Co-Simulation of GT-Suite and CarMaker for Real Traffic and Race Track Simulations GT-Suite Conference Frankfurt, 26 th October 215 Andreas Balazs, BGA-T
Agenda Introduction Methodology FEV GT-Drive model GT-Drive and CarMaker coupling Case study Co-simulation on a race track: Nürburgring investigation Co-simulation in traffic conditions: Bologna Ring Summary 2
Agenda Introduction Methodology FEV GT-Drive model GT-Drive and CarMaker coupling Case study Co-simulation on a race track: Nürburgring investigation Co-simulation in traffic conditions: Bologna Ring Summary 3
Introduction Simulation of real driving requires detailed models for traffic, driver and vehicle longitudinal and lateral dynamics Increasingly detailed and realistic simulation process lead to new needs : Realistic driving environment Detailed tire model Vehicle dynamics Source: IPG tire force vertical damping K vertical stiffness C Various driver behaviors slip max. slip total tire slip 4
Agenda Introduction Methodology FEV GT-Drive model GT-Drive and CarMaker coupling Case study Co-simulation on a race track: Nürburgring investigation Co-simulation in traffic conditions: Bologna Ring Summary 5
Methodology Varying fidelity levels are available for each Module depending on the simulation needs FEV GT-Suite model Modular Architecture Each module with varying levels of fidelity Highly customizable Conventional and Hybrid powertrain topologies Fuel consumption, emissions and performance of various powertrains can be investigated 6
Methodology Varying fidelity levels are available for each Module depending on the simulation needs FEV modular architecture for varying fidelity levels and system complexity Base Level Auxiliaries base model Advanced Level I Auxiliaries advanced model Advanced Level II User Modification Level 7
Methodology Data for model validation provided by customer and also by FEV database & map scaling tool Input data provided by customers FEV Modular architecture 8
Methodology Data for model validation provided by customer and also by FEV database & map scaling tool FEV Database FEV Modular architecture 9
Methodology Data for model validation provided by customer and also by FEV database & map scaling tool FEV Map scaling tool FEV Modular architecture BMEP [bar] 25 2 15 1 5 2 4 6 BMEP [bar] 25 2 15 1 5 2 4 6 Exhaust Intake BDC TDC BDC 1
Methodology A wide range of engine technologies and powertrain components & architectures can be simulated with the GT-Suite model Valvetrain variability Boosting Transmission optimization Cooled external EGR Friction E-Machines optimization Variable compression Engine technologies Miller cycle Powertrain architectures and components Various levels of hybridization Battery size optimization 11
Methodology How do new engine technologies and the powertrain architectures affect fuel consumption in real driving conditions? Emissions analysis Exhaust BDC TDC BDC Source: VW Intake Source: Delphi HC mass flow / g/s Time / s Fuel consumption analysis WLTC-High Vehicle speed / (km/h) Vehicle speed / (km/h) 14 12 1 8 6 4 2 14 12 1 8 6 4 2 WLTP 2 4 6 8 1 12 14 16 18 NEDC 2 4 6 8 1 12 Time / s CO 2 emissions / g/km NEDC WLTC-Low Vehicle mass / kg 12
Methodology How do new engine technologies and the powertrain architectures affect fuel consumption in real driving conditions? Emissions analysis Exhaust BDC TDC BDC Source: VW Intake Source: Delphi HC mass flow / g/s Time / s Fuel consumption analysis WLTC-High Vehicle speed / (km/h) Vehicle speed / (km/h) 14 12 1 8 6 4 2 14 12 1 8 6 4 2 WLTP 2 4 6 8 1 12 14 16 18 NEDC 2 4 6 8 1 12 Time / s CO 2 emissions / g/km NEDC WLTC-Low Vehicle mass / kg 13
Methodology GT-Suite tool has limitations for simulation of real driving conditions Detailed vehicle lateral dynamics simulations are not comfortable with GT-Suite. It is not possible to implement quickly: Realistic road with curves Road infrastructures (traffic light, speed limit ) Traffic Scenario with various vehicles on the road Vehicle speed / (km/h 14 12 1 8 6 4 2 2 4 6 8 1 12 Time / s Vehicle Speed / Km/h 6 5 4 3 2 1 5 1 15 2 Vehicle Distance / m 14
Introduction CarMaker is a useful tool for vehicle simulation and HIL tests under realistic boundary conditions What is CarMaker? Vehicle longitudinal and lateral dynamics simulation tool that provides: Detailed driver parametrizations Traffic and infrastructures model Vehicle lateral dynamics model Detailed tire model Hardware-in-the-loop (HIL) tests can be performed with this tool, on single or multi ECU systems Source: IPG 15
Methodology Driver, tires and road detailed models are available in CarMaker for quick implementation Driver model Detailed parametrization Various behaviors Learning procedure Tire models IPG Tire Pacejka Model Tame Tire MF-Tire/MF-Swift 6.1 Road model Road from GPS Data Road infrastructures Navigation tool available 16
23 24 25 27 31 46.1.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 Methodology The GT-Suite model can be exported as FMU, which enables exchange of signals with CarMaker ambient FMU GT-Suite model as a black box Control signals Brake pedal Gas pedal Gear number Physical signals Braking torque Resistances torque Driveline torque Driver model Tire model Road model Results Engine Engine Torque / Nm Speed / (1/min) 4 2 3 15 2 1 1 5 25 7 2 6 5 15 4 1 3 2 5 1 2 4 6 8 1 12 Time / s Gear Number / - Vehicle Velocity/ (km/h) mean effectivepressure / bar 25 2 15 1 5 NEDC 1 2 3 4 5 6 Engine speed / 1/min fuel share / % 17
Agenda Introduction Methodology FEV GT-Drive model GT-Drive and CarMaker coupling Case study Co-simulation on a race track: Nürburgring investigation Co-simulation in urban conditions: Bologna Ring Summary 18
Case study Nürburgring investigation: Investigation of a conventional and a hybrid powertrain on a race track Purpose of investigation: Testing and comparing performances of a conventional and a hybrid powertrain on a race track Tools for investigation: GT-Suite and IPG CarMaker cosimulation Track of the investigation: Nordschleife Nürburgring Length of track: 21 km CarMaker Race Track GT-Drive Hybrid Powertrain CarMaker Vehicle GT-Drive Conventional Powertrain 19
Case study Nürburgring investigation: Simulation model validation made with measurement data A detailed comparison and simulation model validation with measurement data was performed to match vehicle speed, acceleration, yaw rate and vehicle heading Vehicle Heading / rad Yaw Rate / rad/s 6 4 2-2 -4-6 1.2.8.4. -.4 -.8 Measurements Co-simulation -1.2 36 375 39 45 42 435 Distance / m Measurements Co-simulation Vehicle Trajectory 445 m 36 m Measurements Co-simulation.121.1214.1218.1222 Longitude / rad.8794.8793.8792.8791.879.8789.8788.8787.8786.8785 Latitude / rad 2
Case study Nürburgring investigation: Better acceleration performance of the hybrid powertrain due to electric machine boosting Conventional powertrain faster Hybrid powertrain faster Longitude / rad Latitude / rad 21
Case study Nürburgring investigation: Better acceleration performance of the hybrid powertrain due to electric machine boosting Vehicle Speed / km/h Longitude / rad Torque / Nm 35 3 25 2 15 1 1 1 Conventional powertrain faster Hybrid powertrain faster Conventional Hybrid 2 EM Torque EM Boost EM Braking Döttinger Höhe Antoniusbuche Conventional powertrain Hybrid powertrain Maximum speed (km/h) 322 33 Lap time 7 min 4 sec 7 min 3 sec -1 Latitude / rad 22
Case study Urban conditions: Investigation of a conventional powertrain in realistic city and traffic conditions Purpose of investigation: Evaluation of fuel consumption in real driving conditions: With and without traffic Different driver behaviors Tools for investigation: GT-Suite and IPG CarMaker co-simulation CarMaker road and infrastructures CarMaker driver parametrization Track of the investigation: Bologna Ring Length: 7 km GT-Suite powertrain model 23
Case study Urban conditions: Different traffic conditions effect fuel consumption on an urban track Co-simulations performed with and without traffic Fuel consumption of the investigated conventional powertrain: 7.5 Fuel Cons / ( l/1km) 7. 6.5 6. 5.5 without traffic with traffic 24
Case study Urban conditions: Aggressive and defensive driver behaviors have significant influence on fuel consumption Co-simulations performed with aggressive and defensive driver behavior: CarMaker driver setting urban track co-simulation fuel consumption and engine operating points evaluated Vehicle Speed / km/h Gas Pedal / - 5 4 3 2 1 1.2.9.6.3. Vehicle Speed Defensive Vehicle Speed Aggressive Gas Pedal Defensive Gas Pedal Aggressive BMEP / bar BMEP / bar 2 15 1 5 2 15 1 5 aggressive 245 25 26 28 35 defensive 245 25 26 28 35 24 24 1 2 3 4 engine speed / (1/min).1.3.5.7.9 1.1 1.3 1.5 1.7 1.9 2.1.1.3.5.7.9 1.1 1.3 1.5 1.7 1.9 2.1 Fuel Cons / ( l/1km) 7.5 7. 6.5 6. 5.5 defensive driver aggressive driver 25
Case study Urban conditions: different preview distances of the driver affect fuel consumption Different preview distances simulated (3, 6, 9 m) Fuel consumption of the investigated powertrain: 7. 3 m 6 m 9 m Fuel Cons / ( l/1km) 6.5 6. 5.5 5. 4.5 9 m 6 m 3 m 26
Methodology Quick post-processing of simulation results with the FEV macro-based tool functions also with CarMaker FEV Evaluation Tool Co-Simulation Plotting E ff. M itte ld ru c k [ b a r] p m e 25 2 15 1 5 25 2 15 1 5 5 DCT 6 DCT 7 DCT 1..9 24 24 24.8 245 245 245 25 25 25.7 26 26 26 28 28 28.6 35 35 35.5 9 DCT 1 DCT 12 DCT.4.3 24 24 24.2 245 245 245 25 25 25 26 26 26.1 28 28 28 35 35 35 1 2 3 4 1 2 3 4 1 2 3 4 Drehzahl [1/min] Drehzahl [1/min] Drehzahl [1/min] Results 27
Agenda Introduction Methodology FEV GT-Drive model GT-Drive and CarMaker coupling Case study Co-simulation on a race track: Nürburgring investigation Co-simulation in urban conditions: Bologna Ring Summary 28
Summary The co-simulation allows to investigate fuel consumption and performances of a detailed powertrain in realistic conditions The co-simulations between GT-Suite and CarMaker allows to simulate a detailed powertrain model with: Various driver behaviors Realistic and detailed tire models Consideration of lateral dynamic forces The implementation of realistic tracks and infrastructures Nürburgring race track Bologna Ring city track 29
Summary The co-simulation allows to investigate fuel consumption and performances of a detailed powertrain in realistic conditions Successful implementation of co-simulations: Investigation of a conventional powertrain on a urban track Evaluation of a sportcar powertrain conventional and hybrid on a race track Vehicle Speed / km/h Gas Pedal / - 5 4 3 2 1 1.2.9.6.3. Vehicle Speed Defensive Vehicle Speed Aggressive BMEP / bar Gas Pedal Defensive Gas Pedal Aggressive.1 BMEP / bar 2 15 1 5 2 15 1 5 35 35 28 28 26 25 26 25 245 245 24 24 1 2 3 4 engine speed / (1/min).1.3.5.7.9 1.1 1.3 1.5 1.7 1.9 2.1.3.5.7.9 1.1 1.3 1.5 1.7 1.9 2.1 L o n g i tu d e / r a d Latitude / rad Torque / Nm 1 Y a w R a te / r a d /s 1.2.8.4 2 EM Torque. -.4 1-1 -.8 Measurements Co-simulation -1.2 36 375 39 45 42 435 EM Boost Distance / m EM Braking 3
Thank you for your attention! 31