An Analytical Approach for the Design of Innovative Hairpin Winding Layouts

Arzillo, A.; Nuzzo, S.; Braglia, P.; Franceschini, G.; Barater, D.; Gerada, D.; Gerada, C.

Abstract

This work deals with an analytical approach aimed at accurately predicting Joule losses in innovative hairpin winding layouts. While hairpin windings are seeing an everincreasing use in automotive and aerospace applications due to their inherently high slot fill factor, they also present drawbacks such as the non-uniform current distribution potentially occurring across their cross section. This phenomenon is emphasized at high frequencies, leading to a significant increase of the effective conductor resistance and, consequently, of copper losses. Hence, particular attention has to be given to the design of electrical machines employing hairpin conductors, aiming to reduce the high-frequency losses as much as possible. In this paper, an analytical model based on previous investigations is updated and modified in order to increase the degrees of freedom in the design and analysis of hairpin windings. With the developed analytical model, the copper losses associated to innovative hairpin configurations can be accurately predicted. The findings also confirm that such alternative layouts can effectively reduce the Joule losses when compared to traditional hairpin technologies.

Citation

Arzillo, A., Nuzzo, S., Braglia, P., Franceschini, G., Barater, D., Gerada, D., & Gerada, C. (2020). An Analytical Approach for the Design of Innovative Hairpin Winding Layouts. . https://doi.org/10.1109/icem49940.2020.9270927

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2020 International Conference on Electrical Machines (ICEM)
• Start Date: Aug 23, 2020
• End Date: Aug 26, 2020
• Acceptance Date: May 26, 2020
• Online Publication Date: Dec 1, 2020
• Publication Date: Aug 23, 2020
• Deposit Date: Feb 26, 2021
• Publicly Available Date: Feb 26, 2021
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 1534-1539
• ISBN: 9781728199450
• DOI: https://doi.org/10.1109/icem49940.2020.9270927
• Public URL: https://nottingham-repository.worktribe.com/output/5352203
• Publisher URL: https://ieeexplore-ieee-org/document/9270927
• 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.