Data-Driven Component Cost Models for Power-Electronic Converters

被引:0
作者
Fronczek, Carsten [1 ]
Fritz, Niklas [1 ]
De Doncker, Rik W. [1 ]
机构
[1] Rhein Westfal TH Aachen, Inst Power Elect & Elect Drives, Campus Blvd 89, Aachen, Germany
来源
2023 25TH EUROPEAN CONFERENCE ON POWER ELECTRONICS AND APPLICATIONS, EPE'23 ECCE EUROPE | 2023年
关键词
Artificial intelligence; Cost analysis; Data analysis; Design optimization; Optimization algorithm; Buck converter;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Multi-objective optimization significantly shortens the design time for converters and improves initial design decisions. In addition to technical objectives, economic aspects such as cost play a role in almost every application. This paper provides cost models for converter components based on publicly available data from spring 2023. These cost models are based on the largest dataset of any converter-component cost model in the literature. Besides physical properties of the components, they include economic factors and allow their application from prototype to series production. The cost models were evaluated using statistical metrics. Further, the derived component cost models serve as a basis to a simplified design optimization for a 10 kW dc-dc converter.
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页数:9
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