Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/140230
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Type: | Journal article |
Title: | Optimal Design of Induction Motors Over Driving Cycles for Electric Vehicles |
Author: | Roshandel, E. Mahmoudi, A. Soong, W.L. Kahourzade, S. |
Citation: | IEEE Transactions on Vehicular Technology, 2023; 72(12):15548-15562 |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Issue Date: | 2023 |
ISSN: | 0018-9545 1939-9359 |
Statement of Responsibility: | Emad Roshandel, Amin Mahmoudi, Wen L. Soong and Solmaz Kahourzade |
Abstract: | Consideration of the overload (OL) performance of electric machines designed for EVs enables increasing the power density of the propulsion system. This paper aims to show the characteristics and advantages of the optimal IMs which have the capability of handling OL. A subdomain model (SDM) with the capability of the saturation prediction is developed and validated using experimental data. A lumped thermal model is developed to predict the transient temperature variation of the IMs. The thermal model is validated using the Motor-CAD transient thermal analysis. The fast speed and accuracy of the applied SDM allows to select twelve variables in a large search space for the optimization purpose. Initially, an optimization procedure is proposed to design three IMs over three different driving cycles. The optimal designs are validated from the electromagnetic and thermal aspects by the finite element analysis. IMs are then designed optimally with consideration of the OL capability. A transient thermal analysis is carried out to validate the designs. The optimal designs with and without consideration of OL are compared in terms of the machine parameters and geometry to understand how dimensions and equivalent circuit parameters of the IMs vary according to the driving cycles. The comparison allows more intuition about the consideration of OL capability in design. |
Rights: | © 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information. |
DOI: | 10.1109/TVT.2023.3292901 |
Grant ID: | http://purl.org/au-research/grants/arc/DP170103343 |
Published version: | http://dx.doi.org/10.1109/tvt.2023.3292901 |
Appears in Collections: | Aurora submissions |
Files in This Item:
File | Description | Size | Format | |
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hdl_140230.pdf | Accepted version | 6.34 MB | Adobe PDF | View/Open |
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