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Variable Time Magnetization Current Trajectory Control Method for Variable Flux Memory Machines

delete2022-09-01
delete8
PRE
AI
Y
Yuxiang Zhong
林鹤云 封面图
林鹤云 (Heyun Lin)
王激尧 封面图
王激尧 (Jiyao Wang) *
R
Rui Tu
H
Hui Yang
S
Shukang Lyu
刘
刘细平 (Xiping Liu)
DOI:10.1109/TTE.2022.3165874delete
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摘要

摘要

En 中文
Magnetization state (MS) manipulation is crucial to the comprehensive performance improvement of variable flux memory machine (VFMM) drive system. This article proposes a novel MS manipulation control method wherein variable time magnetization current trajectories can be adaptively controlled to reduce the MS manipulation losses. A fuzzy proportional integral (PI) feedforward current controller is newly structured to track the trajectories, improving the current tracking ability. First, dynamic MS manipulation processes are simulated and analyzed deeply, in which the variable machine parameters are calculated by finite element method (FEM) and fitted with polynomial formulas. Based on these, the maximum di (d)/ dt of magnetization current pulse trajectory, namely the shortest MS manipulation time, can be adaptively acquired to reduce the MS manipulation losses at different running conditions. Then, a fuzzy PI feedforward current controller is developed by combining the feedforward and fuzzy logic controls, ensuring the real current tracks its reference well at different speed and load conditions, particularly in the MS manipulation process. Finally, the effectiveness and feasibility of the proposed MS manipulation method are verified by experimental results on a hybrid-magnetic-circuit VFMM (HMC-VFMM) prototype.
Keyword:
Magnetization
Trajectory
Voltage
Couplings
Mathematical models
Demagnetization
Transportation
Current controller
feedforward
fuzzy logic control
magnetization state (MS) manipulation
memory machine
variable flux

期刊

I
IEEE Transactions on Transportation Electrification
IF:
8.3
论文数:
2.9K
被引数:
1.6W

机构

J
jiangxi university of science & technology
学者数:
6.7K
论文数: 4.5K
被引数: 3
S
southeast university - china
学者数:
5.3W
论文数: 4.9W
被引数: 57
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