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An Automated Design Synthesis System Involving Hardware-In-the-Loop Simulation Steve Hann

An Automated Design Synthesis System Involving Hardware-In-the-Loop Simulation Steve Hann Wensi Jin Mechanical Simulation Corporation Opal-RT Technologies May 2003. Outline. Introduction Hardware in-the-loop Why use iSIGHT for HIL?

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An Automated Design Synthesis System Involving Hardware-In-the-Loop Simulation Steve Hann

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  1. An Automated Design Synthesis System Involving Hardware-In-the-Loop Simulation Steve Hann Wensi Jin Mechanical Simulation Corporation Opal-RT Technologies May 2003

  2. Outline • Introduction • Hardware in-the-loop • Why use iSIGHT for HIL? • Experiment • Automated design synthesis with a development ECU • Underlying Technologies • HIL platform: RT-LAB (Opal-RT) • Real-time simulation: CarSim (Mechanical Simulation) • Process integration and design methods: iSIGHT • Summary

  3. Introduction Real-Time Simulation & HIL • Real-Time Simulation • Simulating at the same speed as real life, not faster/slower • Based on fixed time step integration, with time step usually measured in micro- or milli-seconds • Hardware-in-the-Loop (HIL) • Part of the simulation is the hardware under study/test • Requires real-time performance • Physical hardware will not wait for the simulation • The Hardware • Can be a valve, an electronic control module (ECU), an ECU network, a brake system assembly, an engine, a transmission … a full vehicle

  4. Introduction Hardware In-the-Loop • Hardware-in-the-Loop • Widely used in control system development • Design – rapid control prototyping • Test – “in-the-loop” testing • Allows experimentation with physical parts in a controlled synthetic environment • Experiments can be repeated and automated • Allows parallel development of mechanical and control systems • An important technique to reduce design cycle while improving product quality

  5. Hardware In-the-Loop Example: ECU In-the-Loop • Allowing controller development while mechanical system is being built • Achieving a high degree of test coverage in the lab before driving mechanical system • Reducing test effort through automated regression Host PC(development env.) ECU under test RT Simulator (3 x Pentium 3, 1 GHz CPU)

  6. Hardware-In-the-LoopAutomatic Transmission In-the-Loop • Moving engineering development from expensive test vehicles to lab • Increasing repeatability through controlled environments • Accelerating test cycles with minimum operator intervention

  7. Why Use iSIGHT for HIL • HIL systems have evolved rapidly in recent years • Latest CPUs and parallel processing • Provides computing power for detailed models • New hardware technologies • Reduces needs for custom hardware • New user interface technologies • Enhances ease-of-use • Increased use of HIL in automotive engineering • However, HIL is not used to its fullest potential • Although HIL systems have evolved away from custom, one-off designs, their usage has not

  8. Why Use iSIGHT for HIL • What is lacking? • High fidelity plant models • Tools integration • Design method integration • Process integration • We believe these factors are limiting the effectiveness of HIL • Solutions have emerged in the offline simulation/CAE world • This is the motivation for the feasibility study with Engineous Software using iSIGHT • Let’s take a look at the experiment in the study

  9. Experiment Setup ABS/ECU Wheel Speeds VEHICLE BRAKES ECU Brake Torques Solenoid Signals Brake Pedal Input

  10. HITL for ECU Evaluation CarSim Software Brake Model RT–LAB Conditioning DAQ Boards Wheel Speeds ECU Solenoid Signals

  11. Description of Problem • Use iSIGHT to find value of Mass center of unladen sprung mass that minimizes straight line stopping distance (initial value of 1014 mm)

  12. Description Of Simulations • Choose/Define the vehicle • Initial speed of 114.5 kph • Split Mu road (0.2 and 0.5) • Driver model set for straight line • Step Braking of 15 Mpa (locks brakes) • Calculate stopping distance

  13. HIL Platform: RT-LAB Workstation PC TCP/IP Firewire Supports CarSim/TruckSim AMEsim GT-Power Matlab/Simulink MATRIXx/SystemBuild Highlights Intel CPU & PC hardware Open system Scalability through parallel processing Widely connected … Real-Time PC (QNX)

  14. RT Vehicle Dynamics Simulation: CarSim

  15. Summary • Nominal value of Mass center of unladen sprung mass of 1014 mm yields total stopping distance of 145.3 m • Optimized value of Mass center of unladen sprung mass, 1024.63 mm, yields total stopping distance of 142.92 m (reducing total stopping distance by 2.38 m)

  16. Summary

  17. Summary Execution Results Summary Total runs: 37 Feasible runs: 37 Infeasible runs: 0 Failed runs: 0 Optimization Plan: NewPlan Executed between RunCounter 1 and 37 (37 runs) Techniques used: Step1: Adaptive Simulated Annealing Step2: Sequential Quadratic Programming - NLPQL Best design: currently previously RunCounter 7 7 ObjectiveAndPenalty 611.839351 611.839351 Objective 611.839351 611.839351 Penalty 0.0 0.0 Best design did not improve after executing this Optimization Plan Best design parameter values: LXCG = 1024.63218047333 Distance = 611.839351

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