This presentation describes how LMS Imagine.Lab Amesim and HEEDS software, part of the Simcenter portfolio, can be used combined for an easy parameter calibration of the LMS Amesim model. This approach is applied on a railroad switch to automatically calibrate the model parameters from a baseline design to some better parameter values found by HEEDS to minimize the difference between experimental data and simulation result. The study demonstrates the advantages that can be had from combining two powerful software packages, respectively specializing in the system simulation and design exploration domains. For more information, please visit our website: siemens.com/plm/simcenter

1. Achieving test
correlation, faster
Easy parameter calibration of railroad switches
and turnouts with LMS Amesim and HEEDS
Realize innovation.Unrestricted © Siemens AG 2017

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Agenda
• Introduction to the product portfolio
• Railways challenges
• Motivation for the calibration study
• Set-up the 1D LMS Amesim model
• Set-up the HEEDS calibration process
• Results of the LMS Amesim / HEEDS
analysis
• Going further

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Cloud
Licensing
flexibility
Simcenter™ Portfolio for Predictive Engineering Analytics
Cornerstones for a future-proof engineering approach
Covering full range of
methods
Analytics, reporting &
exploration
Deployment flexibility
Openness &
Scalability
User experience
Industry &
engineering expertise
Systems approach
Collaboration &
workflow
Multidiscipline
& multiphysics
R
F
L
P
Controls
1D
3D
TEST
CFD

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Simcenter™ Portfolio for Predictive Engineering Analytics
LMS Imagine.Lab
LMS Imagine.Lab Amesim
Collaboration &
workflow

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Simcenter™ Portfolio for Predictive Engineering Analytics
HEEDS – Multidisciplinary design exploration
HEEDS

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Agenda
• Introduction to the product portfolio
• Railways challenges
• Motivation for the calibration study
• Set-up the 1D LMS Amesim model
• Set-up the HEEDS calibration process
• Results of the LMS Amesim / HEEDS
analysis
• Going further

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Empowering railway industries
Bringing innovative products faster to market
Metros
LocomotivesVery high/high speed Titling trains
Intercity trains
Commuter / regional
trains
Freight cars
Trams

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Solution portfolio for all applications and subsystems
Energy management
• Full vehicle simulation
• Prediction of losses
• Trend analysis for
components and
control system design
Engine design
• Engine pre-design,
integration and control
• Design of subsystems
• Waste heat recovery
Thermal comfort
• HVAC system design
• Impact on energy
consumption
• Cabin and passenger
comfort prediction
Dynamics and safety
• Braking system design
• Braking distance
estimation
• Suspension and tilting
systems design

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What your customers care about
Energy efficiency
Optimize energy efficiency of machines systems and architectures
Reliability
Ensure accuracy, structural durability and avoid critical vibrations
Performance
Ensure production throughput and ability to meet flexible needs
Smarter machines
Controls and mechatronics

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Agenda
• Introduction to the product portfolio
• Railways challenges
• Motivation for the calibration study
• Set-up the 1D LMS Amesim model
• Set-up the HEEDS calibration process
• Results of the LMS Amesim / HEEDS
analysis
• Going further

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Point operating systems are essential for all train networks
Requirements and concerns to address
• Enable trains to switch from one track to another
• High safety standards: reliability and precision
• Maintenance expensive

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Higher availability
Failure identification through simulation reduces interruption
to train service
Failure detection
Failure simulation
Maintenance required
Stiff lock
Combination of physical and virtual worlds
Failure identification

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Agenda
• Introduction to the product portfolio
• Railways challenges
• Motivation for the calibration study
• Set-up the 1D LMS Amesim model
• Set-up the HEEDS calibration process
• Results of the LMS Amesim / HEEDS
analysis
• Going further

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LMS Amesim, to go from a real component to a virtual model
LMS Imagine.Lab Amesim
• Simulation Platform for 1D Simulation
• Physical modeling approach
• Comes with dedicated libraries and components
• Extensive analysis tools
• Easy-to-use solver technology

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Point blades
LMS Amesim model of the S700K point machine
Control of the variable friction
DC series wounded motor
Screw / nut
transmission
Notched clutch
LMS Amesim

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LMS Amesim model of the track and locking devices
Point machine
Elastic contact
Between the blade and the stock rail
Lumped parameters to represent
3D interactions
Linear Coulomb friction
Between the throw bar and the lock

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LMS Amesim model of the point operating system
Run the model with various values for
parameters such as the parameters of
viscous and dry frictions
Model of point machine, track and locks
However, some parameters, such as frictions
are hardly measurable. The model first needs
to be calibrated.
LMS Amesim

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Agenda
• Introduction to the product portfolio
• Railways challenges
• Motivation for the calibration study
• Set-up the 1D LMS Amesim model
• Set-up the HEEDS calibration process
• Results of the LMS Amesim / HEEDS
analysis
• Going further

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Design variables
Calibration of the LMS Amesim model: objectives
• Minimize curve between experimental data and simulation result
• Measurement: power consumption of the switch
• Coulomb forces dependent on stiction forces
• 5 design variables
• Stiction and Coloumb force of right blade
• Stiction and Couloumb force of envelope mass
• Electrical resistance
Challenge
System specifications

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Calibration of the LMS Amesim model: worflow
HEEDS
LMS AmesimExperimental
test bench
Experimental data LMS Amesim model of the S700K point machine
Calibrated LMS Amesim model

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LMS Amesim portal in HEEDS 2017.04
HEEDS
LMS Amesim
LMS Amesim portal

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Usage of the LMS Amesim-portal in HEEDS
• The HEEDS Amesim-portal works directly on the *.ame files
• Baseline parameters are extracted directly from the *.ame file
• LMS Amesim is executed to evaluate designs
• Scalar and vector results are extracted from the *.ame file after the simulation
• HEEDS then determines changes to model variables and iterates to find an
improved configuration that meets the objectives and constraints
HEEDSLMS Amesim

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5 design variables of interest in the LMS Amesim model
Coulomb friction force - Right rail
Stiction force - Right rail
Coulomb friction force - Envelope mass
Stiction force - Envelope mass
Electrical resistance





LMS Amesim

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Agenda
• Introduction to the product portfolio
• Railways challenges
• Motivation for the calibration study
• Set-up the 1D LMS Amesim model
• Set-up the HEEDS calibration process
• Results of the LMS Amesim / HEEDS
analysis
• Going further

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Performance history – From baseline design to best design
• Significant improvement in the first 28
evaluations
• Best design after 54 evaluations
HEEDS
Baseline design
Best design

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Target curve (Experimental data)
Simulation curve
Comparison of curves – Baseline design
Baseline design
Performance history
HEEDS

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Comparison of curves - Intermediate analysis
Intermediate analysis
Target curve (Experimental data)
Simulation curve
Performance history
HEEDS

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Comparison of curves - Intermediate analysis
Intermediate analysis
Target curve (Experimental data)
Simulation curve
Performance history
HEEDS

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Comparison of curves – Best design
Best design
Target curve (Experimental data)
Simulation curve
Performance history
HEEDS
Perfect match with
experimental data

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Quantitative comparison of the baseline design & HEEDS results
Parameter name
Parameter value for
baseline design
Parameter values
found by HEEDS
 Coulomb friction force - Right rail 159 N 256 N
 Stiction force - Right rail 160 N 257 N
 Coulomb friction force - Mass envelope 999 N 1261 N
 Stiction force - Mass envelope 1000 N 1262 N
 Electrial resistance 2 Ohm 3 Ohm
RMS 44,7852 8,4225
• Curve fit allows to measure the closeness of the fit
between a target curve and a curve from the
experiments

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Agenda
• Introduction to the product portfolio
• Railways challenges
• Motivation for the calibration study
• Set-up the 1D LMS Amesim model
• Set-up the HEEDS calibration process
• Results of the LMS Amesim / HEEDS
analysis
• Going further

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Help documentation in HEEDS
HEEDS Getting Started Guide

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HEEDS-Amesim training – On-demand
HEEDS-Amesim tutorials based on applications

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Contact
Laura SALSON | Siemens AG, Corporate Technology
Dr. Stefan BOSCHERT | Siemens AG, Corporate Technology
Abdelaziz BACHAR | Siemens PLM, Digital Factory
Stéphane NEYRAT | Siemens PLM, LMS Amesim Platform
Jean-Pierre ROUX | Siemens PLM, HEEDS
Siemens Industry Software S.A.S.
Digital Factory Division
Product Lifecycle Management
Simulation & Test Solutions
DF PL STS CAE 1D
siemens.com