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A general framework for automated physics-based reduced-order modeling of electromechanical systems
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Summer Computer Simulation Conference archive
Proceedings of the 2007 summer computer simulation conference table of contents
San Diego, California
SESSION: Model-based specification & simulation-based design and procurement: machines: physics based, reduced order, artificial intelligence and finite element analysis table of contents
Pages 221-228  
Year of Publication: 2007
ISBN:1-56555-316-0
Authors
Ali Davoudi  University of Illinois at Urbana-Champaign, Urbana, IL
Patrick Chapman  University of Illinois at Urbana-Champaign, Urbana, IL
Sponsor
SCS : Society for Modeling and Simulation International
Publisher
Bibliometrics
Downloads (6 Weeks): 4,   Downloads (12 Months): 29,   Citation Count: 0
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ABSTRACT

Physics-based models of electromechanical systems, such as finite element-based models and/or high-fidelity magnetic equivalent circuits, accurately represent underlying magnetic devices. However, these models usually introduce hundreds to thousands of state variables and are computationally intensive. Moreover, including relative motion in the physics-based dynamic modeling of electromechanical systems is not a trivial task. In this paper, relative motion is incorporated in highly accurate full-order models that are based on geometrical and material data. Automated linear and nonlinear order-reduction techniques are introduced to mathematically extract the essential system dynamics in the desired bandwidth, thus preserving both accuracy and computational efficiency. The resulting reduced-order systems are verified using finite element-based models and magnetic equivalent circuits in both time and frequency domains.


REFERENCES

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Collaborative Colleagues:
Ali Davoudi: colleagues
Patrick Chapman: colleagues