Model order reduction of 1D diffusion systems via residue grouping

Research output: Contribution to journalArticle

66 Citations (Scopus)

Abstract

A model order reduction method is developed and applied to 1D diffusion systems with negative real eigenvalues. Spatially distributed residues are found either analytically (from a transcendental transfer function) or numerically (from a finite element or finite difference state space model), and residues with similar eigenvalues are grouped together to reduce the model order. Two examples are presented from a model of a lithium ion electrochemical cell. Reduced order grouped models are compared to full order models and models of the same order in which optimal eigenvalues and residues are found numerically. The grouped models give near-optimal performance with roughly 1/20 the computation time of the full order models and require 1000-5000 times less CPU time for numerical identification compared to the optimization procedure.

Original languageEnglish (US)
Pages (from-to)110121-110128
Number of pages8
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume130
Issue number1
DOIs
StatePublished - Jan 1 2008

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eigenvalues
transcendental functions
Electrochemical cells
electrochemical cells
transfer functions
Program processors
Transfer functions
Lithium
lithium
optimization
Ions
ions

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications

Cite this

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Model order reduction of 1D diffusion systems via residue grouping. / Smith, Kandler A.; Rahn, Christopher D.; Wang, Chao-yang.

In: Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, Vol. 130, No. 1, 01.01.2008, p. 110121-110128.

Research output: Contribution to journalArticle

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