Overview of Circuit Simulation Programs

37
Overview of Circuit Simulation Programs ECE 546 DIGITAL COMPUTATIONAL TECHNIQUES FOR ELECTRONIC CIRCUITS January 10, 2005 Oleg Wasynczuk

Transcript of Overview of Circuit Simulation Programs

Page 1: Overview of Circuit Simulation Programs

Overview of Circuit Simulation Programs

ECE 546 DIGITAL COMPUTATIONAL TECHNIQUES FOR ELECTRONIC CIRCUITSJanuary 10, 2005Oleg Wasynczuk

Page 2: Overview of Circuit Simulation Programs

Need for System-of-Subsystems Approach

Complex engineered systems such as aircraft, modern automobiles, or the terrestrial electric power grid involve a broad spectrum of technologies and interactive subsystems that must work synergistically in order to operate properlyInter-dependencies between subsystems are becoming more and more prominent

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More-Electric Aircraft Power System

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Modeling Approaches

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Synchronous Machine Subsystem Models

Distributed Parameter Coupled Circuit Steady State

)( uxfx ,dtd

= IZEeV j ~~ −= δ

+−

δjEe

jXRZ +=

I~V~

+

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Power Electronic Subsystem ModelsAverage ValueDetailed

)( uxfx ,dtd

=)()(

)()( );(iiii

f

if

iiiiii

sgst

ttsdtd

,,

,

1

110

x

Txxxfx

=

==

+

−−

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Simulation Approaches

Circuit-Based Approaches (Spice, EMTP, Saber, PSIM, Simplorer)System-Based Approaches (Simulink, ACSL, Dymola)

Block-diagram and/or differential equation orientedExtensive set of tool boxes including

ASMG (Simulink, ACSL)Power System Blockset (Simulink)…

Finite-Element-Based Approaches (Ansys, Maxwell, …)

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Circuit-Based Approaches

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Circuit-Based Approaches

Example Subsystem

(Motor Controller)

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Circuit-Based Approaches

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Circuit-Based Approaches

Resistor-Companion Circuit

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15

2

1

654

321321

9

8

7

+

++

−−−−+++

=

k

SS

S

S

v

vv

ggggggggggg

iiiii

Update Formula

O(n3) computational complexity where n = number of non-datum nodes

Circuit-Based Approaches

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Simulation Approaches

Circuit-Based Approaches (Spice, Saber, PSIM, Simplorer)System-Based Approaches (Simulink, ACSL, Dymola)

Block-diagram and/or differential equation orientedExtensive set of tool boxes including

ASMG (Simlink, ACSL)Power System Blockset (Simulink)…

Finite-Element-Based Approaches (Ansys, Maxwell, …)

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System-Based Approaches

Hierarchical system definition

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System-Based Approaches

Common Simulink Component Models

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System-Based Approaches

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System-Based Approaches

( )∑∑−

−=

−−−

=

−+ +=1

1

1

01 p

i

ikiki

p

i

iki

k th ,xfxx βα

When user starts model, Simulink applies selected integration algorithm to approximate solution at discrete but not necessarily uniform instants of time

General Multi-step Formula

Implicit algorithms require solution of nonlinear equation (dimension = number of states) at each time step. Newton-Raphson iteration generally used.

Explicit if 01 =−β

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System-Based Approaches

Stiff System: A system with both fast and slow dynamics

Stiffly Stable Integration Algorithm: the ability to increase the time step after fast transients subside

Stiffly Stable Algorithms are implicit!

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System-Based Approaches

Computational Complexity

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System-Based Approaches

Dilemma

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Simulink Algorithms

Shampine and Reichelt, The MATLAB ODE Suite, SIAM J. Sci. Comput.,Vol. 18, No. 1, pp. 1-22, January 1997.

System-Based Approaches

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Simulation Approaches

Circuit-Based Approaches (Spice, Saber, PSIM, Simplorer)System-Based Approaches (Simulink, ACSL, Dymola)

Block-diagram and/or differential equation orientedExtensive set of tool boxes including

ASMG (Simulink, ACSL)Power System Blockset (Simulink)…

Finite-Element-Based Approaches (Ansys, Maxwell, …)

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Finite-Element Based Approaches

4000-10000 Nodes

uSaaM =+dtd

FEA

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Conventional Parallel Computing Paradigm

Integration algorithm (master)

slave 1

��� ��� ��� ��

slave 2 slave n -1

� � �

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Σ+

+

���������

Σ+

+

���������

��

��

���

��

��

Conventional Parallel Computing Paradigm

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Conventional Parallel Computing Paradigm

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Conventional Parallel Computing Paradigm

At best m-fold reduction in computation time assuming zero communication latencyComputational gain further bounded by Amdahl’s Law

pT)α1(αTT 1

1 −+=p where serial portion [ ]1,0α∈

therefore

α1S)α1(α

1TTS 1 ≡≤

−+

== ∞

pp

p

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Distributed Heterogeneous Simulation (DHS)

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DHS Definition

Synchronized interconnection of any number of dynamic subsystem simulations

Developed using any combination of programs/languages

Implemented on:• Single computer/workstation/supercomputer• Local area network (Intranet)• Wide area network (Internet)

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Sample DHS Computer Setup

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DHS Concept

Much better than M-fold (potentially M3) improvement in speed

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DHS Links Environment

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Flexibility of DHS

Heterogeneous platforms (Windows, Unix, Linux, ...)Heterogeneous languages (ACSL, MATLAB/Simulink, Saber, EASY5, C, C++, FORTRAN, Java,…)Heterogeneous simulation approaches (single-rate, multi-rate, state model based, resistor-companion, finite difference/element,...)Heterogeneous networks (Ethernet, SCI, ScramnetTM, MyrinetTM,...)

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Use “best” language for each component/subsystemProprietary information protectedSuper-linear increase in computational speed across a network of desktop computersNo need to translate models into common languageLegacy code can be used directlyConducive to team design/analysisRemote interconnectionEliminate need to develop average-value models for system stability assessmentReal-time (hardware-in-the-loop) capability for some systemsSystem Integrator(s) do not have to be familiar with the language(s) used to create subsystem simulation(s)

Key Advantages of DHS

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More-Electric Aircraft Power System

Optimum Allocation

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Optimum Allocation

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Optimum Allocation

18.5 speedup with 4 computers