new techniques for physical modeling and simulation tom lee ph.d., vice president, applications...
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New techniques for physical modeling and simulation
Tom Lee Ph.D., Vice President, Applications Engineering, MaplesoftKent Chisamore, Account Manager, Maplesoft
Tom Lee [email protected] Chisamore [email protected]
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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
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• 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
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• 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
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Introduction to MapleSim
© 2010 Maplesoft, a Division of Waterloo Maple
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Simple Introductory Application
Single arm robot control system
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Introduction to MapleSimRapid
Physical Model Development
ExceptionalMulti-bodyDynamics
ExtensiveAnalysis Tools
Fast, high-fidelityPlant Models
For RT/HIL
© 2010 Maplesoft, a Division of Waterloo Maple
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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
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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
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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
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Case studies and applications• Full vehicle realtime simulation• Mars rover power management
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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
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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
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With Stability ControllerWithout Stability Controller
63ms cycle time with no loss of fidelity
HIL with full-vehicle physical model becomes feasible!
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Power system management and optimization tool for space missions
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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
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Power System Management and Optimization Tool for Space Missions
January 27, 2010 – © 2010 Amir Khajepour
System Component Modeling
Component Library
Mars rover: NASA/JPL
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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