基于MOPSO的电力变换器多目标优化

Multi-Objective Optimization of Power Converter Based on MOPSO

  • 摘要: 为克服电力变换器优化设计中各种目标的相互冲突,以效率、物理尺寸(体积、质量和面积)和成本为优化目标建立电力变换器多目标优化模型,采用多目标粒子群优化(MOPSO)算法对建立的模型进行求解,决策者可在最终提供的最优解集中找到不同折衷的最优解。本文以Vienna整流器和Buck变换器作为研究对象,分别建立各自的多目标优化函数,导入器件数据库,在Matlab上实现了MOPSO算法。仿真实验结果表明了MOPSO算法的可行性、覆盖性和收敛性,并能在比较短的时间里收敛到最优解集。

     

    Abstract: In order to overcome the conflicts among various objectives in the optimization design of power converters, a multi-objective optimization model of power converters with efficiency, physical size (volume, weight and area) and cost is established as optimization objectives in the paper. The model is solved by using multi-objective particle swarm optimization (MOPSO) algorithm and decision makers can find different compromise optimal solutions in the final set of optimal solutions provided. Vienna rectifier and Buck converter are taken as research objects. Their respective multi-objective optimization functions are established, and introduced into the device database, and the MOPSO algorithm is implemented on Matlab. Simulation results show that the MOPSO algorithm is feasible, coverage and convergence, and it can converge to the optimal solution set in a relatively short time.

     

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