R. M. Ram Kumar
A Hybrid Computational Tool to Analyze the Performance of Electric Machines with Reduced Content of Permanent Magnet
Ram Kumar, R. M.; Khowja, Muhammad Raza; Vakil, Gaurang; Gerada, David; Gerada, Chris; Paciura, Krzysztof; Fernandes, B. G.
Authors
Mr MUHAMMAD RAZA KHOWJA RAZA.KHOWJA@NOTTINGHAM.AC.UK
SENIOR RESEARCH FELLOW
Dr GAURANG VAKIL GAURANG.VAKIL@NOTTINGHAM.AC.UK
ASSOCIATE PROFESSOR
Professor DAVID GERADA D.Gerada@nottingham.ac.uk
PROFESSOR OF ELECTRICAL ENGINEERING
Professor CHRISTOPHER GERADA CHRIS.GERADA@NOTTINGHAM.AC.UK
PROFESSOR OF ELECTRICAL MACHINES
Krzysztof Paciura
B. G. Fernandes
Abstract
Electric vehicles (EVs) are equipped with interior permanent magnet (IPM) or permanent magnet assisted synchronous reluctance (PM-SynRel) machines because of their superior performance in field weakening region. The effect of saturation is more pronounced in these machines. This prohibits the use of simple analytical tools utilizing constant machine parameters for d and q axis inductance (mathrmL_mathrmd and mathrmL_mathrmq) from accurately predicting control variables like current advance angle, terminal voltage, torque, etc. As a result, design and optimization of IPM and PM-SynRel machines are constrained to time consuming transient finite element analysis (FEA) performed at rated operating point. A hybrid method is introduced in this paper to estimate the complete torque speed characteristics of IPM and PM-SynRel machines. The hybrid method works by employing simple analytical formulation alongside static FEA, thereby, reducing the computational time by more than 10 times. This enables optimization of electric machines considering complete torque speed characteristics with reduced computational burden. In addition, the accuracy of hybrid method utilizing static FEA is found to be on par with complete transient FEA analysis.
Citation
Ram Kumar, R. M., Khowja, M. R., Vakil, G., Gerada, D., Gerada, C., Paciura, K., & Fernandes, B. G. (2020, June). A Hybrid Computational Tool to Analyze the Performance of Electric Machines with Reduced Content of Permanent Magnet. Presented at IEEE Transportation Electrification Conference & Expo (ITEC 2020), Chicago, IL, USA
Presentation Conference Type | Edited Proceedings |
---|---|
Conference Name | IEEE Transportation Electrification Conference & Expo (ITEC 2020) |
Start Date | Jun 23, 2020 |
End Date | Jun 26, 2020 |
Acceptance Date | Feb 28, 2020 |
Online Publication Date | Aug 7, 2020 |
Publication Date | Jun 26, 2020 |
Deposit Date | Jan 11, 2021 |
Publicly Available Date | Jan 13, 2021 |
Pages | 340-345 |
Book Title | 2020 IEEE Transportation Electrification Conference & Expo (ITEC) |
DOI | https://doi.org/10.1109/itec48692.2020.9161631 |
Public URL | https://nottingham-repository.worktribe.com/output/5222243 |
Publisher URL | https://ieeexplore.ieee.org/document/9161631 |
Additional Information | © 2020 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. |
Files
A Hybrid Computational Tool To Analyze The Performance Of Electric Machines With Reduced Content Of Permanent Magnet
(865 Kb)
PDF
You might also like
Design Strategies for Scalable and Modular Aerospace Electrical Machines
(2024)
Presentation / Conference Contribution
PM Synchronous Motor with an Integrated Common-Mode Voltage Filter Considering Parasitic Capacitance Distribution
(2024)
Presentation / Conference Contribution
A Taguchi-LHS-RSM Double-Staged Approach for Design Optimization of Self-Ventilated Cooling Systems Utilized in PMSMs
(2023)
Presentation / Conference Contribution
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search