Experimental statistical method predicting AC losses on random windings and PWM effect evaluation

Preci, Eraldo and Valente, Giorgio and Galassini, Alessandro and Yuan, Xin and Degano, Michele and Gerada, David and Buticchi, Giampaolo and Gerada, Chris (2020) Experimental statistical method predicting AC losses on random windings and PWM effect evaluation. IEEE Transactions on Energy Conversion . p. 1. ISSN 0885-8969

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Abstract

Nowadays, one of the challenges in transport electrification is the reduction of the components’ size and weight in order to improve the power density. This is often achieved by designing electrical machines with higher rotational speeds and excitation frequencies. In addition, the converter needs to control the machine over a wide speed range given by the mission profile. Therefore, copper losses can significantly increase due to the combination of high frequency excitation and the harmonics introduced by the converter .The winding arrangement design plays a key role in the minimization of the copper losses. This paper presents an in depth study on AC losses in random windings for high frequency motor applications. An analytical method is compared against 2-D Finite Element (FE) simulation results. These are then compared to experimental measurements taken on a custom motorette. Importantly, in order to take into account the random positions of each strand within the machine slots, an Experimental Statistic Method (ESM) is proposed. The ESM allows to define the probability distribution which is useful to evaluate the winding copper losses at the design stage. The contribution of the Pulse Width Modulation (PWM) effect is also considered and experimentally evaluated. IEEE

Item Type: Article
Keywords: Random windings; AC losses evaluation; high frequency; PWM effects; Electrical Machines.
Schools/Departments: University of Nottingham Ningbo China > Faculty of Science and Engineering > Department of Electrical and Electronic Engineering
Identification Number: https://doi.org/10.1109/TEC.2020.3040265
Depositing User: QIU, Lulu
Date Deposited: 28 Dec 2020 08:07
Last Modified: 28 Dec 2020 08:07
URI: http://eprints.nottingham.ac.uk/id/eprint/64166

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