堆积
最大功率转移定理
铁氧体磁芯
铁氧体(磁铁)
材料科学
电子工程
电气工程
计算机科学
功率(物理)
工程类
机械工程
电磁线圈
核磁共振
物理
量子力学
作者
Wenhua Ding,Yufei Wang,Tingyu Chen,Li Zhenghong,You Yue,Jingyu Wang,Zhicong Huang
摘要
Abstract This paper presents a magnetic coupler design method for WPT systems based on stacking machine‐learning algorithms. A synthetic dataset generated by ANSYS Maxwell is used for training and evaluating machine‐learning models. Stacking technology effectively combines the results from multiple models and make best predictions. The designed model allows us to obtain the optimal values of the coil inner radius and number of turns , when other coil design parameters such as the coil outer radius , the wire diameter , and the coil inductance , are given based on the application environment. The proposed method provides practical solutions meeting design requirements quickly, easily accommodating magnetic couplers with ferrite cores, and showing advantages in designing magnetic couplers with optimal power transfer efficiency.
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