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Optimized Multiport DC/DC Converter for Vehicle Drivetrains: Topology and Design Optimization. / Tran, Dai-Duong; Chakraborty, Sajib; Lan, Yuanfeng; Van Mierlo, Joeri; Hegazy, Omar.

In: Applied Sciences, Vol. 8, No. 8, 1351, 11.08.2018.

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@article{9152cfd92bcc47afadc4e324865b9308,
title = "Optimized Multiport DC/DC Converter for Vehicle Drivetrains: Topology and Design Optimization",
abstract = "DC/DC Multiport Converters (MPC) are gaining interest in the hybrid electric drivetrains (i.e., vehicles or machines), where multiple sources are combined to enhance their capabilities and performances in terms of efficiency, integrated design and reliability. This hybridization will lead to more complexity and high development/design time. Therefore, a proper design approach is needed to optimize the design of the MPC as well as its performance and to reduce development time. In this research article, a new design methodology based on a Multi-Objective Genetic Algorithm (MOGA) for non-isolated interleaved MPCs is developed to minimize the weight, losses and input current ripples that have a significant impact on the lifetime of the energy sources. The inductor parameters obtained from the optimization framework is verified by the Finite Element Method (FEM) COMSOL software, which shows that inductor weight of optimized design is lower than that of the conventional design. The comparison of input current ripples and losses distribution between optimized and conventional designs are also analyzed in detailed, which validates the perspective of the proposed optimization method, taking into account emerging technologies such as wide bandgap semiconductors (SiC, GaN).",
keywords = "interleaved multiport converte, multi-objective genetic algorithm, hybrid electric vehicles, losses model, wide bandgap (WBG) technologies, Energy Storage systems",
author = "Dai-Duong Tran and Sajib Chakraborty and Yuanfeng Lan and {Van Mierlo}, Joeri and Omar Hegazy",
year = "2018",
month = "8",
day = "11",
doi = "10.3390/app8081351",
language = "English",
volume = "8",
journal = "Applied Sciences",
issn = "2076-3417",
publisher = "MDPI",
number = "8",

}

RIS

TY - JOUR

T1 - Optimized Multiport DC/DC Converter for Vehicle Drivetrains: Topology and Design Optimization

AU - Tran, Dai-Duong

AU - Chakraborty, Sajib

AU - Lan, Yuanfeng

AU - Van Mierlo, Joeri

AU - Hegazy, Omar

PY - 2018/8/11

Y1 - 2018/8/11

N2 - DC/DC Multiport Converters (MPC) are gaining interest in the hybrid electric drivetrains (i.e., vehicles or machines), where multiple sources are combined to enhance their capabilities and performances in terms of efficiency, integrated design and reliability. This hybridization will lead to more complexity and high development/design time. Therefore, a proper design approach is needed to optimize the design of the MPC as well as its performance and to reduce development time. In this research article, a new design methodology based on a Multi-Objective Genetic Algorithm (MOGA) for non-isolated interleaved MPCs is developed to minimize the weight, losses and input current ripples that have a significant impact on the lifetime of the energy sources. The inductor parameters obtained from the optimization framework is verified by the Finite Element Method (FEM) COMSOL software, which shows that inductor weight of optimized design is lower than that of the conventional design. The comparison of input current ripples and losses distribution between optimized and conventional designs are also analyzed in detailed, which validates the perspective of the proposed optimization method, taking into account emerging technologies such as wide bandgap semiconductors (SiC, GaN).

AB - DC/DC Multiport Converters (MPC) are gaining interest in the hybrid electric drivetrains (i.e., vehicles or machines), where multiple sources are combined to enhance their capabilities and performances in terms of efficiency, integrated design and reliability. This hybridization will lead to more complexity and high development/design time. Therefore, a proper design approach is needed to optimize the design of the MPC as well as its performance and to reduce development time. In this research article, a new design methodology based on a Multi-Objective Genetic Algorithm (MOGA) for non-isolated interleaved MPCs is developed to minimize the weight, losses and input current ripples that have a significant impact on the lifetime of the energy sources. The inductor parameters obtained from the optimization framework is verified by the Finite Element Method (FEM) COMSOL software, which shows that inductor weight of optimized design is lower than that of the conventional design. The comparison of input current ripples and losses distribution between optimized and conventional designs are also analyzed in detailed, which validates the perspective of the proposed optimization method, taking into account emerging technologies such as wide bandgap semiconductors (SiC, GaN).

KW - interleaved multiport converte

KW - multi-objective genetic algorithm

KW - hybrid electric vehicles

KW - losses model

KW - wide bandgap (WBG) technologies

KW - Energy Storage systems

UR - http://www.mdpi.com/2076-3417/8/8/1351

UR - http://www.mendeley.com/research/optimized-multiport-dcdc-converter-vehicle-drivetrains-topology-design-optimization

U2 - 10.3390/app8081351

DO - 10.3390/app8081351

M3 - Article

VL - 8

JO - Applied Sciences

JF - Applied Sciences

SN - 2076-3417

IS - 8

M1 - 1351

ER -

ID: 39242121