bogie 07 conference september 3rd – 6th, 2007 budapest – hungary numerical simulation for...

BOGIE 07 Conference September 3rd – 6th, 2007

Budapest – HUNGARY

Numerical simulation for improving the design of running gear – Part 1: improvement of vehicle dynamic behaviour

Paolo BELFORTE, S. BRUNI (Politecnico di Milano - Department of Mechanical Engineering)

Michael JÖCKEL (Fraunhofer Institute for Structural Durability and System Reliability - LBF)

Paolo Belforte (Politecnico di Milano - Italy)

MODTRAIN Project

2

“ “ Innovative modular vehicle concepts for an integrated Innovative modular vehicle concepts for an integrated European railway system “European railway system “

6th FRAMEWORK PROGRAMME PRIORITY 6.3 – Transport6th FRAMEWORK PROGRAMME PRIORITY 6.3 – Transport

4 Years Project – Started January 20044 Years Project – Started January 2004

MODTRAIN projectMODTRAIN project

Modular approach to train designModular approach to train design

Interoperability: new generation rolling stockInteroperability: new generation rolling stock

Harmonised European criteria for rolling stock Harmonised European criteria for rolling stock homologationhomologation


MODTRAIN Project

3

It consist of five different sub-projects:It consist of five different sub-projects:

MODBOGIEMODBOGIE

MODCONTROLMODCONTROL

MODPOWERMODPOWER

MODLINKMODLINK

MODUSERMODUSER


INTRODUCTION: NUMERICAL SIMULATIONS TOWARDS “VIRTUAL HOMOLOGATION”

5

• In last years, the improved calculation technologies allowed the development of more detailed and accurate numerical models of rail vehicle dynamics, which can be used as a very useful tool for the design and development of a railway stock.

• With the development of new generations of HS trains, numerical simulations can give an important contribution in order to raise service speed and satisfy operators requirements which claims always for improved performance in terms of comfort and safety

• This work targets the capabilities of multi body simulation models in the design and verification phase of the railway running gear.

Paolo Belforte (Politecnico di Milano - Italy) 6

INDEX


Vehicle model: HS concentrated power locomotive

Carbody with two motor bogies

Two motors bogie-suspended by means of dedicated motor hangers per each bogie

VEHICLE SCHEMATISATIONVEHICLE SCHEMATISATION

41,,,, ....;;;;; T

w

T

w

Tenr

Tbr

Tenf

Tbf

Tc

TV qqxxxxxx

The equation of motion The equation of motion Lagrange equations Lagrange equations

txxQxQvxxQQxKxRxM VVCVnlVVmVVVVVVV ,,,,

REFERENCE SYSTEMSREFERENCE SYSTEMS

W/R contact forces

Vehicle inertia

Fixed reference

Moving reference with constant speed V

Moving reference on body c.o.g .

XG

ZG

YG

Xo

Zo

Yo

ZGi

YGi

V

i

i

i

Loco of a concentrated power train

Only rigid modes also for the wheelsets problem confined to low frequency


rail and wheel profilescontact geometrical

parametersgeometrical analysis

elastic deformation in normal direction

(penetration)

tangential & longitudinal creepages

generalized contact forcestangential & longitudinal

forces(Shen-Hedrick-Elkins

theory)

normal forces(multi-hertzian model)

Wheel rail contact forces model


COMPARISON A.D.Tre.S. – SIMPACKEigenvalues and time histories comparison

9

Natural frequencies comparison

Z

X z

x

z

x

V

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Nat

ura

l F

req

ue

nc

y [H

z]

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]

Force

[N]

SimpackADTreS

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]

Force

[N]

SimpackADTreS


INDEX


Tuning procedure by sensitivity analysis

TYPE OF ANALYSIS : parametric analysis on primary suspension parameters and bogie wheel-base:

straight track running behaviourstraight track running behaviour -> critical speed

curve negotiationcurve negotiation -> steady state Q (vertical force values)

steady state Y (lateral force values)

steady state ‘wear index’


Tuning procedure by sensitivity analysis: effect of wheel-base

Vehicle configurations

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 Reducing the wheelbase the critical speed decreasesspeed decreases

Reducing the wheelbase the vehicle has a Reducing the wheelbase the vehicle has a better steering behaviourbetter steering behaviour


Tuning procedure by sensitivity analysis: effect of wheel-base


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 shift Reducing the wheelbase the track shift force is lightly increasedforce is lightly increased

Wear index is lower in case of reduced wheelbase

Radius curve [m]


INDEX


Analysis of technological options: ‘virtual dynamic homologation’ simulation acc. to EN14363

Vehicle configurations taken into account for EN14363 full Vehicle configurations taken into account for EN14363 full analysisanalysis


Bogie Wheelbase

[m]

Longitudinal axlebox stiffness[kN/mm]

Lateral axlebox stiffness [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) .


‘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


‘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.


Sensitivity analysis and scatter prediction

Numerical simulation can be used even for the evaluation of the impact of the scatter variation of vehicle’s parameters on running

behaviour.


Sensitivity analysis and scatter prediction: effect of damper parameters

Exemplary Simulation Results (12 Parameters Varied Simultaneously): example of the 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 104

outp

ut

D11

0.5 1 1.5 2 2.5 3

x 104

9.6

9.65

9.7

9.75

9.8x 104

outp

ut

Max

. nor

mal

forc

e F

ma

x [N

]

Damper coefficient D1 [Ns/m] Damper coefficient D2 [Ns/m]

Strong correlation No correlation

Scatter

of

output

Secondary suspension:

vertical damper (“left”)

Primary suspension:

vertical damper (“left

front”)

Each point: Output for one sample-set (simulation)


INDEX


Full factorial approach:• Dynamic performances analysis in straight track: vehicle stability• Dynamic performances analysis in curved track: curving performance

Nine configuration are taken as reference, according to the full

factorial approach

NUMERICAL SIMULATIONS

CURVING PERFORMANCE

OPTIMIZATION

STRAIGHT TRACK

Methodology for the assessment of technological options:FULL FACTORIAL APPROACH


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 and systematic variation polinomial equation of full factorial plan where coefficients are determined applying the least square analysis

2128

2217

226

215

21423121ˆ

xxxxxx

xxxxy

polynomial equation that describes the full factorial plan

Reduced number of configurations

Evaluate the influence of a simultaneous variation of parameters


RESULTS IN STRAIGHT TRACK: critical speed as a function of bogie wheelbase and axle boxes stiffness

Higher axlebox stiffness, leads to an increase of the critical speed

Higher bogie wheelbase stabilises the vehicle running dynamics

BW = 2.5 m

BW = 2.75 m

BW = 2.5 m

BW = 3 m

265 km/h245 km/h

230 km/h

24%


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 of bogie wheelbase and axle boxes stiffness


Wear index based optimisationWear index based optimisation

Reference vs. Opt.1:Reference vs. Opt.1: reduced wear 2%

increased critical speed 5%

SolutionSolution Bogie Bogie wheelbase wheelbase

[m][m]

CzCz

[kN/mm][kN/mm]

CyCy

[kN/mm][kN/mm]

Wear Wear

[kJ][kJ]

Critical Critical speed [km/h]speed [km/h]

Reference 33 1010 1818 1230012300 210210

Opt. 1 2.752.75 1010 21.521.5 1206912069 221221

Two different optimisation functions were used.

Combined optimisation:Combined optimisation:

Reference vs. Opt. 2:Reference vs. Opt. 2: increased critical speed of 16 %

increased wear of 4%


[m][m]

CzCz

[kN/mm][kN/mm]

CyCy

[kN/mm][kN/mm]

Wear Wear

[kJ][kJ]


Reference 33 1010 1818 1230012300 210210

Opt. 2 33 1010 37.237.2 1257812578 256256

OPTIMIZATION: results with different optimization functions

)max(),,_( _ WIspeedcryz CCkkbasewf


CONCLUSIONS

• Numerical simulation can be used in order to complement physical testing for homologation;

•Montecarlo approach coupled with multi-body simulations can account for the effect of scatter in component performances on ride safety;

• Numerical simulations can also be used for optimising vehicle performances still meeting the constraints imposed by ride safety.


Thanks for your attention

Paolo BELFORTE Paolo BELFORTE [email protected]@polimi.it

Stefano BRUNI Stefano BRUNI [email protected]@polimi.it

BOGIE ’07 Conference September 3rd - 6th, 2007

Budapest – HUNGARY

Michael Michael JÖCKEL [email protected]@lbf.fraunhofer.de


33Methodology for the assessment of technological options:SIMULATIONS PARAMETERS

STRAIGHT TRACKSTRAIGHT TRACK •Per each configurationPer each configuration:

MB simulations increasing speed (steps 5 km/h) Evaluation of rms values Evaluation of prescribed limits & identification of critical speed

•Simulation parameters: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 spectrum value identified

• Time history filtered with a band-pass filter f0±2 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/s2 Vlim 240km/h

rms(

y )

[m/s

2 ]

V [km/h]

Lead. axle

Trail. axle


34

CURVED TRACK CURVED TRACK Simulation parametersSimulation parameters

Steady state condition for different radius curve (300 – 2500 m) – random combination of Track irregularityW/R profileCant deficiency

Methodology for the assessment of technological options:SIMULATIONS PARAMETERS

Three tests zone: 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 ij]


35Methodology for the assessment of technological options:OPTIMISATION PROCEDURE

)max(),,_( wwCSyz CCCCwbbogief

Best vehicle w.r.t stability and wear optimisation function

Ccs & Cww critical speed and minimum frictional work

& weighting coefficient

All the indexes prescribed in the standard were considered as constrains


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 = 2.5mBW = 3mBW = 3m

Leading outer wheel guiding force: small radius curve Leading outer wheel guiding force: small radius curve


37Results -- OPTIMISATION

Best vehicle parameters : optimisation procedure resultBest vehicle parameters : optimisation procedure result

high lateral stiffness and high boogie wheelbase

Ref vs Opt.1:Ref vs Opt.1: Increased critical speed of 16 %

Increased wear of 4%

Ref vs Opt.2:Ref vs Opt.2: Increased critical speed of 16 %

decreased wear of 2%


[m][m]

CzCz

[kN/mm][kN/mm]

CyCy

[kN/mm][kN/mm]

Wear Wear

[kJ][kJ]


Reference 33 1010 1818 1230012300 210210

Opt.1 33 1010 37.237.2 1257812578 256256

Opt.2 2.752.75 1010 21.521.5 1206912069 221221


INDEX

)max(),,_( _ WIspeedcryz CCkkbasewf

bogie 07 conference september 3rd – 6th, 2007 budapest – hungary numerical simulation for...

Documents

paolo belforte politecnico

milano italy comparison

milano italy introduction

bruni politecnico

milano department

stock homologation slide

vehicle model

bogie design