Schedule Integration for Flexray

Schedule Integration for Time-Triggered Systems Outline Motivation • Automotive software • Automotive architectures • Integration Challenge Time-triggered automotive systems • Sychronization • Schedule Integration • FlexRay ILP scheduling approach Case study & Scalability Conclusion 2 Example: Adaptive Cruise Control (AUDI AG, ACC) Florian Sagstetter 3 Distributed Control System Speed Adjustment Radar Actuator System Sensor Network Controller Network ACC ECU Florian Sagstetter 4 Delay Requirements Sensor ts Network m1 Controller tc Network m2 Actuator ta τnetwork τnetwork τcontrol Florian Sagstetter 5 Increasing Complexity in Automotive Electronics 400 350 300 250 240 200 175 150 90 100 100 100 50 13 50 1 3 5 0 Memory [MB] ECUs Sources: Paul Milbredt, AUDI AG, EFTA 2010 - Switched FlexRay: Increasing the Effective Bandwidth and Safety of FlexRay Networks BMW Group, FTF 2010 Orlando - Energy Saving Strategies in Future Automotive E/E Architectures Florian Sagstetter 6 Integration Challenge Application: Implementation: Sender Bus Receiver Mapping, Configuration and Schedule Integration: Defined by: • Message • Timing • Deadline Florian Sagstetter 7 Rising Gap between Required and Actual System Complexity TODAY: INTEGRATION CHALLENGE ? Source: The Software Car: Information and Communication Technology (ICT) as an Engine for the Electromobility of the Future – ForTISS GmbH Florian Sagstetter 8 Paradigm Shift Event-triggered Time-triggered systems systems utilization Ethernet (PTP) flexibility predictability (real-time properties (real-time properties are guaranteed) need to be verified) Florian Sagstetter 9 Introduction: Asynchronous vs. Synchronous Jitter, lost/unused data Asynchronous task 1 bus x x task 2 Synchronous task 1 bus task 2 time Florian Sagstetter 10 Vision: Holistic Scheduling for Time Triggered Systems Sender Bus Receiver Sender Ethernet PTP Bus (Backbone) Receiver Gate- way Task level Sender Communication TT- Bus Bus controller Receiver Florian Sagstetter 11 Related Work: Global Scheduling • Schedule Optimization of Time-Triggered Systems Communicating Over the FlexRay Static Segment H. Zeng, M. Di Natale, A. Ghosal, and A. Sangiovanni-Vincentelli. IEEE Transactions on Industrial Informatics, 7(1):1–17, 2011. • Modular Scheduling of Distributed Hetero- geneous Time-Triggered Automotive Systems. M. Lukasiewycz, R. Schneider, D. Goswami, and S. Chakraborty. In Proceedings of ASPDAC 2012, pages 665–670, 2012. Florian Sagstetter 12 Schedule Integration approach Cluster Schedules: Sender Sender Sender Bus Bus Bus Receiver Receiver Receiver Integration: Sender Bus Receiver Florian Sagstetter 13 Degrees of Freedom Sender Schedules: Bus Receiver Sender Sender Bus Bus Receiver Receiver Global Schedule: Sender Bus x x Receiver Florian Sagstetter 14 Introduction to FlexRay 3.0 Release of version 3.0, Presentation: “FlexRay – Past Present Disbandment of Future Perfect” - Christopher Temple consortium Foundation of FlexRay Consortium Used in active damping (more than 100 members by 2005) system of BMW X5 2000 2005 2006 2008 2010 future ISO standard in preparation Release of version 2.1, Fully introduced with the current industry BMW 7 series standard 2.1 BMW 7-series Florian Sagstetter 15 FlexRay Protocol (Static Segment) … CC0 (Communication Cycle) CC1 CCC Dynamic Symbol Network Static Segment Segment Window Idle Time Static Static … Static Slot 1 Slot 2 Slot n Florian Sagstetter 16 Schedule Integration for FlexRay CC0 CC1 CC2 CC3 … CCC Static Static Static Static Segment Segment Segment Segment x x+1 x+2 x x+1 x+2 x x+1 x+2 x x+1 x+2 Florian Sagstetter 17 ILP-based Schedule Integration Approach Only occupy static FlexRay segment Each static slot is only occupied once Search Space Reduction: Filter Offsets: Cycle Breaking: Florian Sagstetter 18 Case Study cluster ECUs frames repetition variance body 2 9 2,4 3-217 chassis 3 12 2,4 0-85 information 2 11 4,8 9-278 electric 3 10 1,2 0-55 total 10 42 1,2,4,8 0-278 • Utilization of FlexRay bus: 29% • Feasible schedule for FlexRay 2.1 in 163ms (Xeon 3.2GHz Quadcore,12GB RAM) • ILP formulation of 5207 variables and 146926 constraints • Feasible schedule for FlexRay 3.0 in 208ms • ILP formulation of 14895 variables and 1070730 constraints Florian Sagstetter 19 Scalability Analysis with 5400 Synthetic Test Cases Florian Sagstetter 20 Conclusion • Automotive functions benefit from a synchronous schedule • Concurrent scheduling of ECUs and buses necessary • Concurrent scheduling allows reduction of integration efforts • ILP based scheduling Florian Sagstetter 21 .

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