Introduction of FlexRay
Chien-Chih(Paul) Chao
Chih-Chiang(Michael) Chang
Instructor: Dr. Ann Gordon-Ross
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Summary
 General Background
 Performance Analysis of FlexRay-based ECU Networks
 Motivations
 Basic framework
 Modeling FlexRay
 Case Study
 Conclusion
 FlexRay Schedule Optimization of the Static Segment
 Background & Introduction
 Motivation
 Problem definition
 Methodology
 Experimental Results
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 Conclusion
General Background
 What is FlexRay?
A next generation automotive network communications protocol.
 When was it released?
First public release(Version 2.0) on Jun 2004.
The latest version 3.0.1 was released on Oct 2010.
 Why uses FlexRay?
1.
2.
3.
4.
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High bandwidth
Flexibility
Fault-tolerance
Reliability
General Background
FlexRay
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Controller Area Network(CAN)
 10Mbps x 2 bandwidth
 Bandwidth up to 1Mbps
 Time-triggered for real-time
 Contention resolved by
transmission
 Event-triggered for lowpriority data
 Synchronous
 Deterministic system design
priority.
 Asynchronous
 Acknowledgment and
retransmission when
message is corrupted
General Background
 Who developed FlexRay?
 Where used FlexRay?
BMW X5 on 2006, BMW 5-Series, BMW 7-Series
Audi A8, Bentley Mulsanne, Rolls-Royce Ghost
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General Background
 How does it work?
 Dual channel - scalable system fault-tolerance
 Bus Guardian
 Interconnect topologies: centralized or bus
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General Background
 Macrotick- the node’s own internal clock or timer.
 Microtick- a cluster wide synchronized clock.
 NIT is stand for Network Idle Time which time corrections.
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Performance Analysis of FlexRaybased ECU Networks
Andrei Hagiescu, Unmesh D. Bordoloi, Samarjit Chakraborty
Department of Computer Science, National University of Singapore
Prahladavaradan Sampath, P. Vignesh V. Ganesan, S. Ramesh
General Motors R&D – India Science Laboratory, Bangalore
Design Automation Conference (DAC) 2007,
San Diego, California, USA
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Motivation
 In a high-end car there are up to 70 electronic control units
(ECUs) exchanging up to 2500 signals.
 Commonly used protocols include CAN, local
interconnection network(LIN).
 Previous implementations of FlexRay using only static
segment, with the dynamic segment being unutilized.
• Dynamic part of protocol is more complex.
• The potential messages for dynamic segment is more irregular.
 Techniques for analyzing the static segment are
known(TDMA scheme).
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FlexRay Communication cycles
 The first cycle T1, T3,T5, T6, and T7 have messages to send.
 The Second cycle T2 have messages to send.
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Difficulties in Modeling FlexRay
 A message cannot straddle two communication cycles.
 Once a task misses in the dynamic segment, it will wait
till the next cycle.
 A task can send at most one message in each dynamic
segment, where the maximum length of the message can
be equal to the length of the dynamic segment.
 One minislot is consumed from the available service when
a task is not ready to transfer a message.
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Modeling FlexRay
 Step 1: Extract k1 minislots of
service during each
communication cycle from l .
 Step 2: Discretize the service
bound obtained from step 1.
 Step 3: The resulting service
bound is shifted by d time units.
 Step 4:A minislot is lost even
when a task does not transmit any
message.
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Modeling FlexRay
 The service available to the lower priority tasks (i.e. T2 …)is
made up of two components
 The service that was unavailable to T1.
 The service that was unutilized by T1.
 The procedure is remaining for the rest tasks.
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Case Study
 Adaptive Cruise Control application.
 Implemented framework using Matlab as a front-end.
 Using Java to handle all the function transformation.
m1
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m2
m3
m4
Results
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Conclusion
 Present a compositional performance model for a
network of ECUs communicating via FlexRay bus.
 Formal model of the protocol governing the dynamic
segment of FlexRay.
 The framework can also be used for deriving the
parameters of the FlexRay protocol.
 Help in resource dimensioning and determining optimal
scheduling policies for multitasking ECUs.
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FlexRay Schedule Optimization of
the Static Segment
Martin Lukasiewycz, Michael Glaß, and Jürgen Teich
University of Erlangen-Nuremberg, Germany
Paul Milbredt
I/EE-81, AUDI AG, German
CODES+ISSS 2009, Grenoble, France
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Quick View
 Presenting a Scheduling Optimization scheme for the
static segment of the FlexRay bus in compliance with the
AUTOSAR specification.
 What is AUTOSAR?
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Background & Introduction
 AUTOSAR
 AUTomotive Open System ARchitecture
 FlexRay
 An Automotive Communication System
 Protocol Data Units (PDUs)
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Background – AUTOSAR
 AUTomotive Open System Architecture
 Open and Standardized automotive software architecture
 Partnership for automotive E/E (Electrics/Electronics)
architectures
 Standardization
 Basic systems functions,
 Scalability to different vehicle
 Transferability throughout the network
 Maintainability throughout the entire product life-cycle
 Etc.
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Background – FlexRay
 Static Segment
 Time-triggered
 Enable a guaranteed real-time transmission of critical data
 Periodic and Safety-critical data
 Reserved slots for deterministic data that arrives at a fixed
period
 Dynamic Segment
 Even-triggered
 For low priority data
 Maintenance and Diagnosis data
 does not require determinism
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Background – FlexRay (Cont.)
 Communication Cycle
5
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
Symbol Window
Typically used for network maintenance and signaling for starting the network.

Network Idle Time
A known "quiet" time used to maintain synchronization between node clocks.
Background – FlexRay – Static Seg.
 Static Segment
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Background – FlexRay – Static Seg.
 Made up of n equally sized slots
 each slots is uniquely assigned to one node
 Node may occupy more than one slot
1
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2
3
Background – FlexRay – Static Seg.
 Each slot: header, trailer, and payload segment
PDU
PDU
PDU
PDU
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PDU
PDU
PDU
PDU
Background – PDUs
 The mechanism for communicating information between
protocols, they are most generally called protocol data units
(PDUs).
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OSI Layer
PDU Name
Application
Data
Presentation
Data
Session
Data
Transport
Segment
Network
Packet
Data Link
Frame
Physical
Bits
Motivation
 To minimize the number of used slots in order to maximize
the utilization of the bus
 Scheduling optimization scheme for the static segment of the
FlexRay bus
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Problem definition
 Scheduling Problem:
 Scheduling Requirements
 the static time-triggered segment
 Why optimization?
 high flexibility for incremental schedule changes
 for future automotive networks with a higher data volume
 fast scheduling techniques are necessary
to allow for an effective parameter exploration
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 AUTOSAR Interface Specification
 cycle multiplexing for a single slot
 maximizes the utilization of the
static segment in compliance with
the high requirements for reliability
and robustness
Methodology
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Methodology
Slot
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Bin
Optimal
Methodology
 Problem Transformation
 Transform the scheduling problem into a special two-
dimensional bin packing problem
 1 slot  1 bin
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Methodology
 Bin Packing
 The Heuristic Approach
 “Fast Greedy Heuristic”
 Better with Unconstrained Problems
 ILP Approach
 Better with Constrained Problems:
 Enhanced ILP
 Mutex Packing
 Add Mutual Exclusion to the bin packing
 Reordering
 For Extensibility of a bin and a slot
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Fast Greedy Heuristic
 “Greedy” implies: Local Optimal
Global Optimal
 To put “elements” into “bins”
 The Order of the elements (by height and weight)
 Allocated new empty bin
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Integer Linear Programming (ILP)
 Placing the elements starting from the highest element to the
most left void space in the bin s at the level l results in a
feasible solution of the bin packing problem.
 Enhanced ILP
 This constraint improves the runtime of the ILP: If the optimal
solution is reached and equals the lower bound, the
optimization process terminates immediately.
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Experimental Results
 Schedule Optimization
 Incremental Scheduling
 Scalability Analysis
 ILP & Heuristic
 Slot Size Exploration
 Supportive Test Case
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Results - Schedule Optimization
 Intel Pentium 4 3.20 GHz machine with 512 MB RAM
 highly heterogeneous in terms of their period and size
 the only approach currently, TTX Plan
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Results - Incremental Scheduling
 In contrast to the ILP approach, the heuristic scheduling
method allows an incremental scheduling.
 An incremental scheduling might be favored if the number of
allocated slots is still not critical since integration tests are
time-consuming and expensive.
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Results – Scalability
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Results - Supportive Test Case
 BMW series 7
 Overall 15 nodes
 91 slots each having a payload of 16 bytes
 237 random PDUs were generated
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Conclusion
 There exists no publication regarding the FlexRay bus
scheduling in compliance with the industrial AUTOSAR
Interface Specification.
 The case study show that the heuristic and ILP approach are
superior to a commercial tool in runtime and quality.
 A supportive case study shows the flexibility and robustness
of the proposed algorithms
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Thank you!
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