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
SN - 2076-3417
VL - 8
JO - Applied Sciences
JF - Applied Sciences
IS - 8
M1 - 1351
ER -