Model Reduction Method for Spacecraft Electrical System Based on Singular Perturbation Theory

Accurate and efficient modeling and simulation of spacecraft electrical systems are crucial because of their complexity. However, existing models often struggle to balance simulation efficiency and accuracy. This paper introduces a model reduction method based on singular perturbation theory to simplify the full-order model of spacecraft electrical systems. The experimental results show that the reduced-order simplified model saves 50% of the simulation time with almost no degradation in the simulation accuracy and can be applied to real-world scenarios, such as digital twins. This method offers a new approach for rapid simulation of spacecraft electrical systems and has broad application prospects.

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Publication Details

Journal
Electronics
Published
2024-10-31
DOI
https://doi.org/10.3390/electronics13214291
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
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article

Model Reduction Method for Spacecraft Electrical System Based on Singular Perturbation Theory

Yelun Peng, Lifeng Wang, Juan Luo
Electronics
Machine Fault Diagnosis Techniques
article

Model Reduction Method for Spacecraft Electrical System Based on Singular Perturbation Theory

Yelun Peng, Lifeng Wang, Juan Luo
article en

Abstract

Accurate and efficient modeling and simulation of spacecraft electrical systems are crucial because of their complexity. However, existing models often struggle to balance simulation efficiency and accuracy. This paper introduces a model reduction method based on singular perturbation theory to simplify the full-order model of spacecraft electrical systems. The experimental results show that the reduced-order simplified model saves 50% of the simulation time with almost no degradation in the simulation accuracy and can be applied to real-world scenarios, such as digital twins. This method offers a new approach for rapid simulation of spacecraft electrical systems and has broad application prospects.

ElectronicsVol. 13(21)
Hunan University (CN)
Openalex Percentile: Top 78%
Machine Fault Diagnosis Techniques
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