Simulating Systems in Ground Vehicle Design Frederick J. Ross Director, Ground Transportation

Transcription

1 Simulating Systems in Ground Vehicle Design Frederick J. Ross Director, Ground Transportation

2 Agenda: Simulating Systems Maturity of Simulation Growing from validation to virtual simulation Simulating Systems Driving virtual prototype to look at early design behaviors

3 System Simulation Maturity Model Increased ROI Optimize As simulation matures, greater return of investment is seen. Each analysis goes through phase. First, the process needs to be validated. Once validated, engineers start taking advantage of the tool to troubleshoot existing designs. Key turning point in simulation is where the use becomes more predictive Replace test by virtual simulation Next key turning point is automation Automation leads directly into optimization. To build the best design in the shortest period. Ease-of-Use to run design modifications Automate Predict Troubleshoot Validate (software) Critical inversion point (from reactive to proactive engineering) Ultimate Goal: Find best design in shortest time

4 Increased ROI Powertrain Simulation Roadmap Optimize Automate Predict Troubleshoot Validate 4 Environment Evaluation Dynamometer Testing Engine in Vehicle Drive Cycle Simulation 1 Component Analysis Port Flow Coolant Flow Intake/Exhaust Manifold flow 2 3 Transient Behavior Couple Simulation to 1D Code Look at EGR mixing Exhaust manifold temperatures System Analysis Coolant Filling Crank Case Ventilation Oil Circuits Turbo Charger Aftertreatment Component Analysis Complexity System Analysis

5 Automation: Intake Port Flow Analysis Virtual Port Flow Tool Challenge Combustion efficiency depends a lot on the intake air flow, tumble, and swirl to get complete, and fast burn. CFD has proven to be a valuable tool to optimize port flow. Engineer needs quick design studies to evaluate flow efficiency at different valve lifts. Solution Automated tool has been built and designed. Port Flow optimization. Follows work from established best practices. Pass data to other software/databases without manual interactions. Impact Reduce errors in simulation. Leverage product expertise without needing software expertise. Leverage the expertise of analysis to the experts. Return to a focus on Design as opposed to Analysis!

6 Automation: The SCR Simulation Assistant STAR-CCM+ environment promotes automation Tools from CAD to Results The Simulation Assistant helps guide user for specific applications New for 2013 User can define steps needed to define the workflow

7 Coolant Jacket Simulation Assistant Guiding the user through set up and post processing of a Cylinder Block / Head Coolant Jacket.

8 Optimization: Coolant Flow Challenge: Minimize pressure drop across water jacket Modifying 24 gasket hole Subject to constraints: Specified peak head and liner temperatures Cylinder to cylinder variation in peak liner & dome temperatures < 10 C Peak coolant temperature specified Peak velocity of coolant in head/block water jackets < 10 m/s Optimate+ Results: 1/3 less design evaluations compared to DOE 10% reduction in pressure drop relative to DOEoptimized design 7% reduction in max head temperature 16 feasible designs in highly constrained design space Optimization Baseline Optimal Design Process Optimal Design Improvement in Cooling Jacket Temperature Variation Optimized Baseline Coolant Inlet Gasket Holes 4.38M Cell Polyhedral Mesh 8

9 Simulating Systems: Powertrain Challenge During development process, test are design to look at engine for early design testing. But critical tests need to consider installation of the powertrain in the vehicle. Solution Use existing geometry of the engine in dynamometer and place engine in vehicle. Includes: Cooling Air Flow Air Induction System Coolant Flow Network Oil Flow Impact Reduce prototype of engine/vehicle construction. Reduce time to find out thermal failures. Reduce cost Reduce time to production. Improve information on failure cause. 9

10 System Simulations: Exhaust Aftertreatment Simulation Features NOx reduction in the catalyst Lagrangian multiphase with pulsed spray injection Multi-component droplets (water/urea mixture) CHT (multi-phase fluid + solid pipe walls and mixers) Liquid film + droplet/film wall interaction Droplet/film evaporation + gas mixing (air, Urea gas, NH3, H2O ) Chemical reactions (Thermolysis/Hydrolysis) Porous Media Flow inlet Spray Injector DOC (Diesel Oxidation Catalyst) Mixers SCR DPF (Discrete Particle Filter) Flow outlet

11 Increased ROI SCR Simulation Roadmap Optimize Automate Predict Troubleshoot Validate 3 Crystallization Prediction Full Chemistry Solidification prediction Uniformity Test Urea Injection 1 Wall Modeling NOx Prediction Urea/Gas Mixing Optimization demo exists 2 Surface Chemistry Detail Chemistry Using DARS Clients have validate results Complexity

12 Increased ROI Vehicle Thermal Management Roadmap 8 GUM: Grand Unified Model Complete vehicle simulation Solid Components Cabin Thermal Comfort Vehicle Aerodynamics HVAC Simulation Electronics Cooling Co-Simulation STAR-CCM+ to STAR-CCM+ 7 Full Vehicle Thermal Management Co-Simulation from STAR- CCM+ to STAR-CCM Solid Components Includes Drive Cycle Simulation via Ports 6 Full Vehicle Thermal Management Conduction/Radiation using Radtherm Includes Drive Cycle Simulation 3 Underbody Temperature ~ 100 Solids Includes Exhaust System, hangers, engine mounts, heat shields 5 Power Train Cooling Full Engine CHT model Induction System Exhaust System Oil Flow 1 Front End Air Flow Top Tank Temperature Prediction Turn-Around: 1 Day 2 Local Component Temperature Solids Local to a component Total Vehicle Simulation Using existing sub-models Complexity 4 8

13 Simulation using the Digital Prototype Heat Protection Aerodynamics Digital Prototype becomes enabler for advance simulation Simulation for more advance analysis then just component design HVAC/ Thermal Comfort NVH Simulation includes multi-physics. Simulation can involve motion as needed as well. Whatever best helps engineer design their product efficiently. In the past, these would not have been possible until hardware of the vehicle has been produced. Manufacturing Ride/Handling Climate Control Crash Transmission Durability (BiW) Powertrain Durability Chassis

14 Damping force F ,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 Generation of a Digital Prototype Data Freeze defines digital prototype As with a real prototype, design teams work together to meet a goal for the design freeze. Review board checks, to make sure all components are fitted together and data pool is complete. Data Filter: Filters data for simulation Data needed for simulation is filtered from the overall data pool, and provided for the virtual simulation. Key component for data transfer Example of data filters: Red Cedars Heeds Custom tool designed to pull data together. OpenRoad CAD plugin can help provide data filter PLM (product lifecycle management) tools enable communication between different tools. Analysis Response Feeds back into the data pool for design improvement. Geometrical Data Grade 1 Grade 2 Deflection speed v Functional Data

15 Damping force F ,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 1 Automation: Front End Cooling/Aerodynamics Challenge: Data Filtering Large CAD database needs to be quickly moved from 1000 s of CAD parts to few boundaries needed for CFD. Grade 1 Grade 2 Solution: OpenRoad Provides part filtering with link to boundary setup for the simulation. Forms template for the full simulation process including dual stream heat exchangers. Geometrical Data Deflection speed v Functional Data Impact: Enables users to quickly predict drag and/or front end air flow. Enabler for more complex studies such as component temperature prediction, soiling, aero-acoustics Runs fully in batch: good for optimization with Heeds

16 1 Optimization: Front End Cooling/Aerodynamics Challenge: Cooling Performance Engineers have two competing design criteria's Need to provide cooling air for engine. Decrease grill/bumper opening to reduce drag Solution: Optimization study can be done looking at grill/bumper openings and fan size and determine best case where both criteria's can be satisfied. Involves looking at drag at high speed while cooling performance is done with a uphill trailer tow study. Impact: Using SHERPA improvements are seen within 50 design iterations

17 2 System Simulation: Brake Cooling Modeling Brake Cooling Thermal temperature prediction of brake disk. Brake drive cycle studies Brake cooling duct design Optimization: Minimize rotor temperature while reducing drag. Failure protection Water splash/spray on bearings Dust shield design

18 6 System Simulation: An Innovative Approach to Race Track Simulations for Vehicle Thermal Management Challenge: Extreme drive cycle push strain on thermal environment of the engine. Solution: Simulation can help reduce time and costs compared to experimental testing. Allows testing during early concept phases where testing is not possible due to lack of hardware. Allowed simplified thermal components to be modeled quickly in Radtherm, coupled to a detail CFD simulation Impact: Improve endurance on PowerTrain. Reduce thermal drive failures Reduce cost and time. Overall the methodology indicated that fast quasi-transient solutions can be achieved for a highly dynamic profile with our current computational resources Kristian Haehndel, BMW Group 18

19 7 System Simulation: Steady-State Full VTM Simulation Airflow + Solids using co-simulation Air model is ~35 million cells. Solid Model is ~35 million cells. Over 4000 solid components modeled in the simulation

20 Shell Vs Solid Modeling Accuracy Solids are more accurate Air flow imping on edge Heat capacity of solid Number of parts considered is more critical How many parts can be modeled in 4 weeks Turn-around time? Recommendation Use what provides fastest turnaround time CD-adapco Goal: Using solid elements should provide fastest modeling and modification time since the true part has thickness Working at automating part contact with solid elements. Zero thickness can be a problem

21 System Simulation: Thermal Analysis & Design Improvement of an Internal Air-Cooled Electric Machine Challenge: Use simulation to improve the thermal performance of an internal aircooled induction machine Solution: Compute EM losses in SPEED and map as heat loads to STAR-CCM+ EM Loss/Heat Loads

22 Battery Modelling A Multi-Physics and Multi-Length Scales Solution Characterizes cell electrochemical and physical description Cell performance validated against experimental data. Skin temperature applied to cell, and thermal cooling prediction is carried out with STAR-CCM+. Battery design studio used to determine cell performance. Cell performance can then be supplied to surface of cell to determine packaging of battery back.

23 System Simulations: Transmission Case Studies Oil Slosh: Gearbox, Hydraulic Reservoir Gears: Planetary, Screw, Pinion ETC Bearings Clutch Plate Torque Converter Operating Conditions Flooding Leakage into transmission Thermal Fatigue Stress Operating Load Point Heat up or Cool Down Drive Cycle Key Enablers: Overset Grids Robust VOF Simulation

24 System Simulation: Headlamps Challenge: Two challenges Condensation Thermal deformation Solution: Simulation of Condensation Investigating removal time for condensation on/in headlamp Look at ventilation patterns in headlamp Thermal Environment Investigating thermal stresses that may cause deformation or melting Impact: Improves safety and customer satisfaction. STAR-CCM+ is capable of handling conjugate heat transfer phenomena between different bodies as well as radiation and solid stress. Andrea Menotti, Olsa S.P.A 24

25 System Simulation: Cabin Comfort Passenger Thermal Comfort Thermal comfort manikin Transient heat up/cool down modes Highlights importance of fast radiation modeling Need Solar, diffused solar, and reflective radiation Experience with heat transfer through walls and heat capacity Deice/Defog Simulation Important use of wall film models

26 System Simulations: Manufacturing Paint Dip/E-Coat Drying Spray Paint Casting

27 Summary System Simulation is impacting design Reduce turn-around time in design Reduce costs from reducing number of prototypes Simulation is expanding Users are looking at replacing more expensive tests with simulation As capability grows and mature in simulation tools, so does the demand on extending the features. Design Exploration Growing With increased automation provided by the STAR-CCM+ suite, optimization expanding to provide engineers with best design, in the shortest design cycle.

28 Thank You!