CosiMate + SaberMulti Physic analysis for validation of

vehicle platform

7th April 2016Detroit Marriott Troy

Agenda

• Introduction Chiastek and Cosimulation(5’)

• FMI : an open standard for model exchange

(5’)

• Monte Carlo Analysis for the Validation of

Modern Automotive Vehicle Platforms (10’)

• DOE with SaberRD and FMU’s (10’)

• Table top demo aside

Chiastek : Company Profile

• Chiastek• SMB, privately held, headquarter in Toulouse, France

• Chiastek Inc (Chicago), Chiastek GmbH (Dusseldorf)

• Distributors in Japan (AZAPA), China (Get Technology,

Greatalent), Korea (Dahan Tech)

• VAR/Partners : Altran, DPS in France and US

• CosiMate

• Current release : CosiMate 2014.12 (v8.1)

• 250 + licenses, 150+ active users

• Worldwide customer support

• Clients• Boeing, Airbus (F, Ge, Ind,) Altran, Safran (Hispano-Suiza)

• GM, PSA, Toyota, Denso, Continental, OPEL Ge, Hitachi

Automotive, Mazda

• Parker, Hydro-Quebec, EDF, Nikon, Hitachi3

What is CosiMate?

CosiMate is a simulation framework based

on an open bus architecture to support

multiphysic simulation at all level of

abstraction.

CosiMate is part of the System Engineering

solution

- own process and data management

capabilities (archiving, versioning, DOE.)

- easily instantiated in a SLM/PDM tool (Autonomie, Sysdm, System Synthesis, adhoc)

What is CosiMate?

Complete co-simulation framework

– Development platform

• Supports native and non native simulation

environment

– Test platform

• Integrates test & measurement tools (e.g. Labview,

LabWindows/CVI)

• C/C++ debuggers/monitors (Eclipse)

– Verification platform

• Supports co-simulation between different

abstraction levels

• Non regression of model functionality along the

design flow

CosiMate is an open multiphysic

platform• Supports all field of simulation thanks to various

coupling:• Coupling standards : FMI (1.0 and 2.0) , DIS, HLA

• 1D : AMEsim, Dymola, Easy5, GT-SUITE, KULI, ModelSim (MG),

Saber, Simulink, OpenModelica,...

• 3D : Inventor, IDEAS/NX-TMG, Vlab.Motion, Adams, Nastran,

Ansys MP

• CARSIM, Rhapsody, Virtualizer, EMTP-RV, PSIM, C/C++, SIL

• Allows modeler to work in native environment• No need for translation or DLL

• Instances can be Black Box

• Easily instantiated within Process Management tool• Autonomie, SysDM

• ModelCenter

Agenda

• Introduction Chiastek and Cosimulation(5’)

• FMI : an open standard for model exchange

(5’)

• Monte Carlo Analysis for the Validation of

Modern Automotive Vehicle Platforms (10’)

• DOE with SaberRD and FMU’s (10’)

• Table top demo a side

FMI – OverviewThe FMI development is part of the ITEA2 MODELISAR project

(2008 - 2011; 29 partners, Budget: 30 Mill. €)

• FMI development initiated, organized and headed by Daimler AG

• Improved Software/Model/Hardware-in-the-Loop Simulation,

of physical models from different vendors.

• Open Standard

• 14 Automotive Use-Cases to evaluate FMI.

Enginewith ECU

Gearboxwith ECU

Thermalsystems

Automatedcargo door

Chassis components,roadway, ECU (e.g. ESP)

etc.

functional mockup interface for model exchange and tool coupling

courtesy Daimler

CosiMate supports FMI

• The first version, FMI 1.0, was published in 2010

• Version 2.0 was released in early 2015.

• Compliance tests:

– CosiMate is currently executing all tests of Compliance Checker

2.0

• MVS does work with FMU

• Committed to 2.1, 3.x and after

10

Chiastek and FMI

• Committed to 2.1, 3.x and after– We participate in FMI meetings

– There are some limitations

– will need more independent standardization (IEEE,

OMG?)

• FMI is a virtual integration capability– FMI is good solution for IP protection

– Can be used for deployment

Agenda

• Introduction Chiastek and Cosimulation(5’)

• FMI : an open standard for model exchange

(5’)

• Monte Carlo Analysis for the Validation of

Modern Automotive Vehicle Platforms (10’)

• DOE with SaberRD and FMU’s (10’)

• Table top demo a side

Why Multiphysic Simulation

• Multiphysic• To validate a full system made of several

components (Hydraulic, electrical, mechanical,

etc…)

• Simulation• To avoid prototype

• To manage scenarios for system optimization

» Explore “infinite” number of case scenarios

» Complete study in hours instead of months

DOE and Multiphysic

• Design exploration• Iterative method

• Monte carlo, What if studies, etc…

• Parametric analysis available with simulation tool

(Saber, Amesim, etc…)

• Design optimization• Formal or semi formal method

• Requires specialty tool (Modelcenter, Isight,

etc…)

• Easy to implement on CosiMate platform

Leveraging Cosimulation between Saber and Simulink in conjunction with Monte Carlo Analysis for the

Validation of Modern Automotive Vehicle PlatformsRaphaël COMTE

Engineer Automotive Electrical Architecture Modeling

Introduction

For Stop and Start application

Develop a new collaborative platform for sizing devices using SABER and SIMULINK

Monte Carlo analyses : Set up a cosimulation process

Associated challengesWith SABER : Set up a new approach of design by using the cosimulation

Produce a mock up with Monte Carlo approach in cosimulation

Set up the associated tools and processes

Systems Sizing MethodologiesGoals : Guarantee Engine services and Electrical constraintsStudy the impacts of the Stop&Start function on the other services

• Systems :– Engine with Starter (Simulink)– Electrical Power System (SABER)

• Methodogies :

– Worst Case sizing Approach• Oversize devices• Additional constraints on the EE devices : feasability risk• Higher costs, weights for very few cases

– Statistical sizing approach• Risk : Quantify levels• Determine the number of cases failing to reach a working threshold (PPM

device)• Reach an agreement with the device-specialized teams on tolerable and

quantified risks

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Possible approach : MONTE CARLO analysis

SABER <-> SIMULINK Co Simulation

Quality associated with the Onboard Electrical NetworkNumerical solutions

Goals : Guarantee Engine and Electrical services

Full SABER

•RTW import

•MONTE CARLO Analysis

•Modeling Simulink system in SABER

• Time development and validation

•No import of Simulink S-function

Full MATLAB

•Modeling electrical Power System (SABER) in SIMULINK

• Time development and validation

•No import of Saber’s Model

•No MONTE CARLO Analysis

SABER <-> SIMULINK with SaberSimulinkCosim

•Master simulator : SABER

• Local HOST

• Simulink : Model Size limited

SABER <-> SIMULINK with COSIMATE

•Master simulator : SABER OR SIMULINK OR COSIMATE

• Local HOST or NETWORK

• Simulink : Model Size > 30Mb

•An additional tool : COSIMATE

Possible approach : MONTE CARLO analysis using cosimulation between SABER and SIMULINK / Simulink

Stakes linked with the Cosimulation use in Monte Carlo analysis

Saber

Simulink2

Platform

CosiMate : Standard use at PSApersonalised batch from each simulator

Simulink 1

manual

automatic

« Standard Use »

Launch platform from each simulator

(local or network)

collaborative Platform

For each simulator :

Reuse existing batch

(manual or automatic run)

Change models’ parameters

Each user can exploit the platform from his simulator and with his own tools

Minimize cosimulation’s impacts on the platform’s exploitation

Need to know simulators’ languages

Summary

QualityClosed Loop System : Multi Monte Carlo Analysis with a minimum of two simulator in cosimulation (local or network)

One result for 2 systems

CostReduce cost development

Re-use methodology for another platform

ScheduleAccording to the models and method : Increazing time simulated

PerformancesSize of results / possibility post-processing

Model & analysis : Facilitate creation or modification for non-expert users of SABER or SIMULINK

Low impact for users

Agenda

• Introduction Chiastek and Cosimulation(5’)

• FMI : an open standard for model exchange

(5’)

• Monte Carlo Analysis for the Validation of

Modern Automotive Vehicle Platforms (10’)

• DOE with SaberRD and FMU’s (10’)

• Table top demo a side

Design of Experiment and Co-Simulation

A SaberRD-CosiMate application

Chiastek

SaberRD

Amesim/FMU

Platform

CosiMate for DOE : a real life example

Amesim/FMU

manual

automatic

« Standard Use »

Launch platform from each simulator

(local or network)

collaborative Platform

For each simulator :

Reuse existing batch

(manual or automatic run)

Change models’ parameters

Optimize services according to constraints

Impact studies

Purpose of this demo

Workflow :

1. Show SaberRD capabilities when designing

components using the Experiment Analyzer

2. Use of co-simulation with multi-physics

transient simulation with CosiMate

SaberRD-CosiMate use

• SaberRD is the master of cosimulation

• Several type of analysis• Sensitivity analysis

• Vary analysis

• Monte carlo analysis

• Generate/integrate FMU’s

Purpose of this study (2)Use case :

Suspension parameter design example

1. What are the critical parameters to be

monitored in this design?

2. Design parameters of the simulation

1. Sensitivity Analysis

From given values for customizable parameters in the

design, find what parameters have the strongest

influence on the design objectives (overshoot and rise

time)

Sensitivity analysis

(parameters)

Transient analysis

Measurements

1. Sensitivity Analysis

Parameters: 2 masses and 2 spring stiffnesses

Design parameter stiffness k (spring 1)

2. Vary Analysis

Determine an order of magnitude of the design parameter

Parameters to measure

Test : comparison to specifications

Report

Graphical outputs

Curves and measurements

2. Vary Analysis

Choice: k1 = 5000 N/m

Graph results

Report

Unit test

Overall completion

3. Monte Carlo Analysis

Assess the impact of risk under uncertainty!

Criteria: rise time and overshoot

Parameters: both masses and springs stiffnesses.

Nominal values +/- 10%Parameters and uncertainty

Test : comparison to specifications

Report

Graphical outputs

Curves and measurements

3. Monte Carlo Analysis

Parameters

and discrepancy

Completed with failure :

xx out of 100 tests failed

Compare to

requirements

Report

Graph results

4. FMU Integration

Create a new component

4. FMU Integration

The new component has to be connected

Simple of use for a few variables design only

Connection with native simulator is made simple

with Chiastek’s MVS Tool for complex design with

many inputs/outputs

4. FMU Integration

Workflow becomes :

1. Validate process using native simulator

2. Transform model into FMU (IP)

3. Validate process using FMU

4. Share your model

Starting simulation with the native simulator is

easier. Since the FMU is a « black box », one

cannot modify it if something goes wrong

Agenda

• Introduction Chiastek and Cosimulation(5’)

• FMI : an open standard for model exchange

(5’)

• Monte Carlo Analysis for the Validation of

Modern Automotive Vehicle Platforms (10’)

• DOE with SaberRD and FMU’s (10’)

• Table top demo a side

• Thank You