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Enhancing Hardware-in-the-Loop (HIL) Testing with MapleSim for Efficient Product Development

The 2010 Global Sales Conference presentation emphasizes the critical role of Hardware-in-the-Loop (HIL) simulation in modern engineering. Tom Lee and Paul Goossens discuss how HIL testing can prevent costly errors, save time, and improve product quality. They showcase MapleSim's capabilities, which drastically reduce HIL development time and enable fast, real-time testing of complex systems like vehicles, aircraft, and robotics. The session highlights the necessity of advanced simulation techniques to handle the increasing complexity of controlled systems in various industries.

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Enhancing Hardware-in-the-Loop (HIL) Testing with MapleSim for Efficient Product Development

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  1. Global Sales Conference 2010 Hardware in the Loop Simulation (HIL)Tom Lee VP Applications Engineering, Paul Goossens Director Applications Engineering

  2. Without HIL simulation ... ... people can die ...

  3. 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

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

  5. Role of simulation • Simulation prevents costly rework on real systems • Virtually test different cases before building • Software-only simulation is not enough ControllerModel PlantModel Numerical Integrator Solves the model equations

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

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

  8. Example toolchain – Plant modeling Simulink SimScape+ Dymola AMESim Simplorer • LabVIEW RT • Veristand • Simulink RTW • Quanser QUARC • NI PXI • DSpace • XPC Target • Speedgoat • Sensors • I/O • Etc. Manual • SimScape+ Plant modelequations Plantmodel RT Plant modelcode Realtimesoftwareplatform Realtimehardwareplatform HILVariation1 • Simulink/MATLAB • Simulink RTW-E • ETAS ASCET • Bosch • Mototron Controllerdesign Embeddedcode-gensoftware Realtime Controller hardware

  9. The MapleSim value proposition • LabVIEW RT • Veristand • Simulink RTW • Quanser QUARC • NI PXI • DSpace • XPC Target • Speedgoat • Sensors • I/O • Etc. 1 • From months to days Realtimesoftwareplatform Realtimehardwareplatform HILVariation1 • Plant model equations • Plant model • RT Plant model code • Fast RT: Infeasible  Feasible • Simulink/MATLAB 2 • Simulink RTW-E • ASCET • Bosch • Mototron Controllerdesign Embeddedcode-gensoftware Realtime Controller hardware

  10. Where is CAD? CADconcurrent design activities (new opportunities) Plant modelequations Plantmodel RT Plant modelcode Realtimesoftwareplatform Realtimehardwareplatform HILVariation1 CADDesignimprovement CADManufacture Controllerdesign Embeddedcode-gensoftware Realtime Controller hardware

  11. HIL markets • Space • Space vehicle control • Guidance and nav • Space robotics • Automotive • Vehicle dynamics • Powertrain • Climate control • NVH • Aero/defence • Guidance, navigation • UAV robotics • Simulators • Command and control • Medical • Intelligentprosthetics • Artificialorgans • Power • Wind turbines • New generationpower sources • Futureopportunities

  12. Global Sales Conference 2010 HIL Demonstrations Tom Lee VP Applications Engineering, Paul Goossens Director Applications Engineering Derry Crymble,Quanser Consulting

  13. The demonstrations HIL Variation 1 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 • “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.

  14. Example: Stability Control Test System • Host PC with… • MapleSim • Full-chassis model • Connectivity Toolbox • LabVIEW • Simulation Module Control Output Display • PXI Chassis • LabVIEW/RT Controller Module MotoTron Stability Controller Digital Out CAN bus Interface

  15. Full vehicle 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 Tire Model MapleSim offers a better way

  16. Without Stability Controller With Stability Controller HIL with full-vehicle physical model becomes feasible! 63ms cycle time with no loss of fidelity

  17. Demo 1: Stability control $4595 $1895 $995 $2995 $10480 Plant modelequations Plantmodel RT Plant modelcode Realtimesoftwareplatform Realtimehardwareplatform Controllerdesign Embeddedcode-gensoftware Realtime Controller hardware

  18. Mechatronics research and design • 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 Softwarecontroller Plant test rig

  19. 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

  20. Demo 2: 3 DOF helicopter test rig Plant modelequations Plantmodel RT Plant modelcode Realtimesoftwareplatform Realtimehardwareplatform Controllerdesign Embeddedcode-gensoftware Realtime Controller hardware

  21. 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

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