Simulation Acceleration of High-Fidelity Nonlinear Power Electronic Circuits Using Model Order Reduction

Khan, Hadhiq; Bazaz, Mohammad Abid; Nahvi, Shahkar Ahmad

doi:10.1016/j.ifacol.2018.05.069

Cited by 8 publications

(2 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A framework for accelerating simulation of PECs has been presented by the authors in [34, 35]. The idea was to explore and analyse the suitability of application of various MOR methods to PECs and develop a generalised framework aimed at enhancing the speed of the simulation and at the same time, reducing the computational resources required.…”

Section: Introductionmentioning

confidence: 99%

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

Khan

Bazaz

Nahvi

2020

IET Circuits, Devices & Systems

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

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

Khan

Bazaz

Nahvi

2020

IET Circuits, Devices & Systems

Self Cite

View full text Add to dashboard Cite

show abstract

“…MOR methods have been extensively researched and successfully applied to a wide variety of LSS such as circuits and interconnects, microelectromechanical systems (MEMS), turbomachinery, control design, computational electromagnetics, and VLSI circuits. See [14, 15] for an elaborate survey on applications of MOR. Despite their popularity, works on the application of MOR methods on power electronic circuits are rather limited.…”

Section: Introductionmentioning

confidence: 99%

Singular perturbation‐based model reduction of power electronic circuits

Khan

Bazaz

Nahvi

2019

IET Circuits, Devices & Systems

Self Cite

View full text Add to dashboard Cite

Here, the authors present a model order reduction (MOR) framework based on singular perturbation approximation to accelerate the simulation of high-fidelity power electronic converters. The problem of slow simulation speeds caused due to the wide span of the eigenvalues is mitigated by implementing the proposed framework. The dynamics of the original stiff system is approximated by neglecting the transient contribution of the non-dominant eigenvalues and retaining the steady-state contribution of all the eigenvalues of the system. The model reduction problem has been reformulated to fit the switched nature of these circuits. An error bound for the approximation method has been derived. The method is demonstrated on a DC-DC boost converter and a Class-E amplifier. Significant improvement in speed and reduction in the size of the solution arrays is achieved. It is seen that the reduced-order models are able to replicate the response of the original models and the approximation error is within acceptable limits.

show abstract

Improved Adaptive Multi-resolution Algorithm for Fast Simulation of Power Electronic Converters

Bhat

Bazaz

2023

Lecture Notes in Networks and Systems

View full text Add to dashboard Cite

Simulation Acceleration of High-Fidelity Nonlinear Power Electronic Circuits Using Model Order Reduction

Cited by 8 publications

References 19 publications

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

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

Singular perturbation‐based model reduction of power electronic circuits

Improved Adaptive Multi-resolution Algorithm for Fast Simulation of Power Electronic Converters

Contact Info

Product

Resources

About