摘要
为了提高Boost变换器的效率,节约系统成本,提出了基于多目标粒子群优化算法(MOPSO)的Boost变换器设计.首先分析了Boost变换器的功率损失,根据Boost变换器的设计要求,选择合适的MOSFET、二极管、电感和电容等器件,建立离散元器件数据库.以此数据库为约束条件,以功率损失、系统成本和体积为目标函数,建立了Boost变换器多目标优化设计模型,用MOPSO算法从几百种组合解集中寻找pareto最优解.基于折中分析,可为变换器做出合理的器件选择,以满足不同的设计要求.以光伏发电系统前级Boost变换器为例进行仿真研究,结果表明MOPSO具有处理离散多目标优化问题的能力,能在短时间内找到折中解,证明了该算法的有效性.
In order to improve the efficiency and reduce the system cost of Boost converter, the design of Boost con- verter based on multi-objective particle swarm optimization （MOPSO） algorithm is proposed in this paper. First, the power losses of Boost converter are analyzed. According to the design requirements, the suitable MOSFET, diode, inductor and capacitor are selected to establish the discrete database. Taking the database as constraint condition, regard power losses, system costs and volume assessment model as objective functions, the multi-objective optimization design model of Boost converter is built and by the utilization of MOPSO algorithm, the optimal solution set of Pareto can be calculated from hundreds of combination solutions. Based on compromise analysis, for different design requirements, the proper device of converter can be selected. A pre-stage Boost converter of photovohaic system is used as an example to carry out simulation research. The results show that MOPSO is capable of the dis- crete multi-objective optimization problems, and can find compromise solutions in short time which, prove the effec- tiveness of MOPSO algorithm.
作者
王凯丽
张巧杰
WANG Kai-li ZHANG Qiao-jie(College of Automation, Beijing Information Science and Technology University, Beijing 100192, China)
出处
《烟台大学学报（自然科学与工程版）》
CAS
2017年第4期317-322,共6页
Journal of Yantai University(Natural Science and Engineering Edition)
基金
国家自然科学基金资助项目(51477011)
北京市自然科学基金重点资助项目(KZ201511232035)
北京市属高校科技创新能力提升计划项目(TJSHG201310772024)
关键词
MOPSO
效率
BOOST变换器
优化设计
uhi-objective particle swarm optimization algorithm using matlab
efficiency
Boost converter
optimi- zation design
