DocumentCode :
2272546
Title :
Multi-objective optimization design for output characteristics of LCC resonant converter
Author :
Zhang, Zhiguo ; Xie, Yunxiang ; Yuan, Zhaomei
Author_Institution :
Sch. of Electr. Power, South China Univ. of Technol., Guangzhou, China
fYear :
2011
fDate :
20-23 Aug. 2011
Firstpage :
1
Lastpage :
5
Abstract :
The equivalent circuit and the mathematical model are obtained for the capacitive output filter series-parallel resonant converter by a fundamental model approximation (FMA) method in this paper. Based on them, a Pareto multi-objective optimization with genetic algorithm is applied to improve the output characteristics of the converter. With fine-grained fitness assignment strategy and density estimation, the algorithm can achieve massive and well-distributed Pareto optimal solutions by the minimization of two duality functions. These optimal solutions correspond to the resonant circuit parameters and the control parameters with respect to the different corresponding performance targets. The Pareto multi-objective optimization algorithm can get some good results, which is proved by simulation results. The algorithm can also save the time of circuit debugging.
Keywords :
Pareto optimisation; approximation theory; equivalent circuits; genetic algorithms; resonant power convertors; FMA method; LCC resonant converter; Pareto multiobjective optimization design; capacitive output filter series-parallel resonant converter; circuit debugging; density estimation; equivalent circuit; fine-grained fitness assignment strategy; fundamental model approximation method; genetic algorithm; mathematical model; output characteristics; Equivalent circuits; Evolutionary computation; Frequency modulation; Genetic algorithms; Mathematical model; Optimization; RLC circuits;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Machines and Systems (ICEMS), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1044-5
Type :
conf
DOI :
10.1109/ICEMS.2011.6073415
Filename :
6073415
Link To Document :
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