@inproceedings{da1524dc06114855810bdbfa40ef4ff3,
title = "Optimization of a magnetic contactor using strategy-selecting hybrid optimization algorithm",
abstract = "Conventional magnetic contactors are mostly composed of a solenoid magnetic actuator. However, the continuous energy consumption of the closing coil to maintain the closed state brings problems such as inefficient use of energy and heat generation. To cope with these problems, a permanent magnet type AC magnetic contactor is designed in this paper. An improved optimization algorithm is used to optimize the contact surface of the MC. Optimization algorithm and optimized results are shown.",
keywords = "Actuator, artificial neural network, finite element method, optimization, permanent magnet",
author = "Kang, \{Jae Woo\} and Jung, \{Sang Yong\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 6th International Conference on Electric Power Equipment - Switching Technology, ICEPE-ST 2022 ; Conference date: 15-03-2022 Through 18-03-2022",
year = "2022",
doi = "10.1109/ICEPE-ST51904.2022.9756992",
language = "English",
series = "ICEPE-ST 2022 - 2022 6th International Conference on Electric Power Equipment - Switching Technology",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "335--338",
booktitle = "ICEPE-ST 2022 - 2022 6th International Conference on Electric Power Equipment - Switching Technology",
}