Virtualization as key for efficient development of embedded automotive systems

Transcription

1 Symposium on Automotive Embedded Systems Development Yokohama, Oct 9 th, 2015 Virtualization as key for efficient development of embedded automotive systems Chances and challenges of XiL Dr. Tobias Kreuzinger, Senior Manager Test & Validation, ETAS K.K. 1

2 Agenda Agenda 1 Challenges in test and validation of ECU software 2 Today s development style 3 Virtualization as enabler for efficient validation 4 Chances and Challenges of XiL 5 Summary 2

4 Rapid increase of system complexity Automotive trends drive complexity Rapidly increasing costs for internal development and external resources Engine Management Transmission Management Consumption and emission requirements AUTOSAR Interface AUTOSAR-RTE Basic Software Module (BSM) Microcontroller Abstraction ECU Hardware SW- Component 1 SW- Component 2 AUTOSAR Interface SW- Component 3 AUTOSAR Interface New layered standard architecture Shorter innovation cycles Number of labels Degree of freedom Calibration effort Engine control complexity Vehicle Motion Management Brake Management Battery Management Increased interdomain connectivity New functions and variants 4

5 Challenges in validation How to ensure comprehensive validation under a large variety of possible driving scenarios? Traffic City Extreme conditions Country road Highway Mountain road 5

6 Statements from European OEM of development time no real prototypes are available of engineers get evaluation experience in the global vehicle 6

7 Distributed development requires validation alternatives Geographically distributed co-development between OEM and suppliers further limits hardware-based software validation due to TIER2 Software Lorem Models2 Hardware TIER1 Integration of Components OEM System Integration time-intensive and costly ECU prototype transportation 7

9 Today: Hardware-based validation only in late development stages Feedback loops in the standard V-model Design Integrate System & ECU network Specification, design & implementation Extreme lead time Integration, validation and calibration Correct Validate Sub-system & ECU network ECU Function / Composition Very long lead time Long reaction time 60% of development time no prototypes available Unit / Component require often costly hardware prototypes for validation purposes result in long lead times through late validation 10% Only of engineers get access to real car 9

10 Tier 1 OEM Efficient development of embedded automotive systems Development and maintenance cycles in OEM and Tiers Long and costly feedback loops in the standard V-model Development cycles to improve control model Plant modeling based on real engine data Mass production Correct Validate Integrate Design Trouble at the market Maintenance cycles for after market 10

11 Rectification Cost Factor Efficient development of embedded automotive systems Test and validation as major software development cost driver Test and validation significantly impact ECU software development costs Empirical rule of 10 The costs of rectifying a fault, increase by a factor of 10 with every passed phase before it is detected. 40% of software engineering costs are attributed to test and validation 10,000 8,000 6,000 4,000 Ref: GM 2,000 - Requirement Design Implementation Validation Production Product Engineering Phase Target: Early error identification and elimination through frontloading 11

13 Virtualization as enabler for efficient validation Solution approach Virtualization Frontloading through early execution of debugging, validation, verification and calibration without complete target hardware being available. Object under test and its environment can be simulated through different phases of the V-cycle. Target is to increase development efficiency by reducing development and reaction time reducing development costs increasing quality 13

14 From HiL (Hardware-in-the-Loop) to XiL (X-in-the-Loop) OR EMS MCU BMS TCU Engine E-motor Battery pack Transmission (Configuration example) (Real-time) simulation Real ECU Soft ECU for rest-bus simulation or full Virtual ECU 14

15 Customer reference Full Vehicle Simulator, Asian OEM, Passenger Cars, 15 ECUs Customer need: Integration of ECUs from different Tier1s to verify distributed functions, communication, and diagnostics Scalable solution to maximize utilization along all vehicle families, also to be used for component test Solution: Switching between Soft-ECUs for rest-bus simulation and real ECUs Integration of plant-models of different simulation tools (SimulationX, AVL-Cruise, ETAS/Simulink) Error-safe and convenient variant handling Test process consulting 15

16 FMU = Functional Mockup Unit Efficient development of embedded automotive systems MiL / SiL / HiL system integration platform architecture MiL: Closed-loop simulation of control and plant models on Windows PC SiL: Virtual ECUs can be integrated replacing control models HiL: Real ECUs can be integrated replacing virtual ECUs Plant/ Control FiL/HiL FMU connector Communication layer Integration & simulation platform with visualization & automation MiL SiL HiL Virtual ECU Real ECU COSYM 16

17 The XiL-mapping in the V-model 17

19 Virtualization as enabler for efficient validation Enable earlier feedback loops on all integration levels System & ECU network Specification, design & implementation Virtual integration, validation and calibration Integration, validation and calibration Correct Validate Integrate Design Sub-system & ECU network ECU Software Module through model-based design as well as virtual validation and pre-calibration Benefits Detect defects as early as possible Reduce overall test, validation, and calibration costs Reach better testcoverage Simplify exchange of development artefacts btw. OEMs and Tiers 19

20 So what s the problem? Lack of compatibility between tools and development artifacts Plant-Models Coding (Interfaces/Structure) Test Automation Programming Tools & Compilers Test Systems cause huge manual overhead for migration, refactoring, and assuring consistency 20

21 Standardization ETAS bets on three important standards to enable systems virtualization: AUTOSAR enables virtualization of the ECU and easy exchange of Software artefacts Standard for model exchange and co-simulation of simulation models via FMI* Re-use of test cases by decoupling test automation software from the test system. (ASAM XiL) FMI: functional mockup interface 21

22 Virtualization as enabler for efficient validation With standards, truly seamless virtual validation is possible, System & ECU network Specification, design & implementation Sub-system & ECU network Test-case Virtual integration, validation database and calibration Test Automation Tool Integration, validation and calibration Correct Validate Integrate Design ECU Software Module i.e. reuse of tools, models, and test-cases of each stage without manual efforts 23

23 Other challenges ahead Availability of the right data and the right models remains a challenge Availability of data for parameterization of models prototypes are only available in late development phases accessibility of crucial quantities accuracy of data right measurement equipment Selection of the right plant model: MiL through HiL variable step solver vs. fixed step solver (real-time capability) physical vs. mathematical/data-based required computation power use-case for the model and required complexity, accuracy, and validity 24

24 Model Accuracy = Costs / Effort Efficient development of embedded automotive systems Levels of plant-model complexity 5 Calibration Function Calibration Environment Ultra high fidelity models for calibration, also for complex sub-systems (e.g. exhaust, combustion) 4 Performance 3 - Functional High end performance testing Quantitatively correct model behavior Test-bench data for parameterization of models Extended Vehicle Functionality Qualitatively correct model over wide operation range Parameterization based on physics and vehicle key data 2 - Standard Basic Vehicle Functionality Basic Closed-Loop setup (main control loops) Adequate vehicle acceleration behavior (steady state) 1 - Basic Hardware Emulation for I/O Test Open-Loop stimuli from basic vehicle driving behavior 25

25 Challenges of virtualization The Break-Even for Virtualization Cost/ Effort Plant Model Prototype Break-Even How to increase the ratio of virtualization? Modularity and re-use of component or sub-system models over several development cycles Verified and validated models for a wide operating range 1 Basic 2 Standard 3 Functional 85% of tests 4 System Readiness 5 Calibration Complexity Consistent data New ways of user-friendly and semi-automatized model generation, e.g. ASCMO 26

26 Virtualization use-case example: Model-based calibration (DoE) Hyundai* LABCAR (HiL) as a Virtual Vehicle for Calibration Facts and Figures >2.5% global fuel/co 2 -reduction compared to an existing mature calibration for one of their latest engines Less than 700 measurements on a test bed (~2 days) were necessary to achieve this Advantages by using ETAS ASCMO ASCMO modeling algorithm shows much higher accuracy then the conventional physical models for system simulation Optimal ratio of data-no./model quality high efficiency increase Easy tool handling / good usability also for inexperienced users * Results published in MTZ Worldwide April 2015, Volume 76, Issue 4 pp

28 Summary Virtualization is the key for frontloading development tasks: Virtual and HW-based ECUs are validated seamlessly in same tool chain Standards and compatible tools are THE prerequisite for efficient virtualization Support efficient cooperation between OEM and suppliers Larger number of engineers can get their hands on the virtual vehicle More driving scenarios can be validated in early development phases Increased quality at reduced effort / development costs 29

29 Symposium on Automotive Embedded Systems Development Yokohama, Oct 9 th, 2015 THANK YOU FOR YOUR ATTENTION 30