Optimization and Robust Design with modeFRONTIER · 2010-07-08 · Stuttgart, 24.06.2010 FGA -...
Transcript of Optimization and Robust Design with modeFRONTIER · 2010-07-08 · Stuttgart, 24.06.2010 FGA -...
Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Optimization and Robust Design with modeFRONTIER
Application in automotive Industry
FIAT GROUP AUTOMOBILES – CHASSIS & VEHICLE DYNAMICS
Marco SpinelliChassis & Vehicle DynamicsVirtual Analysis Manager
Francesco LinaresEnginSoft GmbHTechnical Manager SW Solutions
2Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
IntroductionIntroduction : Scenario & : Scenario & TargetsTargets
Examples of DOE, ROBUST DESIGN andExamples of DOE, ROBUST DESIGN andOPTIMIZATION in Chassis & Vehicle DynamicsOPTIMIZATION in Chassis & Vehicle Dynamics
SummarySummary & & ConclusionConclusion
3Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
ScenarioScenario AutomotiveAutomotive industryindustry competitioncompetition
-12,52001 STILO
-6.52006 BRAVO2007 500 -18
-22A
nalis
isc
enar
i
Impo
staz
ion
e
Sviluppo tecnicoe tecnologico
Verif
ica
dipr
oces
so Pre-
serie
Salit
apr
odut
tiva
Scheda “0”contrattuale
Deliberatecnica
briefing job 1 Lanciocommerciale
0
-42008 Delta -16
-42008 MiTo -16
Fiat Group Automobiles Fiat Group Automobiles isis a a referencereference forfor productproduct developmentdevelopment time time
+ + QualityQuality
+ + InnovationInnovation
- - CostsCosts
- - Time Time toto market market
Key success Key success factorfactor : :
VirtualVirtual AnalysisAnalysis
4Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Virtual Analysis in chassis & vehicle dynamicsVirtual Analysis in chassis & vehicle dynamics
Vehicle :Vehicle : HandlingHandling & ride comfort & ride comfort performancesperformances mustmust bebe take in take inaccount at the account at the samesame timetime and and reachreach the Vehicle the Vehicle TecnicalTecnicalSpecificationSpecification comingcoming fromfrom targetsettingtargetsetting ofof Customer Customer CarCar ProfileProfile
SubsystemsSubsystems : : PerformancesPerformances contributioncontribution at at SubsystemsSubsystems levellevelmustmust bebe alsoalso take in account ( take in account (PTmountsPTmounts & & SuspensionSuspension System) System)
ToTo improveimprove QUALITYQUALITY and reduce and reduce TIMETIME a a betterbetter approachapproach couldcouldbebe usedused fromfrom the the beginningbeginning in in virtualvirtual analysisanalysis ofof vehiclevehicledynamicsdynamics : :
DOE DOE –– OPTIMIZATION OPTIMIZATION –– ROBUST DESIGN ROBUST DESIGN
Very high Very high potentialpotential ofof thatthat approachapproach forfor handlinghandling & ride comfort & ride comfortanalisysanalisys basedbased on on integrationintegration ofof : :
MULTIBODY SIMULATION + OPTIMIZATION TOOLSMULTIBODY SIMULATION + OPTIMIZATION TOOLS
5Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Assembling vehiclesubsystems
Analysis:
• K&C SUSPENSION• HANDLING (+driver controls)• RIDE COMFORT• FATIGUE TEST• DRIVEABILITY
Post-processing:• Automatic plotting of graphs
• Calculation of single maneuver synthesis parameters
• Calculation of Handling/Comfort/ Steering/Braking Subjective Quality Indexes
Suspension analysis Handling maneuvers
Multi-bodyModels
Assemblies/ Testrig Full-vehicle Handling Full-vehicle Comfort Suspension K&C Suspension NVH Suspension fatigue Engine …
Subsystems Front Suspension Rear Suspension Steering system Brakes system Conceptual Driveline Anti-roll bar Engine Tires Body
MultibodyMultibody : FIAT : FIAT CustomizationCustomization of of MSC.ADAMSMSC.ADAMS//CarCar
6Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
MultiobjectiveMultiobjective OptimizationOptimization tooltool : : ModeFrontierModeFrontier
Parameter values Solver Design performance
•• ProcessProcess IntegrationIntegration: : integrates any CAE softwareintegrates any CAE software
•• Design Automation: automates design processDesign Automation: automates design process
•• Design Design OptimizationOptimization: : algorithms drive design to optimumalgorithms drive design to optimum
StdA
P.C.
Input variables:Spring Stiffness and preloadBumpstop clearance and characteristicsAnti-roll bar diameterDamper characteristicsBushing characteristics
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MultiobjectiveMultiobjective optimizationoptimization & & robustrobust design : design :Adams/Adams/CarCar linkedlinked withwith modeFrontier modeFrontier
MSC.ADAMS/Car
Model modifications
Results simulation
Output and comparison objectives and constraints
Input variables
modeFRONTIER
8Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Objectives:Objectives:
Key synthesis HandlingKey synthesis Handlingparametersparameters(understeer, sideslip curve, yaw, rolling -gains, time delays)
Key synthesis ComfortKey synthesis Comfortparametersparameters (peak accelerations, timedissipations, RMS/RMF)
Input Variables, Objectives and ConstraintsInput Variables, Objectives and Constraints
Constraints:Constraints:
Ride heightsRide heights in various load conditions
Feasibility of the componentsFeasibility of the components for.ex. rate between axial and radial bushingstiffness, damper characteristics, bumpstoplength and characteristics etc.
Performance constraintsPerformance constraints
StdA
P.C.
Tarature ammortizzatore posteriore 263confronto con tarature X250
-2000
-1500
-1000
-500
0
500
1000
1500
2000
2500
3000
3500
4000
-3000 -2500 -2000 -1500 -1000 -500 0 500 1000 1500 2000 2500 3000
velocità [mm/s 2̂]
Forz
a [N
]
REAR_MVmuletto validato CRF
ISO SMORZANTE 223
Minimo realizzabile per 263 conammortizzatore attuale
MT104
92
93
94
95
96
97
98
99
100
101
0 200 400 600 800 1000 1200
Rigidezza verticale [N]
Eff
icie
nza
am
mo
rtiz
zato
re [
%]
frequency response - lateral acceleration / steering angle80 km/h 0.45g
0.0000
0.0020
0.0040
0.0060
0.0080
0.0100
0.0120
0.0140
0.0160
0.0180
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
AY
/DV
OL
- gai
n (g
/deg
)
263 Muletto c a lc o lo pneumMule (195 "Stilo")
223 s perim pneumMule (195 "Stilo")
263 target
263 7q rev 4 pneumMule (195 "Stilo")
-0 .25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
AY
/DV
OL
- pha
se (s
)
frequency response - yaw rate / steering angle80 km/h 0.45g
0.000
0.050
0.100
0.150
0.200
0.250
0.300
0.350
0.400
0.450
0.500
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
PS
IP/D
VO
L - g
ain
(1/s
)
263 Muletto c a lc o lo pneumMule (195 "Stilo")
223 s perim pneumMule (195 "Stilo")
263 target
263 7q rev 4 pneumMule (195 "Stilo")
-0 .14
-0.12
-0.1
-0.08
-0.06
-0.04
-0.02
0
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
PS
IP/D
VO
L - p
hase
(s)
frequency response - side slip angle / steering angle80 km/h 0.45g
0.0000
0.0100
0.0200
0.0300
0.0400
0.0500
0.0600
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
BE
TA/D
VO
L - g
ain
(deg
/deg
)
263 Muletto c a lc o lo pneumMule (195 "Stilo")
223 s perim pneumMule (195 "Stilo")
263 target
263 7q rev 4 pneumMule (195 "Stilo")
-0 .4
-0.35
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
BE
TA/D
VO
L - p
hase
(s)
frequency response - side slip angle / steering angle100 km/h - 0.4 g
0.0000
0.0100
0.0200
0.0300
0.0400
0.0500
0.0600
0.0700
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5frequency (Hz)
BET
A/D
VOL
- gai
n (d
eg/d
eg)
Option 1
Option 2
Input variables:Input variables:
Suspension Vertical Stiffness andSuspension Vertical Stiffness andDampingDamping(spring, shock absorber)(spring, shock absorber)
Suspension LongitudinalSuspension LongitudinalStiffness and DampingStiffness and Damping (bushings,(bushings,shock absorber)shock absorber)
Suspension Rolling stiffnessSuspension Rolling stiffness(spring, anti-roll-bar)(spring, anti-roll-bar)
Suspension Suspension Elasto-KinematicElasto-KinematicInput variables:Spring Stiffness and preloadBumpstop clearance and characteristicsAnti-roll bar diameterDamper characteristicsBushing characteristics
9Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
DOE Study and Optimization MethodDOE Study and Optimization Method
Preliminary Study :DoE Study (Sobol/Reduced-factorial distribution) =>Selection of principal variables / constraints / objectives
Main Study : DoE Study or DoE Study + Optimization of alimited number of input variables & objectivesusing detailed model or response surfaces Pareto FRONTIER => Selection of “optimum”solutions of vehicle target setting Robustness evaluation of Pareto optimalsolution
Main Influences(Inputs and Outputs)
Linear and non-linearcorrelations
Target feasibility
-16% -12% -17% -14% -30%
Target feasibility & optimization
Results of DOE study:
Sensitivity and correlationdirect/inverse of design variables vs targets &between each design variables
Principal Heavy costraints(boundary condition)
Main Goal DOE / Optimization:
Optimization of targets
Trade-off scenarios
Robustness of solutions
10Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
IntroductionIntroduction
Examples of DOE, ROBUST DESIGN andExamples of DOE, ROBUST DESIGN andOPTIMIZATION in Chassis & Vehicle DynamicsOPTIMIZATION in Chassis & Vehicle Dynamics
SummarySummary & & ConclusionConclusion
11Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Handling & Ride ComfortHandling & Ride Comfort
K&C SuspensionK&C Suspension PT Mounts SystemPT Mounts System
Suspension NVH - HandlingSuspension NVH - Handling Active Systems (ARB)Active Systems (ARB)
Focus on Focus on Timing & optimization resultsTiming & optimization results Method comparison Method comparison
ApplicationsApplications –– some some examplesexamples
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Angolo d’Assetto
Velocità d’Imbardata
frequency response - lateral acceleration / steering angle100 km/h - 0.5g
0.0000
0.0050
0.0100
0.0150
0.0200
0.0250
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz )
AY/DV
OL -
gain
(g/de
g)
Sol 125
BASE Progetto 263
Sol 105
Sol 162 (90)
Sol 162
-0.4
-0.35
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
AY/DV
OL - p
hase (s
)
frequency response - yaw rate / steering angle100 km/h - 0.5g
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
PSIP/D
VOL -
gain (1
/s)
Sol 125
BASE Progetto 263
Sol 105
Sol 162 (90)
Sol 162
-0.18
-0.16
-0.14
-0.12
-0.1
-0.08
-0.06
-0.04
-0.02
0
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
PSIP/D
VOL -
phase
(s)
frequency response - side slip angle / steering angle100 km/h - 0.5g
0.0000
0.0100
0.0200
0.0300
0.0400
0.0500
0.0600
0.0700
0.0800
0.0900
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
BETA
/DVOL
- gain
(deg/d
eg)
Sol 125
BASE Progetto 263
Sol 105
Sol 162 (90)
Sol 162
-0.45
-0.4
-0.35
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
frequency (Hz)
BETA
/DVOL
- phas
e (s)
Frequency Response
Accelerazione Vert. Guida Sedile
Accelerazione Long. Guida Sedile
Handling&ComfortHandling&Comfort
DOE & Optimization handling&comfort performances
Simulated manoeuvers :K&C : ElastokinematicsHandling : Sweep, Step SteerComfort : Obstacle passing, Motorway, Pavè
9 input variables6 objectives12 constraints7 maneuvers350 designs:70 Sobol x 5 MOGA-II iterationsalt. 350 Sobol3.5 days
Input Variables Constraints Objectives - Spring stiffness and preload - Vehicle Heighs (different load conditions) Handling&Comfort synthesis parameters
- Bumpstop clearance and stiffnesses - components feasibility - Roll,Pitch,yaw velocity,sideslip angles
- Bushing stiffnesses X,Y,Z - time delays,pk/gain frequency
- Shock-absorber characteristics - Peak/peak obstacle passing
- ARB diameter
K&C models Handling model Comfort model
Results:Performance targetoptimization
13Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Ride Comfort (Handling Constraints)Ride Comfort (Handling Constraints)
Simulatedmanoeuvers :K&C : Elastokin.Handling : Sweep, Step SteerComfort : Ostacle, Hole, Pavè track Motorway
SFSF SFSF
SFSFSFSF
DOE & optimization comfort performances satisfying handling targetsInput Variables Constraints Objectives
- Spring stiffness and preload - Vehicle Heighs - Seats acceleration (RMF, amplitude)
- Bumpstop clearance and stiffnesses - components feasibility - Peak/peak obstacle passing
- Bushing stiffnesses X,Y,Z Handling parameters : - body motion (velocity&acceleration)
- Shock-absorber characteristics - gain ay,Theta,Psip,Beta
- time delays Psip/Ay,…
7 input variables9 objectives9 constraints14 maneuvers300 Sobol alt.80 Sobol +MOGA-II 4iterations => 320designs
! = 25.5% ! = 19% ! = 18.8% ! = 0.06 g ! = 0.11 g ! = 16 % ! = 10 %
Run_RMS_PHI Run_RMS_PHIP RMS_ZZP_4_12Hz HW_RMS_ZZG AZ_F AZ_R EN_RMS_ZZG EN_RMS_ZZP
Results:Max performance allowed underconstraintsDriver characteristics 0.00
0.050.100.150.200.250.300.350.400.450.50
0 1 2 3 4
Freq [Hz]
Gai
n [1
/s]
ID0 ID65 ID112 ID318
ISO-Handling
Improved Ride-comfort
14Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Approach :1. DOE + optimization to find Pareto solutions. –>Robust Design of Pareto Solutions
including STDEV as parameter2. DOE & optimization including STDEV for all interesting inputs from the beginning
Input Variables (noise variables) Constraints Objectives - Spring stiffness and preload - Vehicle Heighs (different load conditions) Handling&Comfort synthesis parameters
- Bumpstop clearance and stiffnesses - components feasibility - Roll,Pitch,yaw velocity,sideslip angles
- Shock-absorber characteristics - time delays,pk/gain frequency
- STD DEV Parameters - Peak/peak obstacle passing
Input Variables (optimization var.) - Bushing stiffnesses X,Y,Z
Handling & Comfort Handling & Comfort RobustRobust Design Design
DOE & Robust design of handling & ride comfort performances
Best compromise time - accuracy :1. Large DOE with evaluation main parameters, correlation inputs-outputs,correlation
between objectives2. Reduction of number of input variables & objectives using direct / inverse correlation3. New DOE + optimization to find Pareto solutions4. Evaluation of Pareto solutions including stdev – check max/min performances
15Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Statistic distributioninput variables
Full-vehicle analysis
Optimization of MEANand STDEV
Nominal value
Handling Output
One of ParetoFRONTIER optimum
set-upsbefore Robust Study
Optimum set-upchosen after Robust
StudyOptimization of nominalperformance
50 Sobol + MOGA-II 5iterations => 250designs
25 Sobol x 26 LHS +MOGA-II 5 iterations=> 3300 designs
Handling & Comfort Handling & Comfort RobustRobust Design Design
Results:Robust design evaluation of handling & ridecomfort performances
4 input variables6 objectives2 constraints7 maneuvers
16Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
K&C SuspensionK&C Suspension
Results:Correlation & Sensitivity input/outputvariables
Correlation design variables vs targets
Optimization of K&C targets
DOE & Optimization K&C targets new suspension layout
16 input variables8 objectives5 constraints4 analysis1000 designs: 200 Sobol x 5 MOGA-II iterations17 hours
K&C curve
NP
Strictly correlated outputparameters
Input Variables Constraints ObjectivesSuspension attachments : Layout bushing feasib. Elastokinematics parameters :
- geometry X,Y,Z Durability - toe & camber gain
- Bushing characteristics X,Y,Z - Wheelbase & track var. vs Fx,Fy,Fz
PT1
PT2
PT10
CamberToe PT1
CamberToe
Simulated manoeuvers(ride height StdA & 2P) :
Parallel travel
Lateral load 2W parallel
Braking 1W
17Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
K&CK&C Robust Design Robust Design
Results:Influence of geometric tolerances on K&C and handling VTS
DOE & Robust design of suspension characteristics and tolerances analysis
Influences from input variableson handling output parameter
Influences from input variableson K&C output parameter
0.127 – 0.137s
TPsipAy 0.5Hz
KDVOL
68 – 75 deg/g
0.127 – 0.137s0.127 – 0.137s
TPsipAy 0.5Hz
KDVOL
68 – 75 deg/g68 – 75 deg/g
Input Variables Constraints Objectives - Geometric Tolerances of suspension attach. - K&C
- Handling VTS
18Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Simulated manoeuvers:Static analysis (loads fatigue &misuse)Dynamic analyses (idle,WOT)Ride comfort pavè & motorway
PT PT MountsMounts System System
x1x2x4 x3
K lin
K t
K t
x1x2x4 x3
K lin
K t
K t
12 input variables9 objectives4 maneuvers500 designs:100 Sobol x 5MOGA-II iterations
Input Variables Constraints Objectives - Geometry (Elastic center) - components feasibility - Force trasmission,working points
- Mounts stiffnesses characteristics (X,Y,Z ) - geometry layout - RMS/RMF seat acceleration
- peak acceleration
Optimization of PTMounts System
Targets Force trasmission& geometry Targets Force trasmission& stifnesses
Ride comfort Filtering AV3
Results:Optimize engine suspension characteristics in multiple missionTrade off in performances ride comfort , idle & acoustic
19Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Suspension NVH - HandlingSuspension NVH - Handling
30 60 120 160
1 2 3 4 Mod 1 Mod 2
Mod 3 Mod 4
Results:NVH-Ride Optimization determiningoptimum vehicle set-ups consideringHandling constraints. Responsesurfaces used for FEM modelanalysis and final optimization.
DOE & Optimization forces trasmitted from suspension
3 Models• K&C• Comfort• State SpaceMatrix 8 input variables
5 objectives3 constraints4 analysis/maneuvers500 designs:100 Sobol x 5 MOGA-II iterations1.5 days
Input Variables Constraints Objectives - Bushing stifnesses X,Y,Z Handling performance : Ride performance :
- toe vs Fy, toe vs Mz - Peak/peak obstacle passing
- camber vs Fy - Med./High frequency force trasmission
20Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
modeFrontier - ADAMS - Matlab modeFrontier - ADAMS - Matlab co-simulationco-simulation
New front active ARB
Results:- Handling and comfort targets,- Correlation & sensitivity input/output variables- Study of controls in all vehicle condition
Active Systems : DoE handling and comfort parameters
modeFRONTIER
MSC.ADAMSMatlab/Simulink
InputVariables
Outputs,Objectives &Costraints
MSC.ADAMS
Matlab/Simulink
16 input variables12 objectives6 constraints5 analysis250 designs: 250 Sobol
Input Variables Constraints Objectives - Spring stiffness and preload - specific handling parameters - Handling & Comfort VTS
- Shock-absorber characteristics
- Bushing stiffnesses X,Y,Z
21Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
DOE-Optimization Study resultsDOE-Optimization Study results
Simulation Time %Perf. Improv.
Handling&Comfort 15min/design, 350designs => 3.5ggr 15%
Handling / Comfort Robust Design 8min/design, 3300 designs => 20ggr 10%
K&C Suspension 1min/design, 1000designs => 17h 25%
PT Mounts System 4min/design, 500designs => 1.3ggr 30%
Co-simulation MSC.ADAMS-Matlab Active Control System 70min/design, 250designs => 10ggr +10% of feasible
design
Suspension NVH 4min/design, 500designs => 1.5ggr +25% of feasible design
22Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
Handling and Ride-Comfort Handling and Ride-Comfort PerformancesPerformancesComparisonComparison betweenbetween traditionaltraditional & & multi-objectivemulti-objective optimizationoptimization approachapproach
Methods Comparison Methods Comparison –– a test case a test case
Handling/Comfort simulation - test case TRADITIONAL APPROACH
MULTIOBJECTIVE OPTIMIZATION APPROACH
Needs Knowledge and experiences about
vehicle dynamics & simulation
Knowledge and experiences about vehicle dynamics & simulation . Basic
knoledge of Doe, optimization techniques
Method ‘Trial and error’ Multiobjective & statistical
Human time dedicated (pre/post) 8 days 3 days
Calculation time 1 day 5 days
Total time 2 weeks < 2 weeks
Human activities 80% for model modification & run , 20% postprocessing
20% for model modification & run , 80% postprocessing and scenarios
analysis Numbers of solutions / scenarios evaluated : X 10X – 100X
Optimal performance reached 70-80% 100%
23Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
IntroductionIntroduction
Examples of DOE, ROBUST DESIGN andExamples of DOE, ROBUST DESIGN andOPTIMIZATION in Chassis & Vehicle DynamicsOPTIMIZATION in Chassis & Vehicle Dynamics
SummarySummary & & ConclusionConclusion
24Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
SummarySummary
Fiat’s latest success products, were developed using intensive use of virtual analysisin only 16-18 months.
New target for future projects : increment of virtual analysis to reduce cost & timedevelopment and to allow more robust experimental testing
DOE, Robust design & multiobjective optimization are success key factor
The use of modeFRONTIER in Chassis Virtual Analysis as a DOE or/and optimizationtool enables:
To Reduce time and calculation loops To Gain a deeper understanding of the system and the correlation between input variablesand output parameters To increase possibility to explore best solutions & scenarios To evaluate robust and stable solutions
25Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
ConclusionConclusion & & nextnext stepssteps……
Advantages in extended application :
REDUCTION OF DEVELOPMENT TIME VEHICLE TESTING & EXPERIMENTAL TUNING QUALITY ORIENTED APPROACH THE OPTIMUM SOLUTION ALREADY FROM THE BEGINNING TARGET FEASIBILITY & MAIN COSTRAINTS ARE KNOWN FROM EARLY PHASE CLEAR & OPTIMIZED TRADE OFF OF PERFORMANCES EXPLORE BEST SCENARIOS AND GIVE MORE CHOISES TO MANAGEMENT
Don’t forget to improve…
Model complexity & detail of physical systems and components Statistical approach in model correlation : numerical model & measurements statisticallycorrelated
... Words to take in mind...
“DOE - OPTIMIZATION - ROBUST DESIGN”
26Stuttgart, 24.06.2010 FGA - Engineering & Design – Chassis & Vehicle Dynamics – Virtual Analysis
ThanksThanks ! !
Thank you for your attention