New techniques for physical modeling and simulation Tom Lee Ph.D., Vice President, Applications...

New techniques for physical modeling and simulation

Tom Lee Ph.D., Vice President, Applications Engineering, MaplesoftKent Chisamore, Account Manager, Maplesoft

Tom Lee tlee@maplesoft.comKent Chisamore kchisamore@maplesoft.com

From mathematics to engineering

1980’s: Research project company founded in 1988 Maple product

1990’s: Maple grows to become a dominant product for symbolic math

2000’s: Transition into engineering modeling new modeling products

2007: Strategic partnership with Toyota MC and Toyota TC

2008: Introduction of MapleSim product line breakthrough in Japan

2009, today: Acquisition by Cybernet Systems new office in Germany

• Fidelity may be sacrificed to achieve performance…• …which reduces the usefulness of the model

Fidelity vs. Real-Time Performance

© 2010 Maplesoft, a Division of Waterloo Maple

• Signal-flow approach is cumbersome and limited• May require an equation re-formulation

Engine/Powertrain

AngleInputs

Chassis/TireTorque Outputs

More Challenges: Multi-Domain Systems

Drive

© 2010 Maplesoft, a Division of Waterloo Maple

Introduction to MapleSim

© 2010 Maplesoft, a Division of Waterloo Maple

Simple Introductory Application

Single arm robot control system

Introduction to MapleSimRapid

Physical Model Development

ExceptionalMulti-bodyDynamics

ExtensiveAnalysis Tools

Fast, high-fidelityPlant Models

For RT/HIL

© 2010 Maplesoft, a Division of Waterloo Maple

Advantages of the symbolic approach

© Maplesoft, a division of Waterloo Maple Inc., 2010.

Easy to read and documentFlexible and reusableParameter management

1, 0, cancellations etc.Algebraic, trig identities etc.DAE index reduction

Model simplification

Identify redundant calculationsPre-compute expensive functionsStandard real time toolchains

Optimized code generation

SensitivityParameter optimizationCompletely extensible

Advanced analysis

EQUATIONS

Realtimehardwareplatform

Example toolchain – Plant modeling

Plantmodel

equations

RT Plantmodelcode

Realtimesoftwareplatform

HILPlantmodel

SimulinkSimScape+

DymolaAMESim

Simplorer SimScape+Manual

LabVIEW RTVeristand

Simulink RTWQuanser QUARC

NI PXIDSpace

XPC TargetSpeedgoat

SensorsI/OEtc.

© 2010 Maplesoft, a Division of Waterloo Maple

Realtimehardwareplatform

The MapleSim advantage

Realtimesoftwareplatform

HIL

LabVIEW RTVeristand

Simulink RTWQuanser QUARC

NI PXIDSpace

XPC TargetSpeedgoat

SensorsI/OEtc.

Fast RT: Infeasible Feasible2

Plant model equationsPlant model

RT Plant model code

From months to days1

© 2010 Maplesoft, a Division of Waterloo Maple

Case studies and applications• Full vehicle realtime simulation• Mars rover power management

Full vehicle Model

Tire Model

High fidelity full vehicle physical models are rarely deployed for HIL • Difficult to develop• Too slow in realtime

Engineers are forced tomake approximationsand guesses for any HIL

Host PC with…•MapleSim•Full-chassis model•Connectivity Toolbox•LabVIEW•Simulation Module

PXI Chassis•LabVIEW/RT Controller Module

Digital Out

CAN bus Interface

MotoTronStabilityController

Example: Stability Control Test System

Control Output Display

With Stability ControllerWithout Stability Controller

63ms cycle time with no loss of fidelity

HIL with full-vehicle physical model becomes feasible!

Power system management and optimization tool for space missions

16

Power System Management and Optimization Tool for Space Missions

Software/Hardware Structure

January 27, 2010

Inte

rfa

ce

HardwareSoftware

Mathematical Model

Simulation

Optimization

Settings

Code Generation

Sensors and Actuators

HMIVisualization

Controls

National Instruments

Physical Subsystems

17

Power System Management and Optimization Tool for Space Missions

January 27, 2010 – © 2010 Amir Khajepour

System Component Modeling

Component Library

Mars rover: NASA/JPL

18

Power System Management and Optimization Tool for Space Missions

System Component Modeling

Rover dynamics

Component Library

Mars rover: NASA/JPL

January 27, 2010 – © 2010 Amir Khajepour

19

Power System Management and Optimization Tool for Space Missions

System Component Modeling

Rover dynamics

Wheels

Component Library

Mars rover: NASA/JPL

January 27, 2010 – © 2010 Amir Khajepour

20

Power System Management and Optimization Tool for Space Missions

System Component Modeling

Rover dynamics

Wheels

Solar cells

Component Library

Mars rover: NASA/JPL

January 27, 2010 – © 2010 Amir Khajepour

21

Power System Management and Optimization Tool for Space Missions

System Component Modeling

Rover dynamics

Wheels

Solar cells

Wheel motors

Component Library

Mars rover: NASA/JPL

January 27, 2010 – © 2010 Amir Khajepour

22

Power System Management and Optimization Tool for Space Missions

System Component Modeling

Rover dynamics

Wheels

Solar cells

Wheel motors

Battery

Component Library

Mars rover: NASA/JPL

January 27, 2010 – © 2010 Amir Khajepour

23

Power System Management and Optimization Tool for Space Missions

System Component Modeling

Rover dynamics

Wheels

Solar cells

Wheel motors

Battery

Power Management System

Component Library

Mars rover: NASA/JPL

January 27, 2010 – © 2010 Amir Khajepour

24

Power System Management and Optimization Tool for Space Missions

System Component Modeling

Rover dynamics

Wheels

Solar cells

Wheel motors

Battery

Power Management System

Heaters

Component Library

Mars rover: NASA/JPL

January 27, 2010 – © 2010 Amir Khajepour

25

Power System Management and Optimization Tool for Space Missions

System Component Modeling

Rover dynamics

Wheels

Solar cells

Wheel motors

Battery

Power Management System

Heaters

Robotic arms, other peripherals

Component Library

Mars rover: NASA/JPL

January 27, 2010 – © 2010 Amir Khajepour

26

Power System Management and Optimization Tool for Space Missions

System Component Modeling

Rover dynamics

Wheels

Solar cells

Wheel motors

Battery

Power Management System

Heaters

Robotic arms, other peripherals

Terrain

Component Library

Mars rover: NASA/JPL

27

Power System Management and Optimization Tool for Space Missions

System Component Modeling

Rover dynamics

Wheels

Solar cells

Wheel motors

Battery

Power Management System

Heaters

Robotic arms, other peripherals

Terrain

Environment

Component Library

Mars rover: NASA/JPL

January 27, 2010 – © 2010 Amir Khajepour

28

Power System Management and Optimization Tool for Space Missions

Power Management and Optimization

Power Management Controller

Power ComponentsR

over Dynam

ics

Electric Motors

Battery

Terrain - Environm

ent

Optimizer(Genetic Algorithm)

Solar Cells

Heaters

Electronics

Robotic Arms

January 27, 2010 – © 2010 Amir Khajepour

Key conclusions

• HIL simulation is becoming increasingly important

• New tools are emerging to manage the complexity

• A symbolic technology-based approach can provide high-fidelity physical models at fast realtime speeds

© 2010 Maplesoft, a Division of Waterloo Maple