model based systems engineering overview and practicesem... · 2020. 10. 17. · lms imagine.lab...

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09.2017Page 1 Siemens PLM Software

Model Based Systems Engineering

overview and practices

MBSE



Introduction to systems

• Systems have structure, defined by parts and their

composition

• Systems have behavior, which involves inputs, processing

and outputs of material, energy or information

• Systems have interconnectivity: the various parts of a

system have functional as well as structural relationships

between each other

• Systems have by themselves functions or groups of

functions

SURROUNDINGS

SYSTEM

BOUNDARY



What is a system? Examples

Washing machine

Control

Electric

Hydraulic

Mechanic

Thermal




Hybrid vehicle

Control

Electric

Hydraulic

Mechanic

Thermal




Electro-hydraulic power steering

Control

Electric

Hydraulic

Mechanic



What is mechatronic system simulation?

• Classical design issues :• Is the electric motor powerful enough?

• What is the time response of the system?

• What maximum pressure can be reach?

• Is there any risk of vibration?

• How to optimize the control design?

• Key words :

• Multi-physics with power exchange

• Dynamic system (function of time)

• Physical system model = plant model



Abstraction level : power steering example

Power steering example

• Can we build the complete system model with a CAD-based software?

No, since we have no CAD at this stage of design

• Can we simulate it within an acceptable simulation (computational)

time?

No, no 3D software is able to do that

Model

• We need another approach to:

• Pre-design such systems

• Choose an architecture (hydraulic, electro-hydraulic, electric)

• Assess key functions of the system



Simulation as a tool to manage complexity



One model



The Amesim approach : Abstraction level – Equations – Representation

• Equations are usually written as time dependent with a focus on computing state derivative of variables to assess transient evolution

• Physical equations of component behavior are represented by readable objects (icons)

02

/²/*

22

nn szs

KxdtRdxFdtdxM

CIdtdU

IRU

//

*

PdisplT

displQ

*

*

Mechanics

Electric

Hydraulics

And many other physical domains…

Equations level Physical icon representation



An AMESim model – A differential system



The steering system in Amesim



Positioning in CAx world

CONTROL

MECHANICS HYDRAULICS

PNEUMATICS

THERMALPOWER ELECTRONICS

FEM

Control

MBS

CFD

Magnetic

LMS Imagine.Lab

Amesim

3D simulation

Mechatronic system simulation



Aerospace Industry Practice

Next



.

Design of electrical power systems for aircraft

Concept evaluation: 1. Ranking2. Behavior simulation

Methodology for automatic concept generation

Agenda

Conclusions



MBSE & RFLP: Paradigm Shift



Methodology for system modeling and system concept generation

Design goal: create symmetric variants of given EPS architecture

Methodology:

• abstract description as blocks with ports

• graphical representation (cf. UML, SysML)

• design support by automatic architecture generation

(“Design Space Exploration”)





Methodology:





• expressive language to represent engineering knowledge





Methodology:








Generated architecture



Generated architecture

+ 30 more solutions(*)

(*) case completely solved



Generated architectures



Generated architectures

Solving info

# unique solutions 31

Time to solution 31 2 min.

Complete solver time 64 min.

Brute-force # solutions ~3.51040

Strategy CSP, SAT



.




Agenda

Conclusions



Overall flow (automatic!)

Architecture generation

Declaration





DeclarationArchitecture realization

ExportLMS Imagine.Lab Amesim






Architecture ranking

Ranking: based on

reliability



ComposR

Integrated analysis leverages the benefits of model-based development for reliability and safety

Component Fault Tree based safety & reliability analysis

• Divide-and-Conquer strategy for complex systems

• Systematic reuse of safety artifacts along with design

artifacts

• Automated composition of pre-existing safety artifacts

• Support top-down / bottom-up / middle-out approaches

• Quantitative & qualitative FTA using proven-in-use

methods (ZUSIM.NG)

• Integration/Synchronization with any system modeling

approach

CFT

ElementsSystem

description

Component

Fault Tree

Fault Tree Analysis

.NG



Architecture ranking: component fault tree technology

component failure rate λ (hr-1)

generator

battery

7 ·10-4

rectifying unit (RU) 4 ·10-4

AC transformer (ACT)

transforming rectifier unit (TRU)

2 ·10-4

bus (HVAC/LVAC/HVDC/LVDC) 1 ·10-8

Export

Reliability analysis based on automatic component fault tree (CFT)

analysis

1. Associate CFT components (failure rates, failure modes) with blocks

2. Export complete architectures to CFT architectures

3. Automatic evaluation of different failure modes (e.g., minimal cut sets)



Fault Tree Analysis: system reliability


component failure rate λ (hr-1)

generator

battery

7 ·10-4

rectifying unit (RU) 4 ·10-4

AC transformer (ACT)

transforming rectifier unit (TRU)

2 ·10-4

bus (HVAC/LVAC/HVDC/LVDC) 1 ·10-8

Component A Component B

Component A

Component B

Parallel components:

P = P(A AND B) = P(A) P(B)Serial components:

P = P(A OR B) = P(A) + P(B) – P(A) P(B)




Three clusters, based

on HV system topology






Patent US20060061213

(2006, Honeywell)







Ranking: based on

reliability



.




Agenda

Conclusions



SimpleSteady-state power consumption

Global efficiency

Advanced/ExpertTransient behavior

Network quality

Simulation export: demonstrator with LMS Imagine.Lab Amesim

loadsAC DC

Export



Failure scenario & operating power



Simulation Scenario and predictive analysis : Network interactive simulation

Objective :

• Simulate this network and interact with it

3 sub-networks are interconnected:

• On the right and left sides in green are the two

main distributions

• On the center is the essential distribution in bright

red.

• The essential distribution is dedicated to supply

the essential loads (aircraft critical systems :

navigation equipment, passenger oxygen, flight

control systems ...)

• 2 batteries : last source of electrical power



Network interactive simulation

LMS Amesim model




LMS Amesim dasboard (2/2)




Results



.




Agenda

Conclusions


Page 56 Siemens PLM Software

THANK YOU FOR YOUR ATTENTION !

David Almer

System Simulation Manager

Center of Excellence - EMEA

Siemens Industry Software NV

Phone: +32 (0) 471 12 16 77

Mobile: +32 16 38 43 79

E-mail:

[email protected]

siemens.com

Engaged UsersRight information.

Right time. Right context.

Adaptive SystemEasy deployment today

Flexibility for tomorrow

Intelligent ModelsKnowing what they are

and how they’re made.

Realized ProductsVirtual product.

Real production.
mailto:[email protected]

model based systems engineering overview and practicesem... · 2020. 10. 17. · lms imagine.lab...

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