Chess Review November 21, 2005 Berkeley, CA Edited and presented by Industrial Collaboration: Automotive Electronics Alberto Sangiovanni-Vincentelli UC.

Chess ReviewNovember 21, 2005Berkeley, CA

Edited and presented by

Industrial Collaboration:Automotive Electronics

Alberto Sangiovanni-VincentelliUC Berkeley

Chess Review, Nov. 21, 2005"Automotive Electronics", ASV 2

Automotive Collaborations

• General Motors (ASV)– Architecture Exploration Using Metropolis– FlexRay Scheduling– Cost Metrics

• Toyota (K. Hedrick, E. Lee)– Cold Start Engine Controller

• Pirelli (ASV)– Smart Tire

• Daimler-Chrysler (all)– Embedded Software design


ABS: Antilock Brake SystemACC: Adaptive Cruise ControlBCM: Body Control ModuleDoD: Displacement On DemandECS: Electronics, Controls, and Software

EGR: Exhaust Gas Recirculation.GDI: Gas Direct InjectionOBD: Onboard DiagnosticsTCC: Torque Converter ClutchPT: Powertrain

Valu

e f

rom

Ele

ctr

on

ics &

S

oft

ware

-More functions & features-Less hardware-Faster

Forefront of Innovation

Vehicle Integration

System Connection

Subsystem Controls & Features

Potential inflection point. Now! Hybrid PT Hybrid PT

Electric IgnitionElectric Ignition

ACCACC

Rear Vision Rear Vision

Passive Entry

Passive Entry Side

AirbagsSide

Airbags

Fuel CellFuel Cell

Wheel Motor Wheel Motor

……

OnStarOnStar

OBD IIOBD II

HI Spd DataHI Spd Data

Rear aud/vidRear

aud/vidCDsCDs

BCMBCM

ABS

ABS

TCCTCC

EGREGR

Electric FanElectric Fan

Head AirbagsHead

Airbags......

Electric BrakeElectric Brake

DoD DoD

GDIGDI

……

… …

… …

… … … …

… …

1970s 1980s 1990s 2000s 2010s 2020s

Electronics, Controls & Software is shifting the basis of competition in vehicles

$11

82

$

11

82

(+

196

%)

(+1

96

%)

$11

82

$

11

82

(+

196

%)

(+1

96

%)

50 E

CU

s

(+1

50

%)

50 E

CU

s

(+1

50

%)

100

M L

ines o

f C

od

e (+

990

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)

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00

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ines o

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od

e (+

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)

$40

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20 E

CU

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1M

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es

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Lin

es

1M

Lin

es

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Lin

es

Software $Other $ Electronics $ Software $Other $

Mechanical $Mechanical $

Electronics $

AVG. AVG.

Source: Matt Tsien, GM


Specification

Analysis

Dev

elo

pm

ent

Pro

cess

BusesBusesMatlab

CPUs Buses OperatingSystems

Behavior Components Virtual Architectural Components

C-Code IPs

ASCET

ECU-1ECU-1 ECU-2ECU-2

ECU-3ECU-3BusBus

f1f1 f2f2

f3f3

System Behavior System Architecture

Mapping

Performance Analysis

Refinement

Evaluation ofArchitectural

and Partitioning Alternatives

Implementation

Metro: Separation of Concerns


ECU 1

CAN Bus

ECU n…...

Architecture Model: Abstraction Levels

SwTask 1

SwTask i

Middle-ware

OSEK RTOS/CPU

CAN Driver

CAN Controller

…...

(To CAN Bus)

Cpu/Rtos Medium

OSEK RTOSScheduler

Interrupt Handler

(Interrupt requests from devices)

(From Middleware)

(To CAN Driver)

CAN Driver

Sender

CAN Driver Medium

CAN Driver

Receiver

(To CAN Controller)

(To Middleware)

Bus Sender

Bus Receiver

(To CAN Bus)

(Interruption Request to

CPU)

send

receive

(From CAN Driver)


Matching Models of Computation

• The functional and architectural models should be described using the same model of computation

• Architecture Characteristics:– Network of processes connected by

point-to-point FIFOs– Non-blocking reads and writes– Messages may be lost or duplicated

within FIFO• Functional Model

– Functional blocks operate concurrently• Single rate• No synchronization across processes

– Non-blocking read, non-blocking write communication semantics

• Mapping: intersection of behaviors– Before mapping, nondeterministic loss

and/or duplication of messages in functional model

– After mapping, functional loss/duplication follows architecture

f1 f2

Nondeterministic Medium

Process Process

Functional Model


Results

• With 2 send buffers: 1. No priority inversion

2. Average message latency = 4.165ms

• With 1 send buffer: 1. Priority inversion: Message 7 < Message 1~62. Average message latency

= 4.936ms

Message Latencysent from Supervisor ECU

01234567

1 2 3 4 5 6 7 8 9 10

Message

End

-to-

end

Late

ncy

(ms

) 1 Send Buffer

2 Send Buffers

• Functional Model– 14

functional processes

– 48 signals

• CAN controller configurations:– Number of

send buffers

• Metric– Message

End-to-end Latency








Project Background and Motivation

• GM has decided to choose FlexRay as the future communication system

• Importance of deciding the Communication Cycle Length, Slot Size and Slot Order in the FlexRay based system design.

• There is currently no technique to determine these parameters for FlexRay.

• Scheduling is currently done manually in GM, which is time consuming and error prone.

• Need an incremental scheduling tool for FlexRay system which supports any form of automated bus/task schedule


FlexRay Timing Hierarchy

Application Cycle NApp Cycle N-1 App Cycle N+1

Communication Cycle XComm Cyc X-1 Comm Cyc X+1

STATIC SEG DYNAMIC SEG SYMBOL WIN NIT

... 1 ...

STATIC SLOT

2 3 4 5 6 7 8 9 10 11 12 13 14 15

ACTION POINT OFFSET

FRAME ID CHANNEL IDLE

SLOT YSLOT Y-1 SLOT Y+1

Header Segment Payload Segment Trailer Segment

FlexRay Frame 5+(0 … 254) + 3 bytes

Source: FlexRay Specification 2.1


FlexRay Message Passing Mechanism

1 2 3 4 5 6 7... 1 2 3 4 5 6 7 ...

T1 T3 T4s1

T2

s2

T5

@ FlexRay Controller

OSEK Kernel

Middleware

Application Software

Host

ECU 1

T1 T4

T2

@ FlexRay Controller

OSEK Kernel

Middleware

Application Software

Host

ECU 2

T3

T5

s1

s1

s2

s2

s1s2


Comparison for scheduling

In Traditional Schedule:

Incremental changes impossible without full rescheduling

In Optimized Schedule:

A lot more porosity to accommodate new tasks and messages


Scheduling Tool Framework

AETM-DB (XML)

convert

FlexRay communicationSystem design tool-Graphical Design Front End

Internal Data Structure

Scheduling Engine

AETM-DB1 (XML)

Back-annotate

Gant Graph SchedulingResult Display








Toyota: Coldstart Engine Controller Design(C. Zavala and K. Hedrick)

• Objectives:– Minimize the HC emissions of

cold-start – Reduce design-to-

implementation controller cycle time.

• Challenges– Sensors not active, poor

combustion, keep development cost low.

• Strategies– Design of AFR and HC

observers, use of design of automated tools, use of modern controller design techniques Experimental facilities


Transmission Control

Goal:• Improve drivability and fuel

efficiency by automotive control.

Approach:• Utilize dynamical model-based

analysis and controller design.

Control Strategy: • Multi-tiered approach to achieve

shock-free gear shifting by smooth gear shifting control with engine/AT collaboration balancing between fuel economy & performance by optimal shift pattern scheduling

Prospected control structure for intelligent shifting

Smooth Gear Shifting Control

Gas Pedal

Brake Pedal

Vehicle Speed

Optimal Shift Pattern Scheduling

Human Driver Model &Driving Conditions Identification

Optimal Engine Torque Profile

Optimal AT Friction Elements Torque Profiles

Determine

Driver’s Intentions &

Driving Condition in Real Time


Hybrid Systems Modeling

Objectives• Hybrid System Analysis: study of

a general semantics for simulator engines to execute hybrid system models.

• Study of representations of discontinuities and interactions between continuous-time dynamics and simultaneous discrete events

• The code generation project aims to produce application code automatically from graphical models in Ptolemy II

If an outgoing guard is true upon entering a state, because of the triggering semantics of transitions, the time spent in that

state is identically zero. This state is called a ¡°transient state¡±.

Chess Review November 21, 2005 Berkeley, CA Edited and presented by Industrial Collaboration: Automotive Electronics Alberto Sangiovanni-Vincentelli UC.

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