don’t lose time, switch to frequency-domain: design your systems, reduce your models and speed-up...

Don’t lose time: switch to

frequency-domainDesign 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

Siemens PLM Software


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 / freqFreq0 [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

sysinertia

stiffnessf

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 plotNyquist

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

StabilityManage the system stability for different operating points

2

3

1 DesignReduce 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

TargetOutputsInputs

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 GUILLEMINLMS Amesim Platform

Siemens Industry Software S.A.S.

Digital Factory Division

Product Lifecycle Management

Simulation & Test Solutions

DF PL STS CAE 1D

http://www.plm.automation.siemens.com/en_us/products/lms/imagine-lab/index.shtml

don’t lose time, switch to frequency-domain: design your systems, reduce your models and speed-up...

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