Elektronik: zu viel des Guten? · 1995 2010 2015 Mechanics Source: A.T.Kearney Embedded Systems...
Transcript of Elektronik: zu viel des Guten? · 1995 2010 2015 Mechanics Source: A.T.Kearney Embedded Systems...
Elektronik: zu viel des Guten?
2012-06-21 Open University – ACstyria 1© VIRTUAL VEHICLE
Dr. Jost BernaschVirtual Vehicle Research and Test Center
Graz, Austria
COMET K2 Competence Center - Initiated by the Federal Ministry of Transport, Innovation & Technology (BMVIT) and theFederal Ministry of Economics & Labour (BMWFI). Funded by FFG, Land Steiermark and Steirische Wirtschaftsförderung (SFG)
Founded: July 2002Current Staff: 195 (May 2012)
Turnover: EUR 20 Mio.
40%
19%
Shareholder:
VIRTUAL VEHICLE
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Managing Director: Dr. Jost Bernasch
Scientific Director: Prof. Hermann Steffan(Vehicle Safety / Frank Stronach Institute, TU Graz)
10%
19%
12%
Founded: July 2002Current Staff: 190 (Jan 2012)
Turnover: EUR 18 Mio.
40%
19%
Shareholder:
VIRTUAL VEHICLE
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Managing Director: Dr. Jost Bernasch
Scientific Director: Prof. Hermann Steffan(Vehicle Safety / Frank Stronach Institute, TU Graz)
10%
19%
12%
Single Point of Contact
Customer
Single point of contact
Virtual Vehicle connects Customer to:
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TU-Graz and Institutes
Research Facilities
Industrial Partners
Ser
vice
sF
unde
d an
d C
ontr
actu
al R
esea
rch
Virtual Vehicle connects Customer to:
Research Projects
Funded Programme
2008 to 2018
K2
Outline
• Overview• Examples
• Vehicle electrification and power net• Vehicular battery modeling• Functional and vehicle safety• Model library based system simulation
• Outlook: A Glance at the future
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• Outlook: A Glance at the future• Summary
Example: Infotainment – a highly networked system
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Source: Audi AG
Example: Infotainment
PlayerDVD
Entertainment
Telefon
Information
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Stereo, Surround
Radio, TV
CAR Funktionen
Navigation
FM, AM, LW,Sirius, XM,DAB, DVB-T
Source: Audi AG
Functions
CD
Sound
DSP Sound
CD (mp3)
Premium Sound
Standard Sound
SD -card (mp3)
CD
Sound
RadioRadio
1975
Radio
CD
Sound
Radio
1993
CD
Sound
Car Functions
DSP Sound
DVD Navigation
Satellite Radio
DAB
Radio
CD (mp3)
TV (analog, digital)
Sprachbedienung
Telefon
Bluetooth -Telefon
Premium Sound
CD Navigation
Standard Sound
SD -card (mp3)
Car Functions
DSP Sound
DVD Navigation
Satellite Radio
DAB
Radio
CD (mp3)
TV (analog, digital)
Sprachbedienung
2005
Telefon
Bluetooth -Telefon
Premium Sound
CD Navigation
Standard Sound
SD -card (mp3)
TV
Navigation
CD
Radio
Telefon
Telematik
Sprachbedienung
Sound
TV
Navigation
CD
Radio
2001
Telefon
Telematik
Sprachbedienung
Sound
CD
Sound
DSP Sound
CD (mp3)
Premium Sound
Standard Sound
SD -card (mp3)
CD
Sound
Markets & Languages
Infotainment complexity
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Model range VariantsSource: Audi AG
Complexity driven by global market
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Source: Audi AG
Automotive electronics 2012
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Source: Photo courtesy of Hyundai Motor Company
In-vehicle communication
One subset of a modern vehicle‘s network architectu re, showing the trend toward incorporating ever more extensive electronics.
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Source: IEEE In-Vehicle Networks, 2010
Automotive electronics – the future?
Intelligent, adaptable, safe & secure, reliable, high performance, electrified vehicles
which operate within an integrated environment
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which operate within an integrated environment
E/E research and development
Challenges and research demand of today’s E/E syste ms
• Safety-critical software
• Function-oriented, model-based design
• Increasing software complexity
• Range of variants and versions
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• Range of variants and versions
• Range of vehicle architectures
• Increasing effort of integration and testing
• Consistent tool sequences and integrated data management
• More complex process, change, configuration, requirements management
• Standard architectures of ECUs (AUTOSAR)
Impact of trends on automotive innovations
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Source: Oliver Wyman, Car Innovations 2015
Automotive electronics
Major share of innovations driven by electronics an d embedded software.
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Source: Oliver Wyman, Car Innovations 2015
Research directions and challenges
Embedded software, sensors, electronics technology development � to foster improved system and vehicle performance, control, adaptability, and
intelligent communication (for conventional as well as electrified vehicles)� System integration (fusion of methods, technology and information)� Centralized and onboard SW-based diagnostics� Real-time systems and HW/SW integration� Seamless development chain (methods, processes, tools)� Data management along xiL (simulation, test data, measurement data)
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Contribution to evolving architectures and emerging standards� Open system IT platform� Functional safety (ISO26262)� Modular, interchangeable, reconfigurable and reusable systems to manage
increasing functionality (safety and mobility)
Research directions and challenges
Architectures (communication and electrical energy system)� Improved simulation techniques to ensure safe and reliable operation� System fault diagnosis and onboard, self-diagnostic systems� Predictive maintenance� Adaptive systems („morphing architectures“)� Reconfigurable systems � Data collection and information fusion
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Electrified and electrical components ���� increase of efficiency� Battery (lifetime prediction, SoX)� Mechanical component electrification (e.g. transmission)� Auxiliary loads� New sensors and sensor systems� Accurate models vs. fast models� Multi-level onboard electrical systems (12V, <60V, >130V)
Research challenges
Efficiency in development and product� Cross-domain simulation� Data management: Mechatronic model library (MML)� Seamless tool chains and processes� Tool and tool chain qualification according to emerging standards� Improved simulation techniques to ensure efficient operation
(Model -based) system integration and shift to software
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(Model -based) system integration and shift to software� Open system vehicle IT platform� Standards for integration� Dynamic network management� X-by-wire (redundancy, control)� Adaptability (driver and vehicle monitoring, „on demand“ apps, diagnostic
systems) � upgradeability, modularity, functionality (xCUs)� SW design for reliability, re-use and safety� ADAS, e.g. adaptive cruise control and data fusion (video, radar, pedestrian
protection)
Observable trends in E/E research and development
Paradigm shift in the development of E/E architectu res
• Open systems and standardized interfaces (e.g. AUTOSAR)• Reusability and scalability of software functions• Model-based design methods (Model-based systems engineering, MBSE)• Centralized data processing and partially autonomous sensors, actuators• “Cooperate on standards, compete on innovations”
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Development trends on system level
• Highly integrated control networks (e.g. global chassis control)• Electronics and software as a method to differentiate products• Mechatronic system (r)evolution• System level vs. component level
Source: Artemis, Internet of Energy, 2012
Challenge “Overall Vehicle”
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Challenge “Overall Vehicle”
Mechanics
Source: Daimler
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Mechanics
Challenge “Overall Vehicle”
Electrics /
Source: Daimler
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MechanicsElectrics / Electronics
Source : VW Käfer, Volkswagen, 1960
Challenge “Overall Vehicle”
MechanicsEmbedded Software
Source : DaimlerSource : Bosch
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Electrics / Electronics
Source : VW Käfer, Volkswagen, 1960
Challenge “Overall Vehicle”
MechanicsEmbedded Software
Source : DaimlerSource : Bosch
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Electrics / Electronics
Source : VW Käfer, Volkswagen, 1960
Challenge “Overall Vehicle”
MechanicsEmbedded Software
Source : DaimlerSource : Bosch
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Electrics / Electronics
Source : VW Käfer, Volkswagen, 1960
Target: Virtual design of the mechatronic system
„Overall Vehicle“
Overall Vehicle: System Sngineering (SE)
Frühe Produktreifegrade verbessernFrühe Produktreifegrade verbessernImprove the “early product”
Fixation of costs
Costs of changes
Frontloading:
Utilization of
inter-disciplinary & integrative development methods for holistic and
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Concept phase Development phase Production Maintenance,
repair
Possibility of cost reduction
Utilization of methods and IT-solutions in the
early phase of the development
development methods for holistic and sustainable decisions
CO2 reduction targets
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CO2 reduction
Clean ICE
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PEV
40%
60%
Electric & Electronics
0%
20%
40%
60%
Embedded Software
� Complexity is increasing� Multiple disciplines (mechanics,
electrics, electronics, embedded software, chemical engineering)
Trend towards embedded software
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0%
20%
0%
20%
40%
60%
1995 2010 2015
Mechanics
Source: A.T.Kearney Embedded Systems Study 2010
���� Model-based development
���� Software engineering aligned with mechanical engineering
Model-based system design
Model-based design, used to its fullest,• provides a single design environment • enables developers to use a single model of their entire system for data analysis,
model visualization, testing and validation, and ultimately product deployment• with or without automatic code generation.
At a minimum model-based design can be used as • a specification that contains greater detail than text-based specifications.• In real-time applications, it enables developers to evaluate multiple options , predict
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• In real-time applications, it enables developers to evaluate multiple options , predict systems performance , test systems functionality by imposing I/O conditions that might be operationally expected (before product deployment), and test designs .
Research and development demands• Traceability between different steps (requirements, design, optimization, validation)• Functional and technical representation• Seamless tracking of changes and variants• …
Model-based system design
Technical
Requirements
…Risk Assessment
Functional Safety
Item definition
…
FMEAFTA
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Engineering data backbone
Technical Architecture
Model (Simulation-Validation)
Functional Architecture Metamodel
(System)
e.g. MATLABUML-based
Model-based system design
Model-based design (Model-based systems engineering, MBSE) • aims at cutting design time • aims at providing final designs that more closely approximate pre-design expectations
for performance, systems functionality, and features an d schedule.
It provides:• Faster design iterations that produce desired performance, functionality
and capabilities.• Design cycles that are more predictable and result in faster product
shipments
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shipments• Reduction in design, development and implementation costs.
It comprises model-based• requirements engineering• design• control• validation and test• …
Source: dSPACE, ATZ online 2011
Electrification: Stairway to future vehicle
More safety
Eco-friendly
Fun todrive
Source: http://www.greencar.at
Green car
Source: Opel
Fun car
Safe car
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Source: http://e-vectoorc.eu/
Future vehicle
Source: http://www.crashstuff.com/
Motivation: Emergence of megacities
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Source: Oliver Wyman, Car Innovations 2015
Electrification: Stairway to future vehicle
• Extremely high energy and power demand from new types of E/E systems.
• More complex system architecture due to hard constraints with regard to system weight, quality, effort of R&D and cost.
• Securing concept for safety critical system/ function.
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Hofmann, W. et al., Prognosen für Industrie und KFZ-Elektronik / ZVEI, Elektronik Praxis Nr.6, 03 2010
Batteryelectrochemical modeling,
electrical / thermal integration,aging effects
Batteryelectrochemical modeling,
electrical / thermal integration,aging effects
Embedded Systems distributed systems,
functional safety,
Embedded Systems distributed systems,
functional safety,
Vehicle E/E research topics at ViF
Electrical systemtwo-(more-)voltage systems,
Electrical systemtwo-(more-)voltage systems,
Coupled Simulationcoupling methods,
simulation tool integration, simulation data management
Coupled Simulationcoupling methods,
simulation tool integration, simulation data management
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Control systemsreal time systems,
robust control, model based control
Control systemsreal time systems,
robust control, model based control
Electrical Drivetrainenergy flow simulation,
electrified drivetrain, design of electrical components
Electrical Drivetrainenergy flow simulation,
electrified drivetrain, design of electrical components
functional safety, HW/SW integration methods
functional safety, HW/SW integration methods
two-(more-)voltage systems, stability analysis,
development methods
two-(more-)voltage systems, stability analysis,
development methods
Outline
• Overview
• Examples• Vehicular battery modeling
• Functional and vehicle safety
• Model library based system simulation
• Vehicle electrification and power net
• Outlook: A Glance at the future
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• Outlook: A Glance at the future
• Summary
The limiting factor: Key technology battery
• Electric mobility is stongly influenced by energy storage systems• Storage of energy is a difficult technical issue• Lithium-ion batteries show currently the best properties• For mass production the 7 parameters have to be improved / optimized:
Costs
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Weight
Safety
Lifetime Energy density
Costs
Charging
Process maturity
Range of operation
EV:
80-90% DOD, ~3500 cycles
>3000 turnovers / 5 yrs
HEV:
5-10% DOD, ~350k cycles
~20.000 turnovers / 10 yrs
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Source: Johnson Controls, 2009
HEV
Plug-In HEV EV
Key component battery
Cell level:• It is common sense at the moment that the gravimetric energy density of current lithium-ion cell
materials can still be increased by approx. 25%.
• Next generation technologies (Lithium-Sulfur, Lithium-Air) should enable an increase by a factor of 3-4 � fundamental research
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Battery:• 700 up to 1000 €/kWh should be reduced to <300 €/kWh
• Cell- and battery mass production
• Battery safety (electrical, crash, crush) is not solved satisfactorily
Source: A123
Production of Li-ion batteries
� Knowledge in production and development is shifted to Asia
� Today about 90% of the world wide cell production is located in Asia
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Source: McKinsey & Company, Perspective on EV batteries, 2010
EV, PHEV battery packs
LG Chem, Compact Power, Inc
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LG Chem, Compact Power, Inc
A123 Systems L5 Hymotion
Why modeling of lithium-ion batteries?
• Determination of key parameters
• Temperature distribution / thermal validation
• Mechanical and thermal abuse
• Prediction of cell lifetime (ageing)Flir A40
Simulation
Flir A40
Cables for thermal sensors are not in the simulation
Flir A40
Simulation
Flir A40
Cables for thermal sensors are not in the simulation
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• Optimal design von electrodes, geometries,…
• Investigation of manufacturing effects
…
SimulationSimulation
Crash
Temperature
CurrentElectro -
Different models for different applications
Empiricalmodels Thermal models
Mechanical models
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Voltage
Chemistry
Electro -chemicalmodels
RC models
0D 1D 2D 3D
Modeling of lithium-ion cells for HEVs
Model Setup( ) ( ) ( ) ( ) ( )
( ) ( )
−−=−−
RT
UF
RT
UF
lspsppscpapp
ppcpppap
apapcpapcp eecccckkFi
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f
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RTti ln1
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∂∂++Φ∇−= +
±κκ
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Di
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νν
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li
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si
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asaj ∇−=−=
Parameterisation
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Flir A40
Simulation
Flir A40
Simulation
Cables for thermal sensors are not in the simulation
Flir A40
Simulation
Flir A40
Simulation
Cables for thermal sensors are not in the simulation
Verification
Calculations
Source: GAIA Akkumulatorenwerke GmbH
Sim
Thermal modeling
3D modeling of thermal behavior
• prismatic cells• Temperature distribution• Spatial U(I) distribution• 1C discharge
• round cells• Temperature distribution• Spatial U(I) distribution• Nail penetration test
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Nail
Mechanical modeling
3D finite element model
prismatic cells• Inhomogeneous material models for wounded electrodes• Analysis of short circuits within postprocessing• Different loads and impactors• Test facilities at Virtual Vehicle and TU Graz
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Cycling ageing
Calendaric ageing
Deviation between cells
Pulse timeDischarge
currentCharge current
Calendar time
SOC
Celltemperature
∆ Mechanicalstress
Cell ageing and battery management
DOD
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SOC/SOH estimationand control
e.g. replacement ofmodules / package
necessary?
SOC/SOH estimationand control
e.g. replacement ofmodules / package
necessary?
∆ SOC∆ Temperature∆ Productionparameters
BATTERY PACK
V
S
CE
LL M
OD
ULE
S
CE
LL M
OD
ULE
SPI
BATTERY PACK
V
S
CE
LL M
OD
ULE
S
CE
LL M
OD
ULE
BATTERY PACK
S
CE
LL M
OD
ULE
S
CE
LL M
OD
ULE
CANCANM = Master UnitV = Vassal UnitS = Slave Unit
HO
ST
SY
ST
EM
CAN, Ethernet, RS-232, RS-485, USB, FO
SPI SPIM
-
(Contactors, relays, current measurement
etc.)
+
-
PERIPHERALS
ON/OFF
Battery management
Battery integration via co-simulation
Parallel HEV concept with Li-Ion battery
Lithium-
Ion-
BatteryDRIVE
TRAIN
EM
Tn
T
n U, I, P
SOC
Temp
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Driver
Driving Cylce
ICE
Hybrid
Controller
Cooling
system
Tdem
Tdem
pp, brake
vdem
v
pbrake
v
n
Tn
nTemp
mechanical coupling
electrical coupling
thermal coupling
Battery integration via co-simulation
Lithium-
Ion-
BatteryDRIVE
TRAIN
EM
Tn
T
n U, I, P
SOC
Temp
Parallel HEV concept with Li-Ion battery
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Driver
Driving Cylce
ICE
Hybrid
Controller
Cooling
system
Tdem
Tdem
pp, brake
vdem
v
pbrake
v
n
Tn
nTemp
mechanical coupling
electrical coupling
thermal coupling
EngineDrivetrain Electric Motor
Li-Ion Battery
Hybrid Controller
Cooling Package
DriverDriving Cycle
Co-simulation representation
Intelligent energy management
� Predictive control based on topographical information
� Optimal charge / discharge of battery
� Model-predictive control using environmental data
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Outline
• Overview• Examples
• Vehicular battery modeling• Functional and vehicle safety• Model library based system simulation• Vehicle electrification and power net
• Outlook: A Glance at the future
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• Outlook: A Glance at the future• Summary
Integrated
Safety
FunctionalHigh voltage
HV battery ISO 26262Embedded systems
Automotive electronics and safety
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Active Passive
active during accident(seat belts, airbags, deformation zones…)
active prior to accident(collision warning, ESP, ASB…)
HV batteryPower electronicsE-Machine
Embedded systemsEmbedded softwareECU hardwareCommunication
Automotive electronics in vehicle safety
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Source: IEEE In-Vehicle Networks, 2010
Brief introduction to integrated vehicle safety
?2s ?100ms?2s ?100ms~2s ~100ms
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Unfallvermeidung Verringerung der Unfallschwere
Aktive Sicherheit !! Potenzial zur Unfallvermeidung oder Verringerung der Unfallschwere !!
Passive Sicherheit
Integrierte Sicherheit
Unfallvermeidung Verringerung der UnfallschwereCollision Avoidance Collision Mitigation
Aktive Sicherheit !! Potenzial zur Unfallvermeidung oder Verringerung der Unfallschwere !!
Passive Sicherheit
Primary Safety!! High Potential for Collision Avoidance or Mitiga tion !!
Secondary Safety
Integrated Vehicle Safety
Co-Simulation approach
Crash
Driving Dynamics
Sensors
Cra
sh t0
Interaction
Environment
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Safety Controller
Driver Cra
sh n
ot a
void
able
AccidentAccident avoidanceavoidance ReductionReduction ofof AccidentAccident SeveritySeverity
ActiveActive SafetySafety Passive Passive SafetySafety
Integrated Integrated SafetySafety
time
Functional safety
Software Tools
Classification andqualification of SW Tools
Safety StandardsISO 26262, IEC 61508
Safety Processes
• Supporting processes wrt. ISO 26262
• Process modelling• Management of functional safety
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Systems Engineering
• Safety Concept • Requirements management
• Product developmentat systems, HW and SWlevel
• Modeling and simulation• Verification and validation
SafetyEngineering
• Safety Modelling • Automotive Safety Integrity Level (ASIL) –and safety-orientedanalyses
Functional safety
Potential risk to
individuals
Additional risk
Development effort
(SW development)
SIL 3
SIL 4
ASIL C
ASIL D
Automotive Safety Integrity Levels (ASIL)
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Quality management (QM)(medium degree of maturity, SPICE, CMMI)
ASIL AASIL B
ASIL CASIL D
Additional risk
reduction
measures
Standard automotive
development process
SIL 1
SIL 2
ASIL A
ASIL B
ASIL C
ISO 26262 IEC 61508
Functional safety
Topics to be considered: � Safety concept for battery systems (Functional, electrical, passive, … safety)� Safety analyses for safety lifecycle (concept, system, hardware, software) � Seamless methods for safety analysis
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Functional safety
Topics to be considered: � Safety concept for battery systems (Functional, electrical, passive, … safety)� Safety analyses for safety lifecycle (concept, system, hardware, software) � Seamless methods for safety analysis
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Outline
• Overview• Examples
• Vehicular battery modeling• Functional and vehicle safety• Model library based system simulation
• Outlook: A Glance at the future
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• Outlook: A Glance at the future• Summary
Simulation ConfiguratorSimulation ConfiguratorSimulation Configurator
Model
Configuration
Loading case
Requirement
Outlook: System simulation with SDM support
Simulation Datamanagement (SDM) – BackboneSimulation Datamanagement (SDM) – BackboneSimulation Datamanagement (SDM) – Backbone
User Administration
…
Model Library
Process ImplementationData Repository
Con
sist
ency
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Configuration
Parameter
Result
Co-Simulation framework (i.e. ICOS...)
Work FlowModel Library
Con
sist
ency
…
electrical
connection
En
erg
y
e
En
erg
y
sto
rag
e
Example: virtual prototype
Cooling
circuit
Parallel (mild) HEV concept
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DriverHybrid
controller
mechanical
connection
DrivetrainInternal
combustion
engine
Electrical
machine
thermal
coupling
Example: virtual prototype
Parallel (mild) HEV concept
Engine & DrivetrainEngine & Drivetrain
Energy storage
Electric Motor
Cooling Package
Hybrid Controller
Driver
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DrivetrainDrivetrain storageMotor Package Controller
� Co-Simulation representation
Outline
• Overview• Examples
• Vehicular battery modeling• Functional and vehicle safety• Model library based system simulation
• Outlook: A Glance at the future
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• Outlook: A Glance at the future• Summary
Outline
• Overview• Examples
• Vehicular battery modeling• Functional safety• Model library based system simulation
• Outlook: A Glance at the future• Summary
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• Summary
1000
1000
010
0000
Pav
g [W
]
10
0010
000
1000
00P
avg [W
]
10
0010
000
1000
00P
avg [W
]
1: conventional vehicle
“base” configuration, TODAY
“high” configuration, TODAY
“high” configuration , FUTURE
2: E-vehicle
“base” configuration, TODAY
Power & energy demand of future vehicle
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110
100
1 10 100 1000 10000 100000
P nom [W]
110
100
1 10 100 1000 10000 100000
P nom [W]
110
100
1 10 100 1000 10000 100000
P nom [W]Quelle: L.Brabetz, „Energieeffiziente Bordnetzarchitekturen“,
VDE Kongress Elektromobilität, 2010
1000
1000
010
0000
Pav
g [W
]
1: conventional vehicle
“base” configuration, TODAY
“high” configuration, TODAY
“high” configuration , FUTURE
2: E-vehicle
“base” configuration, TODAY
Power & energy demand of future vehicle
2012-06-21 Open University – ACstyria 68© VIRTUAL VEHICLE
110
100
1 10 100 1000 10000 100000
P nom [W]Quelle: L.Brabetz, „Energieeffiziente Bordnetzarchitekturen“,
VDE Kongress Elektromobilität, 2010
Outline
• Overview• Examples
• Vehicular battery modeling• Functional safety• Model library based system simulation• Vehicle electrification and power net
• Outlook: A Glance at the future
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• Outlook: A Glance at the future• Summary
E/E - the near future
Need for advances in embedded software and electron ics
� foster the integration of systems to provide functionality, reliability, safety, security, and performance
� improve simulation techniques for energy storage, engine / vehicle management and control, electrified components
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� optimize power generation, conversion, and transmission
� manage growing connectivity and information availability
� take into account safety-critical systems and applications
� Seamless tool integration platform and development data management
Summary
� In the field of vehicle E/E, challenges are not only coming from new types of components, but rather from system-level aspects .
� The complexity of vehicle E/E systems makes system and multi-domain competence indispensible in the R&D.
� Computer-based virtual techniques are essential in the further development of vehicle E/E due to high cost pressure and short
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development of vehicle E/E due to high cost pressure and short development time in the automobile industry.
� The research work on vehicle E/E at ViF covers component modeling, simulation methods development, embedded software design, and system engineering.
Summary
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stands for sustainable research and efficient development to significantly contribute and to co-determine mid- and long-term goals
� ZERO emissions� future drive train concepts, intelligent energy man agement, lightweight, predictive control,
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� future drive train concepts, intelligent energy man agement, lightweight, predictive control, electrification, design of components, friction red uction
� ZERO serious and fatal accidents� passive, active, functional, and HV safety
� ZERO prototype vehicles for development of derivatives� increased predictability of simulation models, mult i-domain simulation, combination of
simulation and hardware components, virtual vehicle development
Thank you for your attention!
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