Simulating Systems in Ground

Vehicle Design Frederick J. Ross

Director, Ground Transportation

Maturity of Simulation

– Growing from validation to virtual simulation

Simulating Systems

– Driving virtual prototype to look at early design behaviors

Agenda: Simulating Systems

System Simulation Maturity Model

Validate (software)

Troubleshoot

Predict

Automate

Optimize

Ultimate Goal: Find best design in shortest time

Increased

ROI

Critical inversion point

(from reactive to

proactive engineering)

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

Powertrain Simulation Roadmap

Component Analysis • Port Flow • Coolant Flow • Intake/Exhaust Manifold flow

1 Transient Behavior • Couple Simulation to 1D Code • Look at EGR mixing • Exhaust manifold temperatures

2

System Analysis • Coolant Filling • Crank Case Ventilation • Oil Circuits • Turbo Charger • Aftertreatment

3

Environment Evaluation • Dynamometer Testing • Engine in Vehicle • Drive Cycle Simulation

4

Inc

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Complexity

Validate

Troubleshoot

Predict

Automate

Optimize

Component Analysis System Analysis

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!

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

Automation: The SCR Simulation Assistant

Coolant Jacket Simulation Assistant Guiding the user through set up and post processing

of a Cylinder Block / Head Coolant Jacket.

4.38M Cell Polyhedral Mesh

Coolant Inlet Gasket Holes

Baseline Design

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 DOE-optimized design • 7% reduction in max head temperature

– 16 feasible designs in highly constrained design space

8

Optimization Process Optimal Design

Optimal Design

Improvement in Cooling Jacket Temperature

Variation Baseline Optimized

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.

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

DOC

(Diesel Oxidation Catalyst)

Spray Injector

SCR

DPF

(Discrete Particle Filter)

Mixers

Flow

outlet

Flow

inlet

SCR Simulation Roadmap

Uniformity Test • Urea Injection • Wall Modeling • Urea/Gas Mixing Optimization demo exists

1 NOx Prediction • Surface Chemistry • Detail Chemistry Using DARS Clients have validate results

2

Crystallization Prediction • Full Chemistry • Solidification prediction

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Complexity

Validate

Troubleshoot

Predict

Automate

Optimize

Vehicle Thermal Management Roadmap

1 2 3 4 5 6 7

Front End Air Flow • Top Tank Temperature

Prediction • Turn-Around: 1 Day

1

Local Component Temperature • 30-60 Solids • Local to a component

2

Total Vehicle Simulation • Using existing sub-models 4

Underbody Temperature • ~ 100 Solids • Includes Exhaust System, hangers,

engine mounts, heat shields

3 Power Train Cooling • Full Engine CHT model • Induction System • Exhaust System • Oil Flow

5

Full Vehicle Thermal Management • Conduction/Radiation using

Radtherm • Includes Drive Cycle Simulation

6

Full Vehicle Thermal Management • Co-Simulation from STAR-

CCM+ to STAR-CCM+ • 4000 Solid Components • Includes Drive Cycle

Simulation via Ports

7

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GUM: Grand Unified Model • Complete vehicle simulation

• 4000+ Solid Components • Cabin Thermal Comfort • Vehicle Aerodynamics • HVAC Simulation • Electronics Cooling

• Co-Simulation STAR-CCM+ to STAR-CCM+

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Complexity

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Simulation using the Digital Prototype

Durability

(BiW) Crash

NVH

Ride/Handling

HVAC/

Thermal Comfort

Durability

Chassis

Aerodynamics

Climate Control

Heat

Protection

Manufacturing

Powertrain Transmission

Digital Prototype becomes enabler

for advance simulation

– Simulation for more advance

analysis then just component design

– 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.

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.

0

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0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8

Deflection speed v Dam

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Grade 1

Grade 2

Geometrical Data Functional Data

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.

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.

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

1

0

500

1000

1500

2000

2500

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0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8

Deflection speed v Dam

pin

g f

orc

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Grade 1

Grade 2

Geometrical Data Functional Data

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

1

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

2

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.

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“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

6

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

7

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 turn-around 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

System Simulation: Thermal Analysis & Design

Improvement of an Internal Air-Cooled Electric

Machine

Challenge: Use simulation to

improve the thermal

performance of an internal air-

cooled induction machine

Solution: Compute EM losses in

SPEED and map as heat loads to STAR-CCM+

EM Loss/Heat Loads

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.

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

System Simulations: Transmission

Key Enablers:

• Overset Grids

• Robust VOF Simulation

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.

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“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

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

System Simulation: Cabin Comfort

System Simulations: Manufacturing

Drying

Paint Dip/E-Coat

Spray Paint

Casting

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.

Summary

Thank You!