Hardware in the Loop Simulation (HIL) Tom Lee VP Applications Engineering, Paul Goossens Director Applications Engineering

© 2010 Maplesoft, a division of Waterloo Maple Inc. Without HIL simulation people can die...

© 2010 Maplesoft, a division of Waterloo Maple Inc. Key points HIL testing is a critical process in industry – Saves money, time, design better products faster With MapleSim... – Dramatically reduce time for HIL development – Fastest real-time execution time for the HIL “plant” – Infeasible systems become feasible – More efficient analysis and design Without MapleSim... – Extremely long development time – Low-fidelity models  approximations, guessing

Increasing complexity Measurements Modern cars, aircraft, military equipment, power equipment, and more are controlled by computers System (plant) Computer (controller)

Role of simulation Simulation prevents costly rework on real systems Virtually test different cases before building Software-only simulation is not enough Numerical Integrator Plant Model Controller Model Solves the model equations

HIL Variation 1 Hardware controller + Software plant Also called MIL (Model in the Loop) Numerical Integrator Software Plant Model Real controller HIL Simulation Test real control strategies with a realistic software model of plant Accurate, safe, cost-effective, fast

Software plant model HIL Variation 2 Software controller + Hardware plant Also called SIL (Software in the Loop) Numerical Integrator HIL Simulation Experimental test rig for plant Virtual analysis of system prior to full prototype Better for advanced analysis Plant test rig Software controller

Realtime hardware platform Example toolchain – Plant modeling Plant model equations RT Plant model code Realtime software platform HIL Variation 1 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. Controller design Realtime Controller hardware Embedded code-gen software Simulink RTW-E ETAS ASCET Simulink/MATLAB Bosch Mototron

Realtime hardware platform The MapleSim value proposition Controller design Realtime software platform Realtime Controller hardware Embedded code-gen software HIL Variation 1 LabVIEW RT Veristand Simulink RTW Quanser QUARC NI PXI DSpace XPC Target Speedgoat Simulink RTW-E ASCET Simulink/MATLAB Sensors I/O Etc. Bosch Mototron Plant model equations Plant model RT Plant model code From months to days 1 Fast RT: Infeasible  Feasible 2

Where is CAD? Realtime hardware platform Plant model equations RT Plant model code Realtime software platform HIL Variation 1 Plant model Controller design Realtime Controller hardware Embedded code-gen software CAD Design improvement CAD Manufacture CAD concurrent design activities (new opportunities)

HIL markets Automotive Vehicle dynamics Powertrain Climate control NVH Aero/defence Guidance, navigation UAV robotics Simulators Command and control Power Wind turbines New generation power sources Space Space vehicle control Guidance and nav Space robotics Medical Intelligent prosthetics Artificial organs Future opportunities

HIL Demonstrations Tom Lee VP Applications Engineering, Paul Goossens Director Applications Engineering Derry Crymble, Quanser Consulting

© 2010 Maplesoft, a division of Waterloo Maple Inc. The demonstrations HIL Variation 1 “Full vehicle” plant model – Vehicle stability control – MapleSim for multibody plant model – Very fast realtime performance – Mototron controller, NI Veristand Effective demonstration to automotive OEMs. Very difficult to achieve with other tools. HIL Variation 2 Quanser 3 DOF helicopter test rig – High-fidelity mechatronics model – MapleSim for physical modeling and controller design – Quanser QUARC + NI realtime hardware platform Ideal platform for research and education in universities

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

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 MapleSim offers a better way

With Stability ControllerWithout Stability Controller 63  s cycle time with no loss of fidelity HIL with full-vehicle physical model becomes feasible!

Realtime hardware platform Demo 1: Stability control Plant model equations RT Plant model code Realtime software platform Plant model Controller design Realtime Controller hardware Embedded code-gen software $4595 $1895 $995 $2995 $10480

Mechatronics research and design Plant test rig Software controller Mechatronics are at the heart of the most innovative technologies Computers intelligently control the movement of complex machines Advanced controllers are required for demanding mechatronic applications Impossible to implement without manual derivation and linearization Time consuming, error-prone, natural limitations

MapleSim for controller design MapleSim plant model development MapleSim Control Systems TB – Standard LQR – Kalman filter – Path control Models validated with test rig MapleSim advantages – Clean separation between plant modeling and linearization for control design – Full access to original non-linear DEs – Parameter studies: eigenvalues, sensitivity, Monte Carlo

Realtime hardware platform Demo 2: 3 DOF helicopter test rig Plant model equations RT Plant model code Realtime software platform Plant model Controller design Realtime Controller hardware Embedded code-gen software

© 2010 Maplesoft, a division of Waterloo Maple Inc. Key points HIL testing is a critical process in industry – Saves money, time, design better products faster With MapleSim... – Dramatically reduce time for HIL development – Fastest real-time execution time for the HIL “plant” – Infeasible systems become feasible – More efficient analysis and design Without MapleSim... – Extremely long development time – Low-fidelity models  approximations, guessing