Enabling Advanced Vehicle Heat Protection Through the Digital Prototype. Frederick J. Ross Director, Ground Transportation

Transcription

1 Enabling Advanced Vehicle Heat Protection Through the Digital Prototype Frederick J. Ross Director, Ground Transportation

2 Agenda STAR-CCM+ Designed for Vehicle Heat Protection Over 25 years of experience STAR-CCM+ Design Focus on VTM Benefit of Siemens Automation tools to help reduce turn-around time Vsim: Automating Front End Air Flow C2M: Automating Component Modeling Case Studies

3 STAR-CCM+ For Vehicle Thermal Management v2.0 was first enabler using client-server with mesh generation 2 Solver Team New Client Server STAR-CCM+ V2: Mesh Development Team 1 1 Cell Quality Remediation 2 1 Surface Wrapping: Clean Surface Bring in CAD Tree 1 Goals Robustness Job needs to run with minimum user interaction. 3 3 Heat Exchanger Models Fast S2S Radiation 2 3 Imprint/Boolean Operations Thin Mesher 2 Reduce Turn Around Automation Ease-of-Use Quick Modifications 2 2 Shell Conduction Co-Simulation 2 2 Parts Based Meshing Parallel Trimmer 3 Accuracy Need to simulate real world test conductions 2 Parts Based Profile 2 Concurrent Meshing STAR-CCM+ V11: 2016

4 Vehicle Thermal Management Maturity Roadmap Level 1 Fully automatic Single or Dual Stream No Solid Modeling Fast turn-around time Level 2: Simulation of Systems Automating Procedures Solids + Radiation 3 Exhaust System CHT Solids Radia?on & CHT Heat Shield Design/ Placement Level 3: Virtual Prototype Working from CAD to Simulation Simulating Systems: Solids/Fluid Solids with Radiation & co-sim 5 Full Vehicle Thermal Management solids Coolant/Oil etc Drive Cycle Simula?on 1 Front End Air Flow Top Tank Temperature Predic?on 2 Brake Cooling Radia?on & CHT Rota?ng Parts/Fric?on Hea?ng Op?mize Cooling 4 Power Train Cooling Engine CHT Coolant Oil, Intake/Exhaust Flows Complexity

5 ,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 Generation of a Digital Prototype Producing a digital twin CAD 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 PLM (product lifecycle management) tools enable communication between different tools. Geometrical Data Damping force F Grade 1 Grade 2 Deflection speed v Functional Data Analysis Response Feeds back into the data pool for design improvement.

6 Siemens PLM Software + CD-adapco: Market Leader in Systems Driven Product Development The clear leader amongst PLM solution providers in simulation and test software, and associated services. STAR-CCM+ HEEDS Optimate SPEED BDS Virtual.Lab Samtech Imagine.Lab Test.Lab Computational Fluid Dynamics (CFD), Computational Solid Mechanics (CSM), heat transfer, particle dynamics, reacting flow, electrochemistry, acoustics and rheology. Multidisciplinary optimization and design space exploration Electric machine simulation and design Behavioral simulation: 1D cross-discipline simulation, like mechanical and electrics, e.g. fuel economy & range simulation for hybrid vehicles 3D mechanical simulation: e.g. stiffness, noise, vibration Testing: Solutions for prototype testing (stationary & mobile) NX CAD NX CAE Nastran Teamcenter Tecnomatix Streamlines and accelerates the product development process in a collaborative environment Includes a modern, multi-discipline CAE environment

7 ,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 Generation of a Digital Prototype Producing a digital twin TeamCenter Allows user to sort throw CAD, pick assemblies to be modelled Export PLMXML data with JtOpen Coarse/Medium/Fine Tesselation Brep: Passing geometry Material Properties linked to parts Geometrical Data Damping force F Grade 1 Grade 2 Deflection speed v Functional Data AmeSim 1D tool for modeling cooling circuit Helps predicting top tank temperature STAR-CCM+ Read CAD and prepare mesh for simulation Simulate 3D flow field Post results

8 8 STAR-CCM+ Workflow Computational Process & Tools CAD Import Parasolid Files Team Center Interface STL Data coolant oil exhaust Front End Air Flow Setup air stream through engine compartment Define zones for heat exchangers/fans Connect to 1D tools for coolant circuit if needed convection conduction Solid CHT CAD cleanup Build Interfaces between parts Concurrent meshing radiation CosimulaPon Parallel Surface-2-Surface RadiaPon Solids run full thermal transient Fluid either steady or transient driving cycle Source: M. Disch (upcoming Ph.D thesis, FKFS) 1D thermal network

9 Front End Air Flow Workflow Import CAD Separate region for fan/heat exchangers Underhood Regions: Group surfaces for underhood region Separate by mesh and physics size: Set prevent contact for important gaps Close large holes? Use gap closure/anti seed point to prevent leakage into main cabin Wrap Region Setup heat exchanger/fans: Create interfaces for sub-regions Wrap fan region, if needed. Just remesh heat exchangers Create physics continua (including material properties) Create all reports, monitors, plots for monitoring convergence Use parallel trimmer to reduce mesh generation time. April 3, 2014 Page 9

10 2 Solid Conjugate Heat Transfer Model Goal Predict local component temperature Typical Applications Components Surrounding Exhaust Brake Cooling Important Physics Convection Conduction Radiation Solutions Convection: Vsim Conduction: Parts Based Meshing Framework C2M: Cad to Mesh Tool Radiation: Parallel Surface-to-Surface

11 Solid Conjugate Heat Transfer Workflow Import CAD Check CAD Check fit and completeness multiple components per leaf-level part and split into separate parts Check for duplicate parts and tag / delete Repair CAD problems Extrude parts without thickness Clean CAD surface errors (pierced faces, free edges, non-manifold) Replace or fix gross non-fitting CAD Wrap poor quality parts Boolean subtract all intersecting components Split part surfaces at special internal BC locations Create physics continua Apply physics to regions Set material properties for each region Apply all radiative surface properties to boundaries Create all reports, monitors, and plots for monitoring convergence Mesh using parts based meshing to allow multiple pipelines Enable concurrent meshing to reduce meshing time April 3, 2014

12 Agenda STAR-CCM+ Designed for Vehicle Heat Protection Over 20 years of experience Focus of STAR-CCM+ since version 2.0 Benefit of Siemens Automation tools to help reduce turn-around time Vsim: Automating Front End Air Flow C2M: Automating Component Modeling Case Studies Note: The automapon tools can be provided by CD-adapco as examples for clients to use. They are maintained for each release, and as long as they are maintained, clients can get updated.

13 1 VSim: Aero/Thermal Automation STAR-CCM+ reading setup information directly from excel Automated Process from CAD to Report Reads CAD from subdirectory Spreadsheet Contains Settings CAD Grouping to CFD Boundaries Heat Exchanger/Fan Information Thermal Boundary Conditions Input: Cad/Excel Run: Mesh/Solve/Post Output: PowerPoint

14 1 VSim: Aero/Thermal Automation STAR-CCM+ reading setup information directly from excel 1 2 OperaPng CondiPons Group CAD to Boundaries Mesh SeYngs Fan/Heat Exchanger ProperPes Monitors and Post Processing

15 2 Automation: C2M Toolbox Checks Surface for errors Repair parts with severe errors Move into surface repair Alternatively wrap/replace part Generate Volume mesh Sets up parts based meshing tree Find and Generate Interfaces between components

16 Agenda STAR-CCM+ Designed for Vehicle Heat Protection Over 20 years of experience Focus of STAR-CCM+ since version 2.0 Benefit of Siemens Automation tools to help reduce turn-around time Vsim: Automating Front End Air Flow C2M: Automating Component Modeling Case Studies

17 Case Study: Cranfield Univ., Jaguar Land Rover SAE Full Vehicle Aero-Thermal Cooling Drag Sensitivity Analysis Challenge: Investigation of overall aerodynamic drag reduction impact on front end cooling is difficult to predict experimentally. Solution: Simulation can be used to look at cooling drag at both 55mph and 120mph to ensure aerodynamic drag reduction still meet cooling requirement. Impact: Digital prototype can aid engineer to reduce overall energy used by vehicle, including aerodynamics drag to front end cooling.

18 1 Customer Success: MulP objecpve design explorapon } Challenge: } OpPmize across mulpple compepng objecpves } Minimize vehicle drag } Minimize radiator inlet temperature } While varying these design variables: } Geometry of grill and bumper vents } Radiator fan geometry and speed } Subject to constraints } OpPmate+ Results: } Drag reduced 5.4% } Radiator temperature decreased 11.3% } Evaluated 120 designs; 135 hours on 128 cores Vehicle Drag Load Case Baseline Radiator Temp Load Case Optimized Optimization process 18 Copyright Red Cedar Technology: All Rights Reserved A U T O M O T I V E

19 3 Case Study: Daimler AG Thermal Management of Dynamic Driving Cycles Challenge: Use computational methods for prototype development Reduce turnaround time for prediction of thermal behaviour in driving cycles Solution: Transient Vehicle Thermal Management approach in STAR-CCM+ Co-Simulation of a transient solid model with steady state fluid model Comparison with measurements Impact: Turnaround time of two weeks for full vehicle transient VTM Good prediction of temperature Optimization of thermal management through computational methods Reduction of testing/prototypes

20 Steady-State Full VTM Simulation Airflow + Solids using Co-Simulation Airflow model is 50+ million cells. Solid Model is 40+ million cells. Over 5000 solid components modeled in the simulation

21 3 Case Study: Daimler AG SGC 2016 Simulating the Idle: A New Load Case for Vehicle Thermal Management Challenge: Use simulation to replace endurance testing for source of component temperature failure. Solution: Use 3D simulation of solids and air to run repeat real world test conditions. Impact: Digital prototype helps reduce costs and design time from physical testing.

22 3 Virtual Powertrain Development Combines work done by individual analysis to accurately predict metal temperature Coolant Circuit Oil Circuit Crankcase Breathing Piston Cooling In-Cylinder Simulation FEA model Exhaust/Intake Ports Exhaust/Intake Manifold Engine Thermal Prediction Concept: Bring models from different simulations to the same detailed engine CHT model to accurately predict metal temperature

23 3 General Motors In-Vehicle Engine Testing Simulation Challenge Engines that pass the dynamometer still fail when installed into the vehicle. Once vehicle design has been finalized, it can be costly to adjust cooling to the engine. At early design stages, it is important to determine possible thermal issues. Solution Use existing geometry of the engine in dynamometer and place engine in vehicle. 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. 23

24 Summary Maturity of VTM Easy to automate front end air flow CAD improving making solid conduction easier and improving component prediction. STAR-CCM+ Key Features Java based interface, easy to automate steps CAD structure to match material properties Parts based meshing to enable easy part replacement Fast surface-to-surface radiation Co-simulation to enable drive cycles Vehicle Heat Protection Toolbox Vsim: Automate aerodynamics/front end cooling C2M: Helps automate modeling solid assemblies

25 Case Study: Thank You!