Driveability Simulation in the continuous development process. Dr. Josef Zehetner, DI Matthias Dank, Dr. Peter Schöggl, AVL List GmbH, Graz

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1 Driveability Simulation in the continuous development process Dr. Josef Zehetner, DI Matthias Dank, Dr. Peter Schöggl, AVL List GmbH, Graz

2 Target: Objective Driveability Assessment and Simulation throughout the whole Development Process Motivation Objective assessment of vehicle driveability feeling in all vehicle development phases Driveability assessment in early development phases Frontloading of development activities Use of computer based optimization systems Customer benefits Save development costs and resources by reducing number of prototype vehicles and in vehicle testing avoiding repeating loops Improve quality of Driveability Start Driveability assessment and development at an earlier stage of the development process 2

3 Traditional, Sequential Development Strategy Emissions Fuel Consumption Power Driveability Durability Time 3

4 New, Simultaneous Development Strategy Emissions Fuel Consumption Power Driveability Durability 1. Reduction of Development Time 2. Improved Global Optimum 3. Computer based automatic optimization Time 4

5 What characteristics influence a driver s perception? 60 criteria with influence on driving fun Acceleration Pedal response Pedal to torque relation Precise gear shift Consistent starts Uniformity of rotation Noise, comfort, etc. 210 criteria with neutral or negative impact Hesitations, jerks, Kicks, stumble Oscillations, surge Overshoot, undershoot Torque variations Noise and vibrations etc. America: Cruise and comfort are important Europe: Tip In, acceleration, gear shift Japan: Idle, vibration 5

6 Driveability Assessment Driveability Assessment Driveability Quality & Branding High Driveability Quality Driveability impact of new concepts (DCT, Downsizing, Hybrid, etc.) Specification of target Driveability & branding Improvement of development efficiency Combined CO2 and driveability development Efficient Identification of improvement potential Start earlier development Road to Rig to Math Automated Driveability calibration 10 Alfa Spider 2.2 JTS Audi TT 2.0 TFSI BMW Z4 3.0i HONDA S2000 Mazda MX5 Mercedes SLK 350 NISSAN Z350 PORSCHE Boxster Cost & Resource reduction Globalization 5 4 Tip In after closed throttle Kick Initial Bump Jerks Response delay Torque increase Absolute Torque Common world wide development & supplier quality evaluation 6

7 Objective Driveability Assessment the AVL-DRIVETM Approach 1. Measurement of Driver input & Vehicle reaction Data Logging 2. Automated Driving Mode Detection 1 Nr Driveability Evaluation Single Driving Mode Rating Overall Vehicle Assessment Time Driving maneuver Drive Away Launch Upshift During WOT Acceleration WOT Tipout After Acceleration 3. Parameter Calculation Single Event 18,9 [m/s3] 0,81 [s] Acceleration Gradient Disengage 25,5 [m/s3] 8,19 Acceleration Gradient Engage 0,48 [m/s2] Engagement Shock Traction Interruption Time 0,47 [s] Zero Acceleration Time 7

8 Driveability Applications from Road to Rig AVL-DRIVE Development process Applications Automated Evaluation of Driveability Vehicle benchmarking Manual calibration support Meas. of development progress Quality tests Target dev. / setting Branding Manual and automated calibration Emission and driveability development End of line quality testing Manual and automated calibration Unmanned closed loop calibration Estimation of calibration effort Virtual component installation and assessment Quality test of virtual components Pre-calibration Preparation of test bed setups Layout of mechanical components Virtual packaging 8

9 Powertrain Development with Simulation and objective Assessment of Driveability Development of: Performance Development of: Development of: Consumption Consumption Emission Objective Driveability 8,93 Objective Driveability 8,64 Objective Driveability 8,81 Improved overall quality Reduction of prototype vehicles and vehicle development effort High efficiency with computer based automatic development routines 9

10 VSM Features VSM Vehicle Simulation Model simulation of driveablitiy in real-time Simulation of 85% of AVL-DRIVE TM criteria with an accuracy of above 90% Simulation of driveability relevant oscillations including tire oscillations up to 50 Hz Dynamic coupling of drivetrain (5 masses) and chassis 3-D engine bearing simulation Simulation of seat acceleration sensor with seat and driver model Automated testrun generation from AVL-DRIVE TM measurements Automated model parameterization from: AVL-DRIVE TM measurements (road2model) component testrig measurements (rig2model) CAE and component simulation models (math2model) 10

11 VSM Applications Transfer of calibration applications from the vehicle to earlier development steps through simulation of driveability Virtual pre-optimization of vehicle and drivetrain in the office and on the testbed Combined optimization of power, consumption, emissions and driveability possible Virtual replacement of hardware components: Axles, Shafts, Tires, VSM driveability simulation package is a platform independent model and modeling environment 11

12 VSM Model Components Real-Time 24+ DOF model Engine Control Units (ECU, TCU) Drivetrain Engagement Device (Clutch, Torque Converter) Gearbox (MT, AT, AMT, DCT) Differential(s) Shafts Vehicle Multi Body dynamics Suspension Kinematics/Dynamics Tires Brakes Steering Aerodynamics Driver & Road Longitudinal-, lateral- and gear-shift-controller Road profile Drivetrain Aerodynamics Tires Vehicle dynamics Suspension, brakes 12

13 Application Example: R20 instead of R17 tires Virtual Variation of drive shaft stiffness Approach: Find optimum regarding driveability for drive shaft stiffness changed tire dimensions Variation of Drive Shaft Stiffness Variations with VSM 13

14 Application Example: R20 instead of R17 tires Virtual Variation of drive shaft stiffness R20 R17 Optimum for R16 / R 17 Tyres R17 Optimum for R20 Tyres R20 14

15 Application Example: R20 instead of R17 tires Virtual Calibration of load reversal damping Transfer of driveability optimum for R20 tires with virtual calibration of load reversal damping. VSM AVL-DRIVE TM Original: 6.77 Modified: 7.23 Motormoment Längsbeschleunigung 15

16 Application Example: R20 instead of R17 tires Virtual Calibration of load reversal damping Transfer of driveability optimum for R20 tires with virtual calibration of load reversal damping. Before After Optimum for R16 / R 17 Tyres Optimum for R16 / R 17 Tyres Optimum for R20 Tyres Optimum for R20 Tyres 16

17 Application Example: VSM on AVL-PUMA Testbeds Virtual Driveability Calibration and Optimization VSM is fully integrated into AVL- PUMA testbeds Testbed operators can use the familiar AVL-PUMA user interface Driveability Library is available on AVL-PUMA Benefits of vertical integration into existing systems Re-use of existing simulation models Minor additional training required for AVL-PUMA users Simultaneous simulation and evaluation of driveability AVL-PUMA POI Testbed User Interface ARTE AVL R/T Environment VSM Driveability Simulation AVL-DRIVE Automated Evaluation of Driveability 17

18 Application Example: VSM on AVL-PUMA Testbeds Comparison of AVL-DRIVE TM results In Vehicle Measurement Testbed Measurement Tip in After closed pedal Kick 5.63 Initial bump 7.40 Jerks 7.03 Response delay 8.48 Torque increase 7.03 Sub Event Rating 6.65 Tip in After closed pedal Kick 5.96 Initial bump 7.97 Jerks 6.84 Response delay 8.08 Torque increase 7.06 Sub Event Rating

19 Application Example: Closed Loop Driveability Optimization with AVL-CAMEO Driving Cycle ECU Parameter variation Objective Driveability Rating Measurement Data 19

20 Driveability Simulation and IPG CarMaker CarMaker users can work with the familiar user interface Benefits of vertical integration into existing systems: Identical parameterization and working environment (IPG CarMaker) Minor additional training required for IPG CarMaker users Simultaneous simulation and evaluation of Driveability (VSM and AVL-DRIVE) Horizontal continuity throughout the vehicle development process: Office HiL Testbed (with AVL- PUMA testbeds) IPG CarMaker IPG GUI and Environment VSM Driveability Simulation AVL-DRIVE Automated Evaluation of Driveability 20

21 VSM, AVL-DRIVE and IPG CarMaker: Continuous Toolchain in the Vehicle Development Process 21

22 Conclusions Objective driveability assessment throughout the complete engine and vehicle development process Tools for driveability assessment and driveability simulation Fully integration into simulation and AVL test bed environments Reduction of prototype vehicles and vehicle development effort with Frontloading High efficiency development with computer based automatic simulation and optimization tools Simulation of driveability in real-time enables frontloading of development tasks to testbed and office Continuous tool chain in the Vehicle Development Process using AVL- DRIVE and VSM, AVL-PUMA and IPG CarMaker: OFFICE LAB TESTBED VEHICLE 22

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