Enabling Advanced Vehicle Heat Protection Through the Digital - - PowerPoint PPT Presentation

Enabling Advanced Vehicle Heat Protection Through the Digital Prototype

Frederick J k J. R . Ross Di Director, Gr , Ground nd T Trans nsportation n

Agend nda

STAR-C

• CCM+ De

Designe ned f for V Vehi hicle le H Heat P Protection n

Over 25 years of experience STAR-CCM+ Design Focus on VTM Benefit of Siemens

Automa mation t n tools ls t to he help lp r reduce t turn-a n-around nd t time me

Vsim: Automating Front End Air Flow C2M: Automating Component Modeling

Case S Studies

STAR-C

• CCM+ F

For V Vehi hicle le T The herma mal M l Mana nageme ment nt

v2.0 was first enabler using client-server with mesh generation

Solv lver T Team m

New Client Server Cell Quality Remediation Heat Exchanger Models Fast S2S Radiation Shell Conduction Co-Simulation Parts Based Profile

Mesh De h Develo lopme ment nt T Team m

Surface Wrapping: Clean Surface Bring in CAD Tree Imprint/Boolean Operations Thin Mesher Parts Based Meshing Parallel Trimmer Concurrent Meshing

STAR-CCM+ V2: 2006 STAR-CCM+ V11: 2016 Robustne ness Job needs to run with minimum user interaction.

1 1

Reduce T Turn A n Around nd Automation Ease-of-Use Quick Modifications

2 2

Accuracy y Need to simulate real world test conductions

3 3 Go Goals ls 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 2 2 3 3 2 2 3 3 2 2 2 2 1 1 1 1

Vehi hicle le T The herma mal M l Mana nageme ment nt M Maturity R y Roadma map

1 1 2 2 3 3 4 4 5 5 Complexity

Full Vehicle Thermal Management

• 4000+ solids
• Coolant/Oil etc
• Drive Cycle Simula?on

5

Power Train Cooling

• Engine CHT
• Coolant
• Oil, Intake/Exhaust Flows

4

Brake Cooling

• Radia?on & CHT
• Rota?ng Parts/Fric?on Hea?ng
• Op?mize Cooling

2

Exhaust System CHT

• 100-400 Solids
• Radia?on & CHT
• Heat Shield Design/

Placement

3

Front End Air Flow

• Top Tank Temperature

Predic?on

1 Level 1 l 1

• Fully automatic
• Single or Dual Stream
• No Solid Modeling
• Fast turn-around time

Level 2 l 2: S : Simu mula lation o n of S Sys ystems ms

• Automating Procedures
• 40-400 Solids + Radiation

Level 3 l 3: V : Virtual P l Prototyp ype

• Working from CAD to Simulation
• Simulating Systems: Solids/Fluid
• 4000 + Solids with Radiation & co-sim

Ge Gene neration o n of a a Di Digital P l Prototyp ype

Producing a a d digital t twin

CAD Da D Data F Freeze d define nes d digital p l prototyp ype

– 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.

Analysis Response

– Feeds back into the data pool for design improvement.

Deflection speed v Damping force F Grade 1 Grade 2

Geometrical Data Functional Data

The he c cle lear le leader a amo mong ngst P PLM s solu lution p n providers i in s n simu mula lation a n and nd t test s software, a , and nd a associated s services. .

Sieme mens ns P PLM S Software + + C CD-a D-adapco: :

Market L Leader i in S n Sys ystems ms Dr Driven P n Product De Develo lopme ment nt

§ 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

STAR-C

• CCM+

HEEDS DS Optima mate SPEED D BDS DS

§ 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)

Virtual.L l.Lab Samt mtech h Ima Imagine ne.L .Lab Test.L .Lab

§ Streamlines and accelerates the product development process in a collaborative environment § Includes a modern, multi-discipline CAE environment

NX C X CAD D NX C X CAE Nastran n Teamc mcent nter Tecno noma matix

Ge Gene neration o n of a a Di Digital P l Prototyp ype

Producing a a d digital t twin

TeamC mCent nter

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

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

Geometrical Data

Deflection speed v Damping force F Grade 1 Grade 2

Functional Data

CAD Import

• Parasolid Files
• Team Center Interface
• STL Data

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

Solid CHT

• CAD cleanup
• Build Interfaces between parts
• Concurrent meshing

Co- simulaPon

• Parallel Surface-2-Surface RadiaPon
• Solids run full thermal transient
• Fluid either steady or transient

STAR-C

• CCM+ W

Workf kflo low

8 8

Computational Process & Tools radiation conduction convection

• il

coolant exhaust driving cycle 1D thermal network

So Source rce: M.

• M. Disch

isch ( (upco comin ming Ph Ph.D thesis sis, FKF KFS) S)

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.

Front End Air Flow Workflow

Page 9 April 3, 2014

Solid Conjugate Heat Transfer Model

Go Goal l

Predict lo local c l compone nent nt t temperature

Typ ypical A l Appli lications ns

Components Surrounding Exhaust Brake Cooling

Im Important nt P Phys ysics

Convection Conduction Radiation

Solu lutions ns

Convection: Vsim Conduction: Parts Based Meshing Framework

C2M: Cad to Mesh Tool

Radiation: Parallel Surface-to-Surface

2

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

Solid Conjugate Heat Transfer Workflow

April 3, 2014

Agend nda

STAR-C

• CCM+ De

Designe ned f for V Vehi hicle le H Heat P Protection n

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 S 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.

VS VSim: A : Aero/The herma mal A l Automa mation n

STAR-CCM+ reading setup information directly from excel Automa mated P Process f from C m CAD t D to R Report Reads CAD from subdirectory Spreadsheet Contains Settings

• CAD Grouping to CFD Boundaries
• Heat Exchanger/Fan Information
• Thermal Boundary Conditions

Run: Me Mesh sh/So Solve lve/Po Post st Output: Po PowerPo rPoin int Input: Cad/Exce Excel l Run: Me Mesh sh/So Solve lve/Po Post st 1 1

VS VSim: A : Aero/The herma mal A l Automa mation n

STAR-CCM+ reading setup information directly from excel 1 1

1

• OperaPng

CondiPons

2

• Group CAD to

Boundaries

3

• Mesh SeYngs

4

• Fan/Heat Exchanger

ProperPes

5

• Monitors and Post

Processing

Automa mation: C n: C2M T Toolb lbox

Che hecks ks S Surface f for e errors Repair p parts w with s h severe e errors

Move into surface repair Alternatively wrap/replace part

Ge Gene nerate V Volu lume me me mesh h

Sets up parts based meshing tree

Find nd a and nd Ge Gene nerate Int Interfaces b between n compone nent nts 2

Agend nda

STAR-C

• CCM+ De

Designe ned f for V Vehi hicle le H Heat P Protection n

Over 20 years of experience Focus of STAR-CCM+ since version 2.0 Benefit of Siemens

Automa mation t n tools ls t to he help lp r reduce t turn-a n-around nd t time me

Vsim: Automating Front End Air Flow C2M: Automating Component Modeling

Case S Studies

Case Case St Study:

Cha halle lleng nge: : In Investigation o n of o

• verall a

ll aerodyna ynami mic d drag r reduction n impact o

• n f

n front nt e end nd c cooli ling ng i is d difficult lt t to p predict experime ment ntally lly. . Solu lution: n: Simu mula lation c n can b n be u used t to lo look a k at c cooli ling ng d drag a at both 5 h 55mph a h and nd 1 120mph t h to e ens nsure a aerodyna ynami mic drag r reduction s n still me ll meet c cooli ling ng r requireme ment nt. . Im Impact: : Di Digital p l prototyp ype c can a n aid e eng ngine neer t to r reduce

• verall e

ll ene nergy u y used b by v y vehi hicle le, i , inc nclu luding ng aerodyna ynami mics d drag t to f front nt e end nd c cooli ling ng. .

Full V ll Vehi hicle le A Aero-The herma mal C l Cooli ling ng Dr Drag S Sens nsitivity A y Ana nalys lysis

Cranf nfield ld U Uni niv., J ., Jaguar L Land nd R Rover SA

SAE 2016-01-1578

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

18 | Copyrig yright 2014 -

• Red Cedar

r Tech chnolo logy: y: All All Rig ights s Rese serve rved

A U T O M O T I V E Baseline Optimized Optimization process

Vehicle Drag Load Case Radiator Temp Load Case

1 1

Case Case St Study:

Cha halle lleng nge:

:

Use computational methods for prototype development Reduce turnaround time for prediction of thermal behaviour in driving cycles

Solu lution:

:

Transient Vehicle Thermal Management approach in STAR-CCM+ Co-Simulation of a transient solid model with steady state fluid model Comparison with measurements

Im 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

Thermal Management of Dynamic Driving Cycles

Da Daimle mler A AG

3 3

Steady-S

• State F

Full V ll VTM S Simu mula lation n Airflo low + + S Soli lids u using ng C Co-S

• Simu

mula lation n

• Airflow model is

50+ million cells.

• Solid Model is

40+ million cells.

• Over 5000 solid

components modeled in the simulation

Case Case St Study:

Cha halle lleng nge: : Us Use s simu mula lation t n to r repla lace e end nduranc nce t testing ng f for source o

• f c

compone nent nt t temperature f failu lure. . Solu lution: n: Us Use 3 3D s D simu mula lation o n of s soli lids a and nd a air t to r run r n repeat r real l world ld t test c cond nditions ns. . Im Impact: : Di Digital p l prototyp ype he help lps r reduce c costs a and nd d design t n time me from p m phys ysical t l testing ng. .

Simu mula lating ng t the he Id Idle le: A : A N New L Load C Case f for V Vehi hicle le T The herma mal M l Mana nageme ment nt

Da Daimle mler A AG S G SGC GC 2 2016

3 3

Virtual Powertrain Development

Combines work done by individual analysis to accurately predict metal temperature Concept: Bring models from different simulations to the same detailed engine CHT model to accurately predict metal temperature

Engine Thermal Prediction In-Cylinder Simulation Coolant Circuit Oil Circuit Crankcase Breathing Piston Cooling FEA model Exhaust/Intake Ports Exhaust/Intake Manifold

3 3

Cha halle lleng nge

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.

Solu lution n

Use existing geometry of the engine in dynamometer and place engine in vehicle.

Im 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.

In-Vehicle Engine Testing Simulation

Ge Gene neral M l Motors

23

3 3

Maturity o y of V VTM

Easy to automate front end air flow CAD improving making solid conduction easier and improving component prediction.

STAR-C

• CCM+ K

Key F y 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

Vehi hicle le H Heat P Protection T n Toolb lbox

Vsim: Automate aerodynamics/front end cooling C2M: Helps automate modeling solid assemblies

Summa mmary y

Case Case St Study:

Tha hank Y nk You!