基于微粒群算法的Buck-Boost矩阵变换器主电路参数优化

Optimization of BBMC main circuit parameters based on particle swarm optimization

鉴于Buck-Boost矩阵变换器输出电压波形的谐波失真度与其主电路参数直接相关,为此采用微粒群算法对其主电路参数进行优化.文中介绍了微粒群算法的基本原理,阐述了采用微粒群算法对BBMC主电路参数进行优化的具体设计方法,并利用Matlab/Simulink对其优化效果进行了仿真验证.结果表明,利用微粒群优化算法获得的主电路参数较传统计算方法获得的主电路参数其输出电压波形的谐波失真度更小,因而具有一定的应用价值.

In view of the harmonic distortion of Buck -Boost matrix converter （BBMC ）output voltage waveform was directly related to its main circuit parameters,the Particle Swarm Optimization （PSO）was used to optimize its main circuit parameters.The basis of PSO was explained,and the method of optimizing its main circuit parameters by PSO was elaborated.Its optimization effect was tested by using Matlab/Simulink.Results show that compared with traditional method,main circuit parameters obtaine by PSO have lower harmonic distortion of output voltage waveform,and thus it has the certain application value.