Elektronik: zu viel des Guten? - Steiermark · Elektronik: zu viel des Guten? 2012-06-21 Open...

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


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


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:


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


• Outlook: A Glance at the future• Summary

Example: Infotainment – a highly networked system


Source: Audi AG

Example: Infotainment

PlayerDVD

Entertainment

Telefon

Information


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


Model range VariantsSource: Audi AG

Complexity driven by global market


Source: Audi AG

Automotive electronics 2012


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.


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


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


• 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


Source: Oliver Wyman, Car Innovations 2015

Automotive electronics

Major share of innovations driven by electronics an d embedded software.



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)


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


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


(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”


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”



Mechanics

Source: Daimler


Mechanics


Electrics /

Source: Daimler


MechanicsElectrics / Electronics

Source : VW Käfer, Volkswagen, 1960


MechanicsEmbedded Software

Source : DaimlerSource : Bosch


Electrics / Electronics














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


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


CO2 reduction

Clean ICE


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


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


• 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• …


Technical

Requirements

…Risk Assessment

Functional Safety

Item definition

…

FMEAFTA


Engineering data backbone

Technical Architecture

Model (Simulation-Validation)

Functional Architecture Metamodel

(System)

e.g. MATLABUML-based


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


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


Source: http://e-vectoorc.eu/

Future vehicle

Source: http://www.crashstuff.com/

Motivation: Emergence of megacities



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.


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


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




• 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


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


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


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


Source: McKinsey & Company, Perspective on EV batteries, 2010

EV, PHEV battery packs

LG Chem, Compact Power, Inc


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



• Optimal design von electrodes, geometries,…

• Investigation of manufacturing effects

…

SimulationSimulation

Crash

Temperature

CurrentElectro -

Different models for different applications

Empiricalmodels Thermal models

Mechanical models


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

ηαηαααααα

max,

psnlns iii ,, Φ∇−=−= σ ( ) ll

ll ctc

f

F

RTti ln1

ln

ln1

2)( 0 ∇−

∂∂++Φ∇−= +

±κκ

vcc

c

RT

Di

Fz

tN iec

Ti

i

ii +∇−= µε

νν

0

∂∂

∂∂=

∂∂

r

crD

rrt

c ss

s 22

1

∇−−+

∇

−∇=

∂∂

++++

+ 00

0 1

ln

ln1 t

Fz

iaj

tc

cd

cdD

t

c lnl

lll

ll

ννεε

RNt

ci

i +−∇=∂∂ε

li

ni

n inF

si

nF

asaj ∇−=−=

Parameterisation


Flir A40

Simulation

Flir A40

Simulation


Flir A40

Simulation

Flir A40

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


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


Cycling ageing

Calendaric ageing

Deviation between cells

Pulse timeDischarge

currentCharge current

Calendar time

SOC

Celltemperature

∆ Mechanicalstress

Cell ageing and battery management

DOD


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


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


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


Outline


• Vehicular battery modeling• Functional and vehicle safety• Model library based system simulation• Vehicle electrification and power net




Integrated

Safety

FunctionalHigh voltage

HV battery ISO 26262Embedded systems

Automotive electronics and safety


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


Source: IEEE In-Vehicle Networks, 2010

Brief introduction to integrated vehicle safety

?2s ?100ms?2s ?100ms~2s ~100ms


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


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


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)


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


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


Outline


• Vehicular battery modeling• Functional and vehicle safety• Model library based system simulation




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


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


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


DrivetrainDrivetrain storageMotor Package Controller

� Co-Simulation representation

Outline


• Vehicular battery modeling• Functional and vehicle safety• Model library based system simulation




Outline


• Vehicular battery modeling• Functional safety• Model library based system simulation



• 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


Power & energy demand of future vehicle


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


“high” configuration, TODAY

“high” configuration , FUTURE

2: E-vehicle


Power & energy demand of future vehicle


110

100

1 10 100 1000 10000 100000

P nom [W]Quelle: L.Brabetz, „Energieeffiziente Bordnetzarchitekturen“,

VDE Kongress Elektromobilität, 2010

Outline


• Vehicular battery modeling• Functional safety• Model library based system simulation• Vehicle electrification and power net




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


� 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


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

VIRTUAL VEHICLE

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,


� 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!


Elektronik: zu viel des Guten? - Steiermark · Elektronik: zu viel des Guten? 2012-06-21 Open...

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