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

An Automated Design Synthesis An Automated Design Synthesis System Involving Hardware-In-the-System Involving Hardware-In-the-

Loop SimulationLoop Simulation

Steve Hann Wensi JinSteve Hann Wensi Jin

Mechanical Simulation Corporation Opal-RT TechnologiesMechanical Simulation Corporation Opal-RT Technologies

May 2003May 2003

Introduction

Experiment

Underlying Technologies

Summary

Innovation in the Loop

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

Outline

Introduction

Experiment


Summary


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

Introduction Real-Time Simulation & HIL

Introduction

Experiment


Summary


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

Introduction Hardware In-the-Loop

Introduction

Experiment


Summary


Hardware In-the-Loop Example: ECU In-the-Loop

RT Simulator(3 x Pentium 3, 1 GHz CPU)

ECUunder test

Host PC(development env.)

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

Introduction

Experiment


Summary


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

Introduction

Experiment


Summary


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

Why Use iSIGHT for HIL

Introduction

Experiment


Summary


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

Why Use iSIGHT for HIL

Introduction

Experiment


Summary


Experiment Setup ABS/ECU

VEHICLE

ECU

BRAKES

Solenoid Signals

Brake Torques

Wheel Speeds

Brake Pedal Input

Introduction

Experiment


Summary


HITL for ECU Evaluation

ECU

Solenoid Signals

Wheel Speeds

DAQ Boards

Conditioning

Software Brake Model

CarSim

RT–LAB

Introduction

Experiment


Summary


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

Description of Problem

Introduction

Experiment


Summary


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

Description Of Simulations

Introduction

Experiment


Summary


…

Firewire

Real-Time PC (QNX)

TCP/IPHOST

Workstation PC

Supports

CarSim/TruckSim

AMEsim

GT-Power

Matlab/Simulink

MATRIXx/SystemBuild

HIL Platform: RT-LABHighlights

Intel CPU & PC hardware

Open system

Scalability through

parallel processing

Widely connected

Introduction

Experiment


Summary


RT Vehicle Dynamics Simulation: CarSim

Introduction

Experiment


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)

Summary

Introduction

Experiment


Summary


Summary

Introduction

Experiment


Summary


SummaryExecution 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

Documents

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