New techniques for physical modeling and simulation Tom Lee Ph.D., Vice President, Applications Engineering, Maplesoft Kent Chisamore, Account Manager, Maplesoft Tom Lee Kent Chisamore

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/Tire Torque 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 MapleSim Rapid Physical Model Development Exceptional Multi-body Dynamics Extensive Analysis Tools Fast, high-fidelity Plant Models For RT/HIL © 2010 Maplesoft, a Division of Waterloo Maple

Advantages of the symbolic approach © Maplesoft, a division of Waterloo Maple Inc., Easy to read and document Flexible and reusable Parameter management 1, 0, cancellations etc. Algebraic, trig identities etc. DAE index reduction Model simplification Identify redundant calculations Pre-compute expensive functions Standard real time toolchains Optimized code generation Sensitivity Parameter optimization Completely extensible Advanced analysis EQUATIONS

Realtime hardware platform Example toolchain – Plant modeling Plant model equations RT Plant model code Realtime software platform HIL Plant model Simulink SimScape+ Dymola AMESim Simplorer SimScape+ Manual LabVIEW RT Veristand Simulink RTW Quanser QUARC NI PXI DSpace XPC Target Speedgoat Sensors I/O Etc. © 2010 Maplesoft, a Division of Waterloo Maple

Realtime hardware platform The MapleSim advantage Realtime software platform HIL LabVIEW RT Veristand Simulink RTW Quanser QUARC NI PXI DSpace XPC Target Speedgoat Sensors I/O Etc. Fast RT: Infeasible  Feasible 2 Plant model equations Plant model RT Plant model code From months to days 1 © 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 to make approximations and 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 MotoTron Stability Controller Example: Stability Control Test System Control Output Display

With Stability ControllerWithout Stability Controller 63  s 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 Interface Hardware Software Mathematical Model Simulation Optimization Settings Code Generation Sensors and Actuators HMI Visualization 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 Components Rover Dynamics Electric Motors Battery Terrain - Environment 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