshold limiTechnology not able to meet future stringent EOBD threshold limitstststs
Need for a more sensitive technology such as an onononon----board board board board PM sensorPM sensorPM sensorPM sensor downstream of the DPFdownstream of the DPFdownstream of the DPFdownstream of the DPF
Various PM sensor technologies under developmentVarious PM sensor technologies under developmentVarious PM sensor technologies under developmentVarious PM sensor technologies under development Continuous and cumulative measurement concepts Continuous and cumulative measurement concepts Continuous and cumulative measurement concepts Continuous and cumulative measurement concepts
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Outline
Context and objectives PM sensor basic approaches PM sensor design optimization PM sensor response characterization and analysis Vehicle evaluation on chassis dyno PM sensor response modeling Conclusion and outlook
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PM sensor basic approaches:Spark discharge
Source : Journal of Engineering for Gas Turbine and Power / March 2009, Vol 131 / Allen et al
Source : SAE 2006-05-0285 / Gheorghiu et al Source : SAE 2012 OBD Symposium /
Stuttgart / Gheorghiu
PM concentration related to changes in the voltage waveform of a repetitive, low energy spark discharge
Cross-sensitivities to check High voltage to manage
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PM sensor basic approaches:Electrochemical polarization Produced by a difference in O2 partial pressures
between 2 electrodes, which is due to PM deposit and oxidation on the anode
Source : SAE 2011-01-2059 / Yoshihara et al. Very localized phenomenon
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PM sensor basic approaches:The electrostatic concept: image charge Measurement of the current emitted by the inherent
PM electrical charge
Source : ETH Conference 2004 / Kittelson et al / University of Minnesota
Poor response signal due to the globally neutral particulate charge within the exhaust pipe
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PM sensor basic approaches:The electrostatic concept: corona discharge
Source : DEER 2009 / Hall et al
The corona discharge increases PM electrical charge
High voltage management necessary
Source : SAE 2011-01-0626 / Zamaras et al
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PM sensor basic approaches :Electrostatic capacity Detection of PM accumulation related to changes in
electrostatic capacity
Source : SAE 2011-01-0302 / Kono et al.
High voltage to manage
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PM sensor basic approaches:The resistive concept Resistance decreases as conductive carbonaceous
particulates accumulate between the electrodes
Source : IFPEN patent FR2760531
Time
Resistance (Ohm)
Concept widely studied due to simplicity and low cost
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Outline
Context and objectives PM sensor basic approaches PM sensor design optimization PM sensor response characterization and analysis Vehicle evaluation on chassis dyno PM sensor response modeling Conclusion and outlook
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PM sensor design optimizationFrom the first prototype in 2000
1 cm
Source : SAE 2000-01-0472 / Bouchez et al
Glow plug for soot burning
Two electrodes for resistance measurement
Prototype developed for concept validation
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Sensitive element
Interdigitalelectrodes for
resistance measurement
Heater for
soot burning
(regeneration)
PM sensor design optimizationto a pre-industrial version today
Packaging & control unit
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Objectives:Objectives:Objectives:Objectives: homogeneous PM depositionhomogeneous PM depositionhomogeneous PM depositionhomogeneous PM deposition avoid deposition of large particlesavoid deposition of large particlesavoid deposition of large particlesavoid deposition of large particles limited heat exchanges for efficient and fast soot burninglimited heat exchanges for efficient and fast soot burninglimited heat exchanges for efficient and fast soot burninglimited heat exchanges for efficient and fast soot burning
PM sensor design optimization3D CFD of the flow around sensor shield
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K-Epsilon RNG turbulence model for fluid Lagrangian representation for particles
Based on spray liquid injection models (no evaporation… Turbulent dispersion also taken into account for particles Simultaneous injection of different particle sizes
255 000 cells and 268 000 nodes 64 processors 25 to100 h (depending on flow conditions…
PM sensor design optimization3D CFD of the flow around sensor shield
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PM sensor design optimization3D CFD of the flow around sensor shield
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PM sensor design optimization3D CFD of the flow around sensor shield
PM deposited on ΣsDeposition ratio =
PM flowing through Σin
Σs
Σin
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0,00
2,00
4,00
6,00
8,00
10,00
1 10 100 1000 10000
Particles size Particles size Particles size Particles size ((((nmnmnmnm…………
Dep
ositi
on ra
tio (%
…D
epos
ition
ratio
(%…
Dep
ositi
on ra
tio (%
…D
epos
ition
ratio
(%… With turbulent dispersion
W/o turbulent dispersion
PM sensor design optimization3D CFD of the flow around sensor shield Turbulent dispersion and particles inertia effects
Particles above 5 µm deposited by inertial impaction
Particles below 5 µm deposited by turbulent dispersion
Typical Diesel Particulate sizedistribution
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Reference design : large particles impact a lot
Config #A : no impact of large particles low impact of smaller
particles
Config #B : no impact of large particles impact of smaller particles
remains significantBest experimental results with Config#B
0,00
2,00
4,00
6,00
8,00
10,00
1 10 100 1000 10000
Particles size Particles size Particles size Particles size ((((nmnmnmnm…………
Dep
ositi
on ra
tio (%
…D
epos
ition
ratio
(%…
Dep
ositi
on ra
tio (%
…D
epos
ition
ratio
(%… Reference
Config #AConfig #B
PM sensor design optimization3D CFD of the flow around sensor shield Various configurations tested
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Context and objectives PM sensor basic approaches PM sensor design optimization PM sensor response characterization and analysis Vehicle evaluation on chassis dyno PM sensor response modeling Conclusion and outlook
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Heater
Particulatespreading out
system
PM sensor
Particulatetank
PM sensor response characterization and analysisDevelopment of a specific PM test bench rig
ΦΦΦΦ: 39 mm Flow rate: 0 350 m3/h
Flow velocity: 0 80 m/sTemperature: 20°°°°C 450 °C
PM concentration: 0 250 mg/m3
Particulate mean diameter (nm)
120165
240
10
100
1000
Engineout
Enginesoot
Carbonblack
Particulate test rig
Eng
ine
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BIP - capteur L18P3D5 - 150 °C - 34.5 m/s - suies m oteur - effet concentration PM
100
1000
10000
100000
0 100 200 300 400 500 600
temps (s)
rési
stan
ce fi
ltrée
cap
teur
(kO
hm)
PM 11 mg/m3 PM 4 mg/m3
time (s)
PM
sen
sor
resi
stan
ce(k
Ω) 150°C / 35 m/s
PM : 11 mg/m3 PM : 4 mg/m3
110 s 430 s
PM sensor response characterization and analysis
Loading time (tload)
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PM sensor response characterization and analysis
0
100
200
300
400
500
600
700
0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 9,0 10,0
PM flow rate (mg/s)
Tim
e to
rea
ch 1
Moh
m (
s)
Particulate test rig feeded by engine soot
Engine test rig
Particulate test rig fed by engine soot
PM flow rate (mg/s)
Load
ing
time
t load
(s)
Comparison between particulate and engine test rigs results
Similar results
Particulate test rig representative of engine conditions and phenomena
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0
20
40
60
80
100
120
0 10 20 30 40
Electrode polarization (V)
Load
ing
time
(s)
Polarization favors formation of particle bridges
Better deposition rate ? (to be confirmed)
PM sensor response characterization and analysis
Fixed flow rate and soot concentration
electrode
electrode
PM sensor sensitivity enhanced by electrode polarization
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BIP - capteur L18P3D5 - 150 °C - 34.5 m/s - suies m oteur - effet concentration PM
100
1000
10000
100000
0 100 200 300 400 500 600
temps (s)
rési
stan
ce fi
ltrée
cap
teur
(kO
hm)
PM 11 mg/m3 PM 4 mg/m3
Time (s)
sens
orre
sist
ance
(kΩ
)
150°C / 35 m/s
PM : 11 mg/m3 PM : 4 mg/m3
tload
PM sensor response characterization and analysis
Pipe section
Qsoot( g/mm2)
Qsoot should be a constant value in perfect conditions
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flow velocity (m/s)
Particulatetest rig
flow velocity (m/s)
EngineBench
PM sensor response characterization and analysis Test repartition vs PM, flow velocity and temperature
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PM sensor response characterization and analysis
Similar tendency whatever the test benchDominant effect of flow velocity and soot concentration
on sensor response
0
20
40
60
80
100
120
0 10 20 30 40 50 60
PM (mg/m3 )Q
soot
(µg/
mm
²)
8-18 m/s
19-33 m/s
37-46 m/s
0
20
40
60
80
100
120
0 10 20 30 40 50 60
PM (mg/m3 )
Qso
ot (µ
g/m
m²)
8-18 m/s
19-33 m/s
37-46 m/s
0 10 20 30 40 50 60
vitesse 9 m/svitesse 34 m/svitesse 60 m/s
velocityvelocity
velocity
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Context and objectives PM sensor basic approaches PM sensor design optimization PM sensor response characterization and analysis Vehicle evaluation on chassis dyno PM sensor response modeling Conclusion and outlook
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Vehicle evaluation on chassis dyno
Citroën C4 - €4 DV6 engine
Drilled DPF to simulate different failure levels
EXXOtestCAN logger
IXXAT CANbridge
Instantaneous PM concentration measurement by AVL 483 (MSS)
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Slightly damaged DPFPM 4.6 mg/km
Vehicle evaluation on chassis dynoNo DPF
PM 15.2 mg/km
PM sensor resistance (kΩ)
Vehicle speed (km/h)
PM (mg/m3)
4 successive hot NEDC driving cycles
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0
0,5
1
1,5
2
2,5
3
3,5
4
4,5
5
0 5 10 15 20
PM mass NEDC (mg/km)
Pm
sen
sor
load
ings
/ N
ED
C
Vehicle evaluation on chassis dyno
PM sensor loading frequency proportional to PM mass
PM sensor able to detect low PM level (~ 4 loadings during NEDC @ 12 mg/km)
PM sensors loading frequency function of the PM mass
12
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Context and objectives PM sensor basic approaches PM sensor design optimization PM sensor response characterization and analysis Vehicle evaluation on chassis dyno PM sensor response modeling Conclusion and outlook
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WhyWhyWhyWhy To analyze the effects of flow and PM sensor design To analyze the effects of flow and PM sensor design To analyze the effects of flow and PM sensor design To analyze the effects of flow and PM sensor design
parametersparametersparametersparameters To be used in modelTo be used in modelTo be used in modelTo be used in model----based DPF onbased DPF onbased DPF onbased DPF on----board diagnostic board diagnostic board diagnostic board diagnostic
algorithms (both modelalgorithms (both modelalgorithms (both modelalgorithms (both model----based and non modelbased and non modelbased and non modelbased and non model----based based based based diagnostics algorithms developed at IFPEN…diagnostics algorithms developed at IFPEN…diagnostics algorithms developed at IFPEN…diagnostics algorithms developed at IFPEN…
How: by coupling two subHow: by coupling two subHow: by coupling two subHow: by coupling two sub----modelsmodelsmodelsmodels PM deposition on the sensing zonePM deposition on the sensing zonePM deposition on the sensing zonePM deposition on the sensing zone Resistive response according to PM quantity deposited over Resistive response according to PM quantity deposited over Resistive response according to PM quantity deposited over Resistive response according to PM quantity deposited over
the sensing zonethe sensing zonethe sensing zonethe sensing zone
PM sensor response modeling
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PM depositionsub-model
Soot depositedquantity
qsoot (t)
Resistive responsesub-model
qsoot
Res
ista
nce
PM sensor response modelingExhaust pipe ØFlow velocity V(t)PM concentration C(t)Temperature T °°°°(t)
Qsoot (t)
time
Res
ista
nce
Rs(t)
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PM deposition ratio (Dr… is a function of flow velocity and PM concentration
0
2
4
6
8
10
0 10 20 30 40 50 60PM (mg/m3)
PM
dep
ositi
on r
atio
(‰
)
Model - 9m/sModel - 34 m/sModel - 60 m/sExperimental - 9 m/s
Experimental - 34 m/sExperimental - 60 m/s
)....1.( 3210 CVACAVAADr +++=
PM sensor response modelingPM deposition ratio sub-model
A1, A2, A3 calibrated from stabilized test results
A0 calibrated from either stabilized or transient test results
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∑+= is RRR /1/1/1 0
PM sensor response modelingResistive response sub-model
Particles in a bridge are series resistors and bridges are resistors connected in parallel
l 0R
Ri
Ri²..
..4
Dm
i Nb
lR
πρ=
PM: mean diameter: resistivity (no specific data available, calibrated
parameter from either stady state or transient test results)ρ
mD
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PM sensor response modeling
A0 and calibrated from this reference test PM sensor resistance – experimental and modeling (kΩ)
Vehicle speed (km/h)
PM (mg/m3)
No DPF – Hot successive NEDC - PM 15.2 mg/km
Good accordance with experimental data
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PM sensor response modeling
0
1
2
3
4
5
6
0 5 10 15 20
PM mass NEDC (mg/km)
Pm
sen
sor
load
ings
/ N
ED
C
Exp.Model
Application of the model for various DPF failure levels
Accurate prediction of the PM sensor loading frequency whatever the DPF failure level
Model evaluation for others driving cycles to be done
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Conclusion
3D3D3D3D----CFD simulationCFD simulationCFD simulationCFD simulation to better understand the particle deposition processesto better understand the particle deposition processesto better understand the particle deposition processesto better understand the particle deposition processes to optimize the sensor collecting tip designto optimize the sensor collecting tip designto optimize the sensor collecting tip designto optimize the sensor collecting tip design
Development of a specific particulate test rigDevelopment of a specific particulate test rigDevelopment of a specific particulate test rigDevelopment of a specific particulate test rig easy and independent control of flow velocity, temperature, PM easy and independent control of flow velocity, temperature, PM easy and independent control of flow velocity, temperature, PM easy and independent control of flow velocity, temperature, PM
concentration and nature (synthetic or engine soot…concentration and nature (synthetic or engine soot…concentration and nature (synthetic or engine soot…concentration and nature (synthetic or engine soot… sensor response analysis and results in accordance with engine tsensor response analysis and results in accordance with engine tsensor response analysis and results in accordance with engine tsensor response analysis and results in accordance with engine testsestsestsests
Engine test benches and vehiclesEngine test benches and vehiclesEngine test benches and vehiclesEngine test benches and vehicles sensitivity validation in steadysensitivity validation in steadysensitivity validation in steadysensitivity validation in steady----state and transient conditionsstate and transient conditionsstate and transient conditionsstate and transient conditions
Tools used to develop a new resistive PM sensor
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Conclusion
High sensitivity to low PM levels, complying with the 12 High sensitivity to low PM levels, complying with the 12 High sensitivity to low PM levels, complying with the 12 High sensitivity to low PM levels, complying with the 12 mg/km European OBD threshold limit (Euro 62 in 2017…mg/km European OBD threshold limit (Euro 62 in 2017…mg/km European OBD threshold limit (Euro 62 in 2017…mg/km European OBD threshold limit (Euro 62 in 2017…
Nearly continuous DPF monitoring despite a basic Nearly continuous DPF monitoring despite a basic Nearly continuous DPF monitoring despite a basic Nearly continuous DPF monitoring despite a basic "cumulative process""cumulative process""cumulative process""cumulative process"
Model of PM deposition rate and sensor resistance Model of PM deposition rate and sensor resistance Model of PM deposition rate and sensor resistance Model of PM deposition rate and sensor resistance response developed and validated in both steady state response developed and validated in both steady state response developed and validated in both steady state response developed and validated in both steady state and transient (NEDC cycle… conditionsand transient (NEDC cycle… conditionsand transient (NEDC cycle… conditionsand transient (NEDC cycle… conditions
This on-board PM sensor demonstrated its strong ability to detect DPF malfunction or failure as required by the future OBD standards
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Outlook Validation of DPF failure diagnostic algorithm in real life Validation of DPF failure diagnostic algorithm in real life Validation of DPF failure diagnostic algorithm in real life Validation of DPF failure diagnostic algorithm in real life
conditionsconditionsconditionsconditions SAE paper 2013SAE paper 2013SAE paper 2013SAE paper 2013----01010101----1334 to be presented next week at SAE 1334 to be presented next week at SAE 1334 to be presented next week at SAE 1334 to be presented next week at SAE
World CongressWorld CongressWorld CongressWorld Congress Durability tests under wayDurability tests under wayDurability tests under wayDurability tests under way
aging: 600 h, 2400 regenerations achieved so far on an engineaging: 600 h, 2400 regenerations achieved so far on an engineaging: 600 h, 2400 regenerations achieved so far on an engineaging: 600 h, 2400 regenerations achieved so far on an engine poisoning: from fuel and lubricant additivespoisoning: from fuel and lubricant additivespoisoning: from fuel and lubricant additivespoisoning: from fuel and lubricant additives
Evaluation of PM sensor response to particulate Evaluation of PM sensor response to particulate Evaluation of PM sensor response to particulate Evaluation of PM sensor response to particulate numbernumbernumbernumber Diesel engineDiesel engineDiesel engineDiesel engine GDI engine (GPF developed to comply with future PN GDI engine (GPF developed to comply with future PN GDI engine (GPF developed to comply with future PN GDI engine (GPF developed to comply with future PN
legislation…legislation…legislation…legislation…
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Acknowledgements To coTo coTo coTo co----authorsauthorsauthorsauthors To French authorities for financial support of To French authorities for financial support of To French authorities for financial support of To French authorities for financial support of
"CICLAMEN 1&2" projects"CICLAMEN 1&2" projects"CICLAMEN 1&2" projects"CICLAMEN 1&2" projects
To "CICLAMEN 1&2" project partnersTo "CICLAMEN 1&2" project partnersTo "CICLAMEN 1&2" project partnersTo "CICLAMEN 1&2" project partners
Renewable energies | Eco-friendly production | Innovative transport | Eco-efficient processes | Sustainable resources
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