bogie07 part1 low
TRANSCRIPT
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BOGIE 07 Con ference
September 3rd 6th , 2007
Budapest HUNGARY
Numerical simulation for improving the design ofrunning gear Part 1: improvement of vehicledynamic behaviour
Paolo BELFORTE,S. BRUNI (Politecnico di Milano - Department of Mechanical Engineering)
Michael JCKEL (Fraunhofer Institute for Structural Durability and System Reliability - LBF)
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Paolo Belforte (Politecnico di Milano - Italy)
MODTRAIN Project
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Innovative modular vehicle concepts for an integratedEuropean railway system
6th FRAMEWORK PROGRAMME PRIORITY 6.3 Transport
4 Years Project Started January 2004
MODTRAIN project
Modular approach to train design
Interoperability: new generation rolling stock
Harmonised European criteria for rolling stockhomologation
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Paolo Belforte (Politecnico di Milano - Italy)
MODTRAIN Project
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It consist of five different sub-projects:
MODBOGIE
MODCONTROL
MODPOWER
MODLINK
MODUSER
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Paolo Belforte (Politecnico di Milano - Italy)
INTRODUCTION: NUMERICAL SIMULATIONSTOWARDS VIRTUAL HOMOLOGATION
5
In last years, the improved calculation technologies allowed the
development ofmore detai led and accu rate num erical models ofrai l vehicle dynam ics, which can be used as a very useful tool forthe design and development of a railway stock.
With the development of new generations of HS trains,numerica l simu lat ions can g ive an im por tant contr ibut ionin order
to raise service speed and satisfy operators requirements whichclaims always for improved performance in terms of comfort andsafety
This work targets the capabilities of multi body simulationmodels in the design and verification phase of the railway running
gear.
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INDEX
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Paolo Belforte (Politecnico di Milano - Italy) 7
Vehicle model:HS concentrated power locomotive
Carbody with two motor bogies
Two motors bogie-suspended by means ofdedicated motor hangers per each bogie
VEHICLE SCHEMATISATION
41,,,,....;;;;;
T
w
T
w
T
enr
T
br
T
enf
T
bf
T
c
T
V qqxxxxxx
The equation of motion Lagrange equations txxQxQvxxQQxKxRxM VVCVnlVVmVVVVVVV ,,,,
REFERENCE SYSTEMS
W/R contact
forces
Vehicleinertia
Fixedreference
Moving referencewith constantspeed V
Moving referenceon body c.o.g .
XG
ZG
YG
Xo
ZoYo
ZGi
YGi
V
si
bi
ri
Loco of a concentrated power train
Only rigid modes also for the wheelsets problem confined to low frequency
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tread contact1
2
1
2
FN1
FL1
FT1
FL2
FT2
FN2
flange contact
rail and wheel profiles contact geometricalparametersgeometrical analysis
elastic deformation innormal direction
(penetration)
tangential & longitudinalcreepages
generalizedcontact forcestangential & longitudinalforces
(Shen-Hedrick-Elkinstheory)
normal forces(multi-hertzian model)
Wheel rail contact forces model
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COMPARISON A.D.Tre.S. SIMPACKEigenvalues and time histories comparison
9
Natural frequencies comparison
Z
Xz
x
z
x
V
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
NaturalFrequency
[Hz]
Vertical Lateral Yaw Pitch Roll
ADtres
Simpack
Carbody natural frequencies
Straight track with concentrated
track defect: 5 mm lateral and 14 mrad roll;
20 m wavelength;
speed 72 km/h.
Leading Wheelset of Bogie 1:
Vertical Force at Right Wheel
60000
64000
68000
72000
76000
80000
84000
88000
92000
96000
100000
2 3 4 5 6 7
Time [s]
For
ce
[N]
Simpack
ADTreS
Leading Wheelset of Bogie 1:
Lateral Force at Right Wheel
-6000
-4000
-2000
0
2000
4000
6000
2 3 4 5 6 7
Time [s]
For
ce
[N]
Simpack
ADTreS
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INDEX
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Tuning procedure by sensitivity analysis
TYPE OF ANALYSIS :parametric analysis on primary
suspension parameters and bogie wheel-base:
straight track running behaviour->critical speed
curve negotiation ->steady state Q (vertical force values)
steady state Y (lateral force values)
steady state wear index
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Tuning procedure by sensitivity analysis:effect of wheel-base
Vehicleconfigurations
Wheelbase[m]
Cz[kN/mm]
Cy[kN/mm]
AD 3 10 18V1 2.7 10 18V2 2.5 10 18
Reducing the wheelbase the critical
speed decreases
Reducing the wheelbase the vehicle has a
better steering behaviour
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Tuning procedure by sensitivity analysis:effect of wheel-base
Vehicleconfigurations
Wheelbase[m]
Cz[kN/mm]
Cy[kN/mm]
AD 3 10 18V1 2.7 10 18V2 2.5 10 18
Reducing the wheelbase the track shiftforce is lightly increased
Wear index is lower in case of reducedwheelbase
Radius curve [m]
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INDEX
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Analysis of technological options: virtual dynamic
homologation simulation acc. to EN14363
Vehicle configurations taken into account for EN14363 full
analysisVehicle
configurationsBogie
Wheelbase[m]
Longitudinal axleboxstiffness[kN/mm]
Lateral axleboxstiffness [kN/mm]
Reference 3 10 18
V1 3 30 15
V2 2.5 30 15
Three curve ranges are considered:
Small radius curve (250 400 m);
Medium-small radius curve (400 600 m); Large radius curve (600 2500 m) .
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Virtual dynamic homologation procedure: main
curving indexes
TRACK SHIFT FORCEEN14363 limit
EN14363 limit
Y/Q
VERTICAL FORCE
EN14363 limit
Main parameters are obtained for all vehicle configurations
Vi t l d i h l ti d
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Virtual dynamic homologation procedure:
critical speed and wear index.
WEAR INDEX CRITICAL SPEED
Additional information is the wear index which can be used for the
evaluation of the aggressiveness of the vehicle.
S iti it l i d tt di ti
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Sensitivity analysis and scatter prediction
Numerical simulation can be used even for the evaluation of the
impact of the scatter variation of vehicles parameters on runningbehaviour.
S iti it l i d tt di ti
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Sensitivity analysis and scatter prediction:effect of damper parameters
Exemplary Simulation Results (12 Parameters Varied Simultaneously): example ofthe correlation of the damper parameters with vertical wheel/rail contact forces.
0 2 4 6 8 10 12
x 104
9.6
9.65
9.7
9.75
9.8x 10
4
D11
0.5 1 1.5 2 2.5 3
x 104
9.6
9.65
9.7
9.75
9.8x 10
4
Max.normalforceF
max
[N]
Damper coefficient D1 [Ns/m] Damper coefficient D2 [Ns/m]
Strong correlation No correlation
Scatter
of
output
Secondarysuspension:
verticaldamper
(left)
Primarysuspension:
verticaldamper (left
front)
Each point: Output for one sample-set (simulation)
INDEX
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INDEX
Methodolog for the assessment of technological options
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Full factorial approach:
Dynamic performances analysis in straight track: vehicle stability Dynamic performances analysis in curved track: curving performance
Nine configuration are taken asreference, according to the full
factorial approach
NUMERICALSIMULATIONS
CURVINGPERFORMANCE
OPTIMIZATION
STRAIGHTTRACK
Methodology for the assessment of technological options:FULL FACTORIAL APPROACH
Methodology for the assessment of technological options:
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Paolo Belforte (Politecnico di Milano - Italy)
Methodology for the assessment of technological options:FULL FACTORIAL APPROACH
Definition of factor and factor levels: bogie wheelbase: 3 m - 2.75m - 2.5 m; lateral axlebox stiffness:10-25-40 kN/mm; longitudinal axlebox stiffness: 10-30-50
kN/mm.
ANOVA method : distinction random andsystematic variation polinomial equationof full factorial plan where coefficients a aredetermined applying the least square
analysis
2
128
2
217
2
26
2
15
21423121
xxxxxx
xxxxy
aaaa
aaaa
polynomial equation thatdescribes the full factorial plan
Reduced number ofconfigurations
Evaluate the influence of a simultaneous variation of parameters
RESULTS IN STRAIGHT TRACK: critical speed as a
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Paolo Belforte (Politecnico di Milano - Italy)
RESULTS IN STRAIGHT TRACK: critical speed as afunction of bogie wheelbase and axle boxes stiffness
Higher axlebox stiffness, leads toan increase of the critical speed
Higher bogie wheelbase stabilisesthe vehicle running dynamics
BW = 2.5 mBW = 2.75 m
BW = 2.5 m
BW = 3 m
265 km/h245 km/h
230 km/h
24%
RESULTS IN CURVEDTRACK: wear rate as a function of
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Paolo Belforte (Politecnico di Milano - Italy) 26
Reducing bogie wheelbase -> lower wear rate
Increasing axlebox stiffness -> higher wear rate
Leading outer wheel frictional work: small radius curve
20%
18 kJ
14 kJ
BW = 3 m
BW = 2.5 m
RESULTS IN CURVEDTRACK: wear rate as a function ofbogie wheelbase and axle boxes stiffness
OPTIMIZATION: results with different
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Paolo Belforte (Politecnico di Milano - Italy)
Wear index based optimisation
Reference vs. Opt.1: reduced wear 2%increased critical speed 5%
Solution Bogiewheelbase
[m]
Cz[kN/mm]
Cy[kN/mm]
Wear[kJ]
Criticalspeed [km/h]
Reference 3 10 18 12300 210
Opt. 1 2.75 10 21.5 12069 221
Two different optimisation functions were used.
Combined optimisation:
Reference vs. Opt. 2: increased critical speed of 16 %
increased wear of 4%
Solution Bogiewheelbase
[m]
Cz
[kN/mm]
Cy
[kN/mm]
Wear
[kJ]
Criticalspeed [km/h]
Reference 3 10 18 12300 210
Opt. 2 3 10 37.2 12578 256
OPTIMIZATION: results with differentoptimization functions
)max(),,_( _ WIspeedcryz CCkkbasewf ba
CONCLUSIONS
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Paolo Belforte (Politecnico di Milano - Italy)
CONCLUSIONS
Numerical simulation can be used in order to complement
physical testing for homologation;
Montecarlo approach coupled with multi-body simulations canaccount for the effect of scatter in component performances onride safety;
Numerical simulations can also be used for optimising vehicleperformances still meeting the constraints imposed by ride safety.
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Paolo Belforte (Politecnico di Milano - Italy) 29
Thanks for you r attent ion
Paolo [email protected]
Stefano [email protected]
BOGIE 07 ConferenceSeptember 3rd - 6th, 2007
Budapest HUNGARY
Michael [email protected]
33Methodology for the assessment of technological options:
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Paolo Belforte (Politecnico di Milano - Italy)
33Methodology for the assessment of technological options:SIMULATIONS PARAMETERS
STRAIGHT TRACKPer each configuration:
MB simulations increasing speed (steps 5 km/h)
Evaluation of rms values
Evaluation of prescribed limits & identification of critical speed
Simulation parameters:
W/R profile: theo. Rail / worn wheel cant 1:40 Track irreg: ERRI LOW
The overall assessment of one vehicle configuration requires at least 50 simulations
RMS calculation:Fourier trasform of the last 10 s of the simulation
Frequency f0 corrisponding to the maximum spectrumvalue identified Time history filtered with a band-pass filter f02 Hz
220 225 230 235 240 245 2500
1
2
3
4
5
6
7Leading bogie - Critical speed - RMS Lateral acc. criterion
limit lateral acceleration EN 14363: 4.83m/s 2 Vlim 240km/h
rms(y
)[m/s2]
V [km/h]
Lead. axle
Trail. axle
34Methodology for the assessment of technological options:
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Paolo Belforte (Politecnico di Milano - Italy)
34
CURVED TRACKSimulation parameters
Steady state condition for different radius curve (300 2500 m) randomcombination of
Track irregularity
W/R profile
Cant deficiency
Methodology for the assessment of technological options:SIMULATIONS PARAMETERS
Three tests zone:
small radius curves [250 -400 m];
small radius curves [400 600m];
radius curves [600 2500m];
For each zone -> 30 sections -> data collected with simulations
0 10 20 30 40 50 60 70 80 90 1000
0.5
1
1.5
2
2.5
3
[sample number]
[Sf i
j]
35Methodology for the assessment of technological options:
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Paolo Belforte (Politecnico di Milano - Italy)
35Methodology for the assessment of technological options:OPTIMISATION PROCEDURE
)max(),,_( wwCSyz CCCCwbbogief ba
Best vehicle w.r.t stability and wear optimisation function
Ccs & Cww critical speed and minimum frictional work
a & b weighting coefficient
All the indexes prescribed in the standard were consideredas constrains
Results -- CURVED TRACK:
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Paolo Belforte (Politecnico di Milano - Italy) 36
Results CURVED TRACK:Guiding force as function of bogie wheelbase and axle boxes stiffness
Low bogie wheelbase has positive effects on the vehicle curving behaviour
Longitudinal stiffness reduces the bogie steering capability
BW = 2.5mBW = 3m
Leading outer wheel guiding force: small radius curve
37Results -- OPTIMISATION
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37Results OPTIMISATION
Best vehicle parameters : optimisation procedure result
high lateral stiffness and high boogie wheelbase
Ref vs Opt.1: Increased critical speed of 16 %
Increased wear of 4%
Ref vs Opt.2: Increased critical speed of 16 %
decreased wear of 2%
Solution Bogiewheelbase
[m]
Cz[kN/mm]
Cy[kN/mm]
Wear[kJ]
Criticalspeed [km/h]
Reference 3 10 18 12300 210
Opt.1 3 10 37.2 12578 256
Opt.22.75 10 21.5 12069 221
INDEX
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INDEX
)max(),,_( _ WIspeedcryz CCkkbasewf ba