NSGA-II Genetic Algorithm Based Optimization of Parameters of Multiphase Interleaving Buck/Boost DC-DC Converter

Buck/Boost DC-DC converters can be used in grids with bidirectional power flows. In the actual designing process of a distribution box, power loss would cause converter to heat, which might cause damage to components in the converter if the heat generated greater than the thermal dispersion capacity of the converter. While ripple currents and the volume are also considered in distribution box designing. This paper considers the above-mentioned factors, establishes objective functions, and use NSGA-II genetic algorithm to optimize the parameter design of multiphase interleaving Buck/Boost DC-DC converters. Then several relatively better outputs have been selected, scored and weighted to estimate working performance under the parameter sets. Finally, the very best parameter set of the converter can be obtained.