Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/163036
Title: Quantitative comparison on permanent-magnet vernier machines with improved flux modulation effect for automatic guided vehicles
Authors: Cao, Libing
Zuo, Yuefei
Chen, Hao
Xie, Shuangchun
Han, Boon Siew
Hoang, Chi Cuong
Lee, Christopher Ho Tin
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Source: Cao, L., Zuo, Y., Chen, H., Xie, S., Han, B. S., Hoang, C. C. & Lee, C. H. T. (2022). Quantitative comparison on permanent-magnet vernier machines with improved flux modulation effect for automatic guided vehicles. IEEE Transactions On Vehicular Technology, 71(11), 11367-11378. https://dx.doi.org/10.1109/TVT.2022.3193144
Project: IAF-ICP-I2001E0067
Journal: IEEE Transactions on Vehicular Technology
Abstract: In this paper, the interior permanent-magnet vernier (PMV) machines and the conventional PMV machine are quantitatively compared regarding the requirements for electric automatic guided vehicles (AGV). The key feature of the interior PMV machines is to place the middle iron pole sandwiched by PMs in the slots between the salient rotor poles. As a result, three types of interior PMV machines with different PM arrangements, namely two V-type PMV (V-PMV) and one U-type PMV (U-PMV) machines, are developed. Due to the improved flux modulation effect, the V-PMV and U-PMV machines can respectively provide over 20% and 30% higher torque density than the conventional PMV counterpart, under a high power factor level of 0.86. The working principle is illustrated based on the field modulation theory. A comparative study among the conventional PMV and interior PMV machines is conducted in terms of electromagnetic performances and dynamic responses, after performing global optimization of design parameters. Finally, a prototype is manufactured and tested for experimental validations.
URI: https://hdl.handle.net/10356/163036
ISSN: 0018-9545
DOI: 10.1109/TVT.2022.3193144
Rights: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TVT.2022.3193144.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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