Multi-ECU HiL-Systems for Virtual Characteristic Rating of Vehicle Dynamics Control Systems
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1 Multi-ECU HiL-Systems for Virtual Characteristic Rating of Vehicle Dynamics Control Systems Dipl.-Ing. Ronnie Dessort, M.Sc. Philipp Simon - TESIS DYNAware GmbH Dipl.-Ing. Jörg Pfau - Audi AG VDI-Conference Simvec Spezial Simulation Fahrdynamik, Baden-Baden (December 11, 2013) TESIS DYNAware GmbH, 1
2 Motivation The Strategic Goal Validation of ESC-Software for all vehicle variants using HiL-simulation. SW-Release Validation Requires the Integration of all relevant vehicle dynamics controllers Task of the OEM Complete integration of all control units delivered by different suppliers The Challenge Due to the increasing interaction of ECUs and growing array of vehicle variants, a test environment encompassing only the ESC is no longer adequate 2
3 Content State of the art for virtual characteristic rating of vehicle dynamics control systems Challenges related to ECU interaction Possible solutions Test automation Application examples 3
4 Typical Simulation System Setup for Virtual Characteristic Rating of an ESC-unit Test Rig Vehicle Model Sim.Control / Evaluation Brake System Components Real-Time Model (vedyna) HiL operating desk Control Unit (ESC)
5 Test Rig Setup Spindle Drive Inverter Interface IO (actuator controller) Vacuum Brake Booster Interface Hydraulic Modulator ESC IO (Bus) Brake FL Brake FR Brake RL Brake RR Interface IO (Sensors) Pressure sensor Pressure sensor Pressure sensor Pressure sensor 5
6 Real-Time Platform Simulation Model vedyna - Vehicle Dynamics Model Restbus: required signals of other control units not under test (e.g. motor, transmission, airbag, ) Maneuver control (test scenario) I/O Bus-Communication (CAN, FlexRay, ) Sensors Brake Actuator Controller (Brake Pedal) 6
7 Challenges related to ECU interaction Active Front Steering Dynamic Steering Active Lateral Torque Distribution Torque Vectoring Front Axle Differential Lock XDS Active Rear Steering Brake System ESC ABS Recuperation Active Anti-Roll Bar Motor ASR MSR Electrification Active Longitudinal Torque Distribution Haldex Transmission Spring air spring Damper CDC MagneticRide 7
8 Possible Solutions: Two Approaches for Testing Vehicle Control Systems Integration of Real Control Units Integration of Soft-ECUs technically identical to the real vehicle entire integration in the vehicle series project regarding hardware and software availability acceptance of test results higher commissioning effort complexity of model, hardware and I/O no need for hardware and I/O Reliance on suppliers reduced accuracy integration with the HiL environment Availability reliable characteristic rating is problematic validation of software is problematic Integration of real control units in a multi-ecu HiL-system 8
9 Example of an Multi-ECU HiL-System Vacuum Brake Booster Actuator Inverter Hydraulic Modulator ESC Control Unit Real-Time Platform Front Axle Brakes Pressure Sensors Rear Axle Brakes Haldex Control Unit Damper Control Unit Damper Enhanced test rig with hardware control units of allwheel and damper control 9
10 Test Automation HAP a custom solution (HiL Workplace) Software framework for the management of the entire testing process Testing maneuver management test automation test settings Project Management simulation projects general settings Model Management parameter configuration component handling real-time process execution Results Management criteria evaluation animation/plot report automation 10
11 Application Example ABS-Braking on μ-split Test Description Full braking (clutch disengaged) at 100 km/h Road condition: μ-split Interaction between brake and damper control systems μ -low μ -high Criteria Stopping distance Yaw rate Friction utilization Steering effort Lane deviation Side slip angle 11
12 Maneuver Analysis ABS-Braking on μ-split ABS-Control active Controlled damping force reduces pitch oscillations and wheel load variation especially whilst the brake pressure is building up. No influence by AWD control unit, even when clutch is engaged (in which case the MSR control function is also active). 12
13 Criteria Evaluation ABS-Braking on μ-split ID Criterion Unit Physical Value B1 stopping distance [m] S4 max. yaw rate [ /s] 3.92 R1b friction utilization [%] BK5 steering effort [ ] S3 track deviation [m] B1 S6 max. side slip angle [ ] 2.68 S6 5 S4 0 Conversion of physical values to a rating from S3 R1b BK5 13
14 Application Example Double Lane Change Test Description Double lane change at 110 km/h Road condition: wet Clutch engaged, full throttle Complex interaction between AWD, damper and active yaw control systems Criteria Stability 14
15 Maneuver Analysis Double Lane Change (Torque) Crank torque is limited by ASR control commands 1st critical situation: lane change reduction of crank torque Moderate ESC intervention left 2nd critical situation: lane keeping Strong ESC intervention right AWD controller action supports stabilisation 15
16 Capabilities of the Multi-ECU HiL-System approach Qualified for characteristic rating and validation of every software version of all vehicle dynamics controllers Qualified for testing of interconnected control unit functions Qualified for testing with regard to functional safety validation Robustness analysis Cross functional development (e.g. pre-set-up of controller parameters) Research / advanced development in regard to brand-specific software Qualified platform for a driving simulator to experience and parametrize vehicle dynamics controllers in an early development stage 16
17 Conclusions Finding: The virtual characteristic rating of vehicle dynamics control systems increasingly requires a solution comprising of several interconnected control units. Contributing factors: The increasing quantity of actuators in the vehicle is accompanied by a rising diversity of variants. Focusing on validation of ESC software for vehicle variants necessitates the integration of further real hardware control units. The use of Multi-ECU Test systems opens up a wide range of opportunities in the areas of functional and characteristic testing, sensitivity analysis of controller parameters and development of new functions. 17
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