Model Order Reduction Method for Large-Scale $RC$  Interconnect and Implementation of Adaptive Digital PI Controller

Mohamed, Kouki

doi:10.1109/tvlsi.2019.2922219

Cited by 5 publications

(2 citation statements)

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“…Different MOR techniques have been proposed and applied to combat the complexity of interconnected problems [1][2][3] and finite-element equations of electromagnetic problems [4][5][6][7]. However, there are few works oriented for 3-D temperature fields.…”

Section: Introductionmentioning

confidence: 99%

A Block Arnoldi Algorithm Based Reduced-Order Model Applied to Large-Scale Algebraic Equations of a 3-D Field Problem

et al. 2021

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In simulations of three-dimensional transient physics filled through a numerical approach, the order of the equation set of high-fidelity models is extremely high. To eliminate the large dimension of equations, a model order reduction (MOR) technique is introduced. In the existing MOR methods, the block Arnoldi algorithm-based MOR method is numerically stable, achieving a passively reduced order model. Nevertheless, this method performs poorly when it is applied to very wide-frequency transients. To eliminate this deficiency, multipoint MOR methods are emerging. However, it is hard to directly apply an existing multipoint MOR method to a 3-D transient field equation set. The implementation issues in a reduction process (such as the selection of expansion points, the number of moments matched at a point and the error bound) have not been explored in detail. In this respect, an adaptive multipoint model reduction model based on the Arnoldi algorithm is proposed to obtain the reduced-order models of a 3-D temperature field. The originality of this study is the proposal of a novel adaptive algorithm for selecting expansion points, matching moments automatically, using a posterior-error estimator based on temperature response coupled with a network topological method (NTM). The computational efficiency and accuracy of the proposed method are evaluated by the numerical results from solving the temperature field of a prototype insulated-gate bipolar transistor (IGBT).

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Section: Introductionmentioning

confidence: 99%

A Block Arnoldi Algorithm Based Reduced-Order Model Applied to Large-Scale Algebraic Equations of a 3-D Field Problem

et al. 2021

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“…MOR has been conventionally applied to large-scale-systems [30][31][32][33]. Its application in the power electronics domain seems rather counter-intuitive since these systems are of considerably smaller size.…”

Section: Introductionmentioning

confidence: 99%

Adaptive multi‐resolution framework for fast simulation of power electronic circuits

Khan

Bazaz

Nahvi

2020

IET Circuits, Devices & Systems

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An adaptive multi-resolution simulation (AMRS) framework for fast and accurate simulation of high-fidelity models of power electronic circuits (PECs) is presented in this study. The wide span of eigenvalues makes PEC simulation prohibitively slow. This problem can be tackled using the proposed approach. Singular perturbation approximation is used to extract simplified models by ignoring the transient contribution of the non-dominant eigenvalues. Simplified models of different orders or resolutions, each corresponding to a particular level of accuracy are derived on the fly at no additional computational cost. The simulation engine is set such that it adaptively switches across resolutions based on a predefined tolerance during the simulation. This approach is advantageous in the sense that instead of simulating the original model over the entire time-range, a combination of the original and simplified models is simulated. The combined use of the original and the simplified models is thus shown to be a powerful tool for efficient and accurate simulation of PECs. The examples illustrated, show that the AMRS approach makes the simulation considerably faster and ensures the complete response of the system is obtained with negligible error. The method is illustrated on a Class-E amplifier and a DC-DC buck-boost converter.

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Model Order Reduction via Moment-Matching: A State of the Art Review

Rafiq

Bazaz

2021

Arch Computat Methods Eng

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Model Order Reduction Method for Large-Scale $RC$ Interconnect and Implementation of Adaptive Digital PI Controller

Cited by 5 publications

References 50 publications

A Block Arnoldi Algorithm Based Reduced-Order Model Applied to Large-Scale Algebraic Equations of a 3-D Field Problem

A Block Arnoldi Algorithm Based Reduced-Order Model Applied to Large-Scale Algebraic Equations of a 3-D Field Problem

Adaptive multi‐resolution framework for fast simulation of power electronic circuits

Model Order Reduction via Moment-Matching: A State of the Art Review

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