@inproceedings{32b77831387a44c6b7530e234373e498,
title = "Rectangular and Random Conductors: AC Losses Evaluations and Manufacturing Considerations",
abstract = "This paper presents a comparison between hairpin and random distributed winding in electrical machines for automotive applications. Indeed, the overall performance of an electrical drive system is seriously affected by its winding design. The considered electrical machine has a peak power of 115kW and a maximum operating speed of 12000 rpm. Both cost and manufacturing aspects are here discussed in detail. Two different machine topologies have been investigated and Finite Element Analysis (FEA) results are presented and discussed. Then, the comparison between hairpin and random winding configuration in terms of AC copper losses are presented for the selected geometry. The accurate AC losses estimation can be done by modelling each single conductor. In order to significantly reduce the simulation time, a domain model reduction has been adopted. Based on two different driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Test (HWFET), the AC losses have been evaluated. It is shown that horizontal pin segmentation can contribute to considerable AC loss reduction.",
keywords = "AC losses, HWFET, UDDS, automotive, electrical machines, hairpin, high frequency, manufacturing, mass production, random, segmented hairpin, winding",
author = "Eraldo Preci and Giorgio Valente and Anuvav Bardalai and Tommaso Transi and Tianjie Zou and David Gerada and Michele Degano and Giampaolo Buticchi and Christopher Gerada",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020 ; Conference date: 19-10-2020 Through 21-10-2020",
year = "2020",
month = oct,
day = "18",
doi = "10.1109/IECON43393.2020.9254278",
language = "English",
series = "IECON Proceedings (Industrial Electronics Conference)",
publisher = "IEEE Computer Society",
pages = "1076--1081",
booktitle = "Proceedings - IECON 2020",
address = "United States",
}