International Automotive Research Centre
ELECTRICAL PROJECTS
Ross McMurran - Project Manager
Peter Jones- Principal Investigator
Mark Amor-Segan – Principal Engineer
Gunny Dhadyalla – Principal Engineer
© 2007
University of
Warwick
International Automotive Research Centre:
Motivation behind Electrical Projects
The vast majority of new technology looks like this…..
Function
Growth
Processor
Actuator
Sensor
Software
Lanekeeping
Rear Multi- ISG
media Satellite
Typical Premium Architecture (Current Generation)
Remote
Diagnostics
In Car PC
Radio
El. Water
Adaptive
Pump
Auto wipers Headlamps
EM Valves
Surround ACC
IVDC
Sound
Auto lights
Adaptive
suspension
ECU
Telematics
PTC Heater
Optical Buses
Navigation
E-Connectivity
Steer-byWire
Active
steering
Security
Voice Activation
Adv.
ABS
Body Elec.
Blind Spot
Restraints
Airbag
Instruments
Keyless Detection
ESP
Engine Control
Transmission Control
EPAS
Vehicle
Bus
1980
1990
2000
© 2007
University of
Warwick
Your Project Title Goes Here …….
2010
Brake-byWire
Fuel Cell
CY
2
Automotive Electronics Complexity Issues
Typical Premium Architecture (Current Generation)
As “Systems of Systems” become more
complex it becomes harder to:

Specify and implement what is required
ECU
Bus

Predict behaviour (Emergent properties)

Verify complete SoS or sub-systems in
isolation

Plan delivery and manage change

Diagnose faults

Maintain delivery skills at pace of technology
evolution
Key
Areas of
Research
© 2007
University of
Warwick
Your Project Title Goes Here …….
3
PARD1 PROJECTS:
Electrical Test for Advanced Architectures
Software Integration
HMI Assessment Methodology
Environmental Condition Recognition
Status: Completed Feb 07
© 2007
University of
Warwick
PARD1 Completed Project:
Electrical Test for Advanced Architectures
inputs
system
outputs
model
model of
normal
system
model of
unknown
system
Model Based
Diagnostics
Manufacturing Test
Validation with HIL
compare
fault detection
& diagnosis
Architecture
Team
EBS Function
Owner
EBS Model Developer
(Typically Function
Owner)
Model
Reviewer
EBS Vital Team
EBS Supplier
New Project
Determine what models are Required
What I/O of models is required
Develop High Level Requirements
(May be contained directly in model)
Communicate Functional Requirements
Communicate I/O Requirements
Develop Core Stateflow Models
using Generic I/O
not application specific
Process
Mapping
& RADS
Stage 1 Model Review (I/O)
Test Core Model
Functionality
Stage 2 Model Review (Structure)
Core Models Complete
Develop I/O Model
Application specific I/O
to core model
Develop
SAL Spec.
Stage 1 Model Review (I/O)
Stage 2 Model Review (Structure)
Release SAL (Signal Abstraction Layer) Specification to VITAL Team
Integrate
ConstructSAL
SALModel
Model
toinVITAL
platform
Simulink
Model Update
Stage 3 Model Review (Complete)
Post M1 DJ
Release of Models to VITAL Team
Model Based Testing
Basic Interactive Test
Power mode etc.
Proveout Test
Proveout Test Review
Not OK
OK
Automated DV
Automated DV Test Review
Not OK
Bayesian
Diagnostics
OK
Release Models & SAL to Supplier
Autocode
from models
Supplier Update
Integrate to ECU &
Platform software
Component
Based Testing
Release ECU
Basic Interactive Test
Power mode etc.
Proveout Test
Not OK
Model
Proveout Test Review
NOT OK
Supplier
OK
Automated DV
Automated DV Test Review
Not OK
Model
© 2007
University of
Warwick
NOT OK
Supplier
OK
Trigger, either event or time based
KEY:
OEM
Role
Supplier
Role
Activity
Validation Activity
Role that drives an interaction
Role that is involved in an interaction
Your Project Title Goes Here …….
5
Handcode low
level code
from SAL
PARD1 Completed Project:
Software Integration Project
Intelligent Software
Planning
Agile Development Methods
Current Process - Sequential (V-Model)
V-Model
Testing
Requirements
Integration
Risk
Specification
Agile
Coding
Potential Agile Process - Iterative Feature Driven
Requirements
Feature
Next iteration
List
Feature List
Time
Completion
Development Iteration Timeline
Weekly update
2-6 wks
Testing
Cycle
Coding
1
24
Planning Meeting
Development
Integration / Test
3
Integration
0
Formal
Verification
Methods
days
7
14
21
Design
Correct?
Requirements

28
SysML for Improved
Requirements
© 2007
University of
Warwick
Your Project Title Goes Here …….
6
PARD1 Completed Project:
Environmental Condition Recognition
13
14
15
16
17
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
r
r
r
b
r
b
r
r
r
g
g
b
g
g
b
r
g
g
g
r
b
r
r
b
r
r
b
g
b
r
b
b
b
r
g
g
r
g
g
r
r
g
b
dhadya_g:
Monitor rapid
change in
temperature
(thermal
shock)
b
b
r
b
r
r
b
b
r
r
g
r
b
b
b
g
dhadya_g:
Use ground
clearance to surface
as indication of
submersion.
r
g
r
g
r
g
dhadya_g:
These are the total number
of incidences of high rating
dhadya_g:
These are the total number
of incidences of medium
rating
g
?
b
b
dhadya_g:
These are the total number
of incidences of low rating
2
1
1
4
g
r
g
g
r
g
r
dhadya_g:
Roof rack wind
noise. Internal
acoustic
characteristic
changes
b
4
2
2
8
2
5
Audio
ABS
AIR_SUS (Air SUSpension controller)
Centre differential control
Rear differential control
TCU (Transmission Control Unit)
Gear selection
EMS (Engine Management System)
Combustion management
Emission control
SCS (Slip Control System )
Is this just ABS or
different?
IPK (Instrument PacK)
Driver information
Warnings
2
0
1
5
0
3
2
3
5
0
r
dhadya_g:
Monitor turbulance
20
2
0
2
45
4
3
0
13
1
0
4
11
1
b
r
r
b
b
r
r
b
r
r
b
g
g
g
r
r
r
g
g
10
1
0
1
b
11
1
0
2
b
r
r
g
g
g
g
b
0
1
27
3
0
0
28
2
3
1
25
2
2
1
25
2
2
1
r
r
r
36
4
0
0
g
g
g
18
1
3
0
r
b
12
1
0
3
g
r
45
3
6
0
r
12
1
1
0
27
3
0
0
b
b
b
r
g
b
0
2
g
r
b
1
2
r
g
g
9
25
g
r
b
1
r
r
b
2
3
12
g
g
r
0
0
b
r
r
r
b
g
0
0
0
0
12
1
1
0
12
1
0
3
7
0
2
1
15
1
1
3
0
0
0
0
0
0
Sensor Technology
0
0
0
0
0
0
0
Wet Grass
Mud
Deep Soft Sand Boulders
Water (wading) Ruts
Articulation
Inclines
Towing
dhadya_g:
Check to see if there has
been any research in to
measuring wetness, may
be also tyre
high relevance
medium relevance
low relevance
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Sensor System 8:
INFRA RED
Temperature Sensor
55
0
0
Sensor System 7:
GeneralTemperature
Sensor
Gravel Road
…
Rough Tracks
…
…
…
…
Sensor System 11:
Fog Sensor
54
0
Sensor System 10:
Rain Sensor
Environmental Condition
Cost
Suitability to
automotive
Availability
Visual - colour
Visual - Contrast
Visual - Intensity
Visual Reflectivity
Brake control
Transfer box - Hi-Lo ratio
control
2
0
19
48
4
r
Entertainment audio
volume control etc.
DLCR (Drive Line Controller – Centre / Rear
differential)
2
1
1
b
g
Engine Control through
engine torque
Vehicle speed control
(e.g. boulder crawl)
DLCT (Drive Line Controller) Transfer case
2
2
45
b
r
Environmental Condition
vs.
Control Application
Ride height
Load levelling
26
21
24
r
g
Attribute Cue
Control Application / System
ECM (Engine Control Module)
1
2
44
83
Sensor System 3:
INFRA RED SENSOR
at front
Traction control through
brake and throttle
intervention
6
1
g
Sensor System 4:
INFRA RED SENSOR
at back
TCM (Traction Control Module)
3
5
b
Sensor System 2:
CAMERA attached
with wheel
Short range proximity
detection
2
4
46
50
g
Sensor System 1:
General CAMERA
PAM
4
4
g
r
b
59
AFS Adaptive Front lighting
2
4
0
58
Lighting mode
Beam direction
(cornering)
Auto headlamp levelling
32
52
0
57
ACC Automatic Cruise Control
4
1
4
2
3
50
56
Speed Conrol
Headway Control
0
4
4
7
5
53
Terrain Optimisation
5
2
4
49
52
Ice
1
34
49
Environmental Condition vs. Attribute Cue
51
Function
24
34
48
Mapping Control Application Against Environmental Condition to identify feature enhancements
AS
77
b
r
r
AR
52
r
?
b
AQ
g
r
b
AP
g
b
r
AO
Total score is calculated by
rating
high correlation=9,
medium correlation=3
low correlation=1 and
summing the total scores
r
b
AN
Total low correlation
AM
…
Speed
AL
Total score
AK
Total High correlation
AJ
g
r
g
r
AI
r
b
g
r
r
AH
r
b
r
r
AG
r
r
r
r
AF
g
r
g
AE
r
r
r
b
r
r
g
b
r
b
r
r
g
g
b
g
r
dhadya_g:
Does wading
change weigth of
car (buoyancy)?
r
AD
Towbar/towball forces
g
AC
dhadya_g:
Check to see if there has
been any research in to
measuring wetness, may
be also tyre
Predictive Data
b
AB
Wetness
Air direction
AA
Ground Clearance
Z
Cartographic data
Flow Rate (Water)
Depth (water)
Y
g
r
g
r
X
Attribute cue
?
b
b
W
dhadya_g:
Characteristics of
submerged ultrasonic
sensor (parking aid)
could lead to info. Also
if one or more sensor is
submerged gives
confidence level.
r
g
V
Air speed
Proximity
Weight
?
g
r
U
?
r
r
T
Air pressure
g
S
dhadya_g:
Check to see if there is any
data that supports aire
pressure as an indication fo
particular weather conditions.
Fiction
b
b
g
b
Temperature
?
r
b
Humidity
g
b
R
Historic data
r
Q
Smell
g
P
g
g
r
b
O
Vehicle accellerations/
torques/forces
g
Visual - Light Intensity
Visual - colour
Visual - Contrast
r
g
N
Sensor System 5:
INFRA RED SENSOR 3
12
g
M
Visual - Pattern
Visual - Light
Intensity
Visual - visibility
(fog)
Surface adhesion
Attribute Cue
vs.
Sensor Technology
Audible - volume
Audible frequency
Audible
Pattern/characteri
stic
Temperature
Humidity
Smell
Vehicle
accellerations/
torques/forces
Proximity
© 2007
University of
Warwick
Your Project Title Goes Here …….
8
Sensor System 12:
MOS Based Gas
Sensor
11
g
r
L
Sensor System 9:
Humidity Sensor
9
r
K
Sensor System 6:
Integrated
WEATHERSTATION
8
10
Rain
swamp
Wet roads
Snow
Ice
Gravel Road
Rough Tracks
Wet Grass
Mud
Deep Soft Sand
Boulders
Water (wading)
Ruts
Inclines
Towing
Vehicle Loads & Distribution
Fog
Light Intensity- darkness
Light Intensity- brightness (sunlight)
Snow falling
Wind speed
Wind direction
Humidity
Altitude
Barometric Pressure
Absolute position
Speed over ground
Temperature
Pitch
Heave
Roll
Longitudinal accell
Lateral Acelleration
Yaw
Surface type
Road Geometry
Traffic Environment Sensing
- Blind spot/parking
Relative position
Road class
Tyre condition (pressure/wear)
Tyre type
Air quality
I
J
dhadya_g:
Pattern recognition could
be looking back at the
pattern the wheels have
left behind analysing
Tyre deflection
7
Visual - Pattern
6
Visual - Reflectivity
4
5
H
Interesting to see if
there are different
reflectivity
characteristics between
Audible - volume
F dhadya_g:
G
Audible - frequency
D
Audible
Pattern/characteristic
C
Visual - visibility (fog)
B
Surface adhesion
A
3
Total Medium
correlation
Recognising environmental conditions to enable
adaptive control and feature enhancement
PARD ELECTRICAL PROJECT
EXTENSION:
HIL Technology Migration
HMI Development Tools Integration
Electrical Training
Diagnostics
Software Planning
Status: March 07 to March 08
© 2007
University of
Warwick
Electrical IMDS Training – Background
Breadth of knowledge
Knowledge Gap
Project Engineers/
Technical Project Mgrs/
Trouble-shooters
Broad understanding
of a number of fields
ELECTRICAL
MODULAR
TRAINING
Tranche 1
Automotive Networking
Automotive Diagnostics
Technical Specialists
/Experts
Electrical Test Techniques
Deep
Understanding
• High level of practical ‘hands-on’
content
of
particular
fields but
• Tailored to application context
few in number
• Subject Matter Experts – for content & lecturing
• Post Module Assignment
Technical Specialists
/Experts
Deep Understanding
of particular fields but
few in number
Depth of knowledge
© 2007
University of
Warwick
Your Project Title Goes Here …….
10
EVoCS Project
Evolutionary Validation of Complex
Systems
Status: Current 2006-2010
© 2007
University of
Warwick
EVoCS Project
Evolutionary Validation of Complex Systems
Complex Systems of Systems
Super System

A System of Systems (SoS) is composed of parts
which:
e.g. Broadcast, Manufacturing & Service systems, Interfaces with
Consumer devices, Intelligent Transportation Systems


System of Systems
i.e. Vehicle Electrical System
System
have individual goals and a level of autonomy
are linked to achieve a higher level purpose or to share
resources e.g. information, interfaces etc.
e.g. Infotainment System
Sub-System
e.g. FM Radio
Component
As SoS become more complex it becomes harder:
e.g. Radio Receiver


to predict behaviour (Emergent properties)
to verify complete SoS or sub-systems in isolation
Project Objectives
To maximise confidence in the design and implementation
of complex automotive electrical systems through:
Innovative techniques for the validation of the design at a
System of Systems level

Typical Premium Architecture (Current Generation)
A platform for the validation of the implementation at a Systems
of Systems level
© 2007
University of
Warwick
Formal
Methods
Bus
Project Partners
Project Scope
Automated
Model Based
Testing
ECU
Improved
sub-system
Validation
Static
Analysis
Tools
For further information contact:
ross.mcmurran@warwick.ac.uk
Architectural
Modelling
Compositional
Rules
e.g. Assumption/
commitment
With funding from
THE TECHNOLOGY PROGRAMME
Your Project Title Goes Here …….
12
EVoCS - System of Systems Design Validation
Model Based
Development
Processes
Automated
Model Based
Testing
Typical Premium Architecture (Current Generation)
Test case
generation &
coverage
metrics
© 2007
University of
Warwick

Enhanced
Physical
Modelling
Interaction
Modelling
ECU
Bus
Design for
Robustness
Formal
Methods for
Dependability
Static Code
Analysis
Tools
Your Project Title Goes Here …….
13
EVoCS - System of Systems Validation Platforms
Next
Generation
HIL Tests
Flexible HIL
Platform
Platforms for
full vehicle
tests
HMI
Simulation &
Testing
Test
Automation
Validation of
Manufacturing
Systems
Machine
Vision
Robustness
Testing
Low Voltage
Testing
© 2007
University of
Warwick
Your Project Title Goes Here …….
14
Self Healing Vehicle Project
Status: Submission to WIMRC Board June 07
2008 – 2010
Partner interest sought
© 2007
University of
Warwick
Self Healing Vehicle
Background
Increasing complexity and criticality of applications
•
Despite improvements in validation techniques, faults will still get to
market,
•
Electronics & software will fail.
Human-assisted monitoring, maintenance, and intervention
will become prohibitively costly, unacceptably slow, and
sometimes ineffective.
An intelligent vehicle needs to play a more proactive role in
fault management
© 2007
University of
Warwick
Your Project Title Goes Here …….
16
What is a Self Healing Vehicle?
“A vehicle with the ability to:

autonomously predict or detect and diagnose failure conditions,

confirm any given diagnosis,

and perform appropriate corrective intervention(s),
•
including the use of telematics to interact with external service providers
and infrastructures.”
© 2007
University of
Warwick
Your Project Title Goes Here …….
17
Self Healing Vehicle
Concept
Confirmed/Classified
Failure Information
Vehicle Data
Distributed
Vehicle
Electronics
System
Interrogation
commands
Corrective Action
or Intervention
Verification of
Intervention
outcomes
Prognostic
Diagnostic
Monitor
Intelligent
Rectification
Manager
Intervention
Initiator
Failure Details +
Recommended
Intervention
In-vehicle Fault Management System
Diagnostic &
Prognostic
Information,
Data Logging
Remote
Telematics
Support
System
SW Downloads,
Enhancements &
Upgrades to diagnostic
System, Remote
commands.
© 2007
University of
Warwick
Your Project Title Goes Here …….
18
Areas Of Interest For Future Research
Systems Engineering, Model Driven Development &
Validation





Requirements Engineering
Modelling
Formal Methods
Automated Model Based Testing
Auto-coding
Advanced Vehicle Control



Sensing & Data Processing
Vision Systems
Robotics & Autonomous Vehicles
Robust and Fault Tolerant Systems


Design for robustness
Advanced Diagnostics
Telematics

Data Processing for new applications, e.g. Driver Support,
Prognostics, PAYD Insurance
© 2007
University of
Warwick
Your Project Title Goes Here …….
19
End
© 2007
University of
Warwick