Don’t lose time, switch to frequency-domain: Design your systems, reduce your models and speed-up your runs with LMS Amesim

Don’t lose time: switch to
frequency-domain
Design your systems, reduce your models and
speed-up your runs with LMS Imagine.Lab Amesim
Realize innovation.Unrestricted © Siemens AG 2017

Unrestricted © Siemens AG 2017
Page 2 Siemens PLM Software
Agenda
• Why Linear Analysis in LMS Amesim?
• Linear Analysis in details
• 20 years of experience and proven
results
• Going further

Two views of the same system
Time-domain [s] and frequency-domain [Hz]
Mass-spring-damper system
time (seconds)
displacement (meter) velocity (meter/second)
frequency (Hertz)
Time-Domain, f(t) [s] Frequency Domain, H(freq) [Hz]
period [s] = 1 / freq
Freq0 [Hz]

Linear Analysis for frequency-domain analysis
Type of analysis
Time-
domain
Frequency-
domain
Use time-domain and frequency-
domain to analyze your model
Hz

Linear Analysis: frequency response in time-domain
Dual-mass flywheel (DMF)
System frequency of the DMF 8.51 Hz
System frequency of the drivetrain 63.17 Hz
DMF acts like a low-pass filter
Analytical calculation of
system frequencies:
sys
sys
inertia
stiffness
f
2
1


Linear Analysis: modal shapes
Internal combustion engine (ICE) crankshaft
pulley flywheelcyl. 1- 4

Torsional vibration
Modes analysis and trouble shooting
Modal shapes with multiphysics couplings
Find solutions to reduce oscillation amplitudes in driveline
Natural modes coupling analysis including actuators: clutches, piloted
differential, transfer box, …
Time response
Results check using:
• Spectral maps
• Order tracking
• LMS Test.Lab interface

Few examples of Linear Analysis use cases
For various industries: Automotive, Aerospace, Off-highway, …

Agenda
results
• Going further

Features of the Linear Analysis
Eigenvalues Modal shapes Transfer functions Root locus
Frequ.,  , Real, Imag Magnitude Energy Bode Nichols Nyquist With batch runs
natural
frequencies,
damping ratios
distribution over system
topology
output/input
frequency response:
Y(s)/U(s)
sensitivity
analysis in
frequency-
domain
State variables (system),
already included
Observer
variables needed
Observer
variables needed
Control and
Observer variables
needed
Control and
Observer variables
needed
Control and
Observer variables
needed
State variables (system),
already included
4 types of analysis for different needs

Frequency-domain analysis
Workflow
System
definition
Extract useful
information for
your needs
Linearize at a
specified time
Set boundary
and initial
conditions
Optimize your
system,
speed-up your
runs, export to
real-time
Speed Efficiency

Key differentiators and benefits using Linear Analysis
No duplicate model, the same and
unique LMS Amesim model is used
Fast CPU-time for linearization
compared to usual runs
Automatic linearization process, fully
integrated in the GUI
Several built-in Linear Analysis features,
best design found in few iterations
Easy export or reuse of the linearized [A,
B, C, D] state-space representation
LMS Amesim complete model
LMS Amesim linearized model
Fully integrated
linearization
process
No external
toolbox or variant
model (typically
Matlab/Simulink)

Modal shapes on simple examples
Mechanical beam and hydraulic pipe with wave effects

Root locus and typical responses for location of eigenvalues
Application: stability analysis depending on system parameters
IMAGINARY
REAL
Root locus in LMS Amesim Typical responses
Root Locus is a plot (real part/imaginary part) representing the
trajectories in frequency [Hz] and damping ratio [%] of the
natural modes due to some parameters changes

Batch and hold curve support for frequency response
Application: linear analysis of a pressure regulator
Run a batch simulation using the diameter of the
stabilizing orifice as batch parameters
Bode plot
Nyquist
diagram
Nichols
diagram
Once the simulation is complete, create the frequency response diagram: Bode, Nyquist, and Nichols using the
result sets feature directly in the LMS Imagine.Lab Amesim plot

Black-Nichols for open-loop controlled systems
Application: gain margin [dB] and phase margin [degrees]
Instable and stable controlled systems – Open-loop Typical characteristics – Open-loop
GM
PM
Gain [dB]
Phase
[degrees]
0 dB
-
180
°
 
 -
 R
 c
 1
 R0
 =
0
G(0) and
GCL(0)
GCL(0) static gain for the closed loop system
G(0) static gain for the open loop system
1 frequency for G = 0 dB
- frequency for  = -180°
R0 resonant frequency (open loop system)
R resonant frequency (closed loop system)
Q resonance factor
c break frequency at  dB
Q+GCL(0)
PM phase margin
MG gain margin

Performance Analyzer - Automated linearization
Application: 6-Speed dual clutch transmission (DCT) to be run in real-time
The automated linearization
directly provides the maximum
frequency of 212 Hz during the
whole simulation, with an Euler
fixed step value of 0.79 ms to
get stable results
The clutches are piloted by the electronic control unit to
ensure the correct start-up of the vehicle and the gear
changes for all driving conditions and driver demands.
A model of the hardware able to run in real time is necessary
to test the control software of the transmission.
Automated linearization
in the Frequencies pane

Eigenvalue animation tool
Application: simplifying models for co-simulation on a multicore target
Chassis model:
OK with 4th order
Runge-Kutta method
at 1 ms
Braking system model
with ABS & ESC logic:
OK with 1st order Euler
method at 1 ms
Export and simulation on a multicore real-time target
Use the eigenvalue animation together with other LMS Amesim
tools (performance analyzer, modal shapes, activity index …) to get
insights on the dynamics of your models, simplify them and find
suitable fixed-step solver settings for real-time

LMS Amesim Linear Analysis
Right tool drives greater efficiency and performance
Hardware-in-the-Loop (HiL)
Reduce models for real-time applications removing useless frequencies
Stability
Manage the system stability for different operating points2
3
1 Design
Reduce the amplitudes of the excited systems

Agenda
results
• Going further

D. Jonquet, S. Neyrat – S.T.A. – France – [ paper ]
Automatic transmission internal gear oil pump with cavitation

M. Alirand, G. Favennec, M. Lebrun – Renault – France – [ paper ]
Pressure components stability analysis

P. Chaufour and al. – Volvo Trucks – France – [ paper ]
Heavy-truck unit-injector system

S. Ricci and al. – Bologna University – Italy – [ paper ]
Virtual shaker testing for improving vibration test performance

B. Jiang – Chalmers University – Sweden – [ master thesis ]
Dynamics of a wind station driveline

C. Pecollo – Fiat Powertrain Technologies – Italy – [ conference ]
Common rail diesel injection system

Y. Xu – INSA Lyon – France – [ thesis ]
High performance electro-hydraulic test bench

S. Kawasaki and al. - Japan Aerospace Exploration Agency –
Japan – [ paper ] Cavitation instabilities of a rotating machinery

Agenda
results
• Going further

Linear Analysis user guide in LMS Amehelp

Accelerated control development with Model Predictive Control
Embed linearized plant models within advanced control strategies
System Model
Target
OutputsInputs
States
Control System
Model Algorithm
+
• Which system it is working on
 Dynamic model
• What goal it has to achieve
 Objective function
• How to calculate the controls
 Dynamic optimizer
MPC controller
needs to know:
Linearized plant models

LMS Amesim enables you to tailor your platform to your specific needs with the app
designer, plots Python API, application-specific tools for pre-processing and post-
processing as well as customized parameter editing using external executables.
Use advanced LMS Amesim scripting tools for model interaction automation and LMS
Amesim APIs for full command-line building of complete models.
LMS Amesim helps improve your system design with LMS Amesim design exploration,
LMS Amesim export module or the LMS Amesim-Optimus interface.
LMS Amesim enables you to analyze your data and system results with advanced
plotting facilities, dashboard, animation, table editor, linear analysis, activity index and
replay.
LMS Imagine.Lab Amesim comes with unique usability and scalability capabilities with
all the LMS Amesim graphical user interfaces (GUI), interactive help and associated
features such as the supercomponent facility, batch run monitor, experiment manager,
post-processed variables and Statechart designer.
More about the LMS Imagine.Lab Amesim platform
Platform
facilities
Analysis
tools
Optimization, robustness,
design of experiments
Simulator scripting
Customization

LMS Imagine.Lab Amesim supports Modelica, the open standard language for
describing physical systems. The Modelica platform provides the tools you need to
build acausal, multi-domain Modelica models and leverage the LMS Amesim platform
features to analyze the resulting system.
LMS Amesim can be coupled with external software applications such as CAE, CAD,
CAM, FEA/FEM and computational fluid dynamics (CFD). Co-simulation provides
coupling between LMS Amesim and CAE tools with predefined setups to ensure good
dialog between the tools and simulation software.
LMS Amesim provides co-simulation capabilities with any software coupled with LMS
Amesim due to the generic co-simulation capability and functional mock-up interface
(FMI), to complete heterogeneous simulations within an unique integration platform.
The LMS Amesim unique integrated platform provides realistic plant models for every
stage of the development cycle, enabling system and control engineers to start
evaluation and validation phases early in the design cycle using model-in-the-loop
(MiL), software-in-the-loop (SiL) and hardware-in-the-loop (HiL) frameworks.
LMS Amesim integrates cutting-edge numerical methods, performance analyzer,
discrete partitioning library for CPU speed-up, a parallel processing feature for
multiprocessor task distribution as well as High Performance Computing (HPC).
More about the LMS Imagine.Lab Amesim platform
Solvers
and numerics
MiL/SiL/HiL
and real-time
Software
interfaces
1D/3D
CAE
Modelica
platform

Realize innovation.
Stéphane NEYRAT
Jérôme GUILLEMIN
LMS Amesim Platform
Siemens Industry Software S.A.S.
Digital Factory Division
Product Lifecycle Management
Simulation & Test Solutions
DF PL STS CAE 1D

Don’t lose time, switch to frequency-domain: Design your systems, reduce your models and speed-up your runs with LMS Amesim

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Don’t lose time, switch to frequency-domain: Design your systems, reduce your models and speed-up your runs with LMS Amesim