Evaluation Index-Based Multiphysics Coupling Model and Analysis Methodology for High-Reliable Power Supply Module

The performance of a power supply is highly susceptible to environmental variations, which directly impacts the proper functioning of nonlinear loads such as lasers and LEDs. This paper proposes an evaluation index-based multiphysics coupling modeling (EIMCM) technique that enables comprehensive characterization of various physical properties for power supplies. By correlating heat, stress, electricity and magnetism, the technique explores the intrinsic connections between different physical fields and establishes a reliability evaluation model. For the large number of elements and indicators in the evaluation, a back-propagation neural network (BPNN) is employed to train the multi-objective parameters, thereby improving the performance of the module. To demonstrate the capabilities of the proposed methodology, a 600 W power supply for driving laser loads is designed and optimized for heat dissipation, strain, output power, and regulated voltage accuracy. The simulation and experimental results exhibit strong consistency as a systematic error less than 4%, validating the effectiveness of the proposed EIMCM methodology.

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Publication Details

Published
2025-03-16
DOI
https://doi.org/10.1109/apec48143.2025.10977494
Primary Topic
High-Voltage Power Transmission Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluation Index-Based Multiphysics Coupling Model and Analysis Methodology for High-Reliable Power Supply Module

Xiaosen Liu, Haoyu Wang, Xuliang Wang, Yan Wang
High-Voltage Power Transmission Systems
article

Evaluation Index-Based Multiphysics Coupling Model and Analysis Methodology for High-Reliable Power Supply Module

Xiaosen Liu, Haoyu Wang, Xuliang Wang, Yan Wang
article en

Abstract

The performance of a power supply is highly susceptible to environmental variations, which directly impacts the proper functioning of nonlinear loads such as lasers and LEDs. This paper proposes an evaluation index-based multiphysics coupling modeling (EIMCM) technique that enables comprehensive characterization of various physical properties for power supplies. By correlating heat, stress, electricity and magnetism, the technique explores the intrinsic connections between different physical fields and establishes a reliability evaluation model. For the large number of elements and indicators in the evaluation, a back-propagation neural network (BPNN) is employed to train the multi-objective parameters, thereby improving the performance of the module. To demonstrate the capabilities of the proposed methodology, a 600 W power supply for driving laser loads is designed and optimized for heat dissipation, strain, output power, and regulated voltage accuracy. The simulation and experimental results exhibit strong consistency as a systematic error less than 4%, validating the effectiveness of the proposed EIMCM methodology.

Tsinghua University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 93%
High-Voltage Power Transmission Systems
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