OPAL-RT RT14 Conference: AMEsim

The 7th International Conferenceon Real-Time Simulation TechnologiesMontreal | 9-12 June, 2014

1Unrestricted © Siemens AG 2014 All rights reserved.

AMESim – RT-Lab

Co-Simulation Hybrid Bus

Bob Ransijn/Claudio PirolliSIEMENS PLM/ OPAL-RT TECHNOLOGIES

[email protected] / [email protected]

mailto:[email protected]



• Siemens company profile

• Siemens LMS Imagine.Lab AMESim

• Demo

• Partnership

• On-site applications

• Future developments

• Acknowledgments

• Q & A

AMESim – RT-LAB Hybrid Bus Co-simulation



The Siemens Vision: Provide Answers to the Great Challenges of our Time

Siemens –

the pioneer in

• Energy

efficiency

• Industrial

productivity

• Affordable and

personalized

healthcare

• Intelligent

infrastructures

Entrance of Gare Saint-Lazare metro station, Paris




Siemens Organization:Four Sectors Covering the Global Challenges

Industry

Health-care

DiagnosticsImaging & Therapy Clinical Products Customer Solutions

Infra-structure & Cities

Rail SystemsLow and Medium Voltage

Building Technologies

Osram 2)Smart GridMobility and Logistics

Energy

Fossil PowerGeneration

Wind Power Energy ServiceOil & GasPower Transmission

Solar & Hydro

Drive Technologies Customer ServicesIndustry Automation Metals Technologies 1)




Industry Automation:Boosting Industrial Productivity

Product Design and Engineering Production Engineering and Automation

SCSensors andCommunicationKumpfmüller (CEO)

ASIndustrialAutomation SystemsEberle (CEO)

WTWaterTechnologiesDr. Löffler (CEO)

CEControl Components andSystems EngineeringKaul (CEO)

PLPLM Software

Grindstaff (CEO)Affuso (Chairman)

We help boost productivity and improve resource efficiency along the entire product development and production process to enhance the competitiveness of our customers.




Adoption of “systems Engineering”Superior Product Innovation and Managing increasing complexity

“Systems Engineering”

DesignSystem Validation

Simulate & Test

“System of Systems Engineering”

Build Operate

Functional Performance Engineering to Drive PLM & Superior Innovation

The “Smart Industry Solutions” of the Future

Systems Engineering

The “Smart Products” of the Future




Siemens PL and LMSEnabling “Closed-loop System Driven Product Development”

Integrating multi-disciplinary activity...

Adopting Model BasedProduct DevelopmentIn all Stages of Development

…enabled by closed-loop performance verification




Automotive Engineering ChallengesBalancing Emissions, Cost, and Brand Performance

Eco-Driven Powertrain Concepts Innovative and Lightweight Design

Creating Brand Value through Performance Creating Brand Value through Systems




Current Engineering Practice:Struggling to Control Complexity

0

50

100

150

2000 2010 2015

Cost of Software

Dramatic Growth of Electronics Systems Exploding Requirements and Test Cases

Multiple Variants and System Architectures Multiple Sites, Multiple Participants

€25b

€95b

€126b




The LMS Imagine.Lab Platform

Controls ModelingElectronics, Software…

Physical ModelingThermal, Mechanics, Fluids,…

The innovative Model-Based Systems Engineering approach for Mechatronic System Development

LMS Imagine.Lab AMESimSoftware environment for multi-physics, multi-level, mechatronic

system modeling, simulation and analysis.

LMS Imagine.Lab SysDMSolution for the organization and management of mechatronic data,

from mechanical to controls engineering

LMS Imagine.Lab System SynthesisSoftware tool to support configuration management, systems integration and

architecture validation.

LM

S Im

agin

e.L

ab




LMS Imagine.Lab AMESim (1/2)

The Open and Productive Development EnvironmentSimulate and analyze multi-physics controlled systems

ADVANCED ANALYSIS TOOLS

• Fast Fourier Transform

• Plotting facilities, 2D/3D post-processing

tools

• Spectral map & Order Tracking

• Linear analysis (eigenvalues, modal shapes,

root locus, and transfer function

representation)

INTUITIVE GRAPHICAL INTERFACE

• User-friendly modeling environment

• Seamless connection between various

validated and predefined components

• Display of the system throughout the

simulation process

• Several customization and scripting tools

OPEN-ENDED PLATFORM

• Efficient integration with 3rd party software for

SiL, MiL, HiL, real-time simulation, MBS,

process integration and design optimization

• Generic co-simulation interface to couple to

dynamic 3D models

• Modelica-compliant platform

UNRIVALLED NUMERICAL CORE

• Capability to robustly execute

inhomogeneous dynamic systems

• Advanced numerical techniques (ODE, DAE)

• Dynamic selection of calculation methods

• Discrete partitioning, parallel processing and

co-simulation




LMS Imagine.Lab AMESim (2/2)The Validated, Off-the-Shelves Physical LibrariesChose after 4500 multi-domain models

FLUIDSHydraulic, Hydraulic Component Design

Hydraulic Resistance, Filling

Pneumatic, Pneumatic Component

Design

Gas Mixture, Moist Air

THERMODYNAMICSThermal, Thermal Hydraulics

Thermal-Hydraulic Component

Design, Thermal Pneumatic,

Cooling, Air-Conditioning

Two-Phase Flow

ELECTRICSElectrical Basics, Electromechanical

Electrical Motors & Drives

Electrical Static Conversion

Automotive Electrics, Electrochemistry

MECHANICS1D mechanical, Planar mechanical

Transmission, Cam & Followers

Finite-Elements Import

Vehicle Dynamics

ENGINEIFP Drive, IFP Engine

IFP Exhaust

IFP C3D, CFD-1D

CONTROLSSignal and Control

Engine Signal Generator




Multi-Domain simulation in AMESim

Hydraulics

Mechanics

Controller

Pneumatics

Electrical domain




Example: Check Valve

• Goal:

• design check valve geometry given a functional specification

• Results from geometry optimization:

• Response on pressure spike:

Pressure [bar]

Flo

w r

ate

[L/m

in]

Pressure [bar]F

low

rate

[L/m

in]

Optimization

Specification

Component design

Specification

Component design

Pressure [bar]

Flo

w r

ate

[L/m

in]

Specification

Component design

0-5 bar in

0.1 sec.




Example: Check Valve

• Operating condition of system:

• Pump speed of 1650 rev/min

• Pump flow ripple of 55 Hz

• Orifice closing from 100% to 50%

• Unstable behavior resonance between pump flow ripple and check valve

Pump outlet pressure

Check valve opening

Pump flow ripple Cracking pressure 2 bar

Line dynamics

Valve dynamics

Pump dynamics




Closed loop powertrain model for drivabilityOverview

HF Engine physical model(crank angle degree resolution)

Automatic transmission (6

gears)

Longitudinal 2D vehicle carbody

Driver and mission profile

Simulink interfaces

Powertrain model including:• HF 4 cylinder engine model (crank angle degree resolution)

• 6 gear Automatic transmission

Engine3D bloc

& mounts

• 3D engine bloc and mounts

• 2D longitudinal vehicle + Driver and mission profile definition




LMS Imagine.Lab solutions for transmission For control design, virtual testing and pre-calibration

• Model In the Loop:

• Design the transmission control strategies with help of a representative plant model

• Virtual models for the control and the transmission

Hardware-in-the-Loop:• Test and validation of the control strategies

implemented on the Control Unit

• Regulation, security and failure tests without any

risk

• Test of the interaction between several

ECU/TCUs…

Software-in-the-Loop:• Test the C-code used in the controller using a plant model including CAN or FlexRay protocol

• Test using the generated C code (using AMESet) or a Simulink model

• Possible tests in a “virtual” real-time environment

Virtual pre-calibration:• First step of control calibration (offline) using

detailed engine/vehicle plant models

• Put the control in usage context for a simulation

of a virtual vehicle

• Reduce time and cost of test on the real

system




Hybrid Bus Co-simulation

RT-LAB integrated with AMESim

DEMO




• Host Computer• Windows 8 Professional

• MATLAB R2011B

• RT-LAB v10.6.0

• AMESim Rev 13

• Target computer• QNX® 6.5.0

Software environment




• In AMESim• Add Simulink Interface in the AMESim model

• Run the AMESim model off-line (passing from the parameter mode to the simulation mode – thus generating the s-function)

• Generate files for real-time simulation

• In Simulink and RT-LAB• Add s-function block and specify the C source file name and parameters

• Run the model offline with fixed-step solver and verify results

• Run the model in real-time and compare the results

Model Preparation




Applications (1/2)

Detailed injection model Access to in-cylinder composition Transient operation Efficient link with Simulink Complete physical model in LMS Imagine.Lab Co-Simulation with Matlab/Simulink

Target: control the Burned Gas Ratio so as to limit the NOx emissions

Gain: 1 year saved in the development process



Applications (2/2)

22 copyright LMS International - 2011

Air Path + MVEM

Driveline

Injection

Thermal

Electricalsystems

Target: Develop an HiL simulator to test & validate the injection system management using a virtual powertrain

Gain: Suppress the model maintenance efforts (20% of the project time)

Physical models for all the powertrain subsystems Model simplification from design to HiL Robust Real Time simulation

Driver

Key Differentiators:



• OPAL-RT and LMS have collaborated for about 6 years

• Enable real-time simulation of these models on OPAL-RT platforms.

• AMESim has tools that allow the user to adapt models for real-time simulation by optimizing model reduction.

• This integration allows powerful real-time plant simulation capabilities for HIL

• Open approach that allows customers to use modeling tools of their preference

• Tools can be used together for a complex system such as a hybrid bus, for which HIL is absolutely critical for integration testing of multiple ECU

Partnership




• Demonstrate how AMESim models (such as the hybrid bus) can be run on OPAL-RT systems for HiL on a wider scale in the automotive and aerospace sectors.

• Create an action plan to ensure version compatibility across tools (AMESim, RT-LAB and MATLAB/Simulink)

• Expand compatibility to Redhat

• Leveraging RT-LAB 11 structure to run AMESim code

Future developments




• September 16-18, 2014 – Leuven, Beligium• 3-day workshop on real time system modelling in context of HiL testing

• The topics covered in the workshop include:• The benefits of real time simulation

• Model reaction in Imagine.Lab and LMS Virtual.Lab Motion modeling a flight control actuator

• Model analysis and model simplification

• C-code generation

• Compilation

• Performance to the real-time test on the OPAL-RT platform

Future developments



• Janardhan K. SunderRaj (FAE Team Leader – OPAL-RT India)

• Ravi Venugopal (Advanced Technologies Director – OPAL-RT)

• Alan Soltis (Automotive Program Manager – OPAL-RT USA)

• Aditya Inamdar (LMS – Application Engineer)

Acknowledgements




Thank You
