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Joint Research Centre the European Commission's in-house science service
Serving society Stimulating innovation Supporting legislation
The latest developments on HDV CO2 Legislation &
VECTO tool
Belgrade – October, 2017
Disclaimer: The views expressed are purely those of the presenter and may not in any circumstance be regarded as stating an official position of the European Commission
Outline
CO2 emissions from HDVs & The VECTO tool § Current policy situation § VECTO
• Basics • Model & Sub components • Results and Validations
§ HDVs today & tomorrow § Summary & Follow up
Current policy situation
R o a d - t r a n s p o r t a t i o n
accounts for the majority
of transport emissions.
CO2 Emissions from Transport, EU-28
Transport in the EU-28 is responsible for ~20% of GHG emissions.
-- Cars and light duty vehicles (vans) ≈ 70% -- Heavy duty trucks, buses and coaches ≈ 30%
LDVs established certification, monitoring and targets since long time How about HDVs?
Data source: European Commission Transport pocketbook 2015
In May 2014 the Commission adopted a Communication entitled "Strategy for reducing HDV fuel consumption and CO2 emissions" COM(2014)285. Reference to HDV CO2 certification and reporting via simulation.
HDV CO2 policy context (1/2)
Roadmap for the Energy Union (Feb 15) sets the timetable: Establishing a monitoring and reporting system for HDVs with view to improving purchase information: 2016-2017
In July 2016 the Commission issued Strategy for Low-Emissions Mobility "Given the average lifetime of a lorry of about 10 years, vehicles sold in
2020 will still be on European roads in 2030. In order to be able to make
swift progress different options for standards will be considered,
including for engines only or for the whole vehicles, with the objective of
curbing emissions well before 2030.”
HDV CO2 policy context (2/2)
Developments: • DG-GROW proposed Legislative Act voted by MS in TCMV (11/05/17) regarding
Certification. Amendment to Regulation 595/2009. 2nd round is expected in 2nd half
2017, including the verification procedure and possibly other provisions.
• A 2nd legislation (co-decision) for monitoring and reporting of CO2 emissions and FC is
necessary. DG Clima proposal adopted by Comm. (31/5/17) to be discussed in Council
and EP.
• Possible first reporting year 2019 à possible first monitoring year 2020
VECTO basics
- Low, medium, high, long, short cab etc
- 2,3,4,5,6 axles, 4x2, 4x4, 6x2, 6x4, 6x6 etc
- Different tires for each axle, single/twin tires etc
- Same engine but different gear boxes/axles ect
- Rigid, semi-trailer, tractor, coach, bus, citybus etc
- Any combination mentioned above
HDVs are more complicated than LDVs
Which Heavy Duty Vehicles…??????
*Source: ACEA
Simulation tool to calculate both, fuel consumption and CO2 emissions from the whole vehicle Developed by the Commission (DG CLIMA and JRC) with TUG and Ricardo support over the last six years Initially in Visual basic, migrated to C# in latest versions
Scope of VECTO & accompanying regulation
Serve for all possible policy steps including:
• Monitoring, reporting and certification
• Improve market forces (e.g. by comparable customer information)
• Labelling
• Improve/help foot-printing schemes
• Give a reliable real world picture of the fuel consumption/CO2
emissions – accuracy ~ 95 %
• Fit for the future (include new technologies)
• Minimize burden on OEMs
Where to find VECTO: EC official VECTO Web-site (currently under construction will be hosted under the following domain) https://ec.europa.eu/clima/policies/transport/vehicles_en Or, write to: [email protected] (yes this one is already active J ) Register to GIT-VECTO On-line code repository and support platform (under construction will open soon)
VECTO offers a declaration mode, where all generic data and the test cycle are allocated automatically as soon as the vehicle class is defined.
An engineering mode where the user can select and change
all input data to allow recalculation of test data e.g. for model validation.
VECTO's modes
In declaration mode: • CO2 emissions automatically calculated for all CO2 test
cycles allocated to the vehicle and reference payloads • Results are given in g/km, g/cm3-km and g/ton-km or g/
pass-km In Engineering mode: • CO2 and fuel consumption for all the cycles/conditions
chosen by the user • All energy related quantities • Respective time series
VECTO output
VECTO-Structure
VECTO Graphical User Interface (GUI)
Trucks - Urban delivery
- Regional delivery - Long haul
- Construction - Municipal utility
Buses and coaches - City-bus heavy urban
- City-bus urban - City-bus suburban
- Interurban bus - Coach
Mission profiles
• All cycles are target speed – distance cycles (instead of traditional speed vs time ones.
• All cycles include slope.
• Ranging from 30km to 400km in duration.
Example the Regional Delivery Driving Cycle
Normal avg. loaded vehicle
Underpowered heavy loaded vehicle
Truck categories and respective configurations
For each class the corresponding test cycles, the standard body or trailer and the payload are defined as well as the data relevant for the simulation of the generic auxiliaries.
Busses categories and respective configurations
Model Details and subcomponents
Basic concept
Model structure - Four main modules
Model structure - Four main modules
Vehicle specific, component-oriented certification
• A series of components need to be tested in order to produce the necessary input for the final vehicle certification
• Specific methods (including measurements or fall-back options to reference values) are described for
• Air drag calculation
• Engine map and WHTC correction
• Transmission losses
• Torque converter
• Axle losses
• Retarder losses
• Auxiliaries losses
• Tyres
Engine Module: The engine map
• transient engine behaviour not considered • Solution à use of “WHTC correction factor” calculated on the basis of the
actual WHTC measurement
Torq
ue
[Nm
]
Engine speed [RPM] 26
Transmission: general provisions
• 3 different methods for assessing transmission losses Option 1: Measurement of the torque independent losses, calculation of the torque
dependent losses. Electric machine & torque sensor before transmission (output shaft free-rotating)
Option 2: Measurement of the torque independent losses, measurement of the torque loss at maximum torque and interpolation of the torque dependent losses based on a linear model
Option 3: Measurement of total torque loss. Electric machines and torque sensors in front and behind transmission
Source: ACEA 27
Input: Aerodynamic drag
• Constant speed test (at 2 velocities)
• torque meter rim • anemometer • correction for gradient and for
vehicle speed variations • correction for ambient p,T • F = F0 + Cd * A * v² *ρ/2
Important tire and vehicle conditioning for accurate Cd*A results. RRC calculated in these tests not to be used.
28
à Different representative cycles per vehicle category and mission profile including target speed phases and road gradients
Driver model
Cycles: Trucks: Long haul, Regional delivery, urban delivery, Municipal utility, Construction Busses: Urban bus (heavy urban, urban, suburban), Interurban bus, Coach
Overspeed function
Driver model:
Acceleration: limited by full load and max. driver demand
ADAS systems in development
Example: long haul cycle
Gear selection with torque interruption
29
• Implementation of gear shift strategy proposed by ACEA for manual and automated manual transmissions
Up- and down-shift polygons
Default-Option: skipping of gears: Criteria: 1) rpm is still over DownShift-rpm and 2) torque reserve is above a user-defined value (e.g. 20%) Additional parameter for avoidance of ocillating shifts: minimum time between two gear shifts (e.g. 3s)
• AMT = MT with different polygons and early upshifting
• Skipping gears possible based on torque reserve criteria, starting from gear >1
• Automatic GB model under development based on input received from OEMs and GB
manufacturers
Gearshift model MT-AMT
Torque [Nm] Downshift [rpm]
Upshift [rpm]
-500 650 900
0 650 900
500 700 950
... ... ...
30
Auxiliaries' influence in buses & coaches
Drivetrain losses, rolling resistance, air
resistance, etc.., 78.2%
3.0%
5.9%
6.5%
2.4%
4.0%
21.8%
City Bus
Enginecooling fan
Alternator
Aircompressor
Steeringpump
A/Ccompressor
Drivetrain losses, rolling resistance, air
resistance, etc.., 88.3%
1.2%
2.5%
2.6%
1.6%
3.8%
11.7%
Coach
Enginecooling fan
Alternator
Aircompressor
Steeringpump
A/Ccompressor
Auxiliaries,
• High auxiliaries’ influence in the case of buses and coaches • Buses and coaches need more detailed simulation of auxiliaries • Auxiliaries for Trucks ~5% but buses ~22% and coachs ~12%
• A bus auxiliary module was developed and validations are currently on going
VECTO schematic including new Bus Aux
VEC
TO C
ore
‘Classic’ Auxiliaries
Simple Auxiliary 1 (.VAUX)
Simple Auxiliary 2 (.VAUX)
Etc.
Bus Auxiliaries (.AAUX)
Electrics Module
Input Parameters
Combined Alternator Model (.AALT) Input Parameters
Pneumatics Module
Input Parameters
Compressor Map (.ACMP)
Actuations Map (.APAC)
HVAC Module
HVAC SS Model (.AHSM)
Input Parameters
Engine Waste HeatBus Parameter
Database (.ABDB)
First experimental evaluation
on-going
Additional improvements to
be scheduled
VECTO results and Validations
Which metrics would we want to improve?
Depending future legislation provisions other metrics might be also relevant (eg. gCO2/p.km, gCO2/kWh@wheel, MJ@wheel/ MJfuel etc
Validation with Chassis dyno tests
0.9
0.95
1
1.05
1.1
FC(flowmeter) FC(Vecto)
Normalize
dFC
a b
0.9
0.95
1
1.05
1.1
FCFuelflow FCDAF FC(Vecto)
Normalize
dFC
c d
e f
18tonne rigid
0.9
0.95
1
1.05
1.1
FC(flowmeter) FC(Vecto)
Normalize
dFC
a b
0.9
0.95
1
1.05
1.1
FC(flowmeter) FC(Vecto)
Normalize
dFC
c d
40tonne tractor-trailer
Method is quite accurate, under controlled conditions
Test Avg. Test Avg.
Validation with on road tests
36
0.95
0.975
1
1.025
1.05
Measured Sim1 Sim2 Sim3 Sim4 Sim5
Normalize
dFC
CO
2 Pro
cedu
re
Sim
ulat
ion
of
actu
al te
st
0.9
0.92
0.94
0.96
0.98
1
1.02
1.04
Fuelflowmeter Vecto(Sim1) Vecto(Sim2)
Normalized
FC
errorbars=±σ
CO
2 Pro
cedu
re
Act
ual t
est
sim
ulat
ion
Method seems to be quite accurate, even at real world conditions Dashed lines correspond to +-3% Additional validations done by several stakeholders; VECTO within +-5% of test in the majority of the cases.
Test Avg.
Test Avg.
• In order to build trust in the VECTO results à random ex-post verification test • Identify any issues with the component input – data • Ensure quality control of the certification process
• A real-world based test (Ex-Post test) is under development for the purpose • 3 options investigated On-road operation most likely candidate
Transient tests – Ex Post verification (1/2)
Option Steady State Chassis Dyno
Transient Cycle Chassis Dyno On-road operation
Repeatability Very good except
for low-load points
Very good Very good
Representativeness of actual vehicle
operation Lowest
High with some restrictions in
brake applications Highest
Applicability to all HDVs
Restrictions for specific
categories
Restrictions for specific
categories Possible
Cost High High Lowest
Complexity High due to the nature of the test
Low provided all equipment available
Low but requires specific test
protocol
Test Data analysis
Lowest directly comparable to specific VECTO
output
Low High needs
specific boundary conditions
Maturity
(how close to actual
implementation)
Good - A first draft of the
protocol described
Poor - New protocol is required
Fair - Elements from PEMS
protocol can be adopted
Transient tests – Ex Post verification (2/2)
ü On-Road tests, good agreement of measured vs simulated fuel consumption. ü VECTO Ex-Post mode seems to simulate very well on-road measurements with
deviations being <6%. ü Better results measured torque at the wheels is used as input
Estimate 2-3% offset due to Torque drift –
correction possible
CO2 emissions from HDVs
Avg. Performance not straightforward to define
b
A first analysis conducted for Classes 4, 5, 9, 10 2016 Euro VI Trucks – VECTO run in declaration mode Based on and comparable to JRC chassis dyno & on road tests Peak ICE efficiency of the order of 43-45%
How do HDV vehicles perform today?
ClassPayload(kg)
Speed(km/h)
FC(l/100km)
CO2(g/km)
CO2ut.(g/tkm)
BSFC(g/kWh)@ICE
VSFC(g/kWh)@wheel
Efficiency@ICE
Efficiency@wheel
Cycle
Class4 14000 76 25.70 678 48.4 190.4 223.2 43% 37%Class5 19300 79 32.13 848 43.9 196.5 225.1 42% 37%Class9 19300 78 31.04 819 42.4 195.4 224.0 42% 37%Class10 19300 79 32.91 868 45.0 196.2 224.2 42% 37%Class4 4400 59 18.95 500 113.6 195.6 236.8 42% 35%Class5 12900 59 32.81 865 67.1 195.2 222.3 42% 37%Class9 7100 59 23.93 631 88.9 200.7 235.5 41% 35%Class10 12900 59 33.38 880 68.3 195.2 222.3 42% 37%
Class4 4400 7.9 43.33 1143 259.7 242.6 424.8 34% 19%
Class9 7100 8.0 58.37 1540 216.8 267.4 434.4 31% 19%
Longhaul
Region
al
Delivery
Mun
ici
palU
til.
Where are we today (engine)? (100% = total fuel energy)
* Preliminary data based on simplified JRC engine model and HDV engine test bench data
0%
10%
20%
30%
40%
50%
60%
70%
Longhaul Regionaldelivery
Longhaul Regionaldelivery
30ttractortrailer 40ttractortrailer
Totalene
rgy(%
)
Vehicle
Intercooler
Heattransfertoambient
Coolinglosses
Exhaustlosses
Frictionlosses
• HDV engines already achieve high
peak efficiency (46%) over a wide
range of the map
• How much is realistically
achievable with ICE technology
(50%?)
• Exhaust gas enthalpy main loss
component
• To what extent can be exploited
without pollutant emissions trade-
off?
• Ex. Heat. Recovery techs appear
to be most relevant but for which
applications / mission profiles?
• How about downsizing, down
speeding and some form of
hybridization (serial)
Where are we today (vehicle) (100% = total fuel energy)
Class 4 • Technology relevance depending on
application (urban/long haul)
• Main candidates :
• Improved aerodynamics
• Mass reduction / Light weighing
• Tyre improvement
• Improved auxiliaries/powering auxiliaries
from alternative sources (eg EHR, BERS
etc)
• What are realistic peak-
performances?
• What will be the role of
electrification (with current
technology 10tons of batteries would
be required to replace the ICE -40t
Class5)
Median Highest LowestRigidtrucks -3.5% -5.0% -2.0% -2.0%
Tractor-trailers -3.5% -5.0% -2.0% -3.0%
Coaches -3.0% -4.0% -2.0% -2.0%
Enginesoftwaremanagementoptimization
Rigidtrucks -3.5% -5.0% -2.0% -1.1%
Rigidtrucks -0.5% -1.0% 0.0%
Tractor-trailers -0.5% -1.0% 0.0%
Rigidtrucks -0.4% -0.5% -0.3%
Unspecified -0.3%
Rigidtrucks -0.8% -1.0% -0.5%
Tractor-trailers -0.8% -1.0% -0.5%
Rigidtrucks -2.0% -15.0% -1.0%
Tractor-trailers -2.5% -20.0% -1.0%
Coaches -2.5% -12.0% -1.0%
Rigidtrucks -0.5% -1.0% 0.0%
Tractor-trailers -1.0% -1.5% -0.5%
Rigidtrucks -13.0% -16.0% -10.0%
Tractor-trailers -16.0% -22.0% -10.0%
Rigidtrucks -3.5% -5.0% -2.0%
Tractor-trailers -4.5% -5.0% -4.0%
Coaches -1.5% -2.0% -1.0%
Rigidtrucks -3.0%
Tractor-trailers -3.0%
Rigidtrucks -3.5% -4.0% -3.0% -3.0%
Tractor-trailers -3.5% -4.0% -3.0% -3.0%
Coaches -4.5% -5.0% -4.0% -2.0%
Rigidtrucks -0.5% -1.0% 0.0% -0.5%
Tractor-trailers -0.5% -1.0% 0.0% -0.3%
Rigidtrucks -2.5% -3.0% -2.0%
Tractor-trailers -5.0% -7.0% -3.0%
Coaches -5.5% -8.0% -3.0%
Rigidtrucks -0.5% -1.0% 0.0%
Tractor-trailers -0.5% -1.0% 0.0%
Coaches -0.5% -1.0% 0.0%
Hydraulichybrid Rigidtrucks -3.5% -5.0% -2.0% -7.0%
Fullelectrichybrids Rigidtrucks -6.0% -8.0% -4.0%
Mildelectrichybrids Rigidtrucks -2.0% -3.0% -1.0%
Idlecontroltechnologies Unspecified -0.1%
Neutralidle Unspecified -0.4%
A/Csystemefficiency Unspecified -0.2%
Highefficiencyexteriorlighting Rigidtrucks -0.4% -0.5% -0.3%
Aircompressor Rigidtrucks -0.4% -0.5% -0.3%
ACEAestimateonfuel
consumptionCategory Technology Vehicletype Effectonfuelconsumption
Engine
Wasteheatrecovery
Improvedcoolingfan
Improvedalternator
Improvedwaterpumps
Hybrids
Idling
Componentsand
auxiliaries
Trailer-mountedextensions
Boattails/extensionpanels
Vortexgenerators
Completevehicleredesign
AxlesandTransmission
AMT
Aerodynamics
Activeflowcontrol
Externalgrilleshutter
Rooffairingdesign
Wheel/bogiefairingsandsideskirts
-25%-20%-15%-10%-5%0%
Onlinesurveyestimates
ACEAestimates
First technology scan exercise
https://ec.europa.eu/jrc/en/
publication/report-vecto-
technology-simulation-
capabilities-and-future-
outlook
First technology scan exercise – main findings
• Engine efficiency improvement potential is relatively limited in the long run at
least for conventional vehs. Peak efficiencies expected to reach 50% in the next
decade.
• More benefits on reducing energy demand in absolute terms and per transport
work unit.
• Waste energy (exhaust gas enthalpy, brake) may, depending on application, be
used for reducing auxiliary/peripheral energy consumption. Fuel price & payback
times are issues at the moment.
• Aerodynamics and weight most significant contributors in international and
national delivery applications. Important improvements are possible.
• A minimum hybridization level (eg BERS, supercapacitor applications, PV cells,
serial hybridization) might make sense in city applications (payback times?) or
for powering vehicle and engine auxiliaries
• With current battery technology, electrification seems difficult
• A lot of investment in driver aids, trip management, route optimization etc
Summary
• First wave of CO2 legislation on certification voted in May 2017
• First covers delivery trucks of Classes 4,5,9 and 10
• VECTO simulation platform to be used for CO2 quantification
• Component based approach / several tests covering component performance
• Monitoring is intended to start by 2018 for new registrations
• On a second wave other classes including coaches and possibly city buses.
• There are appear to be certain established technologies that can offer significant potential for improvement (low hanging fruits)
Summary
Follow - up
• CO2 targets are being considered and relevant work on-going
• EC runs an Impact Assessment study to investigate possible CO2 targets for post 2020 period
• VECTO to be expanded to additional HD vehicle classes (eg buses, coaches, remaining truck classes)
• Maximize technology coverage (Predictive Cruise Control, Waste Heat Recovery, Hybrids, new AT gearboxes) in the pipeline
• Emphasis should be given in realistically capturing the benefits of certain technologies that can offer important gains and enable their wide-scale introduction in the European market in the mid term future.
• Need to consider how to handle long term, more complex developments which may exceed the capacity of current tools (eg automated vehicles, platoons, etc)
Thank you for your attention!
Contact: Georgios Fontaras
Special Thanks for their feedback and contributions to the people involved in the HDV project: N. Zacharof, T. Grigoratos, A. Tansini, K.
Anagnostopoulos, D. Savvidis, B. Ciuffo
and to all the Technical Staff of Vela 7 Lab
JRC Science Hub: www.ec.europa.eu/jrc
Twitter: @EU_ScienceHub
LinkedIn: european-commission-joint-research-centre
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